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AIS’s Management Insight Series
The Challenges of Pharmacy
Star Ratings: Solutions for Part D
Plan Sponsors and Their Partners
Adapted from an AIS Webinar presented by
Vivien Chan, Pharm.D.
Director of Quality and Cost Strategies
OmedaRx
Kristine Walhof
Program Director, Medicare Star Ratings
Cambia Health Solutions, Inc.
Edited by Erin Trompeter, Managing Editor, AIS
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Table of Contents
Introduction������������������������������������������������������������������������������������������������������������������������������� 1
The Regence Approach to Stars Improvement������������������������������������������������������������������������������������ 3
Improving Medication Adherence�������������������������������������������������������������������������������������������������������� 5
Interventions and Programs������������������������������������������������������������������������������������������������������������������� 9
Q&A Session���������������������������������������������������������������������������������������������������������������������������� 15
Appendix A: AIS Coverage of Medicare Advantage Star Ratings�������������������������������� 19
Results for 2016 Plans���������������������������������������������������������������������������������������������������������������������������� 19
More MA Plans Get Four-Star Ratings for ’16, but Scores of Humana, WellCare Dip��������������������� 19
2013 to 2016 Overall Star-Rating Distribution for MA-PD Contracts��������������������������������������������� 20
Counter to Recent Stars Trend, Local PPOs Fared Better Than HMOs��������������������������������������������� 23
Plans With 4.5 Stars or More��������������������������������������������������������������������������������������������������������������� 24
Plans With 2.5 Stars or Fewer������������������������������������������������������������������������������������������������������������� 26
Percentage of Plans In Each Star Rating Level������������������������������������������������������������������������������������ 26
2016 Part D Star Ratings for Plans Serving Dual Eligibles��������������������������������������������������������������� 27
CMS Regulation and Guidance������������������������������������������������������������������������������������������������������������ 34
CMS Suspension of Automatic Star-Rating Cuts for Sanctioned Plans Stuns Observers����������������� 34
Star Ratings for Duals����������������������������������������������������������������������������������������������������������������������� 37
Inovalon Study Shows Duals’ Characteristics Yield Poor Health Outcomes�������������������������������������� 37
Personal Engagement, Communication Technology Could Boost Star Ratings and
Health Outcomes for Duals Plans�������������������������������������������������������������������������������������������������������� 37
Diabetes Management Could Help Boost Stars for Struggling Duals Plans�������������������������������������� 38
Stars Memo Offers Two Complex Options to Aid Plans Serving Low-SES Members����������������������� 40
Trade Groups Cite Doubts About CMS’s Two Options for Adjusting Stars for SES������������������������� 43
Impact on Performance ������������������������������������������������������������������������������������������������������������������������ 47
Contract Enrollment for Plans Whose Star Ratings Increased in 2016���������������������������������������������� 47
Contract Enrollment for Plans Whose Star Ratings Decreased in 2016��������������������������������������������� 49
Contract Enrollment for Plans Whose Star Ratings Stayed the Same in 2016����������������������������������� 51
Appendix B: CMS Fact Sheet — 2016 Star Ratings���������������������������������������������������������� 57
Appendix C: CMS Guidance and Documentation for 2017 Star Ratings�������������������� 75
Appendix D: Medicare 2016 Part C & D Display Measure Technical Notes������������� 121
The Challenges of Pharmacy Star Ratings • 1
Introduction
Star ratings on numerous Medicare Part D pharmacy measures continue to present
problems for plan sponsors, especially for stand-alone Prescription Drug Plans (PDPs),
which overall fared worse for 2016 than for 2015 on the quality scores. Factors that
complicate Part D measures include CMS’s changing methodologies for measuring
results, the need to involve PBMs and pharmacies, and the importance of ensuring the
appropriate dissemination of data among these entities.
For the 2016 star ratings, the Regence Blue Cross and Blue Shield-branded Part D
plans operated by Cambia Health Solutions, Inc. made significant gains in pharmacy
metrics, including improvements on managing high-risk medications, and five-star
ratings on cholesterol and hypertension adherence. But many plans, particularly PDPs,
continue to struggle on the adherence measures. This report, The Challenges of Pharmacy
Star Ratings: Solutions for Part D Plan Sponsors and Their Partners, discusses the steps
Cambia and its PBM subsidiary, OmedaRx, took to achieve high ratings on these and
other Part D measures.
The publication provides valuable, practical intelligence and training on how insurers and PBMs can:
u Use a cross-functional, holistic collaborative approach via a population-management model to manage member health and improve star ratings across measures.
u Improve Part D measures for gains in star ratings through better member outcomes.
u Influence Part D improvements through a focus on Part C measures.
u Use incentives and partnerships with providers to drive gains.
This report, The Challenges of Pharmacy Star Ratings: Solutions for Part D Plan
Sponsors and Their Partners, was updated from a spring 2016 virtual conference sponsored by Atlantic Information Services, Inc., “Medicare Star Ratings: New Strategies to
Match CMS’s New Goals,” AIS’s 3rd annual virtual conference on Medicare star ratings. This publication is adapted from the session, “A Coordinated PBM-Health Plan
Approach to Improving Part D Star Ratings,” given by Vivien Chan, Pharm.D., director of quality and cost strategies, OmedaRx, and Kristine Walhof, program director,
Medicare star ratings, Cambia. Both speakers answered tough questions from conference attendees after their session.
Appendices filled with relevant background coverage of industry developments
and other resources give insight into the evolving world of MA star ratings. They
include:
u Appendix A: AIS Coverage of Medicare Advantage Star Ratings, a collection of AIS
articles featuring developments and strategies regarding star ratings from AIS’s biweekly newsletter Medicare Advantage News and data from AIS’s health data division.
u Appendix B: CMS Fact Sheet - 2016 Star Ratings, a CMS document detailing findings and trends from 2016 star ratings.
2 • AIS’s Management Insight Series
u Appendix C: CMS Guidance and Documentation for 2017 Star Ratings, a set of CMS
reports and guidance preparing carriers for 2017 star ratings.
u Appendix D: Medicare 2016 Part C & D Display Measure Technical Notes, a document that describes the metric, data source and reporting time period for each Medicare
Part C or Part D display measure for 2016.
Erin Trompeter
Managing Editor
Atlantic Information Services, Inc.
The Challenges of Pharmacy Star Ratings • 3
The Regence Approach to Stars Improvement
The Regence plans owned by Cambia cover four states: Oregon, Washington, Utah
and Idaho. Regence’s commercial enrollment exceeds 2.4 million members, mostly located in Washington and Oregon. Its Medicare Advantage segment as of January 2016
had more than 100,000 members across all its states, but Oregon and Washington again
had the largest enrollment. Cambia offers both PPO and HMO MA products, with the
majority of its enrollment in PPO plans.
Regence achieved 4.5 stars for its MA plans in the Oregon and Utah markets, and 4
stars in its Washington and Idaho plans. These ratings represent an improvement from
3.5 stars across all its markets for its PPO plans, since its HMO contracts were too new
to be rated in 2015.
Part D Improvements
Regence’s prescription drug event (PDE) rates across its markets averaged a full
star improvement from 2015 to 2016, moving from an average rate of 3.4 in 2015 to 4.4
in 2016. Two Part D measures, both triple weighted, achieved five stars in every plan
for medication adherence for both hypertension and cholesterol.
Regence also had three PDE measures that improved in every state, and four PDE
measures that improved at least one full star in each market. Medication adherence
for hypertension and high-risk medication are both triple-weighted measures, and
Regence plans improved an average of two stars across its markets. Medication adherence for cholesterol improved at least one star in every market. Regence’s Part D improvement measure, which carries a weight of five, improved at least one star in every
market, as well.
Regence’s medication adherence for cholesterol and hypertension both experienced
an average rate improvement of 3%. The insurer’s high-risk medication prescribing
rates dropped 7%.
How It Happened
To drive its improvement from an insurer with its share of 3.5-star plans, Regence
conducted some “soul searching.” That effort started with the understanding that its
members deserved better and that, to be a high-performing plan, it needed to transform the way it managed its measures and interventions.
Regence attributes its 2016 star ratings achievement to tactical and intentional shifts
in how it approaches the star ratings program as a whole. The shift in its program began when it evolved its strategy to align with CMS’s National Quality Strategy.
4 • AIS’s Management Insight Series
The six priorities that are built into the CMS’s National Quality Strategy are:
(1) Making care safer by reducing harm caused by the delivery of care;
(2) Ensuring that each person and family are engaged as partners in their care;
(3) Promoting effective communication and coordination of care;
(4) Promoting the most effective prevention and treatment practices for the leading
causes of mortality;
(5) Working with communities to promote wide use of best practices to enable
healthy living; and
(6) Making quality care more affordable for individuals, families, employers, and
governments by developing and spreading new health care delivery models
These priorities are ingrained into the star ratings program through the measures,
the metrics and the methodologies by which CMS administers it. Regence built its
stars strategy to focus on improving not only the quality of care members receive, but
the way in which they experience that care.
Regence set out to create a cross-functional, member-centric stars program in partnership with its PBM, OmedaRx, another Cambia subsidiary. Historically, Regence had
an internal clinical team that focused primarily on Healthcare Effectiveness Data and
Information Set (HEDIS) stars measures and relied on a pharmacy team to focus on
the PDE measures. Each team would conduct its own interventions, including member
and provider outreach activities. This method was not only fragmented and somewhat
uncoordinated, but it caused dissatisfaction among Regence’s providers and members,
who received multiple contacts and interventions.
Regence’s first step was to move away from the silos and to partner with its pharmacy, clinical, quality and member services teams to build a cross-functional core
dedicated to improving star measures.
The company’s second step was to capitalize on this multidisciplinary expertise,
which added a layer of sophistication and integration to how it tapped into the following key levers and capabilities to drive star improvement:
u Disease management,
u A clinical data strategy,
u Provider engagement, and
u Member experience.
When Regence built its core team and started to integrate both Part C and Part D
metrics, the capabilities that supported stars, into the program, it recognized improvements across an array of measures almost immediately. The company also witnessed a
culture shift within the organization around stars, as its other departments and employees started looking at star ratings and realized that every individual within the
organization can have an impact on its star ratings.
The Challenges of Pharmacy Star Ratings • 5
Improving Medication Adherence
A 2009 American Heart Association study showed that, out of all the prescriptions
for chronic medications written, 12% were never filled, 12% never started and another
29% were not taken as directed. As a result, adherence to chronic medication is reported to be as low as 50%. Considering only 50% of patients are taking their medication as
intended, stakeholders are not able to prevent morbidity and mortality as effectively as
desired.
Poor medication adherence leads to poor health outcomes, which increases service
utilization and increases total cost of care. It is estimated that avoidable medical expenditures associated with poor medication adherence can be as high as up to $290 billion
annually, with an even greater impact on productivity loss on a societal level.
In the star ratings program, medication adherence metrics are triple-weighted measures on cholesterol, hypertension and diabetes medication. These medications have
been proven to produce long-term health benefits, so adherence to these therapies is
crucial.
From 2015 to 2016, Regence took steps to ensure strategic and organizational alignment in order to achieve stars improvement on all three adherence measures . The
member-focused strategy took into consideration the entire prescription life cycle.
When members are new to a targeted treatment, Regence sends educational mailings
to help solidify their understanding of their disease state, the long-term benefit of the
medication and the importance of adherence. On an ongoing basis, Regence delivers refill reminders that are automated based on claims monitoring, as well as low
adherence interactive voice responses that help identify barriers and also offer tips to
overcome those barriers for members. In addition, members have the opportunity to
hold a telephonic consultation with a pharmacist. During the fourth quarter of each
year, Regence deploys a live outreach call to members who are at risk of ending the
year with less than 80% adherence with the goal of assisting members with refills and
promoting 90-day fills.
In 2015, Regence partnered with a company that specializes in health care advanced analytics and is able to incorporate data into predictive models. Specifically,
this model identifies members who are currently non-adherent to their medication and
are also at high risk for developing poor outcomes. Using this model, Regence could
pilot an adherence intervention targeting these high-risk members. In 2016, Regence is
accruing data on the pilot in order to evaluate the effectiveness of this approach.
The Provider’s Role in Adherence
In formulating its provider engagement strategies on medication adherence,
Regence’s guiding principle is to make it easy for providers to do the right thing. In
2016, Regence is launching provider notifications based on the presence of primary
medication nonadherence (PMN) and low adherence indicators.
6 • AIS’s Management Insight Series
PMN occurs when a member is prescribed a new medication but never picks it up.
Regence understands that it won’t be able to capture all cases of PMN, but if the prescription is sent to the pharmacy, processed and later reversed, the insurer can use it as
a proxy for PMN. With the increased adoption of e-prescribing, Regence is hopeful it
will be able to capture more cases of PMN.
Kelly: A Member Case Study
In applying Regence’s adherence strategy to individual members, the insurer using
the example of Kelly, who is newly diagnosed with diabetes and needs to start on a
prescription of Metformin. Kelly’s doctor sends the prescription to the pharmacy, she
picks it up, and a few days later, she receives educational materials about Metformin
in the mail.
If Kelly hadn’t picked up her prescription, her doctor would have received a fax
from the plan, and the office’s nurse would call Kelly to urge her to the pharmacy the
next day to pick up her prescription.
Kelly’s pharmacy offers steep discounts on generic medications, and she has in the
past paid cash for some pharmaceuticals. When the pharmacy runs her Metformin as a
cash transaction, it receives an alert that says, “Kelly is in the Regence plan that offers
competitive generic cost share.” The pharmacy runs the prescription through Regence
and finds the cost share to be affordable.
From this point, Kelly receives automated messages to remind her about refills. If
her adherence drops below 80%, she also receives an automated message to help her
understand what is stopping her from refilling and what she can do to get back on
track. In fact, during a phone call to discuss her low adherence, she describes side effects to a pharmacist, who tells her about a long-acting Metformin tablet that can help
reduce these issues. She is able to have her prescription changed.
In the fourth quarter, Regence calls Kelly because she needs one more refill to keep
her adherence above 80% for that year. The pharmacy technician contacts Kelly after
seeing that she’s been filling a 30-day supply of the Metformin at a time and informs
her about Regence’s 90-day retail benefit. With this benefit, she pays two copays for a
three-month supply.
Kelly’s example incorporates a number of health plan considerations: the 90-day
retail benefit, cash claim conversions, tactical strategies, and provider and member
strategies that come together to help the patient identify opportunities to be more adherent to medications.
Integration with care management is also key. Case management nurses can talk to
a member about issues driving non-adherence such as post-discharge medication reconciliation. This collaboration enables health plans to leverage different touch points
with members.
The Challenges of Pharmacy Star Ratings • 7
High-Risk Medication Measure
The high-risk medication (HRM) measure is another important metric in driving
stars performance. HRMs are those identified on the Beers Criteria list, later adopted
by CMS. These drugs have been linked to falls, fractures and other adverse events. It is
recognized, though, that there are unique clinical situations where an HRM is the only
reasonable option for an elderly member. The goal of this metric is not to drive utilization to zero, but to minimize use and mitigate associated risks.
The way the metric is calculated, the first fill of a high-risk medication in a calendar
year doesn’t count negatively to a plan. But once the patient obtains a second fill, then
the member becomes part of this numerator. In this case, a lower rate means better
performance.
From 2015 to 2016, Regence plans’ performance on the HRM measure improved by
one to two stars. Much like with the adherence measures, the improvement was the
result of a combination of strategies. Unlike the approaches that Regence took for improving adherence, which more heavily emphasize motivating the member, the HRM
strategies depend more upon provider engagement.
Regence uses medication therapy management programs not only for retrospective
drug utilization reviews, but also in its quality incentive program for providers. The
incentive program is supported by a provider pool that allows the sharing of utilization and progress reports. At regularly scheduled provider group meetings, pharmacies participate in sharing performance measures and best practices.
Regence also works with pharmacy departments that are embedded in provider
groups and health systems, sharing best practices and providing them with information that can help them identify which Regence members to prioritize in addressing
a trend. Since these pharmacy departments have a much closer working relationship
with their providers, they often carry out the actual interventions.
In 2015, Regence tried a couple of new approaches, such as adding live outreach to
providers when the first fill of a targeted HRM is detected. The calls’ intent is to bring
attention to the HRM used and suggest a safer alternative.
Another strategy Regence tried in 2015 was to be more strategic in targeting certain
members and providers in letters and campaigns. For example, for estrogen, Regence
identified patients who were on both anticoagulants and estrogen and sent letters to
the prescribers of the anticoagulants to ask them to consider making therapy changes.
When it comes to estrogen use in general, it is often the member who drives that
decision, so Regence decided to identify which members might be the most receptive
to the idea of discontinuing estrogen. It targeted members over age 75 or those who
have multiple concurrent medications, with the message to discuss with their providers whether there is still a clinical need to continue estrogen therapy.
One of the most effective strategies to manage HRMs Regence initiated is the addition of prior authorization, which began in 2014. With prior authorization, the pre-
8 • AIS’s Management Insight Series
scriptions of the targeted HRMs must be reviewed and approved before coverage is
determined. In addition, HRMs are moved to non-preferred formulary tiers, aligning
member incentives to favor the safer alternative.
When leveraging analytics, Regence also learned that most of the first and second
fills of HRMs occur in the first quarter of the year, so if the insurer wants to start a new
HRM program, it should have it up and running before the start of the year.
The decision to use an HRM is ultimately between the prescriber and the patient,
but through the programs, Regence can strive to support that shared decision-making
by introducing the right information, tools and incentives.
Regence has paid attention to targeting the right members to intervene, and has
been leveraging the integration of pharmacy and medical data. Looking ahead into
the new quality measures for star ratings, Regence will continue to improve its data
integration.
For 2018, CMS has identified potentially adding post-discharge medication reconciliation and statin use in diabetics as star measures. The asthma management measure
is also under consideration as a star measure in 2018.
The Challenges of Pharmacy Star Ratings • 9
Interventions and Programs
Regence has several interventions and programs in place that traditionally were focused on Part C measures, but actually have a greater influence on Part D when managed holistically with OmedaRx. These programs include:
Disease management. The goal of Regence’s disease management program is to optimize clinical outcomes for participating members through education and care coordination. The company targets candidates for disease management programs based on
condition, looking for members with diabetes, congestive heart failure, hypertension
and chronic obstructive pulmonary disease (COPD). The insurer has an internal team
of disease management nurses who engage members to influence behavior modification through education and counseling, in addition to coordination with the member’s
primary care provider (PCP).
The nurses integrate pharmacy education into these discussions specifically around
medication management and reconciliation, medication adherence, and the potential side effects of high-risk medications. Regence’s nurses want to ensure members
understand how to take their prescriptions, and that they are actually being taken as
prescribed.
By incorporating Part D measures into its disease management scripts and protocols, Regence has discovered it can better identify factors or barriers that could have
a negative impact on a member’s ability to successfully manage his or her condition.
One example might be a member who lacks transportation to see his PCP, or another
who can’t afford her prescription medication. When Regence can identify those factors
and barriers and remedy them, it can see an increase in Part C and Part D gap closure,
which drives improved outcomes.
Another intervention Regence conducted is its readmission prevention program.
The company has a clinical team dedicated to conducting proactive member outreach
post-discharge. This outreach is performed telephonically to help manage care transitions. The team makes sure the member or his or her caregiver fully understands the
discharge plan.
The team also aims to perform the following tasks:
u Ensure the member has access to prescriptions, and that those prescriptions are being taken as prescribed.
u Make sure any ancillary services or supplies that were ordered have been delivered, or at least scheduled, including any durable medical equipment, home health or
physical therapy services.
u Perform a medication reconciliation review and direct coordination with the PCP to
schedule post-discharge follow-up.
Regence has also instituted a fall prevention program, which can include a medication review and reconciliation as a key part of reducing the risk of falling.
10 • AIS’s Management Insight Series
In addition, Regence has a comprehensive in-home assessment program for chronically complex members. In this program, the insurer sends providers into the home
to conduct full health risk assessments, including looking at medications, reconciling
medication lists and conducting a full risk assessment. The provider sends the assessment and any alerts to the health care plan and to the member’s PCP for ongoing care
coordination.
Provider Engagement
Engagement with the PCP is a critical piece of most of Regence’s disease management programs and is a key lever for its stars improvement strategy as well. It’s been
estimated that up to 60% to 70% of a plan’s ratings are driven by the provider. It is
imperative for plans to align their incentives and manage the quality of care delivered
within the network.
Myriad incentives exist in the market, and they come in all different shapes and
sizes. Regence has had numerous programs in place, as well, and they are designed
to drive improved quality outcomes and value. Regence has learned in its provider
engagement strategy that it needs to partner with its providers to make sure its incentive programs align with clinical objectives. The company also wants to make sure its
incentive programs are actually rewarding quality performance and not just giving
providers a list of boxes to check or hoops to jump through.
Regence also finds it’s important to streamline its metrics to limit the number of
items it asks providers to track. Providers are asked to perform many tasks for all their
payers, so plans’ best chance to engage their providers fully comes in making sure
requested tasks can actually be integrated into their day-to-day workflow.
Regence has pay-for-performance incentive programs in partnership with its providers that are based on a number of quality indicators, including coding and documentation accuracy, quality scores for HEDIS and PDE measures, and financial performance indicators.
Education and ongoing feedback are also key components to Regence’s provider
engagement strategy. The insurer deploys a cross-functional team, called a SWAT
team, that is armed with performance data and meets with providers to offer education and invite collaboration and dialogue to work together to improve member
health.
The SWAT team includes members from Regence’s pharmacy team, as well as
revenue management, provider network, stars, quality and sales. The team aims to
meet monthly with providers to identify opportunities for performance improvement.
Because conversations in these meetings are performance-driven, Regence is dependent on complete, accurate and timely data. The insurer emphasizes data exchange to
help both the PCPs and the health plan get a comprehensive, holistic picture of patients’ health status and their performance.
The Challenges of Pharmacy Star Ratings • 11
The Clinical Data Strategy
Regence recognizes that there are multiple sources of data it can leverage for a variety of activities that can drive quality outcomes and improve the member experience,
including claims data, risk scores, consumer data, lab values, biostatistics, health risk
assessments and pharmacy claims. All these elements help paint a picture of members
and their health status, as well as their preferences and potential risk factors. Having
visibility into these types of data is critical and fundamental to Regence’s population
health models and initiatives.
Once Regence has the data, it uses clinical data to identify members with gaps in
care, and then stratifies these members based on risk factors. The insurer develops interventions designed to close those gaps and uses the data to develop predictive models to help project member behavior.
Predictive analytic capabilities have evolved. Historically, the 80/20 rule meant
that 20% of the members drive 80% of the claims. Trying to get a better picture of who
those 20% are and trying to predict what they’re going to do next, Regence looks at
diagnoses and utilization.
The insurer now has many more factors that it can use to predict behavior. Among
the sources data scientists review is prescription drug history, including the number of
prescriptions and adherence levels. The insurer also can look at the number of different provider visits and ER utilization. Social factors also come into play, like whether
members have a transportation issue, are homebound, have a social support system or
are living in rural vs. urban situations. There are many factors that Regence can pull
into its data analytics to enhance its models.
Regence uses predictive analytics to identify who is most likely to adhere to a
medication, who might be more likely to be readmitted to a facility, who might take a
fall and whether that fall could result in an injury, and who is more likely to be compliant with preventive screenings.
The insurer can also use consumer preferences to tailor interventions and outreach
to better meet the needs of its members. Electronic medical record (EMR) alerts and
admissions information help the company identify opportunities to impact some
event-driven measures, including readmissions, osteoporosis if a female presents with
a fracture, or COPD or asthma episodes.
Regence incorporates a large amount of data into its analytics — but the quality of
outputs is dependent on how complete the inputs are. Providers use risk stratification
models in their practices, but they often tell Regence that they don’t have complete
data on their end, either. As a health plan, Regence has disability data that the providers lack in the form of claims data or pharmacy claims data, for example. Providers in
turn have data that insurers don’t — information found in the EMR, lab values and
blood pressure readings, for example.
12 • AIS’s Management Insight Series
Ideally, plans and providers can have an efficient flow of data exchange. Insurers’
clinical decision-making is based on complete and accurate data at the time of the patient encounter with the provider, so the insurer has patient/provider data in the same
place at the same time.
Through its clinical data strategy, Regence aims to capture a comprehensive view
of the health status of all members so it can engage them in a holistic manner based on
their preferences. This approach invites members to actively participate in their health
care in a way that works for them.
Optimizing Member Experience
Regence’s fourth — and perhaps most important — lever is optimizing the member
experience as members navigate through their health journey. Coordinated outreach
optimizes member contacts: Regence wants members to have a positive experience
when they interact with the insurer as a health plan, and wants members to be actively
engaged in their health. To achieve that, Regence must be coordinated internally to be
thoughtful and intentional in the way it engages members. Regence strives to provide
concierge-level service for members where its outreach is coordinated and delivered
in a manner that addresses the member holistically. The insurer also aligns its member
and provider messaging so initiatives are focused and targeted.
Having complete Medicare Part C and Part D gap information available at the
time of the outreach enables the insurer’s team to have a single conversation with the
member. That single conversation can address anything applicable to that member
around gaps in care, PCP selection, chronic disease management, medication adherence or safer alternatives to high-risk medication — and all issues can be addressed in
one phone call.
Regence also utilizes personas to make sure its outreach is member-centric and
relevant. The personas have become part of its program development, because when it
develops outreach initiatives, it helps to personalize the impact of those campaigns.
Meet Polly
One of Regence’s personas is Polly, age 70, who is hypertensive, but is on top of
her health and current with her preventive screenings. She has a good rapport with
her PCP and checks in at least once a year for her annual wellness visit. She’s flying
under the radar until she has an event — it’s icy outside, and she slips, has a fracture
and is admitted to a facility. Before she goes home, she is given a high-risk medication.
Since she has been admitted, she has been unable to go to the pharmacy to pick up her
hypertension medication.
Suddenly, Polly is triggering all sorts of stars alerts on Regence’s end. She has the
osteoporosis management flag and is now at risk of a readmission. She has alerts for
her high-risk medication and her medication adherence.
The Challenges of Pharmacy Star Ratings • 13
When Regence looks at its personas, it thinks of how to communicate with Polly
to make sure that she gets the care she needs in the manner that she prefers. She is a
great example of a member who has had a handful of care needs that traditionally may
have been managed by multiple people within Regence and across the continuum of
care. But with its member experience strategy and stars improvement strategy, utilizing its four levers — disease management, clinical data, provider engagement and the
member experience strategy — Regence can be intentional and mindful in how it coordinates Polly’s transitional care management, through the combined expertise of its
pharmacy team, disease management nurses and care managers and her PCP. While
the insurer may have a lot of activity and personnel working on her transition plan,
from her vantage point, ideally, her road to recovery is seamless and fluid.
The Challenges of Pharmacy Star Ratings • 15
Q&A Session
Question: What is the makeup of your concierge team?
Kristine Walhof: We have 80 member service specialists in total that are fully trained
on how to engage with our Medicare Advantage members. We work very closely with
them. We also work with our care management team to make sure there is some alignment between what outreach is happening, and when and who is being outreached.
So, there is a coordinated effort to ensure our members aren’t being over touched. A
little Regence goes a long way. So if we can only reach out once and be very purposeful and intentional with that, we get better results.
Question: How do you coordinate that one-time call with the needs of member
availability?
Walhof: That is one of our challenges. We are still evolving our processes. But it really
is dependent on getting all of our data pulled together and having a good understanding of what that member needs, and utilizing our internal systems to make sure that
we do have the gap data and member preference data front and center before those
calls are made.
Question: Vivien touched on some of the upcoming changes to the star ratings program. Statins used in diabetics was one of those identified for 2018. How is that different
from the retired diabetes treatment measure, and what challenge does that present?
Vivien Chan: For the statin measure, we are at a point where we have a better coordinated approach, whether it’s a quality incentive program or engagement with providers. I think that would be good leverage for us now compared to previous years
where we didn’t have as strong of a structure in that area. What we’re trying to look at
now is partnering with our care management team, who is already doing some of the
care gap closure work, and trying to understand where the members overlap between
their identification and targeting process and our targeting process, and where are the
different touch points possible where we can insert this measure. We’re having those
conversations now pretty early on, and mapping out organizationally where the touch
points are and how we can approach people with these touch points without duplicating effort to drive this gap closure.
Question: On the 2018 display measures, how much of opioid overutilization are you
incorporating into this integrated approach?
Chan: That’s a very good question. Opioids are a hot topic these days, whether it’s
in the Medicare population or just in the general commercial world. What we have
in place currently is a lot of the things that other plans have been doing: OMS [the
Medicare Part D Overutilization Monitoring System] and the overutilization monitoring that CMS has mandated. We are looking into how to better target these people. We
have some internal pilots that were started in the commercial population. We’re trying
to learn from that, because anytime when we are looking at opioid overutilization, it
really isn’t just about the Part D measures; it really is taking into consideration the care
16 • AIS’s Management Insight Series
of a member. Are they using physical medicine? Are they using other types of pain
control? Are there fraud, waste and abuse issues that are coming up? So, I think it’s
really looking at the holistic approach of how can we get more in tune with the right
measure.
Right at this moment we are mainly doing the Medicare mandated programs. But
through the pilots that we have in place for commercial, which is more of a cross-functional, multidisciplinary review of the top category of patients that are identified, we
are hoping to learn something from that pilot and see if there are any ways to apply
some of the learnings in our Part D world.
Question: We’ve got one more question for you about these measures for the statin use
and diabetes measure. What are your thoughts around overcoming the October 2015
FDA warning that statin use causes type 2 diabetes?
Chan: Isn’t that a perfect storm? I think we are going to have to dive into that clinical
evidence a little bit more to understand that, and to see if there are any subgroups of
patients that we need to be paying attention to in terms of applying our strategies differently. We’re pretty early on in looking at that data. We’ll have more coming up.
Question: This is a question for Kristine. Going back to the concierge team, do you use
clinicians, non-clinicians? What is the makeup of that team?
Walhof: We are still evolving how that team is going to function. It’s really more of a
concept at this point. We want our member services team and our clinical team, when
they are reaching out to the member, to be able to incorporate all of the relevant information for that member. We have clinicians reaching out. We have member services
folks reaching out. We have non-clinician members of our clinical team reaching out
as well. Our goal is to make sure that whenever anyone is picking up the phone, they
have an understanding already of what other contacts were made so that they are
better able to address the whole needs of that member. We’re still evolving with the
concept, trying to make it a little bit more broad based. But the concept is one that has
changed the way we interact with our members.
Question: Could you clarify about the timing of the efforts you undertook to integrate
all these different areas of expertise?
Walhof: It started early 2014 throughout 2015, and they continue to evolve. I think
that’s the beauty of the star ratings program. You can’t just sit still. You have to continue to look at your processes, who is part of your program, and who is helping to drive
improvement so that we can continue to meet the needs of our members and continue
to see improvement.
Question: This question is for Vivien. Can you identify the predictive analytics firm
that you partnered with?
Chan: Not at this point. I think it’s a proprietary issue that we have in agreement with
the firm. So, unfortunately not at this point.
The Challenges of Pharmacy Star Ratings • 17
Question: How are the member-focused strategies and the provider-focused strategies that you mentioned triggered? Are there alerts sent from regions that these people
need to be intervened with?
Chan: A lot of these are triggered real time. There are ones that are triggered real time
by our pharmacy claims monitoring. There are also certain ones with the targeted
mailings that I talked about. Those are retrospectively pulled from the pharmacy
claims data, and we apply analytics to it before we send out the targeted mailing. So,
there are two types. One is real time, like the IVRs [interactive voice response]. The
primary medication nonadherence pieces and provider faxes are real time. We have
certain logics that are built in to make sure that we’re not over-communicating within
a certain timeframe. Let’s say if a member has multiple adherence issues, we’re not
going to keep bombarding them with that. There are certain parameters we have built
around that to cap the number of communications that will be going out. Then the retrospectively reviewed data that are pertaining to some of the targeted mailings, those
are done after the claims have accumulated over a certain time period.
Question: I have another clarification for Kristine. You mentioned up to 60% to 70% of
plans ratings are driven by a provider. Is that Part D plans in general?
Walhof: This would be your overall star ratings, so looking at your HEDIS metrics and
looking at Part D. It’s combined. And it’s an estimate. You look at who is really the
largest influencer of getting gaps closed. But a lot of that is being driven by our providers. That’s one of our critical strategies to make sure the providers in our networks
are really working to be five star level providers.
The Challenges of Pharmacy Star Ratings • 19
Appendix A: AIS Coverage of Medicare
Advantage Star Ratings
Results for 2016 Plans
More MA Plans Get Four-Star Ratings for ’16, but Scores of
Humana, WellCare Dip
There were lots of winners and some losers in the 2016 star quality ratings unveiled
by CMS Oct. 8, 2015, and several in both categories were affected substantially, industry consultants tell AIS, by this being the first year the agency didn’t have fixed fourstar thresholds that plans knew before getting rated. Overall, there were considerably
more Medicare Advantage prescription drug plans — 49% versus 40% of contracts in
2015 — and more big plans getting four stars and above, and the percentage of MA-PD
enrollees in those plans leaped to 71% from 60%. But there also was what one observer
called abundant “churn” in the top performers, and differing directions in performance of MA-PDs versus stand-alone Prescription Drug Plans (PDPs).
The winners in the new rankings included some of the “usual suspects” — five
Kaiser Permanente plans and other vertically integrated insurers, especially in New
England and the upper Midwest — that got the top five-star rating. However, seven of
the 17 plans (including MA-only and PDPs) receiving the top rating are new to the list,
including several for-profit plans. There were 12 MA-PD five-star plans, up from 11 in
2015.
Most publicly held insurers made gains in their enrollment-weighted star ratings
for 2016, according to securities analyst Thomas Carroll of Stifel. Aetna Inc. had the
highest average rating among them at 4.3, up from 3.9 in 2015, and industry giant
UnitedHealth Group, while trailing many others with a 3.9 average rating, was up
from 3.5 in 2015.
The losers in the new ratings, Carroll’s analysis shows, include Humana Inc.,
which had strong gains in 2015 but had its enrollment-weighted average drop to 4.0 in
2016 from 4.2 and lost its only five-star rating, for a CarePlus Health Plans, Inc. unit
in Florida. Also in the minus column was WellCare Health Plans, Inc., which dipped to
a 3.1 average from 3.2 and has two of the six plans that will get CMS’s Low Performer
Icon (LPI) for 2016 because of consistently low star scores.
In addition, there are some losers by plan type and location, and analysts offered
varying reasons and implications for those. PDPs, for instance, dropped from 2015 in
the number of contracts earning 3.5 stars and above and rose in contracts with ratings
of 2.5 and two stars.
20 • AIS’s Management Insight Series
Perhaps an indirect loser in the new ratings is MA Special Needs Plans (SNPs) —
but for an unusual reason. CMS included a column in the 2016 ratings that showed
whether each of the 12 five-star MA-PD contracts had SNPs as part of their contracts,
and seven of them did. Analysts queried by AIS concurred that this could hurt SNPs
in their pleas for relief in the star ratings, which they contend unfairly penalize plans
serving highly disadvantaged populations.
However, Stephen Wood, a principal in Clear View Solutions, LLC, says that the
SNP-related data in CMS’s table can be misleading. He cites as an example a millionmember Kaiser five-star contract that has only 60,000 SNP members, all of them
Medicare-Medicaid dual eligibles. “So the SNP didn’t really contribute to the five
stars” and thus should not enable CMS to argue that SNPs don’t need stars help, Wood
tells AIS.
The MA-PD contracts getting the top rating are Cigna HealthCare of Arizona,
Inc., Essence Healthcare, Inc. in Illinois and Missouri; Group Health Plan, Inc. in
Minnesota and Wisconsin; Gundersen Health Plan in Iowa and Wisconsin; Kaiser
units in California, Colorado, Hawaii, the Mid-Atlantic states and the Northwest;
Martin’s Point Generations, LLC in Maine and New Hampshire; Sierra Health and
Life Insurance Co., a United unit, in nine states (representing Erickson Advantage
plans for Erickson retirement communities); and Tufts Associated Health Maintenance
Organization in Massachusetts.
MA-only contracts that got five stars are Medical Associates Health Plan, Inc.
in Iowa and Illinois; Medical Associates Clinic Health Plan in Wisconsin; and Dean
Health Plan, Inc. in Wisconsin.
The six contracts getting the LPI for 2016 are Cuatro LLC — known as Access
Medicare — in New York; GHS Managed Health Care Plans, Inc. (owned by Health
Care Service Corp.) in Oklahoma; Touchstone Health HMO, Inc. in New York; United’s
Sierra unit in Utah; WellCare of Louisiana, Inc.; and WellCare’s Windsor Health Plan,
2013 to 2016 Overall Star-Rating Distribution for MA-PD Contracts
2013
2014
Overall
Rating
Number
of
Contracts
Weighted
Number
by
of
% Enrollment Contracts
5 stars
11
2.46
9.42
4.5 stars
54 12.08
4 stars
%
3.25
10.23
19.59
65 17.62
25.02
86 21.77
30.32
102 27.64
35.71
30.49
136 34.43
26.78
112 30.35
19.55
16.63
73 18.48
10.98
66 17.89
8.60
2.37
12
3.25
0.90
0.08
0
0.00
0.00
9.56
15.81
64 14.85
62 13.87
12.56
3.5 stars
131 29.31
3 stars
2 stars
Total
Contracts
Average
Star
Rating*
Number
of
Contracts
2016
Weighted
by
Enrollment
2.55
2.5 stars
9.88
20.55
61 15.44
87 20.19
21.68
36.48
143 33.18
127 28.41
20.25
109 25.29
60 13.42
5.28
16
3.71
1.09
26
6.58
0.21
1
0.23
0.01
2
0.51
0.45
447
431
3.71
11
Weighted
Number
by
of
% Enrollment Contracts
2.78
2
11
2015
Weighted
by
% Enrollment
395
3.86
* The average star rating is weighted by enrollment.
SOURCE: CMS Fact Sheet on 2016 star ratings released Oct. 8, 2015.
12
369
3.92
4.03
The Challenges of Pharmacy Star Ratings • 21
Inc. in Arkansas, Mississippi, South Carolina and Tennessee. CMS added a footnote
indicating that the Cuatro, Sierra and Windsor contracts are “eligible for termination at
the end of 2016.”
Looking at the overall implications of the new stars data, John Gorman, executive
chairman of Gorman Health Group, LLC, asserts that not-for-profit plans continue to
“stomp for-profits” in achieving high scores. About 70% of the not-for-profit contracts
got four stars or above, he tells AIS, while just 39% of the for-profits did.
SNP contracts improved at about the same rate as MA HMOs, according to
Gorman, achieving an average star rating of 3.61, up from 3.47 in 2015. HMOs and
PPOs gained to 3.87 from 3.79, he says, adding that the SNP gains are “a very big deal”
and may “debunk” in CMS’s mind the arguments for special treatment.
Gorman cautions that the overall star-ratings climate will change significantly for
2017, noting that only 369 MA-PDs got rated for 2016 but 188 others will be in 2016
because of several factors, including a CMS change in the minimum size qualifying for
star ratings from 1,000 members to 500.
Looking at the MA results as a whole, stars specialist Jane Scott, who recently
became senior vice president of professional services for Health Integrated, says that
there was “not much improvement” from 2015 to 2016. “Measures moved; the industry didn’t,” she tells AIS, referring to such aspects as restored, new, dropped and modified star measures as well as the first year without four-star cut-points that let plans
know in advance what they’ll have to achieve to get that rating.
She points to such reductions as from 4.2 for 2015 to 3.2 for 2016 in the average
score for colorectal cancer screening and from 4.2 to 3.3 in diabetes care – kidney
disease monitoring as among indicators that the trend was mixed. There also was a
drop from 3.7 to 3.1 on diabetes care – eye exam and from 4.6 to 3.3 in improving or
maintaining physical health. Some of these reductions, Scott suggests, result from lack
of sufficient member engagement since the services are available but need a “member
response” to get done.
On the positive side of the MA star-ratings ledger were gains in several measures
that plans have scored poorly on in the past. Improving or maintaining mental health,
for example, went from 2.5 to 3.3, monitoring physical activity from 2.2 to 2.9 and
osteoporosis management from 2.1 to 2.5. Even diabetes care — blood sugar controlled
went from 3.3 to 3.9.
Some of the big changes for plans this time were on Part D measures, and there
were different trends among MA-PD plans versus PDPs. “Medication adherence for
diabetes medications,” for instance, improved from 3.5 to 3.9 for MA-PDs but fell from
3.0 to 2.7 for PDPs.
Most of the moves, though, were in same direction, including appeals auto-forwarded (up from 3.6 to 4.5 for MA-PDs and from 2.5 to 4.1 for PDPs) and appeals
upheld (down from 3.7 to 3.3 for MA-PDs and from 3.9 to 3.1 for PDPs). Scott points
22 • AIS’s Management Insight Series
out that auto-forwarding is a process measure, while appeals upheld relates to the
substance of the appeals. And the downward movement in the latter category, suggests Wood, “has everything to do with drug prices,” including substantial increases
in copayments to help plans offset big price hikes and expensive new drugs.
Several of the analysts saw some of the measure scores involved indicating that
plans must push their pharmacy benefit managers (PBMs) harder to aid them. The
average stars score for price accuracy on the CMS Medicare Plan Finder, for example,
plummeted from 4.6 to 3.5 for the MA-PDs, and the MPF is a “PBM function,” Wood
remarks.
While PDPs did well on that measure, remaining at 4.7 stars for 2016, the decline in
PDP ratings overall (to an average of 3.4 stars from 3.75 in 2015) was the biggest surprise in the new ratings, says Michael Lutz, a director in the health reform practice at
consulting firm Avalere Health LLC. Part of the explanation for this, he tells AIS, lies
in changes on how some of the measures are calculated from year to year, and another
factor was a new measure, comprehensive medication review completion rates in
medication therapy management programs, which got an average score of just 2.3 for
both MA-PDs and PDPs.
Along similar lines, he notes, CMS retired for 2016 a diabetes-related measure on
which plans had done well, although it also restored breast-cancer screening and callcenter foreign-language availability measures — not used in 2015 for methodologychange reasons — on which plans did well. For the PDPs, a bigger factor than new or
restored measures was complaints about the drug plan, for which the average score
fell from 4.3 in 2015 to 3.5 for 2016. Lutz speculates that the causes of this could include PDPs instituting more copayment tiers to deal with rising drug prices.
And the impact of any one sharp star-measure score decline is bigger for PDPs than
for MA-PDs, he adds, since there are far fewer rating measures for the PDPs. Still that
couldn’t explain the entire downward trend for PDPs, especially since average scores
on all three medication-adherence measures were down from 2015 to 2016 for PDPs,
while all three were ip for MA-PDs.
The Challenges of Pharmacy Star Ratings • 23
Counter to Recent Stars Trend, Local PPOs Fared Better Than
HMOs
Local Medicare Advantage PPOs narrowly beat MA HMOs in terms of average MA Star Ratings Quality Performance
By Plan Type, 2012-2016
CMS star quality ratings for 2016, acEnrollment-weighted average star rating
cording to an analysis of the new ratings
4.5
prepared by consulting firm McKinsey &
Co. in October 2015. The PPOs, McKinsey
4.0
said, have an enrollment-weighted star
rating of 4.16 for 2016, the first time in the
3.5
four years tracked that PPOs have scored
HMO/HMO-POS
better on this basis than have HMOs. MA
3.0
Local PPO
private-fee-for-service plans and regional
PFFS
Regional PPO
PPOs continued to trail the two leaders.
2.5
2013
2014
2016
2012
2015
Other findings from the analysis include
Note: PFFS=private fee for service; POS=point of service.
that the change in CMS’s “cutpoint”
SOURCE: McKinsey & Co. analysis of CMS’s 2016 Part C
methodology starting in 2016 to not have
& D Medicare star rating data; October 2015. View the
full report at http://healthcare.mckinsey.com/assessingpredetermined thresholds for earning
2016-medicare-advantage-star-ratings.
a four-star rating on individual scoring
measures had only a negligible net impact on differences in MA plans’ overall stars performance between 2015 and 2016.
24 • AIS’s Management Insight Series
Plans With 4.5 Stars or More
Contract
Number
Organization
Type
Parent Organization
Contract Name
2016 Overall
Rating
H0354
Local CCP
CIGNA
CIGNA HEALTHCARE OF ARIZONA, INC.
5
H0524
H0630
H1230
H2150
Local CCP
Kaiser Foundation Health Plan, Inc.
KAISER FOUNDATION HP, INC.
5
Local CCP
Kaiser Foundation Health Plan, Inc.
KAISER FOUNDATION HP OF CO
5
Local CCP
Kaiser Foundation Health Plan, Inc.
KAISER FOUNDATION HP, INC.
5
1876 Cost
Kaiser Foundation Health Plan, Inc.
KAISER FNDN HP OF THE MID-ATLANTIC STS
5
5
H2256
Local CCP
Tufts Associated HMO, Inc.
TUFTS ASSOCIATED HEALTH MAINTENANCE
ORGANIZATION
H2462
H2610
H5262
H5591
1876 Cost
HealthPartners, Inc.
GROUP HEALTH PLAN, INC. (MN)
5
Local CCP
Essence Group Holdings Corporation
ESSENCE HEALTHCARE, INC.
5
Local CCP
Gundersen Lutheran Health System Inc. GUNDERSEN HEALTH PLAN
5
Local CCP
Martin's Point Health Care, Inc.
MARTIN'S POINT GENERATIONS, LLC
5
5
5
H5652
Local CCP
UnitedHealth Group, Inc.
SIERRA HEALTH AND LIFE INSURANCE
COMPANY, INC.
H9003
H0332
H0609
H0710
H1019
H1170
H1365
H1463
H1468
Local CCP
Kaiser Foundation Health Plan, Inc.
KAISER FOUNDATION HP OF THE N W
Local CCP
Kelsey-Seybold Medical Group, PLLC
KS PLAN ADMINISTRATORS, LLC
4.5
Local CCP
UnitedHealth Group, Inc.
PACIFICARE OF COLORADO, INC
4.5
Local CCP
UnitedHealth Group, Inc.
UNITEDHEALTHCARE INSURANCE COMPANY
4.5
Local CCP
Humana Inc.
CAREPLUS HEALTH PLANS, INC.
4.5
Local CCP
Kaiser Foundation Health Plan, Inc.
KAISER FOUNDATION HP OF GA, INC.
4.5
Local CCP
Martin's Point Health Care, Inc.
MARTIN'S POINT GENERATIONS, LLC
4.5
Local CCP
The Carle Foundation
HEALTH ALLIANCE CONNECT, INC.
4.5
Local CCP
Humana Inc.
HUMANA BENEFIT PLAN OF ILLINOIS, INC.
4.5
4.5
H1537
Local CCP
UnitedHealth Group, Inc.
UNITEDHEALTHCARE INSURANCE COMPANY
OF NEW YORK
H1608
Local CCP
Aetna Inc.
COVENTRY HEALTH AND LIFE INSURANCE
COMPANY
4.5
H1609
Local CCP
Aetna Inc.
AETNA HEALTH, INC.
4.5
4.5
H1951
Local CCP
Humana Inc.
HUMANA HEALTH BENEFIT PLAN OF
LOUISIANA, INC.
H2001
Local CCP
UnitedHealth Group, Inc.
SIERRA HEALTH AND LIFE INSURANCE
COMPANY, INC.
4.5
H2226
H2228
Local CCP
UnitedHealth Group, Inc.
UNITEDHEALTHCARE INSURANCE COMPANY
4.5
Local CCP
UnitedHealth Group, Inc.
UNITEDHEALTHCARE INSURANCE COMPANY
4.5
H2230
Local CCP
Blue Cross and Blue Shield of
Massachusetts, Inc.
BCBS OF MASSACHUSETTS HMO BLUE,
INC.
4.5
H2261
Local CCP
Blue Cross and Blue Shield of
Massachusetts, Inc.
BCBS OF MASSACHUSETTS HMO BLUE,
INC.
4.5
H2320
H2354
H2419
H2422
H2459
Local CCP
Spectrum Health System
PRIORITY HEALTH
4.5
Local CCP
HealthPlus of Michigan
HEALTHPLUS OF MICHIGAN
4.5
Local CCP
South Country Health Alliance
SOUTH COUNTRY HEALTH ALLIANCE
4.5
Local CCP
HealthPartners, Inc.
HEALTHPARTNERS, INC.
4.5
Local CCP
UCare Minnesota
UCARE MINNESOTA
4.5
H2802
Local CCP
UnitedHealth Group, Inc.
UNITEDHEALTHCARE OF THE MIDLANDS,
INC.
4.5
H3132
H3204
H3305
Local CCP
AIDS Healthcare Foundation
AHF MCO OF FLORIDA, INC.
4.5
Local CCP
Presbyterian Healthcare Services
PRESBYTERIAN HEALTH PLAN
4.5
Local CCP
MVP Health Care, Inc.
MVP HEALTH PLAN, INC.
4.5
H3344
Local CCP
Independent Health Association, Inc.
INDEPENDENT HEALTH BENEFITS
CORPORATION
4.5
The Challenges of Pharmacy Star Ratings • 25
Plans With 4.5 Stars or More (continued)
Contract
Number
Organization
Type
Parent Organization
Contract Name
2016 Overall
Rating
H3362
Local CCP
Independent Health Association, Inc.
INDEPENDENT HEALTH ASSOCIATION, INC.
4.5
H3388
Local CCP
Capital District Physicians' Health Plan,
Inc.
CAPITAL DISTRICT PHYSICIANS' HEALTH
PLAN, INC.
4.5
H3447
Local CCP
Anthem Inc.
HEALTHKEEPERS, INC.
4.5
4.5
H3471
Local CCP
The Carle Foundation
HEALTH ALLIANCE NORTHWEST HEALTH
PLAN, INC.
H3597
H3664
H3668
Local CCP
Aetna Inc.
AETNA HEALTH, INC. (ME)
4.5
Local CCP
Aultman Health Foundation
AULTCARE HEALTH INSURING CORPORATION
4.5
Local CCP
Trinity Health
MOUNT CARMEL HEALTH PLAN, INC.
4.5
4.5
H3817
Local CCP
Cambia Health Solutions, Inc.
REGENCE BLUECROSS BLUESHIELD OF
OREGON
H3907
H3916
H3952
H3954
H3957
H4454
H4461
H4604
H4605
H5010
Local CCP
UPMC Health System
UPMC HEALTH PLAN, INC.
4.5
Local CCP
Highmark Health
HIGHMARK SENIOR HEALTH COMPANY
4.5
Local CCP
Independence Health Group, Inc.
KEYSTONE HEALTH PLAN EAST, INC.
4.5
Local CCP
Geisinger Health System
GEISINGER HEALTH PLAN
4.5
Local CCP
Highmark Health
KEYSTONE HEALTH PLAN WEST, INC.
4.5
Local CCP
CIGNA
HEALTHSPRING OF TENNESSEE, INC.
4.5
Local CCP
Humana Inc.
CARITEN HEALTH PLAN INC.
4.5
Local CCP
UnitedHealth Group, Inc.
UNITEDHEALTHCARE OF UTAH, INC.
4.5
Local CCP
Cambia Health Solutions, Inc.
REGENCE BLUECROSS BLUESHIELD OF UTAH
4.5
Local CCP
Cambia Health Solutions, Inc.
ASURIS NORTHWEST HEALTH
4.5
H5042
Local CCP
Capital District Physicians' Health Plan,
Inc.
CDPHP UNIVERSAL BENEFITS, INC.
4.5
H5050
Local CCP
Group Health Cooperative
GROUP HEALTH COOPERATIVE
4.5
4.5
4.5
H5211
Local CCP
Marshfield Clinic Health System, Inc.
SECURITY HEALTH PLAN OF WISCONSIN,
INC.
H5215
Local CCP
Ministry Health Care, Inc.
NETWORK HEALTH INSURANCE
CORPORATION
H5216
H5253
H5410
H5425
H5431
H5521
H5526
H5883
H5938
Local CCP
Humana Inc.
HUMANA INSURANCE COMPANY
4.5
Local CCP
UnitedHealth Group, Inc.
UNITEDHEALTHCARE OF WISCONSIN, INC.
4.5
Local CCP
CIGNA
HEALTHSPRING OF FLORIDA
4.5
Local CCP
SCAN Health Plan
SCAN HEALTH PLAN
4.5
Local CCP
HealthSun Health Plans, Inc
HEALTHSUN HEALTH PLANS, INC.
4.5
Local CCP
Aetna Inc.
AETNA LIFE INSURANCE COMPANY
4.5
Local CCP
HealthNow New York Inc.
HEALTHNOW NEW YORK INC.
4.5
Local CCP
Blue Cross Blue Shield of Michigan
BLUE CARE NETWORK OF MICHIGAN
4.5
Local CCP
Guidewell Mutual Holding Corporation
CAPITAL HEALTH PLAN
4.5
4.5
H6622
Local CCP
Humana Inc.
HUMANA WI HEALTH ORGANIZATION
INSURANCE CORP
H6815
H7301
Local CCP
Health Net, Inc.
HEALTH NET HEALTH PLAN OF OREGON
4.5
Local CCP
Aetna Inc.
COVENTRY HEALTH CARE OF ILLINOIS, INC.
4.5
H7728
Local CCP
Anthem Inc.
ANTHEM HEALTH PLANS OF NEW
HAMPSHIRE, INC.
4.5
Fallon Community Health Plan
FALLON COMMUNITY HEALTH PLAN
4.5
Providence Health & Services
PROVIDENCE HEALTH PLAN
4.5
MVP Health Care, Inc.
MVP HEALTH PLAN, INC.
4.5
Local CCP
H9001
Local CCP
H9047
Local CCP
H9615
SOURCE: CMS.
26 • AIS’s Management Insight Series
Plans With 2.5 Stars or Fewer
Contract
Number
Organization
Type
Parent Organization
Contract Name
2016 Overall
Rating
H0571
Local CCP
Chinese Hospital Association
CHINESE COMMUNITY HEALTH PLAN
2.5
H1112
H1903
H3054
H3327
H4227
H4866
H5698
H5985
Local CCP
WellCare Health Plans, Inc.
WELLCARE OF GEORGIA, INC.
2.5
Local CCP
WellCare Health Plans, Inc.
WELLCARE OF LOUISIANA, INC.
2.5
Local CCP
Constellation Health, LLC.
CONSTELLATION HEALTH, LLC.
2.5
Local CCP
Touchstone Health Partnership, Inc.
TOUCHSTONE HEALTH HMO, INC.
2.5
Local CCP
Independence Health Group, Inc.
VISTA HEALTH PLAN, INC.
2.5
Local CCP
Cuatro LLC.
CUATRO LLC
2.5
Local CCP
WellCare Health Plans, Inc.
WINDSOR HEALTH PLAN, INC.
2.5
Local CCP
Tenet Healthcare Corporation
PHOENIX HEALTH PLANS, INC.
2.5
2.5
H6972
Local CCP
CIGNA
HEALTHSPRING LIFE & HEALTH INSURANCE
COMPANY, INC.
H9285
Local CCP
America's 1st Choice NY Holdings, LLC
ATLANTIS HEALTH PLAN, INC.
2.5
WellCare Health Plans, Inc.
WELLCARE HEALTH INSURANCE COMPANY
OF KENTUCKY, INC
2.5
H9730
Local CCP
SOURCE: CMS.
Percentage of Plans In Each Star Rating Level
3.5 Stars
33.18%
3 Stars
25.29%
2.5 Stars
3.71%
4 Stars
20.19%
SOURCE: CMS
5 Stars
2.55%
4.5 Stars
14.85%
The Challenges of Pharmacy Star Ratings • 27
2016 Part D Star Ratings for Plans Serving Dual Eligibles
CMS
Contract ID
Organization Name
Plan Name
Program Type
Part D Star
Rating
H5991
AFFINITY HEALTH PLAN, INC.
Affinity Medicare Solutions (HMO SNP)
D-SNP
4.5
H5991
H5969
H9122
H3240
H7200
AFFINITY HEALTH PLAN, INC.
Affinity Medicare Ultimate (HMO SNP)
D-SNP
4.5
ALOHACARE
AlohaCare Advantage Plus (HMO SNP)
D-SNP
3.5
ALPHACARE OF NEW YORK, INC.
AlphaCare Total (HMO SNP)
D-SNP
2.5
AMERIGROUP NEW JERSEY, INC.
Amerivantage Specialty + Rx (HMO SNP)
D-SNP
4.0
AMERIGROUP TENNESSEE, INC.
Amerivantage Specialty + Rx (HMO SNP)
D-SNP
3.5
H1849
ANTHEM HEALTH PLANS OF
KENTUCKY, INC.
Anthem Dual Advantage (HMO SNP)
D-SNP
4.0
H5854
ANTHEM HEALTH PLANS, INC.
Anthem Dual Advantage (HMO SNP)
D-SNP
4.5
H5619
ARCADIAN HEALTH PLAN, INC.
Humana Gold Plus SNP-DE H5619-003 (HMO
SNP)
D-SNP
4.0
H0321
H0321
H0321
H3814
H3814
H5995
ARIZONA PHYSICIANS IPA, INC.
UnitedHealthcare Dual Complete (HMO SNP)
AZ D-SNP
3.0
ARIZONA PHYSICIANS IPA, INC.
UnitedHealthcare Dual Complete (HMO SNP)
D-SNP
3.0
ARIZONA PHYSICIANS IPA, INC.
UnitedHealthcare Dual Complete ONE (HMO SNP)
AZ D-SNP
3.0
ATRIO HEALTH PLANS
ATRIO Special Needs Plan (HMO SNP)
D-SNP
3.5
ATRIO HEALTH PLANS
ATRIO Special Needs Plan (Rogue) (HMO SNP)
D-SNP
3.5
ATRIO HEALTH PLANS
ATRIO Special Needs Plan (Willamette) (HMO SNP) D-SNP
3.5
H5422
BLUE CROSS BLUE SHIELD
HEALTHCARE PLAN OF GEORGIA
BCBSHP Dual Advantage (HMO SNP)
D-SNP
3.5
H0564
BLUE CROSS OF CALIFORNIA
Anthem Dual Advantage (HMO SNP)
D-SNP
4.0
5.0
H1350
BLUE CROSS OF IDAHO HEALTH
SERVICE, INC.
True Blue Special Needs Plan (HMO SNP)
ID
LTC+Managed
Care
H2425
BLUE PLUS
SecureBlue (HMO SNP)
CMS Duals
Demo-MN
4.0
H2108
BRAVO HEALTH MID-ATLANTIC,
INC.
Cigna-HealthSpring TotalCare (HMO SNP)
D-SNP
3.0
H3949
BRAVO HEALTH PENNSYLVANIA,
INC.
Cigna-HealthSpring TotalCare (HMO SNP)
D-SNP
3.5
H5590
BRIDGEWAY HEALTH SOLUTIONS
Bridgeway Health Solutions Advantage (HMO SNP) AZ D-SNP
4.0
H0908
BUCKEYE COMMUNITY HEALTH
PLAN, INC.
Buckeye Health Plan Advantage (HMO SNP)
D-SNP
3.5
R6801
CARE IMPROVEMENT PLUS OF
TEXAS INSURANCE COMPANY
Care Improvement Plus Dual Advantage (Regional
PPO SNP)
D-SNP
3.5
R3444
CARE IMPROVEMENT PLUS SOUTH Care Improvement Plus Dual Advantage (Regional
CENTRAL INSURANCE CO.
PPO SNP)
D-SNP
3.5
R9896
CARE IMPROVEMENT PLUS SOUTH Care Improvement Plus Dual Advantage (Regional
CENTRAL INSURANCE CO.
PPO SNP)
D-SNP
3.5
H5209
CARE WISCONSIN HEALTH PLAN,
INC.
Partnership (HMO SNP)
D-SNP
4.0
H5928
H0544
H1019
CARE1ST HEALTH PLAN
Care1st TotalDual Plan (HMO SNP)
D-SNP
3.5
CAREMORE HEALTH PLAN
CareMore Connect (HMO SNP)
D-SNP
5.0
CAREPLUS HEALTH PLANS, INC.
CareNeeds (HMO SNP)
D-SNP
5.0
H4461
CARITEN HEALTH PLAN INC.
Humana Gold Plus SNP-DE H4461-022 (HMO
SNP)
D-SNP
5.0
H5649
CENTRAL HEALTH PLAN OF
CALIFORNIA, INC.
Central Health Medi-Medi Plan (HMO SNP)
D-SNP
4.0
H0571
CHINESE COMMUNITY HEALTH
PLAN
CCHP Senior Select Program (HMO SNP)
D-SNP
4.0
H0439
CIGNA HEALTHCARE OF GEORGIA,
INC.
Cigna-HealthSpring TotalCare (HMO SNP)
D-SNP
3.5
continued 28 • AIS’s Management Insight Series
2016 Part D Star Ratings for Plans Serving Dual Eligibles (continued)
CMS
Contract ID
Organization Name
Plan Name
Program Type
Part D Star
Rating
H9725
CIGNA HEALTHCARE OF NORTH
CAROLINA, INC.
Cigna-HealthSpring TotalCare (HMO SNP)
D-SNP
4.0
H2225
COMMONWEALTH CARE ALLIANCE,
Senior Care Options Program (HMO SNP)
INC.
D-SNP
5.0
H3071
COMMUNITY CARE ALLIANCE OF
ILLINOIS, NFP
Community Care Alliance of Illinois, NFP (HMO
SNP)
D-SNP
3.0
H2034
COMMUNITY CARE HEALTH PLAN,
INC.
Community Care's Partnership Program (HMO
SNP)
D-SNP
3.5
H2034
COMMUNITY CARE HEALTH PLAN,
INC.
Community Care's Partnership Program Disabled
(HMO SNP)
D-SNP
3.5
H5207
COMMUNITY CARE HEALTH PLAN,
INC.
Community Care's Partnership Program (HMO
SNP)
D-SNP
3.5
H3655
COMMUNITY INSURANCE
COMPANY
Anthem Dual Advantage (HMO SNP)
D-SNP
4.5
H9525
COMPCARE HEALTH SERVICES
INSURANCE CORPORATION
Anthem Dual Advantage (HMO SNP)
D-SNP
4.0
H3054
H4866
CONSTELLATION HEALTH, LLC.
Genesis - Constellation Health (HMO SNP)
D-SNP
3.0
CUATRO LLC
Access Medicare Pearl (HMO SNP)
D-SNP
3.0
H5608
DENVER HEALTH MEDICAL PLAN,
INC.
Denver Health Medicare Choice (HMO SNP)
D-SNP
4.0
H5087
H5087
H3347
H3347
EASY CHOICE HEALTH PLAN INC.
Easy Choice Access Plan (HMO SNP)
D-SNP
3.5
EASY CHOICE HEALTH PLAN INC.
Easy Choice Freedom Plan (HMO SNP)
D-SNP
3.5
ELDERPLAN, INC.
Elderplan For Medicaid Beneficiaries (HMO SNP)
D-SNP
3.0
ELDERPLAN, INC.
Elderplan Plus Long Term Care (HMO SNP)
D-SNP
3.0
H3370
EMPIRE HEALTHCHOICE HMO,
INC.
Empire Dual Advantage (HMO SNP)
D-SNP
4.0
H9001
FALLON COMMUNITY HEALTH
PLAN
NaviCare (HMO SNP)
D-SNP
4.0
H3818
H5427
H5427
FAMILYCARE HEALTH PLANS, INC.
FamilyCare Community (HMO SNP)
D-SNP
4.0
FREEDOM HEALTH, INC.
Freedom Medi-Medi Full (HMO SNP)
D-SNP
4.5
FREEDOM HEALTH, INC.
Freedom Medi-Medi Partial (HMO SNP)
D-SNP
4.5
H9190
GATEWAY HEALTH PLAN OF OHIO,
INC.
Gateway Health Medicare Assured Diamond (HMO
SNP)
D-SNP
3.0
H9190
GATEWAY HEALTH PLAN OF OHIO,
INC.
Gateway Health Medicare Assured Ruby (HMO
SNP)
D-SNP
3.0
H5932
GATEWAY HEALTH PLAN, INC.
Gateway Health Medicare Assured Diamond (HMO
SNP)
D-SNP
4.0
H5932
GATEWAY HEALTH PLAN, INC.
Gateway Health Medicare Assured Ruby (HMO
SNP)
D-SNP
4.0
H3954
H5528
H6864
H5685
GEISINGER HEALTH PLAN
Geisinger Gold Secure Rx (HMO SNP)
D-SNP
4.0
GROUP HEALTH INCORPORATED
EmblemHealth Dual Eligible (PPO SNP)
D-SNP
3.5
GUILDNET, INC.
GuildNet Gold (HMO-POS SNP)
D-SNP
3.5
HAP MIDWEST HEALTH PLAN, INC. HAP Midwest Health Plan (HMO SNP)
D-SNP
3.5
H1416
HARMONY HEALTH PLAN OF
ILLINOIS, INC.
WellCare Access (HMO SNP)
D-SNP
3.0
H3822
HEALTH CARE SERVICE
CORPORATION
Blue Cross Medicare Advantage Dual Care (HMO
SNP)
D-SNP
3.5
H5587
HEALTH CHOICE ARIZONA, INC.
Health Choice Generations (HMO SNP)
AZ D-SNP
3.0
H3330
HEALTH INSURANCE PLAN OF
GREATER NEW YORK
EmblemHealth Dual Eligible (HMO SNP)
D-SNP
3.5
H3330
HEALTH INSURANCE PLAN OF
GREATER NEW YORK
EmblemHealth Dual Eligible Group (HMO SNP)
D-SNP
3.5
H0351
HEALTH NET OF ARIZONA, INC.
Health Net Amber (HMO SNP)
AZ D-SNP
4.5
The Challenges of Pharmacy Star Ratings • 29
2016 Part D Star Ratings for Plans Serving Dual Eligibles (continued)
CMS
Contract ID
Part D Star
Rating
Organization Name
Plan Name
Program Type
H0562
H9207
HEALTH NET OF CALIFORNIA,INC.
Health Net Seniority Plus Amber I (HMO SNP)
D-SNP
4.5
HEALTH PARTNERS PLANS, INC.
Health Partners Medicare Special (HMO SNP)
D-SNP
3.0
H5859
HEALTH PLAN OF CAREOREGON,
INC.
CareOregon Advantage Plus (HMO-POS SNP)
D-SNP
3.5
H3959
HEALTHAMERICA PENNSYLVANIA,
INC.
Advantra Cares (HMO SNP)
D-SNP
4.0
H2422
HEALTHPARTNERS, INC.
HealthPartners Minnesota Senior Health Options
(HMO SNP)
CMS Duals
Demo-MN
4.5
H2165
HEALTHSPRING LIFE & HEALTH
INSURANCE COMPANY, INC.
Cigna-HealthSpring TotalCare (HMO SNP)
D-SNP
4.5
H4513
HEALTHSPRING LIFE & HEALTH
INSURANCE COMPANY, INC.
Cigna-HealthSpring TotalCare (HMO SNP)
D-SNP
4.0
H4528
HEALTHSPRING LIFE & HEALTH
INSURANCE COMPANY, INC.
Cigna-HealthSpring TotalCare (HMO SNP)
D-SNP
3.5
H0150
H5410
HEALTHSPRING OF ALABAMA, INC. Cigna-HealthSpring TotalCare (HMO SNP)
D-SNP
4.0
HEALTHSPRING OF FLORIDA
Cigna-HealthSpring TotalCare (HMO SNP)
D-SNP
5.0
H1415
HEALTHSPRING OF TENNESSEE,
INC.
Cigna-HealthSpring TotalCare (HMO SNP)
D-SNP
3.5
H4407
HEALTHSPRING OF TENNESSEE,
INC.
Cigna-HealthSpring TotalCare SMS (HMO SNP)
D-SNP
4.5
H4454
HEALTHSPRING OF TENNESSEE,
INC.
Cigna-HealthSpring TotalCare (HMO SNP)
D-SNP
5.0
H4454
HEALTHSPRING OF TENNESSEE,
INC.
Cigna-HealthSpring TotalCare AR (HMO SNP)
D-SNP
5.0
H3672
HOMETOWN HEALTH PLAN
SecureCare SNP (HMO SNP)
D-SNP
4.0
H4141
HUMANA EMPLOYERS HEALTH
PLAN OF GEORGIA, INC.
Humana Gold Plus SNP-DE H4141-003 (HMO
SNP)
D-SNP
3.0
H4141
HUMANA EMPLOYERS HEALTH
PLAN OF GEORGIA, INC.
Humana Gold Plus SNP-DE H4141-010 (HMO
SNP)
D-SNP
3.0
H1951
HUMANA HEALTH BENEFIT PLAN
OF LOUISIANA, INC.
Humana Gold Plus SNP-DE H1951-032 (HMO
SNP)
D-SNP
4.5
H1951
HUMANA HEALTH BENEFIT PLAN
OF LOUISIANA, INC.
Humana Gold Plus SNP-DE H1951-033 (HMO
SNP)
D-SNP
4.5
H1951
HUMANA HEALTH BENEFIT PLAN
OF LOUISIANA, INC.
Humana Gold Plus SNP-DE H1951-034 (HMO
SNP)
D-SNP
4.5
H1951
HUMANA HEALTH BENEFIT PLAN
OF LOUISIANA, INC.
Humana Gold Plus SNP-DE H1951-041 (HMO
SNP)
D-SNP
4.5
H3533
HUMANA HEALTH COMPANY OF
NEW YORK, INC.
Humana Gold Plus SNP-DE H3533-002 (HMO
SNP)
D-SNP
3.0
H3533
HUMANA HEALTH COMPANY OF
NEW YORK, INC.
Humana Gold Plus SNP-DE H3533-004 (HMO
SNP)
D-SNP
3.0
H8953
HUMANA HEALTH PLAN OF OHIO,
INC.
Humana Gold Plus SNP-DE H8953-007 (HMO
SNP)
D-SNP
4.0
H8953
HUMANA HEALTH PLAN OF OHIO,
INC.
Humana Gold Plus SNP-DE H8953-014 (HMO
SNP)
D-SNP
4.0
H2012
HUMANA HEALTH PLAN, INC.
Humana Gold Plus SNP-DE H2012-042 (HMO
SNP)
D-SNP
4.0
H2012
HUMANA HEALTH PLAN, INC.
Humana Gold Plus SNP-DE H2012-053 (HMO
SNP)
D-SNP
4.0
H2012
HUMANA HEALTH PLAN, INC.
Humana Gold Plus SNP-DE H2012-054 (HMO
SNP)
D-SNP
4.0
H2012
HUMANA HEALTH PLAN, INC.
Humana Gold Plus SNP-DE H2012-064 (HMO
SNP)
D-SNP
4.0
H2012
HUMANA HEALTH PLAN, INC.
Humana Gold Plus SNP-DE H2012-070 (HMO
SNP)
D-SNP
4.0
continued 30 • AIS’s Management Insight Series
2016 Part D Star Ratings for Plans Serving Dual Eligibles (continued)
CMS
Contract ID
Organization Name
Plan Name
Program Type
Part D Star
Rating
H2012
HUMANA HEALTH PLAN, INC.
Humana Gold Plus SNP-DE H2012-095 (HMO
SNP)
D-SNP
4.0
H2649
HUMANA HEALTH PLAN, INC.
Humana Gold Plus SNP-DE H2649-028 (HMO
SNP)
D-SNP
4.0
H4007
HUMANA HEALTH PLANS OF
PUERTO RICO, INC.
Humana Gold Plus SNP-DE H4007-016 (HMO
SNP)
D-SNP
3.5
H1036
HUMANA MEDICAL PLAN, INC.
Humana Community HMO SNP DE (HMO SNP)
D-SNP
4.5
H1036
HUMANA MEDICAL PLAN, INC.
Humana Gold Plus SNP-DE H1036-077A (HMO
SNP)
D-SNP
4.5
H1036
HUMANA MEDICAL PLAN, INC.
Humana Gold Plus SNP-DE H1036-102 (HMO
SNP)
D-SNP
4.5
H1036
HUMANA MEDICAL PLAN, INC.
Humana Gold Plus SNP-DE H1036-103A (HMO
SNP)
D-SNP
4.5
H1036
HUMANA MEDICAL PLAN, INC.
Humana Gold Plus SNP-DE H1036-104A (HMO
SNP)
D-SNP
4.5
H1036
HUMANA MEDICAL PLAN, INC.
Humana Gold Plus SNP-DE H1036-167 (HMO
SNP)
D-SNP
4.5
H1036
HUMANA MEDICAL PLAN, INC.
Humana Gold Plus SNP-DE H1036-168 (HMO
SNP)
D-SNP
4.5
H1036
HUMANA MEDICAL PLAN, INC.
Humana Gold Plus SNP-DE H1036-209 (HMO
SNP)
D-SNP
4.5
H1036
HUMANA MEDICAL PLAN, INC.
Humana Gold Plus SNP-DE H1036-210 (HMO
SNP)
D-SNP
4.5
H1036
HUMANA MEDICAL PLAN, INC.
Humana Gold Plus SNP-DE H1036-213 (HMO
SNP)
D-SNP
4.5
H1036
HUMANA MEDICAL PLAN, INC.
Humana Gold Plus SNP-DE H1036-214 (HMO
SNP)
D-SNP
4.5
H1036
HUMANA MEDICAL PLAN, INC.
Humana Gold Plus SNP-DE H1036-222 (HMO
SNP)
D-SNP
4.5
H1036
HUMANA MEDICAL PLAN, INC.
Humana Gold Plus SNP-DE H1036-226 (HMO
SNP)
D-SNP
4.5
H1036
HUMANA MEDICAL PLAN, INC.
Humana Gold Plus SNP-DE H1036-231 (HMO
SNP)
D-SNP
4.5
H2237
INDEPENDENT CARE HEALTH
PLAN, INC.
iCare Family Care Partnership (HMO SNP)
D-SNP
4.0
H2237
INDEPENDENT CARE HEALTH
PLAN, INC.
iCare Medicare Plan (HMO SNP)
D-SNP
4.0
H2417
ITASCA MEDICAL CARE
IMCare Classic (HMO SNP)
CMS Duals
Demo-MN
4.0
H0630
KAISER FOUNDATION HP OF CO
Senior Advantage Medicare Medicaid Plan (HMO
SNP)
D-SNP
5.0
H1170
KAISER FOUNDATION HP OF GA,
INC.
Senior Advantage Medicare Medicaid Plan (HMO
SNP)
D-SNP
4.0
H0524
KAISER FOUNDATION HP, INC.
Senior Advantage Medicare Medi-Cal Plan North
(HMO SNP)
D-SNP
5.0
H0524
KAISER FOUNDATION HP, INC.
Senior Advantage Medicare Medi-Cal Plan South
(HMO SNP)
D-SNP
5.0
H3337
LIBERTY HEALTH ADVANTAGE, INC. Liberty Health Advantage Dual Power (HMO SNP)
D-SNP
3.0
H8189
MANAGED HEALTH SERVICES,
WISCONSIN
Managed Health Services Advantage (HMO SNP)
D-SNP
3.5
H3359
H3359
MANAGED HEALTH, INC.
Healthfirst CompleteCare (HMO SNP)
D-SNP
4.0
MANAGED HEALTH, INC.
Healthfirst Life Improvement Plan (HMO SNP)
D-SNP
4.0
H6623
MARICOPA COUNTY SPECIAL
HEALTH CARE DISTRICT
Maricopa Care Advantage (HMO SNP)
AZ D-SNP
3.5
H5577
MCS ADVANTAGE, INC.
MCS Classicare Platino Ideal (HMO SNP)
D-SNP
3.0
The Challenges of Pharmacy Star Ratings • 31
2016 Part D Star Ratings for Plans Serving Dual Eligibles (continued)
CMS
Contract ID
H5577
H5577
Part D Star
Rating
Organization Name
Plan Name
Program Type
MCS ADVANTAGE, INC.
MCS Classicare Platino Maximo (HMO SNP)
D-SNP
3.0
MCS ADVANTAGE, INC.
MCS Classicare Platino Superior (HMO SNP)
D-SNP
3.0
4.0
H2458
MEDICA HEALTH PLANS
Medica DUAL Solution (HMO SNP)
CMS Duals
Demo-MN
H5420
MEDICA HEALTHCARE PLANS, INC.
Medica HealthCare Plans MedicareMax Plus
(HMO-POS SNP)
D-SNP
4.0
H5779
MERIDIAN HEALTH PLAN OF
ILLINOIS, INC.
Meridian Advantage Plan of Illinois (HMO SNP)
D-SNP
3.0
H5475
MERIDIAN HEALTH PLAN OF
MICHIGAN, INC.
Meridian Advantage Plan of Michigan (HMO SNP)
D-SNP
3.0
H0423
METROPLUS HEALTH PLAN, INC.
MetroPlus Advantage Plan (HMO SNP)
D-SNP
3.5
H4003
MMM HEALTHCARE, LLC.
Medicare y Mucho Mas - DIAMANTE CHOICE
(HMO SNP)
D-SNP
3.5
H4003
MMM HEALTHCARE, LLC.
Medicare y Mucho Mas - DIAMANTE EXCEL (HMO
SNP)
D-SNP
3.5
H4003
MMM HEALTHCARE, LLC.
Medicare y Mucho Mas - DIAMANTE EXTRA (HMO
SNP)
D-SNP
3.5
H5810
MOLINA HEALTHCARE OF
CALIFORNIA
Molina Medicare Options Plus (HMO SNP)
D-SNP
3.5
H8130
MOLINA HEALTHCARE OF
FLORIDA, INC.
Molina Medicare Options Plus (HMO SNP)
D-SNP
3.5
H5926
MOLINA HEALTHCARE OF
MICHIGAN, INC.
Molina Medicare Options Plus (HMO SNP)
D-SNP
4.0
H9082
MOLINA HEALTHCARE OF NEW
MEXICO, INC.
Molina Medicare Options Plus (HMO SNP)
D-SNP
4.0
H0490
MOLINA HEALTHCARE OF OHIO,
INC.
Molina Medicare Options Plus (HMO SNP)
D-SNP
3.0
H7678
MOLINA HEALTHCARE OF TEXAS,
INC.
Molina Medicare Options Plus (HMO SNP)
D-SNP
4.0
H5628
MOLINA HEALTHCARE OF UTAH,
INC.
Healthy Advantage (HMO SNP)
D-SNP
4.5
H5628
MOLINA HEALTHCARE OF UTAH,
INC.
Molina Medicare Options Plus (HMO SNP)
D-SNP
4.5
H5823
MOLINA HEALTHCARE OF
WASHINGTON, INC.
Molina Medicare Options Plus (HMO SNP)
D-SNP
4.0
H2879
MOLINA HEALTHCARE OF
WISCONSIN
Molina Medicare Options Plus (HMO SNP)
D-SNP
4.5
H5215
NETWORK HEALTH INSURANCE
CORPORATION
NetworkCares (PPO SNP)
D-SNP
4.5
H5430
ONECARE BY CARE1ST HEALTH
PLAN ARIZONA INC.
Care1st+ (HMO SNP)
AZ D-SNP
3.5
H5594
H5594
OPTIMUM HEALTHCARE, INC.
Optimum Emerald Full (HMO SNP)
D-SNP
4.5
OPTIMUM HEALTHCARE, INC.
Optimum Emerald Partial (HMO SNP)
D-SNP
4.5
H5433
ORANGE COUNTY HEALTH
AUTHORITY
OneCare (HMO SNP)
D-SNP
3.5
H3113
H1961
H5985
OXFORD HEALTH PLANS (NJ), INC.
UnitedHealthcare Dual Complete ONE (HMO SNP)
D-SNP
5.0
PEOPLES HEALTH, INC.
Peoples Health Secure Health (HMO SNP)
D-SNP
4.0
PHOENIX HEALTH PLANS, INC.
Phoenix Advantage Plus (HMO SNP)
AZ D-SNP
3.0
H4527
PHYSICIANS HEALTH CHOICE OF
TEXAS LLC
UnitedHealthcare Dual Complete Focus (HMO
SNP)
D-SNP
4.0
H4004
H1045
PMC MEDICARE CHOICE, LLC
Premier Preferred (HMO SNP)
D-SNP
3.5
PREFERRED CARE PARTNERS INC. Preferred Medicare Assist (HMO-POS SNP)
D-SNP
3.5
H2416
PRIMEWEST CTRL COUNTY-BASED
PrimeWest Senior Health Complete (HMO SNP)
PURCHASING INITIATIVE
CMS Duals
Demo-MN
4.0
continued 32 • AIS’s Management Insight Series
2016 Part D Star Ratings for Plans Serving Dual Eligibles (continued)
CMS
Contract ID
Organization Name
Plan Name
Program Type
Part D Star
Rating
H2773
QUALITY HEALTH PLANS OF NEW
YORK, INC.
Advantage Value One NY - Dual (HMO SNP)
D-SNP
4.0
H3811
SAMARITAN HEALTH PLANS, INC.
Samaritan Advantage Special Needs Plan (HMO
SNP)
D-SNP
4.0
H5428
H5425
H5425
H2224
H2224
H4525
H5471
SAN MATEO HEALTH COMMISSION CareAdvantage (HMO SNP)
D-SNP
4.0
SCAN HEALTH PLAN
SCAN Connections (HMO SNP)
D-SNP
4.5
SCAN HEALTH PLAN
SCAN Connections at Home (HMO SNP)
D-SNP
4.5
SENIOR WHOLE HEALTH, LLC
Senior Whole Health (HMO SNP)
D-SNP
4.0
SENIOR WHOLE HEALTH, LLC
Senior Whole Health NHC (HMO SNP)
D-SNP
4.0
SHA, L.L.C
FirstCare Advantage Select (HMO SNP)
D-SNP
3.5
SIMPLY HEALTHCARE PLANS, INC.
Simply Complete (HMO SNP)
D-SNP
3.5
H2419
SOUTH COUNTRY HEALTH
ALLIANCE
SeniorCare Complete (HMO SNP)
CMS Duals
Demo-MN
5.0
H5703
SOUTH COUNTRY HEALTH
ALLIANCE
AbilityCare (HMO SNP)
D-SNP
3.5
H5580
SOUTHWEST CATHOLIC HEALTH
NETWORK CORPORATION
Mercy Care Advantage (HMO SNP)
AZ D-SNP
3.5
H5190
SUNSHINE STATE HEALTH PLAN,
INC.
Sunshine Health Advantage (HMO SNP)
D-SNP
3.5
H5294
SUPERIOR HEALTH PLAN, INC.
Superior HealthPlan Advantage (HMO SNP)
D-SNP
3.5
H3328
THE NEW YORK STATE CATHOLIC
HEALTH PLAN, INC.
Fidelis Dual Advantage (HMO SNP)
D-SNP
4.5
H3328
THE NEW YORK STATE CATHOLIC
HEALTH PLAN, INC.
Fidelis Dual Advantage Flex (HMO SNP)
D-SNP
4.5
H3328
THE NEW YORK STATE CATHOLIC
HEALTH PLAN, INC.
Fidelis Medicaid Advantage Plus (HMO SNP)
D-SNP
4.5
H2174
TRILLIUM COMMUNITY HEALTH
PLAN
Trillium Advantage Dual (HMO SNP)
D-SNP
4.0
H2256
TUFTS ASSOCIATED HEALTH
MAINTENANCE ORGANIZATION
Tufts Health Plan Senior Care Options (HMO SNP)
D-SNP
4.5
H2456
UCARE MINNESOTA
UCare's Minnesota Senior Health Options (HMO
SNP)
CMS Duals
Demo-MN
3.5
H4590
UNITEDHEALTHCARE BENEFITS OF
UnitedHealthcare Dual Complete (HMO SNP)
TEXAS, INC.
D-SNP
4.0
H4514
UNITEDHEALTHCARE COMMUNITY
PLAN OF TEXAS, LLC
UnitedHealthcare Dual Complete (HMO SNP)
D-SNP
3.5
H0624
UNITEDHEALTHCARE INSURANCE
COMPANY
UnitedHealthcare Dual Complete (HMO SNP)
D-SNP
3.5
H2226
UNITEDHEALTHCARE INSURANCE
COMPANY
UnitedHealthcare Senior Care Options (HMO SNP)
D-SNP
5.0
H5008
UNITEDHEALTHCARE INSURANCE
COMPANY
UnitedHealthcare Dual Complete (HMO SNP)
D-SNP
3.5
R3175
UNITEDHEALTHCARE INSURANCE
COMPANY
UnitedHealthcare Dual Complete RP (Regional
PPO SNP)
D-SNP
4.0
R5287
UNITEDHEALTHCARE INSURANCE
COMPANY
UnitedHealthcare Dual Complete RP (Regional
PPO SNP)
D-SNP
3.5
H0151
UNITEDHEALTHCARE OF
ALABAMA, INC.
UnitedHealthcare Dual Complete (HMO SNP)
D-SNP
3.5
H3387
UNITEDHEALTHCARE OF NEW
YORK, INC.
UnitedHealthcare Dual Complete (HMO SNP)
D-SNP
4.0
H5253
UNITEDHEALTHCARE OF
WISCONSIN, INC.
UnitedHealthcare Dual Complete LP (HMO SNP)
D-SNP
4.5
H0251
UNITEDHEALTHCARE PLAN OF THE
UnitedHealthcare Dual Complete (HMO SNP)
RIVER VALLEY, INC.
D-SNP
4.0
The Challenges of Pharmacy Star Ratings • 33
2016 Part D Star Ratings for Plans Serving Dual Eligibles (continued)
CMS
Contract ID
Part D Star
Rating
Organization Name
Plan Name
Program Type
H0838
H4279
UNIVERSAL CARE, INC.
Dual Coverage (HMO SNP)
D-SNP
3.5
UPMC FOR YOU, INC
UPMC for You Advantage (HMO SNP)
D-SNP
4.0
H2161
UPPER PENINSULA HEALTH PLAN,
LLC
Upper Peninsula Health Plan Plus (HMO SNP)
D-SNP
3.5
H4227
H4227
H0154
H5549
H5549
H5549
H3259
VISTA HEALTH PLAN, INC.
AmeriHealth VIP Care (HMO SNP)
D-SNP
3.5
VISTA HEALTH PLAN, INC.
Keystone VIP Choice (HMO SNP)
D-SNP
3.5
VIVA HEALTH, INC.
VIVA Medicare Extra Value (HMO SNP)
D-SNP
4.0
VNS CHOICE
VNSNY CHOICE Medicare Maximum (HMO SNP)
D-SNP
4.0
VNS CHOICE
VNSNY CHOICE Medicare Preferred (HMO SNP)
D-SNP
4.0
VNS CHOICE
VNSNY CHOICE Total (HMO SNP)
D-SNP
4.0
VOLUNTEER STATE HEALTH PLAN
BlueCare Plus (HMO SNP)
D-SNP
3.5
H9730
WELLCARE HEALTH INSURANCE
COMPANY OF KENTUCKY, INC
Wellcare Access (HMO SNP)
D-SNP
2.5
H2491
WELLCARE HEALTH INSURANCE
OF ARIZONA, INC.
'Ohana Liberty (HMO-POS SNP)
D-SNP
3.0
H0712
H1032
H1032
H1032
H1112
H1903
H3361
H3361
H1264
H5698
H5698
WELLCARE OF CONNECTICUT, INC. WellCare Access (HMO SNP)
D-SNP
3.0
WELLCARE OF FLORIDA, INC.
WellCare Access (HMO SNP)
D-SNP
3.5
WELLCARE OF FLORIDA, INC.
WellCare Liberty (HMO SNP)
D-SNP
3.5
WELLCARE OF FLORIDA, INC.
WellCare Select (HMO SNP)
D-SNP
3.5
WELLCARE OF GEORGIA, INC.
WellCare Access (HMO SNP)
D-SNP
2.5
WELLCARE OF LOUISIANA, INC.
WellCare Access (HMO SNP)
D-SNP
2.5
WELLCARE OF NEW YORK, INC.
WellCare Access (HMO SNP)
D-SNP
3.0
WELLCARE OF NEW YORK, INC.
WellCare Liberty (HMO SNP)
D-SNP
3.0
WELLCARE OF TEXAS, INC.
WellCare Access (HMO SNP)
D-SNP
3.5
WINDSOR HEALTH PLAN, INC.
WellCare Access (HMO SNP)
D-SNP
3.0
WINDSOR HEALTH PLAN, INC.
WellCare Comp Access (HMO SNP)
D-SNP
3.0
SOURCE: DUAL Medicare-Medicaid Dual Eligibles Database, an online subscription database and newsfeed from AIS. Visit http://
aishealthdata.com/dual for more information and free interactive demo.
34 • AIS’s Management Insight Series
CMS Regulation and Guidance
CMS Suspension of Automatic Star-Rating Cuts for Sanctioned
Plans Stuns Observers
An unusual March 8, 2016, memo from CMS is causing both astonishment and
thankfulness in portions of the Medicare Advantage industry because of its potential
impact on the star quality rating system and its effect on plan revenues and member
benefits. Other industry segments, along with a few securities analysts and consumer
advocates, wondered why CMS was taking an action that so directly helped one large
insurer, Cigna Corp., which otherwise would have had its high star ratings — and the
upcoming bonuses tied to them — sharply cut back as of March 31, 2016.
The March 8, 2016, memo, not publicized by CMS, suspended the automatic and
major reductions in star ratings that Cigna and another much smaller MA plan would
incur if they are still under the agency’s so-called “intermediate sanctions” as of the
end of March 2016.
“The suspension is a significant positive for Cigna,” wrote Barclays securities
analyst Joshua Raskin in a March 8, 2016, research note. “Candidly, this is the first time
that we can remember CMS making such a significant policy change for a specific carrier” without doing it via a proposed or final rule.
“We are discouraged by CMS’ announcement, which diminishes accountability
and transparency related to plan sanctions,” Stacy Sanders, federal policy director at
the Medicare Rights Center, told Kaiser Health News. If CMS was concerned that the
requirement mandating a reduction to 2.5 stars for a plan undergoing the agency’s intermediate sanctions was too severe for a high-star-rated MA organization (MAO), she
said, it could have elected to drop star ratings by just one star as it does for low-rated
plans rather than suspend star reduction for such sanctioned plans entirely.
CMS in a Jan. 21, 2016, letter from its Medicare Parts C and D Oversight and
Enforcement Group imposed an indefinite suspension on Cigna’s marketing and
enrollment for new members in both its MA and stand-alone Prescription Drug Plan
(PDP) products. The agency cited a host of severe deficiencies — including in coverage
determinations and handling of appeals and grievances — and said that Cigna has a
“longstanding history of noncompliance.”
CMS May Have Feared Market Destabilization
Observers queried by AIS did not attribute the policy change to an agency desire
to show largesse to Cigna, which stands to gain between $213 million and $350 million from the shift based on estimates by securities firms. But some of the observers do
suggest that the size of Cigna, which had more than 550,000 MA enrollees as of CMS’s
February 2016 monthly data, might have led the agency to fear that slashing the insur-
The Challenges of Pharmacy Star Ratings • 35
er’s ratings and thus indirectly its benefits for 2017 might have destabilized substantial
portions of the MA market during the Annual Election Period (AEP) in fall 2015.
Specifically, Cigna/HealthSpring had more than 350,000 members as of the
February 2016 data in five MA plans rated four stars and above for 2016, including
52,485 in a five-star plan in Arizona that was one of only 12 nationwide to earn this top
honor plus nearly 150,000 in 4.5-star plans. And Cigna’s situation takes on greater significance because it has agreed to be acquired by Anthem, Inc. in a still-pending deal.
CMS for its part did not cite the potential impact on the AEP as a reason for the
policy change. The four-paragraph memo from Jennifer Shapiro, acting director of the
Medicare Drug Benefit and C & D Data Group, sent out only via the electronic Health
Plan Management System (HPMS) and not publicized, instead emphasized the changing star-rating achievement background. “When CMS announced this policy for the
2012 Star Ratings,” Shapiro wrote, “relatively few contracts achieved ratings of 4 stars
or above and fewer than 30% of Medicare Advantage plan enrollees were in plans
offered under these highly rated contracts. Today, 49% of MA contracts, representing
71% of MA plan enrollees, have achieved ratings of 4 stars or above, compared to an
estimated 17% in 2009.”
In response to the draft 2017 Call Letter issued Feb. 19, 2016, the memo said, CMS
received “multiple comments” suggesting that it revise the mandatory-stars-reduction
policy for “sanctioned contracts.” Shapiro added that “commenters raised several concerns, including one noting that high-rated contracts can be subjected to a more severe
penalty than low-rated contracts” since the higher ones could lose multiple stars while
low-rated contracts could lose only one star.
MAOs have made this argument before, but their pleas have become more urgent
in recent years. Among the commenters seeking a change was not only the America’s
Health Insurance Plans trade group but also CAPG, which represents the risk-bearing
provider groups that have become big players in MA.
After having considered the comments “and the growth in the number of highly
rated contracts, CMS agrees that we should reassess the impact of intermediate sanctions on the calculation of star ratings,” the memo said. So “effective immediately and
on a prospective basis, CMS is suspending the automatic sanctions-based reduction in
Star Ratings,” according to Shapiro. She wrote that CMS will propose a revised approach in the draft 2018 Call Letter, which comes out in February 2017.
Action Was Needed Before March 31
The reason for announcing the change through an HPMS memo, Shapiro continued, was so that the policy change could be applied prior to the March 31, 2016, deadline for making adjustments to a contract’s star ratings based on its sanction status.
March 31 is the date CMS’s Medicare Plan Finder and Quality Bonus Payment (QBP)
determinations are adjusted for such changes, so the memo before that date allows
36 • AIS’s Management Insight Series
CMS to give this information to MA sponsors before those data updates without
changing its “established timelines,” Shapiro wrote.
This means that CMS will use the original 2016 star ratings, unless changed via
CMS’s appeals process, to determine QBP eligibility for 2017. The whole timetable is
very significant since there appears to be next to no chance that Cigna would be able to
convince CMS by March 31, 2016, to lift the intermediate sanctions. Aetna Inc., which
was hit with those MA and PDP sanctions in April 2010, did not have them lifted until
June 2011, and intermediate sanctions for Health Net, Inc. lasted from November 2010
to August 2011.
Consultants, including two former CMS MA officials, had mixed reactions to the
CMS memo. Avalere Health Vice President Tom Kornfield, who joined the company
from CMS in 2015, says the impact of the major lowering of Cigna’s high star ratings
that would have occurred were it not for the memo could have had a significant impact on beneficiaries, including loss of benefits and even possible loss of some of its
MA plans.
But Kornfield also tells AIS “I’m not certain I understand why CMS didn’t propose
or mention this” issue in the draft Call Letter. “That would have been an appropriate
vehicle” for such a policy change, while doing it via an HPMS memo seems “out of left
field,” he asserts.
Asked if there might have been political factors involved in the decision since
nearly half of the next AEP falls during the final weeks of campaigning in a big election year when an adverse impact on MA premiums and benefits could be an issue,
Kornfield replies that he doesn’t know. He points out it’s possible Cigna has been
making rapid progress on remedying the deficiencies and that the policy change could
be one way of recognizing that. The only other MA plan that appears now to be in MA
intermediate sanctions is Ultimate Health Plans, Inc. in Florida, but Cigna is far larger.
The issue CMS is addressing in the memo seems to be a legitimate one, suggests Michael Adelberg, a former top CMS MA official who now is senior director at
FaegreBD Consulting. “As more beneficiaries come into 4- and 5-star-rated contracts,”
he tells AIS, “the impact of dropping those contracts to 2.5 grows. This is not just an
issue for the MAO, but also for the beneficiaries when the MAO submits bids based on
the payment reductions. Large numbers of beneficiaries with reduced benefits creates
difficulties for everyone.”
Asked about making the change via an HPMS memo, Adelberg replies, “This was
not a ho-hum HPMS memo. Most HPMS memos offer new technical or administrative
guidance. This one was about policy.”
Is there the danger of a mixed message on the importance of CMS sanctions when
the agency does something like this? “With or without a star-ratings reduction,” responds Adelberg, “the potential of missing an open-enrollment season forces appropriate attention from the sanctioned MAO.”
The Challenges of Pharmacy Star Ratings • 37
Star Ratings for Duals
Inovalon Study Shows Duals’ Characteristics Yield Poor Health
Outcomes
Health plans with large percentages of dual-eligible beneficiaries may not be at
fault for the overall poor health outcomes reflected in their Medicare Advantage star
ratings, suggests a March 31, 2015, study from Inovalon, Inc. The study, which analyzed claims data from more than 2.2 million MA plan members, may be the first
large-scale analysis to find a distinction between a plan’s quality of care and the health
outcomes related to its members’ dual status.
Analysts found that non-duals experienced better health outcomes regardless of
the proportion of dual eligible members served by the same plan, even if that plan
had lower-than-average star ratings. Researchers determined that factors outside of a
health plan’s control, such as socioeconomic status, chronic health issues and the surrounding community accounted for more than 70% of the performance gap between
dual and non-dual members.
Hospital readmissions, a measure that gets the top three-point weight in star ratings, were attributed to living in a poor neighborhood in over 18% of cases, according
to Inovalon. When compared to non-dual members, duals live in poverty at much
higher rates. Health problems that are more likely to plague duals, such as dementia,
schizophrenia and chronic obstructive pulmonary disease, are also common causes of
readmission. Duals were also found to be more likely to live in communities with limited access to physicians, another significant cause of high readmission rates and lower
adherence to care.
Because of the complexity of these factors, the Inovalon researchers recommended
that CMS adjust its Star Ratings measures to account for the high-risk characteristics
observed in the duals population. Establishing new guidelines would help pave the
way for accuracy in evaluating quality of care for duals, and plans could move forward without being penalized for issues that are beyond their control, the report said.
Personal Engagement, Communication Technology Could Boost
Star Ratings and Health Outcomes for Duals Plans
Creating a superior experience for seniors is a crucial part of running a successful,
top-rated Medicare Advantage (MA) plan, but there is no one-size-fits-all approach to
member engagement, especially for plans that serve medically frail populations such
as Medicare-Medicaid dual-eligibles.
“[Seniors] have different needs and the way we need to communicate with them
is different,” Jim Fields, a government programs and healthcare reform specialist at
38 • AIS’s Management Insight Series
Oliver Wyman said at a June 11, 2015, Welltok webinar on keeping seniors engaged
with their health outcomes.
Fields said MA plans should focus on authentic and empathetic experiences between members and providers to foster completion of the Agency for Healthcare
Research and Quality’s Consumer Assessment of Healthcare Providers Systems
(CAHPS) surveys and ensure seniors take an active role in their healthcare. These steps
can be much more difficult, however, for plans serving duals, largely because of longstanding socioeconomic and health literacy issues.
“[Duals] may be less independent, so the channels you use may need to shift,”
Fields said. “You often have to help them take the step to get them into the provider
and follow through on care guidelines. It’s a more intensive, more hand-holding activated model.”
Since duals are less likely to have reliable access to transportation, Fields asserted
in-home vendors and certain technology could “without a doubt” improve the population’s adherence to care and opinion of the healthcare system.
“As you get into the Medicaid space, [members are] more likely to have a cell
phone than they are to have a permanent address,” he said. And though some duals
may be too frail to use a phone the same way other seniors can, in-home technology
plans can install to track medication schedules and relay that information back to providers could prove invaluable for duals.
In addition to adherence to care, consumer engagement through Internet technology can also increase a senior’s likelihood to complete a CAHPS survey, a key part
of measuring a plan’s star rating. Plans with dual membership are known to struggle
with star ratings improvement, so influencing these habits could be game-changing.
“Even a snapshot on their screen that says ‘Congratulations on getting your flu
shot this year,’ has a direct effect on how people respond to the CAHPS survey,” Fields
said. “Seniors are increasingly receptive to the Internet as a channel for engagement.”
Another method plans can use to improve health outcomes and boost star ratings
is creating incentives for seniors to adhere to best care practices, such as keeping regular appointments with providers and receiving recommended inoculations. Incentives,
which can range from gift cards to plan savings, may prove enticing for duals.
“Monetary rewards are the most effective,” Fields said. “Plan savings is often
harder for folks to see, as opposed to a tangible monetary thing.”
Diabetes Management Could Help Boost Stars for Struggling
Duals Plans
An increased focus on chronic disease management programs may be one key to
helping struggling Medicare Advantage (MA) plans achieve higher star ratings, experts discussed at AIS’s Oct. 22, 2015, virtual conference, 2016 Medicare Star Ratings:
Translating Trends Into Strategies. This is particularly true for Dual-Eligible Special
The Challenges of Pharmacy Star Ratings • 39
Needs Plans (D-SNPs), which consistently score ratings too low to be eligible for CMS
bonuses; further penalizing plans that in some cases are already struggling to stay
afloat.
Robert Brett, vice president of Medicare at CareSource, mentioned several areas
that have been most challenging for duals plans, including osteoporosis management
and cancer screenings. Focusing on any of these areas could improve performance, but
Brett recommended plans focus on four diabetes measures as the most cost-effective
way to achieve a ratings boost:
u C13 Diabetes Care – Eye Exam; u C14 Diabetes Care – Kidney Disease Monitoring;
u C15 Diabetes Care – Blood Sugar Controlled;
u D12 Medication Adherence for Diabetes Medication.
“Diabetes is a key area to focus on,” he said, adding that these four measures make
up 10% of a plan’s overall star rating. “It’s something where you can get some bang
from your buck when talking about interventions.”
Brett outlined several strategies plans can implement to improve diabetes management, including:
u Improving monitoring of targeted members and performing trend analysis,
u Improving member outreach,
u Facilitating close interaction between members and their primary care physicians.
Member outreach has proven critical to better health outcomes, but this would be a
huge obstacle for duals plans to overcome, according to Stephen Wood, co-founder of
Clear View Solutions, LLC, who also spoke at the conference.
“In many plans, over half of the phone numbers that they have for their duals
members are bad,” he said. “How are you going to go out and have folks get reminded
about having their breast cancer screening if you can’t get a hold of them?”
Brett mentioned several solutions for finding hard-to-reach members, such as sharing data with pharmacy benefit managers, which often have more accurate contact
information on file, and working with physicians to obtain that data from members
directly whenever possible.
While these interventions may prove helpful, the overall stars outlook is still
gloomy for duals plans. Although four D-SNPs achieved overall 5-star ratings for 2016,
Wood said that can be misleading, and needs to be examined more carefully. “If you
peeled the onion and looked at [SNP enrollment] as part of the overall plan, it was a
tiny fraction of the plan’s enrollment,” he said.
With 90% of plans scoring between 3 and 3.5 stars in 2015 failing to improve performance in 2016, Wood said he is not particularly optimistic that plans scoring even
lower than that will ever be able to recover.
40 • AIS’s Management Insight Series
Stars Memo Offers Two Complex Options to Aid Plans Serving
Low-SES Members
There seems to be no question about what CMS regarded as the most important
issue it needed to deal with in its annual star ratings enhancements memo, which the
agency disseminated Nov. 12, 2015. CMS spent more than seven pages outlining two
complex approaches it is considering for adjusting 2017 star ratings to take into account the impact of socioeconomic status (SES) and disability.
While industry executives and consultants tell AIS they appreciate the hard work
and desire to help that CMS is exhibiting in the proposals, they have doubts about
how effective either option would be. “I’m afraid there’s no silver bullet here,” says,
for instance, Christie Teigland, Ph.D., senior director of statistical research at health
data analytics firm Inovalon, Inc., which did a major study of the issue using data and
other input from six MA sponsors and two trade groups in 2014.
There were some other major subjects in the new stars memo, which came from
Amy Larrick, acting director of CMS’s Medicare Drug Benefit and C & D Data Group.
Those subjects included a warning that the agency would be scrutinizing plans’ medication therapy management (MTM) programs for possible evidence of biased data.
And CMS said it would remove two measures from use in scoring star ratings for 2017
and is making methodology changes on six other measures. But the agency is not adding any star scoring measures for 2017, and even a new adjustment it reports considering for Puerto Rico contracts in some ways involves the same kind of SES-related
issues at the apparent forefront of its stars agenda for 2017 and beyond.
In general, Melissa Smith, senior consultant at Gorman Health Group, LLC, tells
AIS, she is “not terribly surprised” by anything in the stars memo. She calls the absence of new stars measures for 2017 “welcome news” for health plans. They also will
be heartened by CMS’s temporary removal, outlined in the memo, of the measure on
improving bladder control, which MA sponsors generally have not done well on, she
says.
The other temporarily withdrawn measure, on high risk medication (HRM), is in a
different situation since 330 plans were rated at four stars or above on it, Smith notes.
And one of the reasons CMS gave for this planned withdrawal is that “there is a significant association between dual eligible/low income status and HRM use….We recommend that the measure developers further review this measure to better understand
the associations.” In the meantime, CMS apparently wants to finalize its own interim
approach to the SES/disability issue in stars.
Its major new step toward that end, outlined after the agency cautioned that “CMS’
work is not complete,” is presenting two alternative approaches to adjusting for such
disadvantaged status.
The first one, which CMS called the Categorical Adjustment Index, is a factor
added to or subtracted from a contract’s overall and/or summary (i.e., MA or Part D)
The Challenges of Pharmacy Star Ratings • 41
star rating to adjust “for the average within-contract disparity” based on the contract’s
percentages of low-income subsidy (LIS)/dual eligible (DE) and/or disabled beneficiaries. “This approach is equivalent to case-mix adjustment or patient-mix adjustment,”
CMS explained before detailing the specific ways it could be derived.
The second option, which CMS called Indirect Standardization, “would be applied
to a subset of the individual star ratings measure scores.” The adjustment would focus,
according to the memo, on the “within-contract LIS/DE and/or disability status difference while allowing for the existence of true differences in quality by contract.” The
method would calculate an “expected measure score” using the percentages of these
disadvantaged groups per measure “multiplied by the adjusted mean national performance for each subgroup.” Then, CMS added, “each contract would be judged against
its expected performance,” and this observed-to-expected ratio would be multiplied
by the adjusted national mean performance for all Medicare beneficiaries to get an
“adjusted measure score.”
The problem on both approaches, according to Teigland, is that there is “lots of
missing information we’d need to evaluate.” Among details she says are needed to
assess the options are how many and which star measures the methods would be applied to. Teigland calls the first option a “much more blunt approach” than the second,
which she reports “leaning toward” preferring. But if the first option used a broader
set of risk-adjustment measures — such as adjustments for age, gender, income and
prevalence of chronic conditions — that “would help,” Teigland says.
Whichever option CMS selects (and it raised the third possibility of a hybrid of the
two), “my gut is it will not have much impact” on plans serving highly disadvantaged
populations, Teigland tells AIS. She fears this could be a step back toward the onlysmall-changes-needed position CMS took Sept. 10, 2015, in unveiling its new research
on the impact of duals/LIS status on stars performance, before both the agency’s
acting administrator and Center for Medicare director indicated about a month later
that meaningful aid is on the way. But Teigland also is quick to acknowledge that CMS
seems to be really trying to give short-term relief to plans that need it.
Inovalon is formulating questions to ask Larrick about the approaches, Teigland
says, and she praises the responsiveness of Larrick’s group in the past. However,
regardless of how quick it is in answering, Inovalon would not be able to do all the
needed modeling before the Dec. 10, 2015, comment deadline, Teigland says. So she’s
hoping indications that CMS is willing to keep making changes until the advance 2017
MA payment notice and Call Letter is released in mid-February 2016 were correct.
John Baackes, CEO of L.A. Care Health Plan, which serves many duals and other
disadvantaged populations, looks at the big picture on the proposed adjustments and
calls it “good news.” While there weren’t sufficient useful data before for CMS to make
pay adjustments for these populations, this is changing, he suggests. And he tells AIS
that the kinds of options CMS is considering in the memo could have a “material” beneficial impact on L.A. Care’s finances.
42 • AIS’s Management Insight Series
In looking at other portions of the stars memo, Smith sees as significant the degree
to which CMS intends in the coming years to introduce more measures related to medication. Among the new measures the memo lists as under consideration for 2018 and
beyond, for example, are ones related to “medication reconciliation post discharge,”
statin therapy for patients with cardiovascular disease and statin use in persons with
diabetes. CMS said all of those will be added to the display page (i.e., not used for
actual stars calculations) for 2017 and that it intends to use them for computing star
ratings in 2018.
Moreover, the agency said it will add three measures related to use of opioids from
multiple providers or at high dosage in persons with cancer to the display page in
2018, although it does not yet recommend adding them for actual star ratings because
of several methodology concerns. It has plans for a new measure on antipsychotic use
in persons with dementia for similar reasons.
The agency also is concerned about how plans are acting on existing medication
measures related to MTM. “We intend to review and apply any relevant MTM program audit findings that could demonstrate sponsors’ MTM data were biased, outside
of the Data Validation results,” the memo said. CMS explained that it suspects such
sponsor activities as “attempts to restrict eligibility from their approved MTM programs, encouraging beneficiary opt-out of MTM programs within the first 60 days,
or CMRs [i.e., Comprehensive Medication Reviews] that do not meet CMS’ definition
per guidance. CMS may perform additional audits or reviews to ensure the validity of
data for specific contracts. Without rigorous validation of star ratings data, there is risk
that CMS would reward contracts with falsely high ratings.”
Smith says what her consulting firm is hearing is that some plans are “working
aggressively to manage the denominator” in MTM calculations such as by removing
member opt-outs from it to get higher fractions for purposes of boosting star-measure
scores. She advises plans to review their “work flows and decision trees” on MTM,
especially regarding opt-out criteria, to ensure they are meeting beneficiary needs and
the goals of CMS.
The agency took a full page in the 27-page memo to discuss an “additional adjustment for contracts in Puerto Rico,” which does not have an LIS, to identify beneficiaries there whose incomes would qualify for an LIS designation in the mainland. This
would be used in conjunction with whichever option CMS selects on the SES/disabled
issue to try to help beneficiaries and plans there. The memo also points to “unique
challenges that Puerto Rican contracts face in improving medication adherence” because beneficiaries there have high out-of-pocket costs. CMS considered reducing
weights of the three Part D medication adherence measures in Puerto Rico but rejected
that when its modeling indicated the highest ratings would be unchanged, and asked
for other proposals “to account for the barriers” there.
The Challenges of Pharmacy Star Ratings • 43
Trade Groups Cite Doubts About CMS’s Two Options for
Adjusting Stars for SES
Trade associations representing Medicare Advantage plans serving disadvantaged populations expressed numerous reservations about the two options CMS in
November 2015 requested comments on for offering interim relief on star quality ratings for such plans. In their comment letters filed by the Dec. 10, 2015, CMS deadline,
the associations all thanked CMS for seeking ways to help these financially ailing plan
sponsors in the short run, but said they had numerous questions remaining even after
a Dec. 3, 2015, one-hour CMS conference call on the two options. And they generally
voiced doubts about how effective either option would be in granting meaningful
relief.
At least one association alluded to another potentially troublesome issue that came
up in the agency’s responses on the conference call. Regardless of which option CMS
chooses, affected plans may not be able to preview their star ratings for the next year
until significantly later in the year than they do now. And if CMS adopts the Indirect
Standardization (IS) option, it needs to be based on the current year’s data, adding
more uncertainties to the process for insurers.
The reservations expressed in the comment letters could lead CMS not to adopt
either option. That would parallel action it took in 2015 when it dropped a proposal
to reduce the weighting of certain stars measures that plans serving populations with
low socioeconomic status (SES) do poorly on after the vast majority of the comments it
received were critical of that approach.
In their comments, stakeholders praised aspects of both the IS option and the
Categorical Adjustment Index (CAI) alternative, which was favored by the Medicare
Payment Advisory Commission (MedPAC), among others. CAI uses a factor added to
or subtracted from a contract’s overall and/or summary star rating to adjust withincontract disparities based on an MA contract’s percentages of low-income subsidy
(LIS)/Medicare-Medicaid dual eligible (DE) and/or disabled beneficiaries. IS instead
would adjust a subset of individual star ratings scores to account for within-contract
LIS/DE and/or disability status differences not related to plan quality and would use
an “expected measure score” as its key standard.
MedPAC, in its Dec. 2, 2015, letter from Chairman Francis (Jay) Crosson, M.D., said
it has “two concerns” regarding the IS approach. One of them, according to the letter,
is that several of the measures for which CMS and MedPAC “found population-based
differences are measures that are reported based on medical record sampling (generally 411 records)” or on which some contracts report based on sampling while others
report based on “the universe of enrollees to whom the measure applies.” The question MedPAC has, explained Crosson, is whether such a sample “yields a sufficient
number of records for a subpopulation within a contract to be able to determine a
valid measure result for the subpopulation.”
44 • AIS’s Management Insight Series
He said the second concern is that “if all enrollees within a subpopulation are
used to determine an all-contract expected rate, then undue weight would be given to
contracts that report based on the universe of enrollees to whom the measure applied.”
An MA contract with far more diabetic enrollees than another plan has would yield a
disproportionate impact on the key calculation of the expected rate, Crosson observed.
By contrast, he asserted, the CAI “is administratively less complicated but still addresses the concerns plans have raised.” So “we would thus urge CMS to implement
this approach as an interim measure” given CMS’s desire to offer interim relief, he
added.
ACAP Seeks Examples on Duals Plans
The Association for Community Affiliated Plans, on the other hand, did not
take a position on the two options, contending that more information from CMS is
needed before ACAP can determine how well the two approaches “adjust for SES.”
Specifically, wrote ACAP CEO Meg Murray in the comments letter, it would like more
detail and numeric examples to show this, “particularly for contracts with majority or
100% dual [i.e., Medicare-Medicaid dual eligibles] enrollment.”
Murray said ACAP also would like estimates of how star ratings would change for
contracts under each approach and the “strengths and weaknesses” of each. And the
letter asked for clarification on whether plans would need a minimum number of LIS/
dual or disabled enrollees in order to receive an adjustment via either approach. Of
ACAP’s 61 “safety net” plan members, 15 are in the ongoing CMS-backed demonstration for duals.
On the CAI, Murray wrote, ACAP
asks to clarify whether institutionalized beneficiaries would be included
in the adjustment. And on the IS option CMS should “clarify to what
extent, if at all, the subset of adjusted
measures would change year-to-year”
and whether insurers “should expect
both upside and downside adjustment” since in a few stars measures
plans with high proportions of disabled duals outperform other plans,
she said.
Consulting firm Avalere Health
LLC prepared an analysis of the two
options as part of a stars-changes
webinar Dec. 8, 2015. In this webinar,
Christie Teigland, Ph.D., an Avalere
CAI and Indirect Standardization Differ
In Approach Across Key Parameters
Method 1: Categorical Method 2: Indirect
Adjustment Index (CAI) Standardization
Star Measures
Adjusted
Subset of 16 HEDIS/
HOS/PDE measures
Subset of 16 HEDIS/
HOS/PDE measures
Data Measurement
Year
Current year or prior year Current year
Adjustment Level
Adjusts based on mean
difference in Star Rating
(adjusted rating vs.
observed rating) for
groups of contracts
Adjusts measure
scores at contract
level
Method
Linear regression to
calculate impact of dual
eligible/disabled on
measure score
Logistic regression to
calculate impact of
dual eligible/disabled
on measure score
Adjustment
Groups of contracts with
similar levels of duals/
disabled
Contract
Note: HEDIS=Healthcare Effectiveness Data and Information Set;
HOS=Health Outcomes Survey; PDE=Prescription Drug Event.
SOURCE: © 2015 Avalere Health/An Inovalon Company; used in
Avalere webinar “Medicare Advantage Star Ratings: Sifting Through
Proposed Changes and What They Mean,” Dec. 8, 2015.
The Challenges of Pharmacy Star Ratings • 45
vice president, said that more information is needed even after CMS’s Dec. 3, 2015, call
on the options, especially on how the average national rates the agency would use in
the options are calculated. But she added that for many of the stars measures, any adjustments would be “pretty small” under either option. This is especially true since the
16 star measures that could be adjusted account for only 27% of potential stars scores,
according to Teigland.
All of those points figured prominently in the comments about the proposals submitted by two other associations, America’s Health Insurance Plans (AHIP) and the
SNP Alliance, which represents MA Special Needs Plans.
The lengthy SNP Alliance comments centered on “four principal concerns” it had
about the proposed options. The first one, the alliance wrote, is that “both options may
only minimally account for underlying disparities in star performance for plans specializing in care of poor Medicare beneficiaries.” It based that conclusion on research
showing that adjusting for just dual and/or LIS status “does not capture the full
amount of within-contract differences in stars performance.”
Moreover, according to the alliance, “The number of measures targeted for inclusion in both models represents a subset of measures that research suggests are impacted by SES. We strongly urge CMS to apply the interim adjustment to all measures
in the star rating system related to patient care” while excluding measures such as
customer service and appeals rates “directly related to plan activity.”
Alliance Fears Interim Policy Could Stay
The alliance also asserted that “neither option incorporates many of the factors
shown in the research to be of greatest importance in accounting for social determinants of health” such as income, education, occupation and social supports. The third
concern was that CMS has not furnished sufficient information for plans to understand
and fully evaluate the feasibility and impact of the options despite the details given in
the agency’s Request for Comments (RFC) and call. Finally, and perhaps underlying
its other three reservations, the alliance said it “is concerned that the interim proposal
could easily become long-term policy without a more aggressive approach to address
social determinants of health.”
Its recommendations, based on these reservations, included that “CMS should risk
adjust quality measures in the star rating system for beneficiaries’ socio-demographic
characteristics beginning in 2018.” For interim relief, it suggested that CMS maximize
the number of measures selected for adjustment, with “at a minimum” using all 12
measures showing “a negative performance gap for dual eligible members, as well as
consideration of neighborhood poverty and physician shortage factors.”
AHIP’s comments, sent by Mark Hamelburg, senior vice president, federal programs, begin by calling the proposals “an important step forward.” But AHIP too says
it is being hampered in commenting by the lack of “detailed analyses of the potential
46 • AIS’s Management Insight Series
impact of each approach.” While CMS has said it would be furnishing more details
on both approaches when it releases the draft 2017 MA pay notice and Call Letter in
February 2016, Hamelburg noted, “we strongly urge the agency to release this information as far in advance of that time as possible,” along with estimates of the “total
impact of each approach on the program as a whole.”
The comments go on to raise concerns about the time factors, pointing out CMS
said in the Dec. 3, 2015, call that the options would require additional data-processing
steps, resulting in a “compressed timeframe” for MA and Part D plans’ preview of
their star ratings.
But AHIP’s strongest comments related to the potential impact on “high performing plans.” Citing comments in both the RFC and Dec. 3,2 015, call that the proposed
adjustments could reduce star ratings for some plans, Hamelburg wrote that “we
strongly disagree with this approach. No contract should be penalized if the adjusted
Part C or D Summary Rating or Overall Rating calculated under the adopted approach
would be lower than the unadjusted rating.” The Social Security Act “does not require
changes to the star ratings system to be budget neutral,” he added.
Those comments may have stemmed from responses made in the CMS call by
Elizabeth Goldstein, Ph.D., director of consumer assessment and plan performance in
the agency’s Medicare Drug Benefit and C&D Data Group. She said that the adjustments could be either positive or negative and that CMS in any interim relief would be
able to make adjustments only for those factors it has sufficient data on.
This raises a question articulated by Avalere Vice President and former CMS official Tom Kornfield during that firm’s webinar. “The question is whether it’s better to
do nothing than to do this,” he asserted, and to wait for the permanent relief CMS may
be able to offer in 2018 after it gets more data. Avalere’s sense of the options outlined
in the RFC, he added, is “this doesn’t really solve the problem.”
The Challenges of Pharmacy Star Ratings • 47
Impact on Performance
Contract Enrollment for Plans Whose Star Ratings Increased in 2016
2015
Overall
Rating
2016
Overall
Rating
2015
Contract
Enrollment
2016
Contract
Enrollment
BLUE CROSS AND BLUE SHIELD OF ALABAMA
3.5
4
49,576
53,395
7.70%
HEALTHSPRING OF ALABAMA, INC.
3.5
4
52,553
59,025
12.32%
Contract
Number
Contract Name
H0104
H0150
H0151
H0154
H0251
UNITEDHEALTHCARE PLAN OF THE RIVER VALLEY,
INC.
H0354
UNITEDHEALTHCARE OF ALABAMA, INC.
%
Change
3
3.5
33,725
35,179
4.31%
3.5
4
45,419
43,315
-4.63%
3
3.5
41,024
43,540
6.13%
CIGNA HEALTHCARE OF ARIZONA, INC.
4.5
5
43,215
52,816
22.22%
H0602
ROCKY MOUNTAIN HEALTH MAINTENANCE
ORGANIZATION
3.5
4
24,343
24,211
-0.54%
H0609
H0624
H0710
H0755
H0908
H0913
H1111
H1304
H1517
H1659
H1849
PACIFICARE OF COLORADO, INC
4
4.5
100,105
240,691
140.44%
UNITEDHEALTHCARE INSURANCE COMPANY
3
3.5
3,647
4,850
32.99%
439.41%
VIVA HEALTH, INC.
4
4.5
2,593
13,987
3.5
4
37,587
42,537
13.17%
2
3
1,025
885
-13.66%
2.5
3
1,044
912
-12.64%
3
3.5
8,490
9,624
13.36%
3.5
4
7,914
5,526
-30.17%
3
3.5
3,358
2,705
-19.45%
2.5
3
4,570
5,151
12.71%
ANTHEM HEALTH PLANS OF KENTUCKY, INC.
3
3.5
6,085
7,143
17.39%
H1951
HUMANA HEALTH BENEFIT PLAN OF LOUISIANA,
INC.
4
4.5
124,570
134,912
8.30%
H2001
SIERRA HEALTH AND LIFE INSURANCE COMPANY,
INC.
4
4.5
611,215
726,013
18.78%
H2029
HUMANA INSURANCE OF PUERTO RICO, INC.
3
3.5
1,833
1,141
-37.75%
H2165
HEALTHSPRING LIFE & HEALTH INSURANCE
COMPANY, INC.
3
3.5
6,310
6,985
10.70%
H2224
H2226
SENIOR WHOLE HEALTH, LLC
3.5
4
10,146
10,642
4.89%
UNITEDHEALTHCARE INSURANCE COMPANY
3.5
4.5
12,775
14,302
11.95%
H2256
TUFTS ASSOCIATED HEALTH MAINTENANCE
ORGANIZATION
4.5
5
104,955
105,966
0.96%
H2354
HEALTHPLUS OF MICHIGAN
2.5
4.5
20,411
17,514
-14.19%
H2416
PRIMEWEST CTRL COUNTY-BASED PURCHASING
INITIATIVE
3.5
4
1,952
1,937
-0.77%
H2419
H2425
H2462
H2610
UNITEDHEALTHCARE INSURANCE COMPANY
OXFORD HEALTH PLANS (CT), INC.
BUCKEYE COMMUNITY HEALTH PLAN, INC.
WELLCARE HEALTH PLANS OF NEW JERSEY, INC.
UNITEDHEALTHCARE OF GEORGIA, INC.
REGENCE BLUE SHIELD OF IDAHO
ANTHEM INSURANCE COMPANIES, INC.
PIEDMONT COMMUNITY HEALTHCARE, INC.
4
4.5
1,554
1,581
1.74%
BLUE PLUS
SOUTH COUNTRY HEALTH ALLIANCE
3.5
4
8,049
7,836
-2.65%
GROUP HEALTH PLAN, INC. (MN)
4.5
5
48,841
50,104
2.59%
ESSENCE HEALTHCARE, INC.
4.5
5
51,896
58,906
13.51%
H2775
AMERICAN PROGRESSIVE LIFE & HLTH INS
COMPANY OF NY
3.5
4
10,913
12,789
17.19%
H2802
UNITEDHEALTHCARE OF THE MIDLANDS, INC.
3.5
4.5
9,980
29,324
193.83%
H2905
SIERRA HEALTH AND LIFE INSURANCE COMPANY,
INC.
2.5
3
3,513
3,415
-2.79%
H2906
H2931
H3107
HOMETOWN HEALTH PLAN, INC.
3.5
4
3,932
3,309
-15.84%
HEALTH PLAN OF NEVADA, INC.
3.5
4
50,917
50,765
-0.30%
3
3.5
75,720
77,144
1.88%
continued OXFORD HEALTH PLANS (NJ), INC.
48 • AIS’s Management Insight Series
Contract Enrollment for Plans Whose Star Ratings Increased in 2016
(continued)
Contract
Number
Contract Name
H3154
H3204
H3240
H3307
HORIZON HEALTHCARE OF NEW JERSEY, INC.
2015
Overall
Rating
2016
Overall
Rating
2015
Contract
Enrollment
2016
Contract
Enrollment
%
Change
3
3.5
25,891
23,684
-8.52%
3.5
4.5
33,047
36,629
10.84%
AMERIGROUP NEW JERSEY, INC.
3
3.5
6,897
7,606
10.28%
OXFORD HEALTH PLANS (NY), INC.
3
3.5
72,471
81,186
12.03%
H3328
THE NEW YORK STATE CATHOLIC HEALTH PLAN,
INC.
3.5
4
35,800
54,272
51.60%
H3337
H3344
H3379
H3421
H3447
H3597
H3668
H3749
H3814
H3817
H3818
H3907
H3957
H4003
H4004
H4005
H4011
H4279
H4407
H4454
H4461
H4525
H4527
H4590
H4604
H4605
H5008
H5009
H5010
H5106
H5294
H5425
LIBERTY HEALTH ADVANTAGE, INC.
PRESBYTERIAN HEALTH PLAN
2.5
3
4,985
5,972
19.80%
INDEPENDENT HEALTH BENEFITS CORPORATION
4
4.5
3,806
3,903
2.55%
UNITEDHEALTHCARE OF NEW YORK, INC.
3
3.5
27,443
29,357
6.97%
AMERICA'S 1ST CHOICE HEALTH PLANS, INC.
3
3.5
3,759
2,960
-21.26%
42.16%
HEALTHKEEPERS, INC.
3.5
4.5
2,538
3,608
AETNA HEALTH, INC. (ME)
4
4.5
7,186
6,507
-9.45%
MOUNT CARMEL HEALTH PLAN, INC.
4
4.5
49,121
54,464
10.88%
UNITEDHEALTHCARE OF OKLAHOMA, INC.
3
3.5
28,003
26,895
-3.96%
ATRIO HEALTH PLANS
3
3.5
2,122
2,206
3.96%
REGENCE BLUECROSS BLUESHIELD OF OREGON
3.5
4.5
64,292
53,688
-16.49%
FAMILYCARE HEALTH PLANS, INC.
3
3.5
3,388
4,370
28.98%
UPMC HEALTH PLAN, INC.
4
4.5
114,746
124,359
8.38%
KEYSTONE HEALTH PLAN WEST, INC.
4
4.5
117,257
118,680
1.21%
MMM HEALTHCARE, LLC.
3.5
4
170,721
168,620
-1.23%
PMC MEDICARE CHOICE, LLC
3.5
4
30,091
23,234
-22.79%
-7.53%
TRIPLE-S ADVANTAGE, INC.
3
3.5
17,778
16,440
MMM HEALTHCARE, LLC.
2.5
3
10,530
*
NA
UPMC FOR YOU, INC
3.5
4
18,922
21,040
11.19%
HEALTHSPRING OF TENNESSEE, INC.
3.5
4
8,317
11,416
37.26%
HEALTHSPRING OF TENNESSEE, INC.
4
4.5
91,134
96,142
5.50%
CARITEN HEALTH PLAN INC.
4
4.5
106,407
108,656
2.11%
SHA, L.L.C
2.5
3.5
3,254
3,145
-3.35%
PHYSICIANS HEALTH CHOICE OF TEXAS LLC
3.5
4
27,426
29,213
6.52%
UNITEDHEALTHCARE BENEFITS OF TEXAS, INC.
3.5
4
200,330
209,620
4.64%
UNITEDHEALTHCARE OF UTAH, INC.
3.5
4.5
46,349
53,594
15.63%
REGENCE BLUECROSS BLUESHIELD OF UTAH
3.5
4.5
12,370
10,917
-11.75%
3
3.5
9,059
12,803
41.33%
UNITEDHEALTHCARE INSURANCE COMPANY
REGENCE BLUESHIELD
3.5
4
28,908
21,404
-25.96%
ASURIS NORTHWEST HEALTH
3.5
4.5
1,389
1,349
-2.88%
HIGHMARK SENIOR SOLUTIONS COMPANY
3.5
4
7,072
7,052
-0.28%
SUPERIOR HEALTH PLAN, INC.
2.5
3
2,275
779
-65.76%
SCAN HEALTH PLAN
4
4.5
157,341
167,513
6.46%
H5430
ONECARE BY CARE1ST HEALTH PLAN ARIZONA
INC.
3
3.5
1,695
1,838
8.44%
H5431
H5439
H5521
H5528
H5533
HEALTHSUN HEALTH PLANS, INC.
4
4.5
27,529
32,429
17.80%
HEALTH NET LIFE INSURANCE COMPANY
3
3.5
1,261
669
-46.95%
AETNA LIFE INSURANCE COMPANY
4
4.5
582,102
680,813
16.96%
GROUP HEALTH INCORPORATED
2.5
3
7,729
7,102
-8.11%
UPMC HEALTH NETWORK, INC.
3.5
4
9,451
8,839
-6.48%
The Challenges of Pharmacy Star Ratings • 49
Contract Enrollment for Plans Whose Star Ratings Increased in 2016
(continued)
2015
Overall
Rating
2016
Overall
Rating
2015
Contract
Enrollment
2016
Contract
Enrollment
%
Change
VANTAGE HEALTH PLAN, INC.
3.5
4
12,951
15,948
23.14%
H5652
SIERRA HEALTH AND LIFE INSURANCE COMPANY,
INC.
4.5
5
4,613
4,763
3.25%
H5746
AMERIGROUP COMMUNITY CARE OF NEW
MEXICO, INC.
2.5
3.5
2,388
1,954
-18.17%
H5817
H5823
H5926
H5932
H5969
H5995
AMERIGROUP TEXAS, INC.
3
4
34,165
29,875
-12.56%
MOLINA HEALTHCARE OF WASHINGTON, INC.
3
3.5
8,853
9,753
10.17%
MOLINA HEALTHCARE OF MICHIGAN, INC.
3
3.5
12,771
10,068
-21.17%
Contract
Number
Contract Name
H5576
GATEWAY HEALTH PLAN, INC.
2.5
3.5
48,761
50,792
4.17%
ALOHACARE
2.5
3.5
458
742
62.01%
3
3.5
3,129
3,087
-1.34%
2.5
3
25,419
25,709
1.14%
36.74%
ATRIO HEALTH PLANS
H6528
CARE IMPROVEMENT PLUS SOUTH CENTRAL
INSURANCE CO.
H6815
H7187
H7678
H7917
H8189
H8748
H9104
HEALTH NET HEALTH PLAN OF OREGON
4
4.5
23,306
31,869
UNITEDHEALTHCARE INSURANCE COMPANY
3
3.5
10,114
10,949
8.26%
MOLINA HEALTHCARE OF TEXAS, INC.
3
3.5
5,969
3,786
-36.57%
SCAN HEALTH PLAN
R6801
CARE IMPROVEMENT PLUS OF TEXAS INSURANCE
COMPANY
R7444
UNITEDHEALTHCARE INSURANCE COMPANY
BLUECROSS BLUESHIELD OF TENNESSEE, INC.
3.5
4
89,791
93,045
3.62%
MANAGED HEALTH SERVICES, WISCONSIN
2.5
3.5
1,040
988
-5.00%
3
3.5
2,480
3,396
36.94%
3.5
4
1,415
219
-84.52%
2.5
3
71,426
78,411
9.78%
3.5
4
20,443
20,847
1.98%
UNITEDHEALTHCARE INSURANCE COMPANY
NOTE: Does not include new or terminated plans.
SOURCE: Calculated by AIS from CMS data for AIS's Medicare and Medicaid Market Data: 2016.
Contract Enrollment for Plans Whose Star Ratings Decreased in 2016
Contract
Number
H0423
H0523
H0544
H0545
H0838
H1019
H1035
H1036
H1045
H1099
H1112
H1350
H1415
Contract Name
2015
Overall
Rating
2016
Overall
Rating
2015
Contract
Enrollment
2016
Contract
Enrollment
% Change
METROPLUS HEALTH PLAN, INC.
3.5
3
8,571
8,500
-0.83%
AETNA HEALTH OF CALIFORNIA INC.
3.5
3
16,778
16,078
-4.17%
CAREMORE HEALTH PLAN
4.5
4
50,997
51,971
1.91%
INTER VALLEY HEALTH PLAN, INC.
4
3.5
22,250
23,089
3.77%
UNIVERSAL CARE, INC.
3.5
3
7,156
10,151
41.85%
CAREPLUS HEALTH PLANS, INC.
5
4.5
105,623
110,197
4.33%
FLORIDA HEALTH CARE PLAN, INC.
4.5
4
13,205
14,256
7.96%
HUMANA MEDICAL PLAN, INC.
4.5
4
424,214
453,064
6.80%
PREFERRED CARE PARTNERS, INC.
4
3.5
54,138
118,863
119.56%
HEALTH FIRST HEALTH PLANS
4
3.5
29,695
34,429
15.94%
WELLCARE OF GEORGIA, INC.
3
2.5
32,202
36,396
13.02%
BLUE CROSS OF IDAHO CARE PLUS, INC.
4.5
4
22,325
19,777
-11.41%
HEALTHSPRING OF TENNESSEE, INC.
3.5
3
17,742
19,718
11.14%
continued
50 • AIS’s Management Insight Series
Contract Enrollment for Plans Whose Star Ratings Decreased in 2016
(continued)
Contract Name
2015
Overall
Rating
2016
Overall
Rating
2015
Contract
Enrollment
2016
Contract
Enrollment
% Change
H1417
H1418
H1716
H1994
H2225
H2450
H2486
H2654
H2663
H2667
H3152
H3156
H3251
H3342
H3384
H3660
H3672
H3813
H3815
H3822
H3864
H3909
H3959
H4523
H4875
H5050
H5302
H5414
H5522
H5594
H5698
H6328
H6360
H6609
H6743
H7149
H7220
HEALTH ALLIANCE CONNECT, INC.
4.5
4
8,584
9,977
16.23%
HUMANA INSURANCE COMPANY
4
3.5
12,221
11,086
-9.29%
HUMANA INSURANCE COMPANY
4
3.5
13,293
11,303
-14.97%
SELECTHEALTH, INC.
4.5
3.5
31,489
37,030
17.60%
COMMONWEALTH CARE ALLIANCE, INC.
4.5
4
6,321
6,924
9.54%
MEDICA INSURANCE COMPANY
4.5
4
169,498
186,103
9.80%
HUMANA MEDICAL PLAN OF UTAH, INC.
4
3.5
5,665
5,309
-6.28%
UNITEDHEALTHCARE OF THE MIDWEST, INC.
4
3.5
47,003
78,061
66.08%
COVENTRY HEALTH CARE OF MISSOURI, INC
4.5
4
56,787
49,936
-12.06%
COVENTRY HEALTH CARE OF MISSOURI, INC
4.5
4
19,534
22,467
15.01%
AETNA HEALTH, INC. (NJ)
4
3.5
37,432
39,800
6.33%
AMERIHEALTH HMO, INC.
3.5
3
18,643
19,120
2.56%
HEALTH CARE SERVICE CORPORATION
4
3
18,712
16,681
-10.85%
EMPIRE HEALTHCHOICE ASSURANCE, INC.
3.5
3
44,327
6,850
-84.55%
HEALTHNOW NEW YORK INC.
4.5
4
23,907
23,396
-2.14%
SUMMACARE INC.
4
3.5
27,126
24,273
-10.52%
HEALTH PLAN OF THE UPPER OHIO VALLEY
4
3.5
5,218
13,111
151.26%
MODA HEALTH PLAN, INC.
4
3.5
12,192
15,456
26.77%
ALIGNMENT HEALTH PLAN
3.5
3
19,038
19,329
1.53%
HEALTH CARE SERVICE CORPORATION
4
3
23,137
28,117
21.52%
PACIFICSOURCE COMMUNITY HEALTH PLANS
4
3.5
24,168
27,342
13.13%
QCC INSURANCE COMPANY
4.5
4
8,800
9,407
6.90%
HEALTHAMERICA PENNSYLVANIA, INC.
4.5
4
69,591
63,262
-9.09%
AETNA HEALTH, INC. (TX)
3.5
3
13,099
23,533
79.65%
PRIORITY HEALTH
4.5
4
17,224
24,278
40.95%
GROUP HEALTH COOPERATIVE
5
4.5
82,410
89,561
8.68%
AETNA HEALTH, INC. (GEORGIA)
3.5
3
1,357
256
-81.13%
AETNA HEALTH, INC. (FL)
4
3.5
18,299
66,803
265.06%
HEALTHASSURANCE PENNSYLVANIA, INC.
4.5
4
72,300
69,659
-3.65%
OPTIMUM HEALTHCARE, INC.
4.5
4
38,941
43,950
12.86%
WINDSOR HEALTH PLAN, INC.
3
2.5
38,471
42,312
9.98%
CARE N' CARE INSURANCE COMPANY, INC.
4
3.5
9,846
10,550
7.15%
HEALTHSPAN INTEGRATED CARE
5
4
13,656
11,445
-16.19%
HUMANA INSURANCE COMPANY
4.5
4
785,863
665,282
-15.34%
ATRIO HEALTH PLANS
3.5
3
6,980
8,681
24.37%
COVENTRY HEALTH CARE OF NEBRASKA, INC. 4
3.5
6,442
8,053
25.01%
INDIANA UNIVERSITY HEALTH PLANS, INC.
4.5
4
11,862
16,361
37.93%
H7787
HEALTHSPRING LIFE & HEALTH INSURANCE
COMPANY, INC.
3.5
3
5,035
6,664
32.35%
H8578
H8953
H9047
H9302
H9859
HEALTH NEW ENGLAND, INC.
4.5
4
8,577
9,143
6.60%
HUMANA HEALTH PLAN OF OHIO, INC.
4
3.5
40,289
47,470
17.82%
PROVIDENCE HEALTH PLAN
5
4.5
46,865
49,783
6.23%
SOUNDPATH HEALTH
3.5
3
20,772
26,405
27.12%
MVP HEALTH PLAN, INC.
4.5
4
11,515
13,042
13.26%
Contract
Number
The Challenges of Pharmacy Star Ratings • 51
Contract Enrollment for Plans Whose Star Ratings Decreased in 2016
(continued)
2015
Overall
Rating
2016
Overall
Rating
2015
Contract
Enrollment
2016
Contract
Enrollment
% Change
R3332
BLUE CROSS AND BLUE SHIELD OF FLORIDA,
INC.
3.5
3
49,517
46,811
-5.46%
R5826
HUMANA INSURANCE COMPANY
4
3.5
499,277
523,542
4.86%
Contract
Number
Contract Name
NOTE: Does not include new or terminated plans.
SOURCE: Calculated by AIS from CMS data for AIS's Medicare and Medicaid Market Data: 2016.
Contract Enrollment for Plans Whose Star Ratings Stayed the Same in
2016
2015
Overall
Rating
2016
Overall
Rating
2015
Contract
Enrollment
2016
Contract
Enrollment
% Change
4
4
10,065
14,866
47.70%
3.5
3.5
6,865
6,978
1.65%
MEDISUN, INC.
4
4
45,791
60,953
33.11%
ARIZONA PHYSICIANS IPA, INC.
3
3
35,940
38,788
7.92%
KS PLAN ADMINISTRATORS, LLC
4.5
4.5
29,432
30,304
2.96%
HEALTH NET OF ARIZONA, INC.
Contract
Number
Contract Name
H0028
CHA HMO, INC.
H0294
CARE IMPROVEMENT PLUS WISCONSIN
INSURANCE COMPANY
H0302
H0321
H0332
H0351
H0504
H0524
H0543
H0562
H0564
H0571
H0630
H0712
H1016
H1026
H1032
H1109
H1170
H1230
H1264
H1286
H1302
H1365
H1406
H1416
H1463
H1468
H1510
H1607
3.5
3.5
38,633
26,138
-32.34%
CALIFORNIA PHYSICIANS' SERVICE
4
4
101,927
94,458
-7.33%
KAISER FOUNDATION HP, INC.
5
5
1,010,165
1,057,312
4.67%
UHC OF CALIFORNIA
4
4
328,182
335,288
2.17%
HEALTH NET OF CALIFORNIA,INC.
4
4
164,571
142,976
-13.12%
BLUE CROSS OF CALIFORNIA
3.5
3.5
12,558
20,371
62.22%
CHINESE COMMUNITY HEALTH PLAN
2.5
2.5
8,542
8,553
0.13%
KAISER FOUNDATION HP OF CO
5
5
95,800
101,441
5.89%
WELLCARE OF CONNECTICUT, INC.
3
3
12,516
7,240
-42.15%
-1.16%
AVMED, INC.
4
4
31,054
30,694
HEALTH OPTIONS, INC.
3.5
3.5
60,439
61,232
1.31%
WELLCARE OF FLORIDA, INC.
3.5
3.5
106,324
92,088
-13.39%
AETNA HEALTH INC.(GEORGIA)
3.5
3.5
3,547
3,855
8.68%
KAISER FOUNDATION HP OF GA, INC.
4.5
4.5
24,362
26,026
6.83%
KAISER FOUNDATION HP, INC.
5
5
30,764
32,038
4.14%
WELLCARE OF TEXAS, INC.
3
3
31,597
33,442
5.84%
UNITEDHEALTHCARE INSURANCE COMPANY
3.5
3.5
13,608
14,966
9.98%
BLUE CROSS OF IDAHO CARE PLUS, INC.
3.5
3.5
10,400
7,322
-29.60%
MARTIN'S POINT GENERATIONS, LLC
4.5
4.5
2,499
2,305
-7.76%
4
4
48,592
54,776
12.73%
HUMANA HEALTH PLAN, INC.
HARMONY HEALTH PLAN OF ILLINOIS, INC.
3
3
14,982
14,735
-1.65%
HEALTH ALLIANCE CONNECT, INC.
4.5
4.5
7,604
8,538
12.28%
HUMANA BENEFIT PLAN OF ILLINOIS, INC.
4.5
4.5
6,266
7,069
12.82%
4
4
41,890
45,804
9.34%
3.5
3.5
8,457
1,719
-79.67%
continued HUMANA INSURANCE COMPANY
ANTHEM INSURANCE COMPANIES, INC.
52 • AIS’s Management Insight Series
Contract Enrollment for Plans Whose Star Ratings Stayed the Same in
2016 (continued)
2015
Overall
Rating
2016
Overall
Rating
2015
Contract
Enrollment
2016
Contract
Enrollment
% Change
H1608
COVENTRY HEALTH AND LIFE INSURANCE
COMPANY
4.5
4.5
30,181
131,953
337.21%
H1609
H1903
H1944
H1961
H2012
H2108
H2150
H2174
H2228
H2230
H2237
H2261
H2312
H2320
AETNA HEALTH, INC.
4.5
4.5
3,746
4,399
17.43%
WELLCARE OF LOUISIANA, INC.
2.5
2.5
9,264
10,098
9.00%
UNITEDHEALTHCARE OF NEW ENGLAND, INC.
4
4
7,314
32,040
338.06%
PEOPLES HEALTH, INC.
4
4
54,106
54,690
1.08%
HUMANA HEALTH PLAN, INC.
4
4
194,553
201,824
3.74%
BRAVO HEALTH MID-ATLANTIC, INC.
3
3
20,907
21,517
2.92%
KAISER FNDN HP OF THE MID-ATLANTIC STS
5
5
61,772
66,254
7.26%
TRILLIUM COMMUNITY HEALTH PLAN
3
3
3,892
3,385
-13.03%
UNITEDHEALTHCARE INSURANCE COMPANY
4.5
4.5
1,729
184,462
10568.71%
BCBS OF MASSACHUSETTS HMO BLUE, INC.
4.5
4.5
28,097
32,536
15.80%
INDEPENDENT CARE HEALTH PLAN, INC.
3.5
3.5
5,932
6,332
6.74%
BCBS OF MASSACHUSETTS HMO BLUE, INC.
4.5
4.5
10,757
10,488
-2.50%
4
4
43,289
43,844
1.28%
PRIORITY HEALTH
4.5
4.5
80,629
85,770
6.38%
H2322
ALLIANCE HEALTH AND LIFE INSURANCE
COMPANY
3.5
3.5
3,258
3,328
2.15%
H2406
SIERRA HEALTH AND LIFE INSURANCE
COMPANY, INC.
4
4
947
1,926
103.38%
H2422
H2456
H2458
H2459
HEALTHPARTNERS, INC.
4.5
4.5
3,180
3,153
-0.85%
UCARE MINNESOTA
3.5
3.5
10,280
10,697
4.06%
4
4
10,039
10,385
3.45%
4.5
4.5
85,475
81,542
-4.60%
H2491
WELLCARE HEALTH INSURANCE OF ARIZONA,
INC.
3
3
10,742
8,111
-24.49%
H2593
H2649
H2672
H2701
CAREMORE HEALTH PLAN OF ARIZONA, INC.
3.5
3.5
16,093
11,777
-26.82%
4
4
134,166
220,746
64.53%
COVENTRY HEALTH CARE OF KANSAS, INC.
3.5
3.5
17,780
17,925
0.82%
NEW WEST HEALTH SERVICES
3.5
3.5
17,960
14,370
-19.99%
H2816
AMERICAN PROGRESSIVE LIFE & HLTH INS
COMPANY OF NY
4
4
27,236
32,413
19.01%
H2836
H2944
H2949
H2960
H3206
H3305
H3312
ANTHEM HEALTH PLANS, INC.
3.5
3.5
1,293
*
NA
HUMANA INSURANCE COMPANY
3.5
3.5
19,217
13,344
-30.56%
HUMANA HEALTH PLAN, INC.
4
4
41,789
44,077
5.48%
HOMETOWN HEALTH PLAN, INC.
4
4
13,652
13,935
2.07%
PRESBYTERIAN INSURANCE COMPANY, INC.
3.5
3.5
8,630
8,092
-6.23%
MVP HEALTH PLAN, INC.
4.5
4.5
35,992
30,526
-15.19%
AETNA HEALTH, INC. (NY)
3.5
3.5
16,606
15,725
-5.31%
H3330
HEALTH INSURANCE PLAN OF GREATER NEW
YORK
3
3
116,037
113,830
-1.90%
H3335
H3347
H3351
H3359
H3361
EXCELLUS HEALTH PLAN, INC.
4
4
45,938
46,223
0.62%
ELDERPLAN, INC.
3
3
14,405
12,018
-16.57%
EXCELLUS HEALTH PLAN, INC.
4
4
71,650
69,173
-3.46%
MANAGED HEALTH, INC.
4
4
127,910
134,043
4.79%
WELLCARE OF NEW YORK, INC.
3
3
45,514
41,481
-8.86%
Contract
Number
Contract Name
HEALTH ALLIANCE PLAN OF MICHIGAN
MEDICA HEALTH PLANS
UCARE MINNESOTA
HUMANA HEALTH PLAN, INC.
The Challenges of Pharmacy Star Ratings • 53
Contract Enrollment for Plans Whose Star Ratings Stayed the Same in
2016 (continued)
Contract
Number
Contract Name
2015
Overall
Rating
2016
Overall
Rating
2015
Contract
Enrollment
2016
Contract
Enrollment
% Change
0.00%
H3362
H3370
H3387
INDEPENDENT HEALTH ASSOCIATION, INC.
4.5
4.5
89,792
89,791
EMPIRE HEALTHCHOICE HMO, INC.
3.5
3.5
63,458
67,499
6.37%
UNITEDHEALTHCARE OF NEW YORK, INC.
3.5
3.5
13,499
26,328
95.04%
H3388
CAPITAL DISTRICT PHYSICIANS' HEALTH PLAN,
INC.
4.5
4.5
39,609
37,072
-6.41%
H3404
BLUE CROSS AND BLUE SHIELD OF NORTH
CAROLINA
3.5
3.5
50,227
37,655
-25.03%
H3449
BLUE CROSS AND BLUE SHIELD OF NORTH
CAROLINA
3.5
3.5
76,525
69,818
-8.76%
H3528
H3653
H3655
H3664
H3706
H3755
H3805
H3810
H3811
H3832
H3916
H3923
CONNECTICARE, INC.
4
4
60,674
56,240
-7.31%
PARAMOUNT CARE, INC.
4
4
15,074
16,177
7.32%
COMMUNITY INSURANCE COMPANY
3.5
3.5
125,615
134,124
6.77%
AULTCARE HEALTH INSURING CORPORATION
4.5
4.5
20,108
20,989
4.38%
GENERATIONS HEALTHCARE, INC.
3.5
3.5
5,697
6,677
17.20%
COMMUNITY CARE HMO, INC
4
4
29,153
29,128
-0.09%
UNITEDHEALTHCARE OF OREGON, INC.
4
4
24,596
92,680
276.81%
H3924
GEISINGER INDEMNITY INSURANCE
COMPANY
H3931
H3949
H3952
H3954
H3962
AETNA HEALTH, INC, (PA)
H4007
HUMANA HEALTH PLANS OF PUERTO RICO,
INC.
H4036
ALLCARE HEALTH PLAN, INC.
4
4
2,129
1,981
-6.95%
3.5
3.5
4,979
5,217
4.78%
4
4
37,076
37,147
0.19%
HIGHMARK SENIOR HEALTH COMPANY
4.5
4.5
175,104
191,920
9.60%
CAPITAL ADVANTAGE INSURANCE COMPANY
3.5
3.5
14,618
14,221
-2.72%
4
4
7,062
15,064
113.31%
SAMARITAN HEALTH PLANS, INC.
HAWAII MEDICAL SERVICE ASSOCIATION
4
4
28,453
53,521
88.10%
BRAVO HEALTH PENNSYLVANIA, INC.
3.5
3.5
57,247
53,205
-7.06%
KEYSTONE HEALTH PLAN EAST, INC.
4.5
4.5
86,438
90,584
4.80%
GEISINGER HEALTH PLAN
4.5
4.5
68,189
71,070
4.23%
4
4
10,872
10,831
-0.38%
3.5
3.5
49,400
37,808
-23.47%
ANTHEM INSURANCE COMPANIES, INC.
4
4
1,457
26,338
1707.69%
H4141
HUMANA EMPLOYERS HEALTH PLAN OF
GEORGIA, INC.
3.5
3.5
36,483
43,665
19.69%
H4152
BLUE CROSS & BLUE SHIELD OF RHODE
ISLAND
4
4
51,317
52,628
2.55%
H4213
H4346
H4506
USABLE MUTUAL INSURANCE COMPANY
KEYSTONE HEALTH PLAN CENTRAL, INC.
3
3
17,380
16,581
-4.60%
3.5
3.5
6,057
6,697
10.57%
SELECTCARE OF TEXAS, INC.
4
4
62,874
65,531
4.23%
H4513
HEALTHSPRING LIFE & HEALTH INSURANCE
COMPANY, INC.
4
4
87,615
99,250
13.28%
H4514
UNITEDHEALTHCARE COMMUNITY PLAN OF
TEXAS, LLC
3
3
29,080
29,045
-0.12%
H4528
HEALTHSPRING LIFE & HEALTH INSURANCE
COMPANY, INC.
3
3
8,769
6,650
-24.16%
H4564
H4754
H4866
H4909
SCOTT AND WHITE HEALTH PLAN
CAREMORE HEALTH PLAN OF NEVADA
4
4
27,879
28,993
4.00%
PACIFICSOURCE COMMUNITY HEALTH PLANS
3.5
3.5
9,190
10,014
8.97%
CUATRO LLC
2.5
2.5
3,458
4,333
25.30%
4
4
2,472
864
-65.05%
ANTHEM HEALTH PLANS OF VIRGINIA, INC.
continued 54 • AIS’s Management Insight Series
Contract Enrollment for Plans Whose Star Ratings Stayed the Same in
2016 (continued)
Contract
Number
Contract Name
2015
Overall
Rating
2016
Overall
Rating
2015
Contract
Enrollment
2016
Contract
Enrollment
% Change
-51.55%
H5042
H5087
H5209
H5211
H5215
H5216
H5253
H5262
H5410
CDPHP UNIVERSAL BENEFITS, INC.
4.5
4.5
7,345
3,559
EASY CHOICE HEALTH PLAN INC.
3.5
3.5
33,568
32,117
-4.32%
4
4
1,002
1,252
24.95%
SECURITY HEALTH PLAN OF WISCONSIN, INC.
4.5
4.5
43,053
43,518
1.08%
NETWORK HEALTH INSURANCE CORPORATION
4.5
4.5
63,003
62,406
-0.95%
HUMANA INSURANCE COMPANY
4.5
4.5
33,771
31,622
-6.36%
UNITEDHEALTHCARE OF WISCONSIN, INC.
4.5
4.5
93,969
326,452
247.40%
H5415
HUMANA HEALTH INSURANCE COMPANY OF
FLORIDA, INC.
H5420
MEDICA HEALTHCARE PLANS, INC.
H5422
BLUE CROSS BLUE SHIELD HEALTHCARE
PLAN OF GEORGIA
H5427
H5428
H5433
FREEDOM HEALTH, INC.
CARE WISCONSIN HEALTH PLAN, INC.
GUNDERSEN HEALTH PLAN
5
5
14,237
14,455
1.53%
HEALTHSPRING OF FLORIDA
4.5
4.5
50,650
52,088
2.84%
4
4
14,932
11,126
-25.49%
3.5
3.5
35,276
37,580
6.53%
3
3
1,489
1,850
24.24%
4
4
62,920
69,386
10.28%
SAN MATEO HEALTH COMMISSION
3.5
3.5
817
783
-4.16%
ORANGE COUNTY HEALTH AUTHORITY
3.5
3.5
12,818
1,294
-89.90%
H5434
BLUE CROSS AND BLUE SHIELD OF FLORIDA,
INC.
3.5
3.5
11,002
10,487
-4.68%
H5435
H5471
H5520
H5525
H5526
H5530
H5549
H5577
UNITEDHEALTHCARE INSURANCE COMPANY
H5580
SOUTHWEST CATHOLIC HEALTH NETWORK
CORPORATION
H5587
H5590
H5591
H5608
H5609
H5619
H5628
H5649
H5656
H5774
H5793
H5810
H5826
H5859
H5883
H5928
HEALTH CHOICE ARIZONA, INC.
3.5
3.5
47,299
39,504
-16.48%
SIMPLY HEALTHCARE PLANS, INC.
4
4
20,989
31,382
49.52%
HEALTH NET LIFE INSURANCE COMPANY
4
4
39,115
37,902
-3.10%
HUMANA BENEFIT PLAN OF ILLINOIS, INC.
4
4
55,130
73,844
33.95%
HEALTHNOW NEW YORK INC.
4.5
4.5
18,793
17,933
-4.58%
ANTHEM HEALTH PLANS OF KENTUCKY, INC.
3.5
3.5
4,841
3,795
-21.61%
VNS CHOICE
MCS ADVANTAGE, INC.
BRIDGEWAY HEALTH SOLUTIONS
MARTIN'S POINT GENERATIONS, LLC
3
3
19,030
21,522
13.10%
3.5
3.5
172,112
197,570
14.79%
3
3
17,544
18,442
5.12%
3
3
9,470
9,675
2.16%
3.5
3.5
1,485
1,575
6.06%
14.09%
5
5
30,536
34,837
DENVER HEALTH MEDICAL PLAN, INC.
3.5
3.5
4,293
4,399
2.47%
GEMCARE HEALTH PLAN INC.
3.5
3.5
8,161
7,508
-8.00%
4
4
7,218
75,847
950.80%
MOLINA HEALTHCARE OF UTAH, INC.
3.5
3.5
8,649
8,498
-1.75%
CENTRAL HEALTH PLAN OF CALIFORNIA, INC.
3.5
3.5
27,243
32,258
18.41%
SELECTCARE HEALTH PLANS, INC.
3
3
3,946
3,139
-20.45%
TRIPLE S ADVANTAGE, INC.
3
3
98,686
104,844
6.24%
AETNA HEALTH, INC. (CT)
4
4
21,703
24,440
12.61%
MOLINA HEALTHCARE OF CALIFORNIA
3
3
3,909
4,248
8.67%
COMMUNITY HEALTH PLAN OF WASHINGTON
3
3
17,386
7,446
-57.17%
HEALTH PLAN OF CAREOREGON, INC.
3.5
3.5
11,298
12,708
12.48%
BLUE CARE NETWORK OF MICHIGAN
4.5
4.5
68,138
75,964
11.49%
CARE1ST HEALTH PLAN
3.5
3.5
51,433
64,856
26.10%
ARCADIAN HEALTH PLAN, INC.
The Challenges of Pharmacy Star Ratings • 55
Contract Enrollment for Plans Whose Star Ratings Stayed the Same in
2016 (continued)
2015
Overall
Rating
2016
Overall
Rating
2015
Contract
Enrollment
2016
Contract
Enrollment
% Change
CAPITAL HEALTH PLAN
4.5
4.5
17,121
18,486
7.97%
H5970
HUMANA INSURANCE COMPANY OF NEW
YORK
3.5
3.5
9,048
11,822
30.66%
H5985
H5991
H6306
PHOENIX HEALTH PLANS, INC.
2.5
2.5
12,933
13,761
6.40%
AFFINITY HEALTH PLAN, INC.
3.5
3.5
6,511
9,939
52.65%
4
4
4,020
5,197
29.28%
H6622
HUMANA WI HEALTH ORGANIZATION
INSURANCE CORP
4.5
4.5
37,872
45,213
19.38%
H6801
H7006
H7200
H7301
GHS MANAGED HEALTH CARE PLANS, INC.
3
3
4,279
4,635
8.32%
ATRIO HEALTH PLANS
4
4
2,988
3,459
15.76%
AMERIGROUP TENNESSEE, INC.
3
3
6,466
7,783
20.37%
COVENTRY HEALTH CARE OF ILLINOIS, INC.
4.5
4.5
15,455
17,724
14.68%
H7728
ANTHEM HEALTH PLANS OF NEW
HAMPSHIRE, INC.
4.5
4.5
1,505
1,713
13.82%
H8145
HUMANA INSURANCE COMPANY
4
4
142,189
131,366
-7.61%
H8552
ANTHEM BLUE CROSS LIFE AND HEALTH INS
COMPANY
3.5
3.5
12,684
7,693
-39.35%
H8604
H8649
H9001
H9003
H9082
THP INSURANCE COMPANY
3.5
3.5
693
1,055
52.24%
AETNA HEALTH OF UTAH, INC.
3.5
3.5
9,301
7,119
-23.46%
FALLON COMMUNITY HEALTH PLAN
4.5
4.5
17,619
18,241
3.53%
5
5
77,157
81,778
5.99%
3.5
3.5
1,564
2,805
79.35%
H9572
BCBS OF MICHIGAN MUTUAL INSURANCE
COMPANY
4
4
326,358
345,110
5.75%
H9615
MVP HEALTH PLAN, INC.
4.5
4.5
19,459
22,858
17.47%
H9730
WELLCARE HEALTH INSURANCE COMPANY OF
KENTUCKY, INC
2.5
2.5
6,420
7,731
20.42%
H9947
BLUE CROSS AND BLUE SHIELD OF GEORGIA,
INC.
3
3
2,721
2,401
-11.76%
R3175
UNITEDHEALTHCARE INSURANCE COMPANY
3.5
3.5
3,417
3,470
1.55%
R3444
CARE IMPROVEMENT PLUS SOUTH CENTRAL
INSURANCE CO.
3
3
56,288
64,956
15.40%
R5287
UNITEDHEALTHCARE INSURANCE COMPANY
3.5
3.5
183,167
202,103
10.34%
R5342
UNITEDHEALTHCARE INSURANCE COMPANY
OF NEW YORK
3.5
3.5
85,946
103,903
20.89%
R5941
ANTHEM INSURANCE COMPANIES, INC.
3
3
103,212
100,147
-2.97%
R9896
CARE IMPROVEMENT PLUS SOUTH CENTRAL
INSURANCE CO.
3
3
163,706
168,125
2.70%
Contract
Number
Contract Name
H5938
FIRSTCAROLINACARE INSURANCE COMPANY
KAISER FOUNDATION HP OF THE N W
MOLINA HEALTHCARE OF NEW MEXICO, INC.
NOTE: Does not include new or terminated plans.
SOURCE: Calculated by AIS from CMS data for AIS's Medicare and Medicaid Market Data: 2016.
The Challenges of Pharmacy Star Ratings • 57
Appendix B: CMS Fact Sheet — 2016 Star
Ratings
Fact Sheet - 2016 Star Ratings
One of the Centers for Medicare & Medicaid Services’ (CMS) most important strategic goals is to improve the
quality of care and general health status for Medicare beneficiaries. CMS publishes the Part C and D Star
Ratings each year to: measure quality in Medicare Advantage (MA) and Prescription Drug Plans (PDPs or Part
D plans), assist beneficiaries in finding the best plan for them, and determine MA Quality Bonus Payments.
Moreover, the ratings support the efforts of CMS to improve the level of accountability for the care provided by
physicians, hospitals, and other providers. CMS continues to see increases in the number of Medicare
beneficiaries in high-performing Medicare Advantage (MA) plans. Star Ratings are driving improvements in
Medicare quality. The information included in this Fact Sheet is evidence of such improvement and is based on
the 2016 Star Ratings published on Medicare Plan Finder (MPF) on October 8, 2015.
Background
Medicare Advantage with prescription drug coverage (MA-PD) contracts are rated on up to 44 unique quality
and performance measures; MA-only contracts (without prescription drug coverage) are rated on up to 32
measures; and stand-alone PDP contracts are rated on up to 15 measures. Each year, CMS conducts a
comprehensive review of the measures that make up the Star Ratings, considering the reliability of the
measures, clinical recommendations, feedback received from stakeholders, and data issues. All measures
transitioned from the Star Ratings are included in the display measure available from this page
http://go.cms.gov/partcanddstarratings. Changes to existing measures are summarized in Attachment A.
The Star Ratings measures span five broad categories:
 Outcomes
 Intermediate Outcomes
 Patient Experience
 Access
 Process
For the 2016 Star Ratings, outcomes and intermediate outcomes continue to be weighted three times as much as
process measures, and patient experience and access measures are weighted 1.5 times as much as process
measures. CMS assigns a weight of 1 to all new measures. The Part C and D quality improvement measures
receive a weight of 5 to further reward contracts for the strides they made to improve the care provided to
Medicare enrollees. CMS continues to lower the overall Star Rating for contracts with serious compliance
issues, defined as the imposition of enrollment or marketing sanctions.
Highlights of Contract Performance in 2016 Star Ratings1
Changes in Ratings from 2015
The last row in Table 1 details the trend in the average overall Star Ratings weighted by enrollment for MA-PDs
for the period of 2013 to 2016.
 Approximately 49 percent of MA-PDs (179 contracts) that will be active in 2016 earned four stars or
higher for their 2016 overall rating.
 This is nearly a 9 percentage point increase from 40 percent of active contracts earning four stars or
higher for their 2015 overall rating.
 Weighted by enrollment, close to 71 percent of MA-PD enrollees are in contracts with four or more stars.
 This is nearly an 11 percentage point increase from 60 percent of enrollees in contracts with four or more
stars in 2015.
1
Tables contained in this document may not have sums of percentages of 100.00 due to rounding.
1
58 • AIS’s Management Insight Series
Table 1: 2013 - 2016 Overall Star Rating Distribution for MA-PD Contracts
2013
Overall Rating
5 stars
4.5 stars
4 stars
Number
of
Contracts
%
2014
Weighted
by
Enrollment
11
54
2.46
12.08
9.42
15.81
Number
of
Contracts
%
2015
Weighted
by
Enrollment
11
64
2.55
14.85
9.56
20.55
Number
of
Contracts
2016
Weighted
by
Enrollment
Number
of
Contracts
11 2.78
61 15.44
9.88
19.59
12
65
3.25
17.62
10.23
25.02
%
%
Weighted
By
Enrollment
62
13.87
12.56
87
20.19
21.68
86 21.77
30.32
102
27.64
35.71
3.5 stars
3 stars
131
127
29.31
28.41
36.48
20.25
143
109
33.18
25.29
30.49
16.63
136 34.43
73 18.48
26.78
10.98
112
66
30.35
17.89
19.55
8.60
2.5 stars
60
13.42
5.28
16
3.71
1.09
26
6.58
2.37
12
3.25
0.90
2
447
0.45
0.21
1
431
0.23
0.01
2
395
0.51
0.08
0
369
0.00
0.00
2 stars
Total Number of Contracts
Average Star Rating*
3.71
3.86
3.92
4.03
* The average Star Rating is weighted by enrollment.
The last row in Table 2 details the trend in the average Part D Ratings weighted by enrollment for PDPs for the
period of 2013 to 2016 (Table 2).

Approximately 41 percent of PDPs (24 contracts) that will be active in 2016 received four or more stars
for their 2016 Part D rating.
Weighted by enrollment, close to 32 percent of PDP enrollees are in contracts with four or more stars.

There were more significant changes in the PDP scores this year due to one measure being retired
(Diabetes Treatment), and 3 measures were included that were not used in the prior year. Given the
smaller number of measures for PDPs, these changes have a more significant impact.
Table 2: 2012 - 2016 Part D Rating Distribution for PDPs
2013
Part D Rating
5 stars
4.5 stars
Number
of
Contracts
%
4
5
5.71
7.14
4 stars
17
3.5 stars
3 stars
17
17
2.5 stars
2 stars
1.5 stars
Total Number of Contracts
2014
Weighted
by
Enrollment
Number
of
Contracts
%
1.85
3.52
5
6
6.94
8.33
24.29
12.2
16
24.29
24.29
23.35
55.08
18
17
9
12.86
3.23
1
0
1.43
0.00
0.77
0.00
70
Average Star Rating*
3.30
* The average Star Rating is weighted by enrollment.
2015
Weighted
by
Enrollment
Number
of
Contracts
%
2016
Weighted Number
by
of
Enrollment Contracts
%
Weighted
by
Enrollment
0.13
3.34
3 4.92
11 18.03
1.50
7.28
2
10
3.39
16.95
0.13
1.63
22.22
5.29
17 27.87
43.94
12
20.34
29.95
25.00
23.61
52.39
14.16
18 29.51
7 11.48
40.40
0.61
12
14
20.34
23.73
21.76
38.88
8
11.11
5.62
3
4.92
5.99
8
13.56
7.65
1
1
1.39
1.39
0.00
19.07
1
1
1.64
1.64
0.01
0.27
1
0
1.69
0.00
0.01
0
72
61
3.05
59
3.75
3.40
5-Star Contracts
17 contracts are highlighted on MPF with a high performing (gold star) icon; 12 are MA-PD contracts (Table 3),
3 are MA-only contracts (Table 4), and 2 are PDPs (Table 5).
The seven new 5-star contracts for this year are:
 Cigna Healthcare of Arizona, Inc. (H0354)
 Tufts Associated Health Maintenance Organizations (H2256)
 Group Health Plan, Inc. (MN) (H2462)
 Essence Healthcare Inc. (H2610)
 Medical Associates Clinic Health Plan (H5256)
 Sierra Health and Life Insurance Company, Inc. (H5652)
 Tufts Insurance Company (S0655)
2
The Challenges of Pharmacy Star Ratings • 59
Table 3: MA-PD Contracts Receiving the 2016 High Performing Icon
H0354
CIGNA HEALTHCARE OF ARIZONA, INC.
Enrolled
Non-EGHP Service Area*
10/2015
43,881 3 counties in AZ
H0524
KAISER FOUNDATION HP, INC.
1,037,349 31 counties in CA
Not applicable
Yes
Yes
H0630
H1230
KAISER FOUNDATION HP OF CO
KAISER FOUNDATION HP, INC.
98,584 17 counties in CO
31,396 3 counties in HI
Not applicable
Not applicable
Yes
Yes
Yes
Yes
H2150
KAISER FNDN HP OF THE MID-ATLANTIC STS
63,681 D.C., 11 counties in MD, 9 counties in VA
H2256
H2462
TUFTS ASSOCIATED HEALTH MAINTENANCE ORGANIZATION
GROUP HEALTH PLAN, INC. (MN)
H2610
H5262
H5591
H5652
SIERRA HEALTH AND LIFE INSURANCE COMPANY, INC.
H9003
KAISER FOUNDATION HP OF THE N W
Contract
Contract Name
EGHP
Service Area*
13 counties in AZ
5 Star
Last Year
No
SNP
Yes
Not applicable
Yes
No
104,812 10 counties in MA
49,484 87 counties in MN, 8 counties in WI
Not applicable
Not applicable
No
No
Yes
No
ESSENCE HEALTHCARE, INC.
52,525 3 counties in IL, 10 counties in MO
Not applicable
No
No
GUNDERSEN HEALTH PLAN
MARTIN'S POINT GENERATIONS, LLC
14,287 5 counties in IA, 11 counties in WI
32,611 16 counties in ME, 2 counties in NH
Not applicable
Most of the U.S.
Yes
Yes
No
Yes
Not applicable
No
Yes
1 county in OR,
1 county in WA
Yes
No
1 county in CO, 1 county in KS, 2 counties in MA,
4,502 3 counties in MD, 1 county in MI, 3 counties in NJ,
2 counties in PA, 2 counties in TX, 1 county in VA
79,591 9 counties in OR, 4 counties in WA
*An EGHP is a non-Employer Group and Employer Group Health Plan.
Table 4: MA-only Contracts Receiving the 2016 High Performing Icon2
Contract
Enrolled
10/2015
Contract Name
Non-EGHP Service Area
EGHP Service Area
5 Star Last Year
H1651
H5256
MEDICAL ASSOCIATES HEALTH PLAN, INC.
MEDICAL ASSOCIATES CLINIC HEALTH PLAN
10,398 6 counties in IA, 1 county in IL
3,176 4 counties in WI
Not applicable
Not applicable
Yes
No
H5264
DEAN HEALTH PLAN, INC.
24,898 8 counties in WI
Not applicable
Yes
Table 5: PDP Contracts Receiving the 2016 High Performing Icon
Contract
Contract Name
Enrolled 10/2015
S0655
TUFTS INSURANCE COMPANY
S5753
WISCONSIN PHYSICIANS SERVICE INSURANCE CORPORATION
Non-EGHP Service Area
7,874 Not applicable
22,999 1 region - Wisconsin
EGHP Service Area
5 Star Last Year
35 regions
No
38 regions
Yes
Low Performers
6 contracts are identified on the MPF with the Low Performing Icon (LPI) for consistently low quality ratings.


3 contracts are receiving the LPI for low Part C ratings of 2.5 or fewer stars from 2014 through 2016.
3 contracts are receiving the LPI for low Part C or D ratings of 2.5 or fewer stars from 2014 through
2016.
Below is the list of contracts receiving an LPI for 2016 (Table 6).
Table 6: 2016 Contracts with a Low Performing Icon (LPI)
Contract
Contract Name
Parent Organization
H1903
H2905*
WELLCARE OF LOUISIANA, INC.
WellCare Health Plans, Inc.
SIERRA HEALTH AND LIFE INSURANCE COMPANY, INC. UnitedHealth Group, Inc.
H3327
H4866*
H5698*
H6801
Reason for LPI Enrolled 10/2015
Part C or D
Part C
10,167
3,490
TOUCHSTONE HEALTH HMO, INC.
Touchstone Health Partnership, Inc Part C or D
10,864
CUATRO LLC
WINDSOR HEALTH PLAN, INC.
Cuatro LLC.
WellCare Health Plans, Inc.
Part C
Part C
4,519
40,606
GHS MANAGED HEALTH CARE PLANS, INC.
Health Care Service Corporation
Part C or D
4,422
*These contracts are eligible for termination at the end of 2016.
2
MA-only contracts cannot offer SNPs.
3
60 • AIS’s Management Insight Series
Tax Status and Performance

Organizations that are non-profit tend to receive higher ratings than those that are for-profit. For MAPDs, approximately 70% of the non-profit contracts received 4 or more stars compared to 39% of the
for-profit MA-PDs. Similarly, for PDPs approximately 63% of non-profit PDPs received 4 or more
stars compared to 24% of the for-profit PDPs. Non-profit organizations also performed better than forprofit organizations last year.
Below is the ratings distribution by tax status for MA-PD (Table 7) and PDP (Table 8) contracts.
Table 7: Distribution of Overall Star Ratings for For-profit and Non-profit MA-PDs
2016 Overall Rating
Number of
For-Profit
% ForProfit
Weighted By
Number of
Enrollment For-Profit Non-Profit
% NonProfit
Weighted By
Enrollment Non-Profit
5 stars
4.5 stars
3
33
1.20
13.15
0.96
23.83
9
32
7.63
27.12
28.96
27.41
4 stars
3.5 stars
61
90
24.30
35.86
38.56
25.70
41
22
34.75
18.64
29.97
7.12
3 stars
52
20.72
9.61
14
11.86
6.55
12
251
4.78
1.34
0
118
0.00
0.00
2.5 stars
Total Number of Contracts
Table 8: Distribution of Part D Ratings for For-profit and Non-profit PDPs
2016 Part D Rating
Number of
For-Profit
% ForProfit
5 stars
4.5 stars
1
4
4 stars
3.5 stars
3 stars
2.5 stars
2 stars
Total Number of Contracts
Weighted By
Number of
Enrollment For-Profit Non-Profit
% NonProfit
Weighted By
Enrollment Non-Profit
2.94
11.76
0.03
0.40
1
5
4.17
20.83
2.38
13.53
3
8.82
28.69
9
37.50
53.96
7
12
20.59
35.29
20.96
40.54
5
2
20.83
8.33
19.9
1.82
7
20.59
9.37
1
4.17
8.22
0
34
0.00
0.00
1
24
4.17
0.18
Length of Time in Program and Performance
On average, higher Star Ratings are associated with more experience in the MA program. We see a similar
pattern for PDPs. The tables below show the distribution of ratings by the number of years in the program
(MA-PDs are shown in Table 9 and PDPs in Table 10).
Table 9: Distribution of Overall Star Ratings by Length of Time in Program for MA-PDs
2016 Overall Rating
5 stars
% Less than 5 years % 5 years to less than 10 years % Greater than 10 years
0.00
0.81
5.45
4.5 stars
4 stars
13.64
25.00
8.94
21.14
23.76
32.18
3.5 stars
18.18
39.02
27.72
3 stars
2.5 stars
29.55
13.64
28.46
1.63
8.91
1.98
44
123
202
Total Number of Contracts
Table 10: Distribution of Part D Ratings by Length of Time in Program for PDPs
2016 Part D Rating
5 stars
4.5 stars
% Less than 5 years % 5 years to less than 10 years
0.00
0.00
6.00
20.00
4 stars
40.00
26.00
3.5 stars
3 stars
0.00
40.00
34.00
8.00
2.5 stars
2 stars
Total Number of Contracts
0.00
6.00
20.00
5
0.00
50
4
The Challenges of Pharmacy Star Ratings • 61
Performance of Contracts Eligible to Receive Low Income Subsidy (LIS) Auto-assignees
Most contracts with a Star Rating and eligible to receive LIS auto-assignees (LIS contracts) continue to earn
a Star Rating of 3 or more (Table 11).

Thirteen out of 15 LIS contracts (86.7%) earned a Star Rating of 3 or more in 2016
compared to 15 contracts (93.8%) in 2015, 16 (84.2%) in 2014, and 17 (89.5%) in 2013.
Table 11: Distribution of Part D Ratings for PDPs Eligible to Receive LIS Auto-assignees
Part D Rating
2013 Number of
2013 % of
2014 Number of
2014 % of
2015 Number of
2015 % of
2016 Number of
LIS Contracts LIS Contracts LIS Contracts LIS Contracts LIS Contracts LIS Contracts LIS Contracts
2016 % of
LIS Contracts
4.5 stars
0
0.00
0
0.00
1
6.25
0
0.00
4 stars
1
5.26
4
21.05
4
25.00
2
13.30
6
31.58
6
31.58
8
50.00
4
26.70
10
52.63
6
31.58
2
12.50
7
46.70
2.5 stars
2
10.53
3
15.79
1
6.25
2
13.30
2 stars
0
0.00
0
0.00
0
0.00
0
0.00
1.5 stars
0
0.00
0
0.00
0
0.00
0
0.00
3.5 stars
3 stars
Total Number of Contracts
19
19
16
15
Geographic Variation
The following eight maps illustrate the average Star Ratings weighted by enrollment per county for MA-PDs
and PDPs across the U.S., including territories, between 2013 and 2016.3 These maps exclude the employer
group health plans. Counties shaded in green indicate that the average Overall Star Rating weighted by
enrollment in the county for MA-PDs or average Part D Rating for PDPs is four or more stars. Counties shaded
in yellow indicate that the average rating weighted by enrollment for the county for MA-PDs or PDPs is three
stars. Areas shaded in orange indicate that the average rating weighted by enrollment is less than three stars.
Areas in gray indicate data are not available for those counties. Among the changes and updates are:



3
The availability of highly rated MA-PDs has increased since 2013.
The MA-PD maps for 2016 compared to 2013 show significantly more light green (3.5 stars) and green
(4 or more stars) compared to yellow (3 stars) and orange (2.5 stars) in 2013.
In 2016 the average rating weighted by enrollment for PDPs across the county is at least 3.0 stars.
Comparisons of Star Ratings across years do not reflect annual revisions made by CMS to the Star Rating’s methodology or measure
set.
5
62 • AIS’s Management Insight Series
6
For a full-color version of maps on the following pages, see https://www.
cms.gov/Medicare/Prescription-Drug-Coverage/PrescriptionDrugCovGenIn/
Downloads/2016-Part-C-and-D-Medicare-Star-Ratings-Data-v04-07-2016-.zip.
Missing Data
1 Star
1.5 Stars
2 Stars
2.5 Stars
3 Stars
3.5 Stars
4 Stars
4.5 Stars
2015 Star Ratings - Enrollment Weighted Average MA-PD Overall Rating in Non-EGHP Counties
5 Stars
7
The Challenges of Pharmacy Star Ratings • 63
Missing Data
1 Star
1.5 Stars
2 Stars
2.5 Stars
3 Stars
3.5 Stars
4 Stars
4.5 Stars
2014 Star Ratings - Enrollment Weighted Average MA-PD Overall Rating in Non-EGHP Counties
5 Stars
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64 • AIS’s Management Insight Series
Missing Data
1 Star
1.5 Stars
2 Stars
2.5 Stars
3 Stars
3.5 Stars
4 Stars
4.5 Stars
2013 Star Ratings - Enrollment Weighted Average MA-PD Overall Rating in Non-EGHP Counties
5 Stars
9
The Challenges of Pharmacy Star Ratings • 65
10
66 • AIS’s Management Insight Series
Missing Data
1 Star
1.5 Stars
2 Stars
2.5 Stars
3 Stars
3.5 Stars
4 Stars
4.5 Stars
2015 Star Ratings - Enrollment Weighted Average PDP Part D Rating in Non-EGHP Counties
5 Stars
11
The Challenges of Pharmacy Star Ratings • 67
Missing Data
1 Star
1.5 Stars
2 Stars
2.5 Stars
3 Stars
3.5 Stars
4 Stars
4.5 Stars
2014 Star Ratings - Enrollment Weighted Average PDP Part D Rating in Non-EGHP Counties
5 Stars
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68 • AIS’s Management Insight Series
Missing Data
1 Star
1.5 Stars
2 Stars
2.5 Stars
3 Stars
3.5 Stars
4 Stars
4.5 Stars
2013 Star Ratings - Enrollment Weighted Average PDP Part D Rating in Non-EGHP Counties
5 Stars
13
The Challenges of Pharmacy Star Ratings • 69
70 • AIS’s Management Insight Series
Average Star Rating for Each Measure
Below we list the average Star Ratings for 2013, 2014, 2015, and 2016 Part C and D measures (Tables 12
and 13). In general, Star Ratings have gone up from 2013 to 2016 for most measures.4
Table 12: Average Star Rating by Part C Measure
2016 Measure
Number
Measure
2013 Average Star 2014 Average Star
2015 Average Star
2016 Average Star
C01
C02
Breast Cancer Screening
Colorectal Cancer Screening
3.0
3.5
3.3 n/a - not used in 2015
3.9
4.2
3.6
3.2
C03
Annual Flu Vaccine
3.2
3.4
3.3
3.3
C04
C05
Improving or Maintaining Physical Health
Improving or Maintaining Mental Health
4.4
2.2
4.5
2.0
4.6
2.5
3.3
3.3
C06
Monitoring Physical Activity
2.1
2.4
2.2
2.9
C07
C08
Adult BMI Assessment
Special Needs Plan (SNP) Care Management
3.7
n/a – new in 2015
3.8
n/a – new in 2015
3.8
2.7
4.1
2.5
C09
Care for Older Adults – Medication Review
3.0
3.6
3.9
4.3
C10
C11
Care for Older Adults – Functional Status Assessment
Care for Older Adults – Pain Assessment
2.8
3.2
3.4
3.2
3.4
4.0
3.9
4.1
C12
Osteoporosis Management in Women who had a Fracture
1.4
1.9
2.1
2.5
C13
C14
Diabetes Care – Eye Exam
Diabetes Care – Kidney Disease Monitoring
3.4
4.3
4.0
4.5
3.7
4.2
3.1
3.3
C15
Diabetes Care – Blood Sugar Controlled
3.1
3.3
3.3
3.9
C16
C17
Controlling Blood Pressure
Rheumatoid Arthritis Management
3.5
3.3
3.5
3.7
3.7
3.5
3.4
3.2
C18
Reducing the Risk of Falling
3.3
3.4
3.3
2.7
C19
C20
Plan All-Cause Readmissions
Getting Needed Care
3.0
3.5
3.5
3.6
3.0
3.4
3.3
3.5
C21
Getting Appointments and Care Quickly
3.4
3.5
3.5
3.4
C22
C23
Customer Service
Rating of Health Care Quality
3.4
3.7
3.5
3.7
3.5
3.7
3.5
3.4
C24
Rating of Health Plan
3.3
3.4
3.4
3.3
C25
C26
Care Coordination
Complaints about the Health Plan
3.4
3.0
3.4
3.0
3.4
4.2
3.4
3.9
C27
Members Choosing to Leave the Plan
3.5
3.7
4.3
4.2
C28
C29
Beneficiary Access and Performance Problems
Health Plan Quality Improvement
3.5
3.1
3.4 n/a - not used in 2015
3.5
3.5
4.2
3.4
C30
Plan Makes Timely Decisions about Appeals
4.0
4.1
4.2
4.1
C31
C32
Reviewing Appeals Decisions
Call Center – Foreign Language Interpreter and TTY Availability
3.3
4.2
3.3
3.7
4.4 n/a - not used in 2015
3.6
4.3
Changes in the average Star Rating do not always reflect changes in performance since for some measures there have been significant changes in industry performance and
shifts in the distribution of scores. The pre-determined star thresholds were removed for the 2016 Star Ratings. Some measures may have greater shifts from 2015 to 2016
compared to other time periods due to the revision to the methodology used to determine the rating.
4
14
The Challenges of Pharmacy Star Ratings • 71
Table 13: Average Star Rating by Part D Measure for MA-PDs
2016 Measure
Measure
Number
D01
Call Center – Foreign Language Interpreter and TTY Availability
2013 MA-PD
Average Star
3.7
2014 MA-PD
Average Star
2015 MA-PD
2016 MA-PD
Average Star
Average Star
3 n/a – not used in 2015
4.2
D02
Appeals Auto–Forward
3.4
3.4
3.6
4.5
D03
D04
Appeals Upheld
Complaints about the Drug Plan
3.2
3.0
3.3
3
3.7
4.2
3.3
3.9
D05
Members Choosing to Leave the Plan
3.5
3.7
4.3
4.2
D06
D07
Beneficiary Access and Performance Problems
Drug Plan Quality Improvement
3.5
3.4
3.3 n/a – not used in 2015
3.7
4.1
4.2
3.8
D08
Rating of Drug Plan
3.4
3.4
3.5
3.3
D09
D10
Getting Needed Prescription Drugs
MPF Price Accuracy
3.5
3.8
3.5
3.9
3.4
4.6
3.4
3.5
D11
High Risk Medication
3.1
3.6
3.2
4.1
D12
D13
Medication Adherence for Diabetes Medications
Medication Adherence for Hypertension (RAS antagonists)
3.1
3.0
3.7
3.7
3.5
3.1
3.9
4.1
D14
Medication Adherence for Cholesterol (Statins)
3.1
3.6
3.3
4.0
D15
MTM Program Completion Rate for CMR
n/a – new in 2016 n/a – new in 2016
n/a – new in 2016
2.3
Table 14: Average Star Rating by Part D Measure for PDPs
2016 Measure
Measure
Number
D01
Call Center – Foreign Language Interpreter and TTY Availability
2013 PDP
Average Star
3.8
2014 PDP
2015 PDP
2016 PDP
Average Star
Average Star
Average Star
3.7 n/a – not used in 2015
4.0
D02
D03
Appeals Auto–Forward
Appeals Upheld
2.4
3.3
2.7
3.3
2.5
3.9
4.1
3.1
D04
Complaints about the Drug Plan
3.7
3.4
4.3
3.5
D05
D06
Members Choosing to Leave the Plan
Beneficiary Access and Performance Problems
3.7
3.8
3.3
3.7
3.8 n/a – not used in 2015
3.6
3.9
D07
Drug Plan Quality Improvement
4.1
3.6
4.2
3.8
D08
D09
Rating of Drug Plan
Getting Needed Prescription Drugs
3.6
3.7
3.7
4.1
3.9
3.8
3.2
3.6
D10
MPF Price Accuracy
4.2
4.1
4.7
4.7
D11
D12
High Risk Medication
Medication Adherence for Diabetes Medications
3.1
3.3
2.8
3.1
2.7
3.0
3.1
2.7
D13
Medication Adherence for Hypertension (RAS antagonists)
3.2
3.6
3.8
3.6
D14
D15
Medication Adherence for Cholesterol (Statins)
MTM Program Completion Rate for CMR
3.2
3.6
n/a – new in 2016 n/a – new in 2016
4.2
n/a – new in 2016
3.5
2.3
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72 • AIS’s Management Insight Series
Attachment A – 2016 Star Ratings Measure Changes
Below are some additional changes to the 2016 Star Ratings in terms of the measures included.
Specification Changes
 Part C measure: C12 – Osteoporosis Management in Women who had a Fracture – NCQA has
added an upper age limit, extended the look back period for exclusions due to prior bone mineral
testing, removed estrogens from this measure, and removed single-photon absorptiometry and dualphoton absorptiometry tests from the list of eligible bone-density tests.
 Part C measure: C16 – Controlling Blood Pressure – measure updated to include two different
blood pressure thresholds based on age and diagnosis.
 Part C measure: C19 – Plan All-Cause Readmissions – now excludes planned readmissions from
the measure and removes the current exclusion from the denominator for hospitalizations with a
discharge date in the 30 days prior to the Index Admission Date.
 Part C measure: C30 – Plan Makes Timely Decisions about Appeals – removed dismissed appeals
from the measure.
 Part C & D measures: C26 & D04 – Complaints about the Health/Drug Plan – modified the
measurement period from 6 months of the current year to 12 months of the prior year.
 Part D measure: D03 – Appeals Upheld – modified the measurement period to coincide with the 12
month period of the Part D Appeals Auto-forward measure.
 Part D measures: D12 & D13 – both measures adjusted to account for beneficiaries with End-Stage
Renal Disease (ESRD).
 Part D measures: D12, D13 & D14 – calculating the proportion of days now uses the date of death
for a member instead of the last day of the month.
 Part D measures: D11 – D14 - Implemented PQA’s 2014 obsolete NDCs methodology.
 Part C & D CAHPS measures: Implemented CAHPS methodology modifications which permit
low-reliability contracts to receive 5 stars or 1 star.
 Eliminated pre-determined 4-star thresholds
 Included data in HEDIS measures for contracts with 500-999 enrolled in July of the measurement
year.
Additions
 Part C measure: C01 - Breast Cancer Screening: with a weight of 1.
 Part D measure: D15 – Medication Therapy Management Program Completion Rate for
Comprehensive Medication Reviews: with a weight of 1.
 Parts C & D measure: C32 & D01 - Call Center – Foreign Language Interpreter and TTY
Availability: with a weight of 1.5.
 Parts C & D measures: C28 & D06 - Beneficiary Access and Performance Problems: with a weight
of 1.
16
The Challenges of Pharmacy Star Ratings • 73
Transitioned Measures
Transitioned measures are measures that have moved to the display page which can be found on the
CMS website at this address: http://go.cms.gov/partcanddstarratings

Part C measure: Improving Bladder Control
Retired measures

Part C measure: Cardiovascular Care: Cholesterol Screening

Part C measure: Diabetes Care: Cholesterol Screening

Part C measure: Diabetes Care: Cholesterol Controlled

Part D measure: Diabetes Treatment
17
The Challenges of Pharmacy Star Ratings • 75
Appendix C: CMS Guidance and
Documentation for 2017 Star Ratings
DEPARTMENT OF HEALTH & HUMAN SERVICES
Centers for Medicare & Medicaid Services
7500 Security Boulevard
Baltimore, Maryland 21244-1850
CENTER FOR MEDICARE
DATE:
November 12, 2015
TO:
All Medicare Advantage Organizations, Prescription Drug Plan Sponsors, and Other
Interested Parties
FROM:
Amy K. Larrick, Acting Director, Medicare Drug Benefit and C & D Data Group
SUBJECT:
Request for Comments: Enhancements to the Star Ratings for 2017 and Beyond
(Due by December 10, 2015 at 5pm ET)
This document proposes methodology changes for the 2017 Star Ratings and display measures for
Medicare Advantage (MA) and Prescription Drug Plans (PDPs). It also provides advanced notice of
potential changes for the Star Ratings and display measures for 2018 and beyond. Based on this
memo, MA Organizations, PDP sponsors, advocates, and other stakeholders have the opportunity
to provide comments prior to the draft Call Letter, which is issued as part of the Advance Notice.
The statutory deadlines in section 1853 result in a short comment period between the Advance
and Final Rate Notices, which contain the Call Letter. We are issuing this Request for Comments
(RFC) to provide an opportunity for stakeholders to provide input prior to the Call Letter process.
CMS structured the current Star Ratings strategy to be consistent with the six priorities in the
National Quality Strategy. The six priorities include: making care safer by reducing harm caused by
the delivery of care; ensuring that each person and family are engaged as partners in their care;
promoting effective communication and coordination of care; promoting the most effective
prevention and treatment practices for the leading causes of mortality; working with communities
to promote wide use of best practices to enable healthy living; and making quality care more
affordable for individuals, families, employers, and governments by developing and spreading new
health care delivery models. The measures span five broad categories, including:

Outcome measures that focus on improvement to a beneficiary’s health as a result of care
that is provided;

Intermediate outcome measures that concentrate on ways to help beneficiaries move
closer to achieving true outcomes;

Patient experience measures that represent beneficiaries’ perspectives about the care they
receive;
1
76 • AIS’s Management Insight Series

Access measures that reflect processes or structures that may create barriers to receiving
needed health care; and

Process-of-care measures that capture a method by which health care is provided.
The Star Ratings help inform beneficiaries about the performance of health and drug plans on the
Medicare Plan Finder (MPF) website, as well as serve as the basis of Quality Bonus Payments
(QBPs) for MA organizations. CMS continues to improve the Part C and Part D quality and
performance measurement system and focuses it on beneficiary outcomes, beneficiary
experience, population health, and health care efficiency. The goal is that the Star Ratings system
will not only influence beneficiaries’ plan choices but also drive organizations and sponsors toward
higher quality and more efficient care.
Star Ratings is a year-round process for both CMS and sponsors. Below is an example for the next
cycle of Star Ratings, beginning with this RFC:

November 2015-February 2016: CMS provides guidance on methodology changes
anticipated for the 2017 Star Ratings and display measures and advanced notice of
potential changes for the Star Ratings and display measures for 2018 and beyond. CMS
does this first through the RFC and then in the draft 2017 Call Letter. Sponsors and other
stakeholders actively participate by submitting comments regarding the potential changes
to the Star Ratings methodology or submitting additional comments to propose other
changes not mentioned in the RFC. Comments to the RFC inform proposals in the draft Call
Letter, and comments to the draft Call Letter inform the final Call Letter.

February-April 2016: After consideration of all comments, CMS announces the
methodology for the 2017 Star Ratings in the final 2017 Call Letter in the Rate
Announcement issued.

Ongoing: Sponsors review the underlying data used for the individual Star Ratings
measures as they become available throughout the year, and notify CMS of any errors or
questions in a timely manner.

Summer 2016: CMS holds a Part C and D User call with sponsors to provide updates to the
upcoming Star Ratings release, and conducts two plan preview periods via the Health Plan
Management System (HPMS) to identify any necessary data corrections or revisions to our
draft Technical Notes. During these preview periods, CMS expects sponsors to raise
concerns about their raw measure data and Star Ratings. Changes to the methodologies for
measure calculations or Star Rating calculations cannot be made during this time.

November 2016: CMS offers MA organizations an appeals process for QBPs. The
administrative review process is a two-step process that includes a request for
reconsideration and a request for an informal hearing after CMS has sent the MA
organization the reconsideration decision. This process may only be initiated on the basis
of non-methodological challenges, such as a calculation error (miscalculation) or a data
inaccuracy (incorrect data).
Comments to this RFC should be submitted via the following link:
https://cmsgov.wufoo.com/forms/enhancements-to-the-star-ratings-for-2017/
2
The Challenges of Pharmacy Star Ratings • 77
The online form allows comments on up to 8 sections. If your organization’s comments exceed
this maximum, you may submit the form more than once. Do not resubmit these comments to
CMS via email. If you wish to submit additional supporting documents, you may send them via
email to: [email protected].
NOTE: If you encounter the following error message while completing the survey, you must clear
cookies and then resubmit the form: “There was a problem with your submission. Unable to create
a new entry.”
Comments submitted by Thursday, December 10 at 5pm ET will be considered as we finalize
proposed changes for the 2017 Star Ratings for the draft 2017 Call Letter. CMS will post on its
website all comments received to the RFC. Stakeholders will have another opportunity to
comment on the 2017 Star Ratings methodology and proposed changes through the Advance
Notice/draft Call Letter process.
Questions related to this RFC may be sent to: [email protected].
Thank you for your participation.
3
78 • AIS’s Management Insight Series
Enhancements to the 2017 Star Ratings and Beyond
One of CMS’ most important strategic goals is to improve the quality of care and general
health status of Medicare beneficiaries. For the 2017 Star Ratings, CMS continues to enhance
the current methodology so it further aligns with our policy goals. Our priorities include
enhancing the measures and methodology to reflect the true performance of organizations
and sponsors, maintaining stability due to the link to payment, and providing advance notice of
future changes. In this document, we describe the enhancements being considered for the
2017 Star Ratings and beyond. CMS is not considering adding any new measures for 2017 Star
Ratings. Unless noted below, we anticipate the methodology remaining the same as the 2016
Star Ratings.
For reference, the list of measures and methodology included in the 2016 Star Ratings is
described in the Technical Notes available on the CMS webpage:
http://go.cms.gov/partcanddstarratings.
The cut points to determine star assignments for all measures and case-mix coefficients for the
Consumer Assessment of Healthcare Providers and Systems (CAHPS) survey and Health
Outcomes Survey (HOS) will be updated for 2017 using the most current data available.
As announced in previous years, we will review data quality across all measures, variation
among organizations and sponsors, and measures’ accuracy and validity before making a final
determination about inclusion of measures in the Star Ratings.
A. Changes to Measures for 2017
CMS’ general policies regarding specification changes to Star Ratings measures:

If a specification change to an existing measure is announced in advance of the
measurement period, the measure remains in the Star Ratings; it will not be moved to
the display page.

If the change announced during the measurement period significantly expands the
denominator or population covered by the measure, the measure is moved to the display
page for at least one year.

If the change announced during the measurement period does not significantly impact
the numerator or denominator of the measure, the measure will continue to be included
in the Star Ratings (e.g., when during the measurement period additional codes are
added that would increase the number of numerator hits for a measure).
The methodology for the following measures is being modified:
1.
Improvement measures (Part C & D). The methodology for the improvement measures
remains the same as in prior years. We have updated the measures included in the
improvement measure to account for measures with at least two years of data. Please refer
to the Appendix for updates to the measures to be used to calculate the 2017 improvement
measures. We are also considering that if a contract’s CAHPS measure score moved to very
low reliability with the exclusion of the enrollees with less than 6 months of continuous
4
The Challenges of Pharmacy Star Ratings • 79
enrollment for the 2015 survey administration, then the 2014 CAHPS measure score (used in
2015 Star Ratings) would be used instead as the baseline for the 2017 improvement
calculation for that measure.
2.
Reviewing Appeals Decisions/Appeals Upheld measures (Part C & D). Currently, these
measures include cases that are reopened and decided by April 1 of the following contract
year. In some instances, appeals filed in the 4th quarter of the year and then subsequently
reopened may not be determined by the Independent Review Entity (IRE) by April 1. We
propose for the 2017 Star Ratings to modify these measure specifications so that if a
Reopening occurs and is decided prior to May 1, 2016, the Reopened decision would be used.
Reopenings decided on or after May 1, 2016 would not be reflected in these data, and the
original decision result would be used.
3.
Contract Enrollment Data (Part C & D). Contract enrollment numbers are pulled from HPMS
for the Part C and D “Complaints about the Health/Drug Plan” and the Part D “Appeals AutoForward” measures. Additionally, plan-level enrollment is pulled for the three Part C “Care
for Older Adults” measures. For these measures, twelve months of enrollment files are pulled
from HPMS, and the average enrollment from those months is used in the measure
calculations. We propose going forward to adjust the twelve months from January to
December to February through January of the relevant measurement period. HPMS
enrollment numbers are determined between the end of the first week to the beginning of
the second week of the prior month. For example, January enrollment numbers reflect
enrollment as determined as of the first week of December. Thus, we are modifying the
enrollment numbers to reflect an average of the HPMS enrollment from February through
January of the measurement year.
4.
Transition from ICD-9 to ICD-10 (Part C & D). The measure stewards, such as the Pharmacy
Quality Alliance (PQA) and the National Committee for Quality Assurance (NCQA), are in the
process of reviewing their measure specifications with diagnosis-related requirements to
transition from ICD-9 to ICD-10.
Once the PQA updates their measure specifications, we will provide more information. We
will test and adopt the changes implemented by PQA as appropriate for the Part D Star
Ratings and display measures.
NCQA has incorporated the ICD-10 codes in the 2016 Healthcare Effectiveness Data and
Information Set (HEDIS). During the transition period both ICD-9 and ICD-10 codes will be
used due to the look-back periods for some measures.
5.
Appeals Upheld measure (Part D). For the 2016 Star Rating Upheld measure, we excluded
appeal cases for beneficiaries enrolled in hospice at any point during 2014. As noted in the
2016 Call Letter, this exclusion was only necessary for the 2016 measure as it is based on 2014
data that may have been affected by policy changes in 2014. This exclusion will not be
continued for the 2017 Star Rating Appeals Upheld measure.
5
80 • AIS’s Management Insight Series
6.
Medication Therapy Management (MTM) Program Completion Rate for Comprehensive
Medication Reviews (CMR) measure (Part D). We will add a detailed file during each HPMS
plan preview period to list each contract’s underlying denominator, numerator, and Data
Validation score since exclusions are applied to the plan-reported MTM data.
The CMR rate measure is an initial measure of the delivery of MTM services, and we continue
to look forward to the development and endorsement of outcomes-based MTM measures as
potential companion measures to the current MTM Star Rating. Lastly, we will be
implementing additional data integrity checks (discussed later in this memo) to safeguard
against inappropriate attempts to bias the data used for this measure.
B.
Removal of Measures from Star Ratings
1. Improving Bladder Control (Part C). This measure, collected through the Health Outcomes
Survey (HOS), assesses the percentage of beneficiaries with a urine leakage problem who
discussed their problem with their provider and received treatment for the problem. NCQA
made three changes to this measure. First, NCQA changed the denominator of both indicators
to include all adults with urinary incontinence, as opposed to limiting the denominator to
those who consider urinary incontinence to be an issue. This will remove a potential bias
toward only sampling patients who were treated unsuccessfully. Second, NCQA changed the
treatment indicator to assess whether treatment was discussed, as opposed to it being
received. This will change the measure focus from receiving potentially inappropriate
treatments, which often have adverse side effects, to shared decision making between the
patient and provider about the appropriateness of treatment. Third, NCQA added an outcome
indicator to assess how much urinary incontinence impacts quality of life for beneficiaries. This
outcome indicator will not be part of the Star Rating system until additional analyses have
been completed.
These changes required revising the underlying survey questions in HOS. The revised
questions were first collected in 2015. As a result of these changes, this measure will not be
reported in the 2017 Star Ratings. The revised measure will be reported on the 2017 display
page since the survey was first fielded with the new questions in 2015. The 2016 display
measure uses data from the old questions.
2.
High Risk Medication (Part D). The High Risk Medication (HRM) measure calculates the
percent of Medicare Part D beneficiaries 65 and older who received two or more prescription
fills for the same HRM drug with a high risk of serious side effects in the elderly. The measure
is endorsed by the PQA and National Quality Forum (NQF), and the HRM rate is calculated
using the PQA specifications and medication list based on American Geriatrics Society (AGS)
recommendations. The AGS recently released the 2015 update of the Beers Criteria.
The HRM measure will be removed from the Star Ratings and moved to the display measures
for 2017. This proposal is based on a number of factors. While the AGS states that the
criteria may be used as both an educational tool and quality measure, the AGS further states
that the intent is not to apply the criteria in a punitive manner. Specifically, the addition of a
drug to the HRM list is not a contraindication to use, rather an encouragement to avoid use in
6
The Challenges of Pharmacy Star Ratings • 81
the senior population without consideration of risks and benefits based on individual patient
considerations. This is a very difficult decisional balance to evaluate in a drug plan that does
not have access to full clinical information. As the measure can be calculated only by using
prescription drug event (PDE) data, medications cannot be included on the HRM List that have
risks conditional on clinical factors that cannot be measured using PDE data alone. As a result,
some “Avoid” medications are included in the measure, while others are not. This may create
unintended consequences including the inappropriate encouragement of certain non-HRM
medications, which may not be the best choice for an individual beneficiary’s clinical
circumstance.
Lastly, because it is under direct provider control and should not be affected by non-clinical
beneficiary characteristics, the HRM measure was not included in CMS’ overall analysis to
assess the impact of socio-economic status (SES) on the Star Ratings (discussed later in this
memo). However, our initial analysis found that after controlling for contract effects and dual
eligible or low income subsidy status, there is a significant association between dual
eligible/low income status and HRM use. This association remains after further controlling for
age, sex, and race/ethnicity. We recommend that the measure developers further review this
measure to better understand the associations.
Avoiding potentially inappropriate medications in older adults remains important for quality
of care for Medicare beneficiaries. Therefore, the HRM measure will move to the 2017
display page and may be considered for the Star Ratings again in the future. We will continue
to provide HRM measure reports to Part D sponsors on a monthly basis through the Patient
Safety Analysis website, and we will continue to identify outliers.
If measure updates are endorsed by the PQA with sufficient lead time ahead of the 2017
formulary and bid deadlines in May and June 2016, CMS may consider adoption for the 2019
display page (using 2017 data). We will provide additional information on updates if available
in the draft 2017 Call Letter.
C.
Data Integrity
It is essential that the data used for CMS’ Star Ratings are accurate and reliable. CMS’ policy is
to reduce a contract’s measure rating to 1 star if it is determined that biased or erroneous data
have been submitted. This would include cases where CMS finds mishandling of data,
inappropriate processing, or implementation of incorrect practices by the
organization/sponsor have resulted in biased or erroneous data. Examples would include, but
are not limited to: a contract’s failure to adhere to HEDIS, HOS, or CAHPS reporting
requirements; a contract’s failure to adhere to Plan Finder or PDE data requirements; a
contract’s errors in processing coverage determinations/exceptions or organization
determinations found through program audits or other reviews; compliance actions due to
errors in operational areas that would directly impact the data reported or processed for
specific measures; or a contract’s failure to pass Part C and D Reporting Requirements Data
Validation related to organization/sponsor-reported data for specific measures.
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82 • AIS’s Management Insight Series
CMS has taken several steps in the past years to protect the integrity of the data; however, we
continue to identify new vulnerabilities where inaccurate or biased data could exist. We also
must safeguard against the Star Ratings program creating perverse incentives for sponsors.
CMS program audits will soon include review of Part D sponsors’ MTM programs. We intend
to review and apply any relevant MTM program audit findings that could demonstrate
sponsors’ MTM data were biased, outside of the Data Validation results. CMS is concerned
about sponsor activities that may not be detected by routine Data Validation standards, such
as attempts to restrict eligibility from their approved MTM programs, encouraging beneficiary
opt-out of MTM programs within the first 60-days, or CMRs that do not meet CMS’ definition
per guidance. CMS may perform additional audits or reviews to ensure the validity of data for
specific contracts. Without rigorous validation of Star Ratings data, there is risk that CMS will
reward contracts with falsely high ratings.
D. Impact of Socio-economic and Disability Status on Star Ratings
A key goal of the MA and Part D programs is to achieve greater value and quality for all
beneficiaries; therefore, an important corollary is that we do not distort quality signals in our
measures, or mask true differences in quality of care. CMS continuously reviews the Star
Ratings methodology to improve the process, incentivize plans, and provide information that is
a true reflection of the performance and experience of the enrollees. The policies
implemented must result in high quality of care and health outcomes for all of our
beneficiaries, while acknowledging the unique challenges of serving traditionally underserved
subsets of the population.
A number of MA organizations and PDP sponsors believe that enrollment of a high percentage
of dual eligible (DE) enrollees and/or enrollees who receive a low income subsidy (LIS) limits
their plan’s ability to achieve high MA or Part D Star Ratings. CMS has responded to the
concern of our stakeholders and has comprehensively gathered information to determine if
the Star Ratings are sensitive to the socio-economic and disability status of a contract’s
enrollees. If adjustments are made to address this issue, they must be data driven. For
example, if a disparity is due to challenges in serving disabled beneficiaries, rather than in
serving those with lower SES, then the adjustment should clearly focus on disability status of
beneficiaries. Similarly, unless our methods are transparent and open to input from a breadth
of sources, contracts will not be able to translate as easily our findings into actionable quality
improvement steps.
With support from our contractors, we have undertaken research to provide the scientific
evidence as to whether MA or Part D sponsors that enroll a disproportionate number of
vulnerable beneficiaries are systematically disadvantaged by the current Star Ratings. Last
year, we issued a Request for Information to gather information directly from organizations to
supplement the data that CMS collects, as we believe that plans and sponsors are uniquely
positioned to provide both qualitative and quantitative information that is not available from
other sources. In February and September 2015, we released details on our research and
8
The Challenges of Pharmacy Star Ratings • 83
findings to-date.1 We have also reviewed reports about the impact of SES on quality ratings,
such as the report published by the National Quality Forum (NQF) posted at
www.qualityforum.org/risk_adjustment_ses.aspx and both the Medicare Payment Advisory
Commission’s (MedPAC) Report to the Congress: Medicare Payment Policy posted at
http://www.medpac.gov/documents/reports/mar2015_entirereport_revised.pdf?sfvrsn=0 and
their recent release on September 10th entitled Factors Affecting Variation in Medicare
Advantage Plan Star Ratings posted at http://www.medpac.gov/documents/september-2015meeting-presentation-factors-affecting-variation-in-medicare-advantage-plan-starratings.pdf?sfvrsn=0. The IMPACT Act (P.L. 113-185) instructs ASPE (Office of the Assistant
Secretary for Planning and Evaluation) to conduct a study before October 2016 that examines
the effect of individuals’ SES on quality measures, resource use and other measures for
individuals under the Medicare program. Because ASPE’s research agenda aligns closely with
our goals, we have and will continue to work collaboratively with ASPE and other
governmental agencies to broaden and expand the focus of the issue. We note that, as
instructed by Congress in the IMPACT Act, ASPE is conducting additional research in this area
and may make recommendations for additional changes in the future. We look forward to
their continued input. Further, CMS has engaged measure developers, NCQA and the PQA, to
examine measure specifications used in the Star Ratings program to determine if measure respecification is warranted.
CMS’ work is not complete, and we will continue to work diligently to address this issue and
others that may lie in the future with the goal that all MA and Part D beneficiaries receive the
highest quality care possible. The Star Rating system was designed to foster continuous quality
improvement in the MA and Part D programs. As such, the Star Ratings program - its measures
and methodology - are reviewed on an ongoing basis. We are committed to providing
beneficiaries information on Medicare Plan Finder that is a true reflection of the care and
experience of the plans’ members and to incentivize plans based on this same information.
As stated in the 2016 Final Call Letter, CMS believed additional research into the nature of the
differential performance on a subset of measures was necessary before any interim or
permanent changes in the Star Ratings measurements could be developed and implemented.
The additional research conducted after the publication of the 2016 Final Call Letter allowed
for further examination of LIS/DE differences (“effects”) and their magnitude. Due to the
considerable overlap between LIS/DE beneficiaries and disabled beneficiaries, the research
was expanded to consider the possible role of disability status. The research considered the
association between the performance on Star Ratings measures and enrollment of
LIS/DE/disabled beneficiaries, and the variability of differences in performance on each
measure by contract to
1
The February release can be found at https://www.cms.gov/medicare/prescription-drugcoverage/prescriptiondrugcovgenin/performancedata.html
The September release can be found at
https://www.cms.gov/Medicare/Prescription-Drug-Coverage/PrescriptionDrugCovGenIn/Downloads/Research-onthe-Impact-of-Socioeconomic-Status-on-Star-Ratingsv1-09082015.pdf
9
84 • AIS’s Management Insight Series
gain a better understanding of LIS/DE differences revealed in the preliminary research.2 The
methodology employed allowed for the delineation of within- and between-contract
differences associated with LIS/DE and/or disability. Within-contract differences are
differences that may exist between subgroups of enrollees in the same contract (e.g., if LIS/DE
enrollees within a contract have a different mean or average performance on a measure than
non-LIS/DE enrollees in the same contract). These differences may be favorable or
unfavorable for LIS/DE/disabled beneficiaries and can be assessed separately from the overall
level of performance for a contract. Between-contract differences in performance associated
with LIS/DE/disability status (“between-contract disparities”) are the possible additional
differences in performance between contracts associated with the contract’s proportion of
LIS/DE/disabled enrollees that remain after considering within-contract disparities by
LIS/DE/disability status. If LIS/DE/disabled beneficiaries are more or less likely than other
beneficiaries to be enrolled in lower-quality contracts, then between-contract disparities may
represent true differences between contracts in quality. Because of this possibility, betweencontract disparities may not be appropriate for adjustment due to the risk of masking true
differences in quality. Adjusting for within-contract disparities is an approach aligned with the
consensus reflected in the NQF report on sociodemographic adjustment, which states that,
“…only the within-unit effects are adjusted for in a risk adjustment procedure because these are
the ones that are related specifically to patient characteristics rather than differences across
units” (National Quality Forum, 2014). Our research focused on measuring within-contract
differences in performance for LIS/DE/disabled compared to non-LIS/DE/disabled beneficiaries.
Our additional research findings are consistent with the preliminary results shared in the 2016
Final Call Letter. The research to date has provided scientific evidence that there exists a
within-contract LIS/DE/disability effect for a subset of the Star Ratings measures. The size of
the effect differs across measures and is not exclusively negative.
CMS is firmly committed to building the foundation for a long-term solution that appropriately
addresses the issue at hand and aligns with our policy goals. Any policy response must
delineate the two distinct aspects of the LIS/DE and/or disability issue - quality and payment.
The Star Rating Program focuses on accurately measuring the quality of care provided so any
response must focus on enhancing the ability to measure actual quality differences among
contracts. To address the LIS/DE/disability issue we must accurately address any sensitivity of
the ratings to the SES of the beneficiaries enrolled in a contract at the basic building block of
the rating system, the measure. CMS has encouraged the measure stewards to examine our
findings and undertake an independent evaluation of the measures’ specifications to
determine if measure re-specification is warranted. Concurrently, the payment response must
focus on resource utilization and the predictive performance of the risk-adjustment models for
2
The research focused on a total of 16 clinical quality measures. A measure was excluded from analysis if the measure
was already case-mix adjusted for SES (i.e., CAHPS and HOS measures), the focus of the measurement was not a
beneficiary-level issue but rather a plan-level issue (e.g., appeals, call center, Part D price accuracy), the measure was
scheduled to be retired or revised, or the measure was applicable to only Special Needs Plans (SNPs) (i.e., SNP Care
Management, Care for Older Adults measures).
10
The Challenges of Pharmacy Star Ratings • 85
the unique cost patterns of beneficiaries in the community. CMS is also considering changes in
the risk adjustment models for payment and issued a separate Request for Comments on
October 28, 2015 to obtain feedback on potential revisions. We feel that these two approaches
are complementary; holding contracts to a same quality standard is most appropriate when
contracts are adequately resourced to provide the support their beneficiaries need to achieve
good health outcomes.
While the measure stewards are undertaking a comprehensive review of their measures used
in the Star Ratings program, CMS is exploring two options for interim analytical adjustments to
address the LIS/DE/disability effect: a Categorical Adjustment Index or Indirect
Standardization. We believe each of the proposed methods, discussed in more detail below,
align with the goals of: making adjustments that reflect the actual magnitude of the
differences observed in the data; providing valid quality ratings to facilitate consumer choice;
and providing incentives for MA and Part D quality improvement. In addition, we recognize
the need for the options to be both transparent and feasible for the plans, as well as to
maintain the integrity of the Star Ratings and the core of its methodology.
Another issue we are examining is the manner to address the unique aspects of
implementation of Medicare in Puerto Rico. Under statute, many of Department of Health and
Human Services’ (HHS) programs, including Medicare and Medicaid, are implemented
differently in Puerto Rico. In addition, Puerto Rico has a unique health care market with many
low-income individuals in both Medicare and Medicaid and a complex legal history that affects
the health care system in many ways. We are cognizant of the particular challenges in Puerto
Rico and propose an additional analytical adjustment for contracts with a service area only in
Puerto Rico to address the fact that the Part D low income subsidy (LIS) is not available there.
The details of the possible interim analytical adjustments follow. While the interim policy
responses to address the LIS/DE/disability effect are distinct analytical adjustments that are
applied on the measure scores, they offer flexibility in their application. CMS is requesting
feedback on each of the possible adjustments and the possible permutations of each option, or
potential hybrid approaches. We welcome comments on the specific measures that should be
adjusted3.
The Categorical Adjustment Index
The Categorical Adjustment Index is a factor that would be added or subtracted to a contract’s
Overall and/or Summary Star Rating to adjust for the average within-contract disparity.
Contracts would be categorized based on their percentages of LIS/DE and/or disabled
3
Our research focused on the following 16 measures: adult BMI assessment, rheumatoid arthritis management,
breast cancer screening, controlling blood pressure, diabetes care – blood sugar controlled, diabetes care – eye exam,
diabetes care – kidney disease monitoring, colorectal cancer screening, osteoporosis management in women who had
a fracture, plan all-cause readmissions, annual flu vaccine, monitoring physical activity, reducing the risk of falling,
medication adherence for diabetes medications, medication adherence for hypertension, and medication adherence
for cholesterol.
11
86 • AIS’s Management Insight Series
beneficiaries, and the Categorical Adjustment Index value would be the same for all contracts
within each category. The Categorical Adjustment Index value is the star adjustment for
contracts by category.
The Categorical Adjustment Index values would be computed by comparing the mean Overall
and/or Summary contract Star Rating derived from measure scores that are adjusted for LIS/DE
and/or disability status to the mean Star Rating derived under the traditional methodology.
The adjusted measure scores would be derived from regression models of beneficiary-level
measure scores that adjust for the average within-contract difference in measure scores by
LIS/DE and/or disability status for MA or PDP contracts without masking potential differences
in quality across contracts. This approach is equivalent to case-mix adjustment or patient-mix
adjustment in a patient-level linear regression model with contract intercepts and beneficiarylevel indicators of LIS/DE/disability status, similar to the approach currently used to adjust
CAHPS patient experience measures. Measure scores are adjusted first and then the adjusted
measure score is converted to a measure-level Star Rating using the measure thresholds for
the given Star Ratings year.
The Categorical Adjustment Index is derived via four steps: (1) contracts are divided into an
initial set of categories based on some combination of LIS/DE/disability (this might be 10
categories corresponding to the 10 deciles of LIS/DE or the 16 combinations of LIS/DE quartile
and disability quartile, or some other grouping); (2) the mean difference between the Adjusted
Overall or Summary Star Rating and the Unadjusted Star Rating is computed within each of the
initial categories; (3) the mean differences of the initial categories in step (2) are examined and
combined into final adjustment groups such that initial categories with similar means form the
groups; and (4) the mean star Adjustment is computed within each of the final adjustment
groups - this is the Categorical Adjustment Index.
The Star Rating measure’s specification is unchanged. The Categorical Adjustment Index is
applied external to the specification and is applied at the Overall and/or Summary Star Rating.
Each contract within a given final LIS/DE/disability group receives the same adjustment to its
Overall and/or Summary Star Ratings. The index would be determined using the current year’s
ratings. For the 2017 Star Ratings (measurement year 2015), the Categorical Adjustment Index
values would be based on the observed values for the 2017 Star Ratings year using data from
contracts that meet current reporting requirements.
The table below depicts an example of the overall method and one possible scenario for
groupings employed to determine the Categorical Adjustment Index. In preliminary work,
these eight possible final categories of LIS/DE/disability were derived by combining 16 initial
combinations of LIS/DE and disability quartiles in the manner described above.
12
The Challenges of Pharmacy Star Ratings • 87
Mean Overall
Grouping of contract, based on %
Unadjusted Star
LIS/DE and % Disabled
Rating
LIS/DE 1st quartile & disability 1st
quartile
LIS/DE 1st quartile & disability 2nd4th quartiles
LIS/DE 2nd quartile & disability 1st
quartile
LIS/DE 2nd quartile & disability
2nd-4th quartile
LIS/DE 3rd quartile & disability 1st2nd quartiles
LIS/DE 3rd quartile & disability 3rd4th quartiles
LIS/DE 4th quartile & disability 1st3rd quartiles
LIS/DE 4th quartile & disability 4th
quartile
Mean Adjusted
Star Rating
Mean Difference in Star Rating
(Adjusted - Unadjusted)
Indirect Standardization
Indirect standardization, an alternative proposal, would be applied to a subset of the individual
Star Ratings measure scores; measure stars are not used because that would incorrectly
assume assignments of measure stars are linear in the underlying measure and thus, lead to
measurement error. The focus of the adjustment is the within-contract LIS/DE and/or
disability status difference while allowing for the existence of true differences in quality by
contract. The standardization would employ the current year’s ratings.
An expected measure score would be calculated using the percent of LIS/DE and/or disabled
and non-LIS/DE and/or non-disabled beneficiaries per measure multiplied by the adjusted
mean national performance for each subgroup. As above, this method could use a variety of
grouping methodologies to determine appropriate subgroups. These contract-adjusted LIS/DE
and/or disabled and non-LIS/DE and/or non-disabled national performance means would be
calculated such that they differed by the national performance mean within-contract LIS/DE
versus non-LIS/DE difference (and/or disabled versus non-disabled difference). The expected
measure score is a weighted average based on the composition of the enrollees of the contract
and the national adjusted mean measure score for the subgroups of interest (e.g., LIS/DE
and/or disabled versus non-LIS/DE and/or non-disabled beneficiaries). For example: Using
indirect standardization at the measure score level, the expected measure score for diabetes
control would use the adjusted national means for performance on diabetes control for the
subgroups of interest (LIS/DE and non-LIS/DE and/or disabled and non-disabled
beneficiaries). To simplify the example, the focus of the standardization is disability status, but
the same method could be expanded to more than two subgroups and include standardization
for LIS/DE and non-LIS/DE. If the adjusted national mean performance on diabetes control is
50% for disabled beneficiaries and 60% for non-disabled beneficiaries, a contract that served
only disabled beneficiaries would be expected to perform at 50% and a contract that served
only non-disabled beneficiaries would be expected to perform at 60%. Contracts that had both
disabled and non-disabled beneficiaries would be expected to perform at a specific level
13
88 • AIS’s Management Insight Series
between 50% and 60%, as a weighted average based on the composition of the enrollees in
the contract for that measure. Each contract would be judged against its expected
performance.
Next, the ratio of the observed-to-expected measure score would be calculated. (The observed
value is the measure score based on the rating year’s data). The observed-to-expected ratio
would equal one for contracts that performed at the level expected given their percentages of
LIS/DE and/or disabled beneficiaries and indicates average performance. In contrast, a ratio
less than one would indicate lower observed performance than expected given the contract
percentage of LIS/DE and/or disabled beneficiaries; similarly, ratios greater than one would
indicate better than expected performance.
The adjusted measure score would then be calculated. The adjusted measure score is the
product of the observed-to-expected ratio for a contract and the adjusted national mean
performance for all Medicare beneficiaries. Two contracts with identical observed measure
performance but different expected measure performance would receive different adjusted
measure scores. The adjusted measure score would be converted to a measure-level Star
Rating using the measure thresholds for the given Star Ratings year. The adjusted measure
level stars would then be used in the determination of the Overall and/or Summary Star
Rating.
The tables below summarize for a single measure the information needed and the overall
methodology to determine the adjusted measure score. The first table provides the national
values needed to indirectly standardize a measure score. The second table and corresponding
information below the table provide a high-level overview of the process of indirect
standardization to determine the adjusted measure score. For ease of presentation, the tables
focus on an adjustment for the subgroups of LIS/DE and non-LIS/DE, but the same method
would be applied for the distinct groupings of LIS/DE, non-LIS/DE, disabled, and non-disabled
combinations.
Measure-specific
National Adjusted Values
Contract
1
Proportion of
LIS/DE
Beneficiaries
D
Adjusted Pass Rate for
LIS/DE Beneficiaries
A
Proportion of
non-LIS/DE
Beneficiaries
E
Adjusted Pass Rate for
non-LIS/DE Beneficiaries
B
Overall
Pass Rate
(Observed)
F
Expected Rate
(Based on
composition of
plan)
G
Adjusted Overall National
Mean
C
Ratio of
Observed to
Expected
H
Adjusted
Measure
Score
I
The contract’s proportion of LIS/DE and non-LIS/DE per measure (values D and E) would be
multiplied by the corresponding national adjusted rates for LIS/DE and non-LIS/DE (values A
and B) to determine the expected performance for the measure score (value G). The formula
applied would be as follows: Expected Rate = A×D + B×E.
14
The Challenges of Pharmacy Star Ratings • 89
Next, the ratio of the observed (actual) would be calculated (Ratio = F/H). The ratio
calculated would be multiplied by the adjusted overall national mean (value C) to determine
the adjusted measure score (value I). The adjusted measure score would be converted to a
measure-level Star Rating, and the traditional Star Ratings methodology would ensue to
determine the adjusted Overall and/or Summary Star Rating for the year.
Additional response to address lack of an LIS indicator for enrollees in Puerto Rico
Notably, Puerto Rican beneficiaries are not eligible for LIS, which is an important element of
both potential methodologies. (Beneficiaries in the 50 states are eligible for LIS in the
mainland if their income is less than 150% of the Federal Poverty Level). To make the proposed
analytical adjustments equitable, CMS is considering an additional adjustment for contracts in
Puerto Rico to identify beneficiaries in Puerto Rico’s contracts whose incomes would result in
an LIS designation in the mainland.
The contract-level modified LIS/DE proportion for Puerto Rico would be developed from two
sources of information: (1) the overall proportion of beneficiaries in Puerto Rico with incomes
less than 150% of the FPL and (2) each contract’s proportion of DE beneficiaries. A linear
regression model would be developed to predict the percentage of LIS in a contract using the
percentage of DE using all MA contracts except those in Puerto Rico. Preliminary evidence
suggests this model has very high accuracy in predicting contract-level LIS from contract-level
DE in the 50 states and the District of Columbia, even when restricted to lower-income subsets
of states. This model would then be adjusted for use in Puerto Rican contracts (i.e., contracts
with a service area only in Puerto Rico) using Puerto Rico’s mean percentage of DE and mean
of LIS (using the percentage of Puerto Rico’s population with incomes less than 150% of the
FPL). Using the model developed, each contract’s proportion of DE beneficiaries in Puerto Rico
would have a corresponding proportion of LIS to create a contract-level measure of LIS/DE
percentage to be used in the Categorical Adjustment Index or Indirect Standardization
adjustments. We welcome comments on this proposed approach to approximate the
percentage of LIS by contract in Puerto Rico, or other possible suggestions of ways to estimate
this percentage.
We also considered options to address the unique challenges that Puerto Rican contracts face
in improving medication adherence. It has been shown that beneficiaries’ out-of-pocket costs
may adversely affect medication adherence, which presents an additional barrier for Puerto
Rican contracts serving beneficiaries whose incomes would result in an LIS designation in the
mainland. One option we considered was to reduce the weights of the three Part D
Medication Adherence measures for Puerto Rican contracts. A prior proposal in the 2015 draft
Call Letter to reduce the weight of the three Part D Medication Adherence measures to 1.5 as
access measures for all Part D sponsors was not supported by the majority of commenters.
MA plans and PDP sponsors expressed concerns that this type of change would be contrary to
efforts to encourage coordination of care, as well as decrease performance in other quality
measures. We simulated this change to assess the potential impact. The highest ratings for
substantially all of the Puerto Rican contracts remained unchanged based on simulation of the
2015 Star Ratings data. We commend the Puerto Rican contracts on their improved
performance overall across the 2016 Star Ratings and the Part D Medication Adherence
15
90 • AIS’s Management Insight Series
measures in particular. We found no changes to the highest ratings for Puerto Rican contracts
when we simulated reducing the weight of the adherence measures using 2016 Star Ratings
data. We welcome other proposals to account for the barriers for Puerto Rican contracts to
improve medication adherence.
Summary
The potential interim analytical adjustments to address the LIS/DE/disability effect, the
Categorical Adjustment Index and Indirect Standardization, share common features. These
adjustments were developed while focusing on measuring within-contract differences, while
allowing for the existence of true differences in quality by contract. In addition, both methods
rely on an adjustment external to the measure specification. The methods result in an
adjustment to the measure scores for a subset of measures. The adjusted measure scores are
converted to a measure-level Star Rating employing the original measure thresholds for the
Star Ratings year before adjustment. For the improvement measure we would use unadjusted
scores.
Both analytical adjustments under consideration would require additional processing of the
data by CMS. Both methods are applied to the measure score and employ a measure-specific
proportion of LIS/DE/disabled which is not constant across measures given measure
specification exclusions. Further, both adjustments are based on the current year’s data and
thus, values needed for the application of the methods (Categorical Adjustment Index values
and the adjusted overall national mean per measure and for each subgroup for Indirect
Standardization) would not be available until after the submission of the data for the year.
Given the additional data processing steps, the analytical adjustments may result in a
compressed timeframe for Part C and D contracts’ review process of the ratings. The
Categorical Adjustment Index values would be incorporated in the Star Ratings Technical
Specifications and would be a set of adjustment factors to the overall and/or summary ratings.
For the Indirect Standardization method, contracts would need to review a larger volume of
intermediate calculations for each measure during the preview periods.
Both of these methods adjust for within-contract differences. Based on our research, we
would not expect either approach to generate major adjustments in the overall Star Ratings,
though any adjustment may be significant for individual contracts. We recognize adjustments
that account for the full between-contract differences (e.g., summary level indirect
standardization) would make a considerably larger difference overall, but these approaches
could risk over-crediting poor quality contracts. Implementing such an approach coupled with
adjustments both upward (for contracts with a high proportion of duals) and downward (for
contracts with a lesser proportion of duals) would likely result in larger swings both positively
and negatively for contracts. CMS is interested in understanding comments about this
approach, including its impact on accurate measurement of quality. CMS also notes that ASPE
will continue to explore options that could be implemented in future years.
16
The Challenges of Pharmacy Star Ratings • 91
E.
2017 CMS Display Measures
Display measures on www.cms.gov are not part of the Star Ratings. These may include
measures that have been transitioned from the Star Ratings, new measures that are being
tested before inclusion into the Star Ratings, or measures displayed for informational
purposes. Similar to the 2016 display page, organizations and sponsors have the opportunity
to preview their data for the display measures prior to release on CMS’ website. Data for
measures moved to the display page will continue to be collected and monitored, and poor
scores on display measures are subject to compliance actions by CMS. It is expected that all
2016 display measures will continue to be shown on www.cms.gov. CMS will continue to
provide advance notice regarding measures considered for implementation as future Star
Ratings measures. Other display measures may be provided as information only.
1.
Timely Receipt of Case Files for Appeals (Part D) & Timely Effectuation of Appeals (Part D).
For the 2016 display measures, the data time frame for both measures was 01/01/2015 –
06/30/2015. CMS proposes to change the data time frame from the first six months of the
current year to January 1 – December 31 of the previous year. For example, the 2017 display
measures would be based on IRE data from January 1, 2015-December 31, 2015. This change
will allow the appeal display measures to match the same timeframe used for the Part D
Appeal Star Ratings measures.
The following are a number of new measures for the 2017 display page.
2.
Medication Reconciliation Post Discharge (Part C). The Medication Reconciliation PostDischarge (MRP) measure assesses the percentage of discharges from acute or non-acute
inpatient facilities for members 66 years of age and older for whom medications were
reconciled within 30 days of discharge. NCQA made two changes: 1) expanded the coverage
on this measure from Medicare Special Needs Plans only to all of MA; and 2) expanded the
age range to members 18 years and older. Both of these changes for HEDIS 2016 are seen as
an important step to measure the quality of care coordination post-discharge for MA
beneficiaries as well as ensuring patient safety. CMS is planning to include this measure on
the 2017 display page and is planning to include it in the 2018 Star Ratings.
3.
Hospitalizations for Potentially Preventable Complications (Part C). NCQA added to HEDIS
2016 a risk-adjusted measure of hospitalization for ambulatory care sensitive conditions
based on the NQF-endorsed Prevention Quality Indicators (PQI), developed by AHRQ. This
measure assesses the rate of hospitalization for complications of chronic and acute
ambulatory care sensitive conditions. The intent of the measure is to assess the quality of
ambulatory care—including coordination of that care—to prevent the complications of
chronic and acute conditions that result in hospitalization. CMS is planning to include this
measure on the 2017 display page and is planning to include it in the 2018 Star Ratings.
4.
Statin Therapy for Patients with Cardiovascular Disease (Part C). NCQA has added two sets
of statin therapy measures to HEDIS aligned with the 2013 ACC/AHA blood cholesterol
guidelines. These measures are focused on two of the major statin benefit groups described in
17
92 • AIS’s Management Insight Series
the guidelines: patients with clinical atherosclerotic cardiovascular disease and patients with
diabetes. Since some of these HEDIS measures overlap with the measures developed by the
PQA, CMS is planning to include only one of the HEDIS measures on the 2017 display page and
is planning to include this measure in the 2018 Star Ratings. This measure focuses on statin
therapy for patients with cardiovascular disease. It is the percentage of males 21 to 75 years
of age and females 40 to 75 years of age who were identified as having clinical atherosclerotic
cardiovascular disease and were dispensed at least one high or moderate-intensity statin
medication during the measurement year.
5.
Asthma Measures (Part C). NCQA has expanded their asthma measures to include older
adults. HEDIS 2016 includes two measures for older adults. Medication Management for
People with Asthma is the percentage of members 5 to 85 years of age who were identified as
having persistent asthma and were dispensed appropriate medications that they remained on
during the treatment period (i.e., first prescription date through end of measurement year).
The Asthma Medication Ratio is the percentage of members who were identified as having
persistent asthma and had a ratio of controller medications to total asthma medications of
0.50 or greater during the measurement year. CMS is planning to include these on the 2017
display page and will consider these for inclusion in Star Ratings for future years.
6.
Statin Use in Persons with Diabetes (SUPD) (Part D). This new PQA-endorsed measure,
Statin Use in Persons with Diabetes (SUPD), calculates the percentage of patients between 40
and 75 years old who received at least two diabetes medication fills and also received a statin
medication during the measurement period. Beneficiaries in hospice according to the
Enrollment Database (EDB) will be excluded from the denominator of the SUPD measure for
the entire year. Part D sponsors have received year of service 2015 SUPD measure reports on
a monthly basis through the Patient Safety Analysis website, and we will add the SUPD
measure to the 2017 display page (using 2015 data). We propose adding the SUPD measure
to the 2018 Star Ratings (using 2016 data).
Forecasting to 2018 and Beyond
The following describes changes to existing measures and potential new measures. CMS will
also monitor any additional measures developed by NCQA or PQA for potential incorporation
into the Star Ratings.
F.
New Measures:
See section E above which describes a number of new measures under consideration for the
2018 Star Ratings that will be reported as 2017 display measures. The following are additional
measures under consideration for the Star Ratings or display measures for 2018 and beyond.
1.
Care Coordination Measures (Part C). Effective care coordination contributes to improved
health outcomes. CMS believes that 5-star contracts perform well on our Star Ratings
measures because they understand how to effectively coordinate care for their enrollees. Our
assumption about plans, however, is based largely on anecdote and discussions with high
performing plans, as well as on data we collect from CAHPS surveys which reflect enrollees’
experiences with the care they receive.
18
The Challenges of Pharmacy Star Ratings • 93
CMS is working to expand efforts in this area. To identify potential new care coordination
measures, CMS is utilizing experts to conduct targeted research, extensive literature reviews,
and data analysis, and to engage in discussions with expert panels and high performing plans.
As part of this effort, we are considering various data sources; whether the measures should
be focused on subgroups of MA enrollees or all MA enrollees; the activities that best
represent care coordination such as ensuring seamless transitions across settings, appropriate
follow up after inpatient and emergency department visits, communication across providers,
and comprehensive assessments; and the relationship between the plan and provider in care
coordination activities. NCQA, using administrative and medical record data, will begin
testing the following proposed measures using 2015 data: primary care provider (PCP)
notification of inpatient admissions, summary of care record in PCP chart, follow-up with
PCP/specialist following hospital discharge or emergency department visit, and in the
ambulatory setting whether there is a comprehensive assessment performed and
documented by the PCP/specialist and whether there is a specialist visit summary in the PCP
chart. Additionally, CMS has recently awarded another contract to develop care coordination
measures using administrative data, including MA encounter data and Part D data. CMS
welcomes comments on measures that could be developed using MA encounter data. We will
continue to provide updates to the industry as this work progresses. Measures developed and
tested may be considered for future inclusion on the display page and in Star Ratings.
2.
Depression Measures (Part C). NCQA has adapted a provider-level depression outcome
measure developed by Minnesota Community Measurement for use in HEDIS. Depression
Remission or Response in Adolescents and Adults (DRR) uses a patient-reported outcome
measure, the PHQ-9 tool, to assess whether patients with depression have achieved remission
or have an improvement in their symptoms. The measure assesses the percentage of
individuals age 12 and older with depression and an elevated PHQ-9 score (greater than 9)
who achieve a PHQ-9 score of less than 5 at six months or have a 50% reduction in their PHQ9 score. This measure also uses a new data collection methodology for HEDIS, relying on data
coming from electronic clinical data systems (e.g., EHRs, clinical registries, case management
records). If approved, the new measure would be published in HEDIS 2017.
3.
Appropriate Pain Management (Part C). NCQA is exploring opportunities to develop a new
measure(s) focusing on appropriate pain management. The intent is to assess the quality of
pain management and treatment. There is no definite timeline established for the
development of this measure.
4.
Use of Opioids from Multiple Providers or at High Dosage in Persons without Cancer (Part
D). In the 2016 Call Letter, we noted that three opioid overutilization measures were in
development by the PQA. We further stated that if these measures were endorsed by the
PQA prior to the 2017 bid deadline in June 2016 that we may adopt them as future display
measures or alternatively use them in the Overutilization Monitoring System (OMS). The
measures were endorsed by the PQA in May 2015.
PQA’s three opioid measures examine multi-provider, high dosage opioid use among
individuals 18 years and older without cancer and not in hospice care.
19
94 • AIS’s Management Insight Series
Measure 1 (Opioid High Dosage): The proportion (XX out of 1,000) of individuals without
cancer or hospice receiving prescriptions for opioids with a daily dosage greater than 120mg
morphine equivalent dose (MED) for 90 consecutive days or longer.
Measure 2 (Multiple Prescribers and Multiple Pharmacies): The proportion (XX out of 1,000)
of individuals without cancer or hospice receiving prescriptions for opioids from four (4) or
more prescribers AND four (4) or more pharmacies.
Measure 3 (Multi-Provider, High Dosage): The proportion (XX out of 1,000) of individuals
without cancer or hospice receiving prescriptions for opioids with a daily dosage greater than
120mg morphine equivalent dose (MED) for 90 consecutive days or longer, AND who received
opioid prescriptions from four (4) or more prescribers AND four (4) or more pharmacies.
We tested the measures using the PQA specifications. We will develop new patient safety
opioid overutilization measure reports (beginning with 2016 dates of service) to provide to
Part D sponsors on a monthly basis through the Patient Safety Analysis website, similar to the
other patient safety measures. The website also includes the OMS. The reports will allow
sponsors to track their performance over time and allow for contract level trending and
outlier analyses. We will also add these three measures to the 2018 Part D display page
(using 2016 data). We do not recommend adding these measures to the Star Ratings at this
time due to concerns (1) about the current lack of consensus clinical guidelines for the use of
opioids to treat chronic, non-cancer pain and potential exceptions due to medical necessity
and (2) pending additional analysis on diagnosis data sources, such as newly available
encounter data for Medicare Part C and resolving timing issues of RAPS file updates, which
are used to identify exclusions for certain cancer conditions.
Additionally, NCQA is adapting the three opioid overuse measures developed by the PQA for
potential use in HEDIS.
5.
Antipsychotic Use in Persons with Dementia (APD) (Part D). CMS has been particularly
concerned with the unnecessary use of antipsychotic drugs in nursing homes and, as a result,
has pursued strategies to increase awareness of antipsychotic use in long term care settings.
In 2013, we began to calculate a general atypical antipsychotic utilization rate, called Rate of
Chronic Use of Atypical Antipsychotics by Elderly Beneficiaries in Nursing Homes, for inclusion
in the Part D display measures. The average rates decreased from approximately 24.0% in
2011 to 21.4% in 2013.
There continues to be increased attention on this important issue. The United States
Government Accountability Office (GAO) released a report4 in January 2015 describing the
inappropriate use of antipsychotics in Part D beneficiaries with dementia, in both community
(i.e., outside of nursing homes) and long-stay nursing home residents during 2012, with
4
Antipsychotic Drug Use: HHS Has Initiatives to Reduce Use among Older Adults in Nursing Homes, but Should Expand
Efforts to Other Settings. http://www.gao.gov/products/GAO-15-211. GAO-15-211: Published: Jan 30, 2015. Publicly
Released: March 2, 2015
20
The Challenges of Pharmacy Star Ratings • 95
recommendations for CMS to address this problem. The GAO conducted this study due to
concerns raised regarding the use of antipsychotic drugs to address the behavioral symptoms
associated with dementia, the FDA’s boxed warning that these drugs may cause an increased
risk of death when used by older adults with dementia, and because the drugs are not
approved for this use.
In addition, the PQA endorsed the measure, Antipsychotic Use in Persons with Dementia
(APD). This provides CMS with a new measure developed through a consensus process to
monitor the inappropriate use of antipsychotics in both the nursing home and community
settings across Medicare Part D plans.
We tested this measure based on the PQA specifications. The APD measure rate was
calculated for all contracts, MA-PDs, PDPs, and at the individual contract-level for all
beneficiaries, community-only residents (never a nursing home resident), and both short-term
and long-term nursing home residents that met the inclusion and exclusion criteria.
Beneficiaries were identified as long-stay nursing home residents if they had stays greater
than 100 cumulative days in a nursing home during the year based data in the Long Term Care
Minimum Data Set (MDS). Each beneficiary was counted in only one category for the entire
measurement period within a contract, not considered separately for time spent in different
settings (e.g., a beneficiary who experienced both short-term and long-term nursing home
stays was included only in the long-term category).
To identify the numerator and denominator populations, we used diagnosis data obtained
from inpatient (IP), outpatient (OP), and carrier claims from the Common Working File (CWF)
and RxHCCs from the RAPS. OP and Carrier claims are available for PDP contracts only. We
also adjusted rates based on the number of months beneficiaries are enrolled in each Part D
contract (i.e., member-years adjustment).
We conducted reliability testing using mixed effect logistic regression with varying intercept.
The testing results indicate that the rate variations at the contract level are statistically
significant, providing evidence that the measure is reliable.
We will develop new patient safety APD measure reports to provide to Part D sponsors on a
monthly basis through the Patient Safety Analysis website beginning with year of service
2016. We also recommend adding the overall APD measure plus breakout rates for
community-only residents, short-term nursing home residents, and long-term nursing home
stay residents to the 2018 Part D display measure set (using 2016 data) to continue to draw
attention to the inappropriate use of antipsychotics in persons with dementia without an
appropriate mental health diagnosis in both the community and nursing home settings. The
APD measure will replace the Rate of Chronic Use of Atypical Antipsychotics by Elderly
Beneficiaries in Nursing Homes display measure. However, we do not recommend adding this
measure to the Star Ratings pending additional research on diagnosis data sources, such as
newly available encounter data for Medicare Part C and resolving timing issues of RAPS file
updates.
21
96 • AIS’s Management Insight Series
G. Changes to Existing Star Ratings and Display Measures and Potential Future Changes:
1.
Colorectal Cancer Screening (Part C Star Rating). The Colorectal Cancer Screening (COL)
measure assesses the percentage of adults age 50-75 years of age who had appropriate
screening for colorectal cancer. This measure is based on the U.S. Preventative Services Task
Force (USPSTF) guideline on colorectal cancer screening in adults age 50-75. NCQA is
monitoring updates to the guideline as the USPSTF has released a draft recommendation
statement for public comment. We have discussed the guideline timing with the Agency for
Healthcare Research and Quality team in charge of the USPSTF process, and they note the
final release is not likely to occur until late 2016. NCQA will consider revisions to the COL
measure once the USPSTF final recommendation statement is published.
2.
Fall Risk Management (Part C Star Rating). The Fall Risk Management (FRM) measure,
collected through the Health Outcomes Survey, consists of the following two indicators: 1)
Discussing Fall Risk assesses the percentage of Medicare members 75 years of age and older
or 65-74 years of age with a balance or walking problem or fall in the past 12 months who
discussed falls or problems with balance or walking with their current practitioner; and 2)
Managing Fall Risk assesses the percentage of Medicare members 65 years of age and older
who had a fall or had problems with balance or walking in the past 12 months and received
fall risk intervention from their current practitioner defined as suggesting use of a cane or
walker, a vision or hearing test, physical therapy or exercise, or taking of a postural blood
pressure. NCQA is currently re-evaluating this measure to align with the most current U.S.
Preventive Services Task Force (USPSTF) guidelines. NCQA is proposing to 1) revise the
denominator in the Discussing Fall Risk indicator to include all Medicare members age 65 and
older and 2) revise the numerator for the Managing Fall Risk indicator to include use of
vitamin D and remove vision or hearing test and taking of postural blood pressure. These
proposed changes, if approved, would be published in HEDIS 2017 or HEDIS 2018.
3.
Pneumococcal Vaccination Status for Older Adults (Part C Display). The Pneumococcal
Vaccination Status for Older Adults (PNU) measure, collected through the Medicare CAHPS
survey, assesses the percentage of Medicare members 65 years of age and older who have
ever received a pneumococcal vaccination. In 2014, The Advisory Committee on Immunization
Practices (ACIP) released new recommendations that all adults 65 years of age and older
should receive sequential administration of both PCV13 and PPSV23. NCQA is considering
changes to the measure to align with the most current guidelines. There is no definite
timeline established for these changes. This measure is on the CMS display page.
4.
CAHPS measures (Part C & D). The current MA & PDP CAHPS Survey includes the core CAHPS
4.0 Health Plan Survey. CMS conducted an experiment in 2015 to understand how CAHPS
measures differ between 4.0 and 5.0, and based on the results we propose to update the
survey for future years to reflect AHRQ’s CAHPS 5.0 Health Plan Survey. The findings from the
experiment suggest that these changes are associated with a small increase in scores for
several evaluative MA measures. These small increases did not significantly differ across
contracts. Since there are no longer fixed thresholds for Star Ratings and they are based on
the actual distribution of scores, there should be no shifts in Star Ratings due to transition to
the version 5.0 instrument compared to what would have been the case with 4.0. Every
22
The Challenges of Pharmacy Star Ratings • 97
contract would have the same expected Star Rating whether version 4.0 or 5.0 is used, and
the correlation between this year’s Star Ratings and next year’s Star Ratings should be the
same regardless of whether 4.0 or 5.0 is used next year.
The 5.0 update applies recent improvements in survey design that resulted from development
and testing of the Clinician & Group Surveys. The 5.0 version of the CAHPS Health Plan Survey
incorporates some minor changes into the wording of core items, and a change in the
placement of one core item that also resulted in the deletion of a screener item. The following
are the changes in the 5.0 version of the Health Plan Surveys:

The items about access to urgent and non-urgent appointment items were modified to
ask respondents if they were able to get an appointment as soon as they needed, as
opposed to as soon as they thought they needed. Non-urgent appointments are described
as a check-up or routine care rather than health care. In addition, the phrase, “…not
counting the times you needed care right away” was deleted from these questions. These
revisions simplify the items and make them consistent with questions in other CAHPS
surveys.

The item about how often it was easy to get appointments with specialists was revised
to ask respondents if they got an appointment to see a specialist as soon as they needed.
This revision makes the item consistent with other CAHPS items that ask about access to
care.

The item about how often it was easy to get care, tests, or treatment was moved from
the Your Health Plan section to the Your Health Care in the Last 6 Months section, because
respondents had difficulty attributing this item to the health plan.

The screener item about getting care, tests, or treatment through the health plan was
deleted because the subsequent question was moved to an earlier section of the survey
and no longer required a screener.
These changes would take effect for the 2017 CAHPS survey administration (2018 Star
Ratings) based on OMB approval. Since we are modifying question wording, we propose the
following standard for deciding that a specification change has occurred for a CAHPS measure
for the purposes of excluding it from the improvement measure calculation: (1) at least one
item within the measure changed in wording, had a wording change in its screener, or had a
wording change in the immediately preceding item, and (2) the measure score in version 5.0
was significantly different from the measure score in version 4.0 in the 5.0 experiment. Three
MA measures met this standard: Getting Care Quickly, Customer Service, and Care
Coordination; thus, these three measures would be excluded from the Part C improvement
measure for the 2018 Star Ratings.
We are also considering changing the sampling for CAHPS when a contract is listed in HPMS as
a consolidation, merger, or novation between July of the prior year and January of the current
year when the CAHPS sample is drawn. We are considering changing the sampling frame for
23
98 • AIS’s Management Insight Series
the surviving contract to include the enrollees for all members of all contracts involved if the
two or more contracts merging, consolidating or novating are under the same parent
organization. This would go into effect for the 2017 sample draw.
5.
Medication Adherence for Hypertension (RAS Antagonists) (Part D Star Rating). Based on
PQA specification change, the measure will exclude from the denominator those patients with
one or more claims for sacubitril/valsartan.
6.
MPF Price Accuracy (Part D Star Rating). As stated in the 2016 Call Letter, CMS is considering
a few updates to this measure for the 2018 Star Ratings. The first proposed change is related
to the method by which claims are excluded from the measure. Currently, the measure is
limited to 30-day claims filled at pharmacies reported by sponsors as retail only or retail and
limited access only in their MPF Pharmacy Cost files. That is, claims filled for near 30 days
supplies, or claims filled for 60 and 90 days supplies are excluded. Additionally, claims filled by
retail pharmacies that are also long term care, mail order, or home infusion pharmacies are
excluded. These restrictions result in the exclusion of many PDEs, thus potentially biasing the
reliability of the measure.
We propose to include claims with 28-34 days supplies, as we believe it would be appropriate
to compare their PDE costs to MPF’s fixed display of 1 month pricing. We also propose to
include 60-62 and 90-93 day supplies. Beginning with CY2015 MPF submissions, plans must
provide brand and generic dispensing fees for 60 and 90 day supply claims in the Pharmacy
Cost file. CMS can use these data, along with 60 and 90 day supply Pricing File data, to
compare MPF and PDE costs. While the majority of claims are for a 30 day supply, we found
that claims with a 90 day supply account for almost one-fifth of available PDE data, thus
allowing for a more comprehensive evaluation of PDE claims.
Additionally, we propose to use the PDE-reported Pharmacy Service Type code in conjunction
with the MPF Pharmacy Cost data to identify retail claims. CMS began requiring pharmacies to
populate the Pharmacy Service Type field on all PDEs at the end of February 2013. We
recommend expanding the retail claims identification process to include all PDEs that are
from retail pharmacies according to the Pharmacy Cost data and have a Pharmacy Service
Type of either Community/Retail or Managed Care Organization (MCO). Although some
sponsors cited concern about the accuracy of these data as reported by pharmacists, Part D
sponsors are ultimately responsible for the accuracy of their submitted PDE to CMS.
According to PDE requirements, CMS expects “…sponsors and their network pharmacies to
develop and implement controls to improve the accuracy of this information during 2013…”
This methodology change would increase the number of PDEs eligible for inclusion in the Price
Accuracy Scores while continuing to identify only retail claims.
We are also considering changes to the methodology by which price accuracy is calculated.
Because the current methodology measures the magnitude of a contract’s overpricing relative
to its overall PDE costs, the Price Accuracy Scores do not reflect the frequency of accurate
price reporting, and can be significantly impacted by high cost PDEs. As a result, contracts
with divergent accurate price reporting and/or consistency can receive the same Price
Accuracy Score. CMS is interested in modifying the methodology to also factor in how often
24
The Challenges of Pharmacy Star Ratings • 99
PDE costs exceeded MPF costs. The frequency of inaccuracy by a contract would be the
percent of claims where PDE cost is greater than MPF cost. The numerator is the number of
claims where PDE cost is greater than MPF cost, and the denominator is the total number of
claims. This ratio is then subtracted from 1 and multiplied by 100 to calculate the Claim
Percentage Score, with 100 as the best possible score and 0 as the worst possible score. The
contract’s accuracy score would be a composite of the Price Accuracy Score and the Claim
Percentage Score.
By capturing the frequency of inaccuracy as well as the magnitude, the measure would better
depict the reliability of a contract’s MPF advertised prices. CMS is aware that while the MPF
display is updated every two weeks, real time pricing, at the point of sale, can change as often
as every day. Some sponsors have expressed concern that in order to perform well in the
Price Accuracy measure, they cannot offer lower prices at point of sale in real time than the
prices are displayed on MPF. We would note that PDEs priced lower than MPF displayed
pricing do not lower a contract’s score in this measure. CMS’ simulation of this proposal found
little change in the range of contracts’ accuracy scores. Other options we explored include
measuring the magnitude of inaccuracy as a percentage cost difference, instead of the current
measure’s use of absolute cost difference. Testing however found this method may overstate
small differences between PDE and MPF costs for low-cost claims. For example, when using
percentage cost differences, a claim with a $2.00 PDE cost and a $1.00 MPF cost would be
considered equally overpriced as a claim with a $200.00 PDE cost and a $100.00 MPF cost.
As noted in the 2016 Call Letter, we propose that these changes are implemented for the
2018 Star Ratings (using 2016 PDE and MPF data). We believe the proposed changes will
greatly improve the Price Accuracy Scores, making them a more comprehensive assessment
of contracts’ price reporting for Part D beneficiaries.
7.
Drug-Drug Interactions (DDI) (Part D Display). The PQA-endorsed DDI measure is currently a
Part D display measure. This measure is defined as the percent of Medicare Part D
beneficiaries who received a prescription for a target medication during the measurement
period and who were dispensed a prescription for a contraindicated medication with or
subsequent to the initial prescription.
The PQA has conducted an extensive review of the drug-drug pairs included in the DDI
measure. They engaged a DDI expert panel convened by the University of Arizona on PQA's
behalf, which completed the review, including a comparison to the DDI list developed for the
Office of the National Coordinator for Health Information Technology (ONC). Next, the Expert
Panel's recommendations will be reviewed by the PQA’s Measure Update Panel for
consideration by the PQA’s Quality Metrics Expert Panel (QMEP). We anticipate that there
will be extensive changes to the DDI measure specifications. We will closely monitor any
updates to this measure, test updated specification when available, and propose changes in
the future for the Part D display measure and patient safety reporting.
8.
Center for Medicare and Medicaid Innovation Model Tests. The CMS Center for Medicare
and Medicaid Innovation has announced the Medicare Advantage Value-Based Insurance
Design (MA-VBID) and the Part D Enhanced MTM model tests. Beginning January 1, 2017, in a
25
100 • AIS’s Management Insight Series
limited number of states, CMS will give MA only, MA-PD or Part D plans participating in these
tests additional flexibilities intended to improve the quality of care and reduce costs in the
Medicare Advantage or Part D programs, respectively. More information about the specific
flexibilities offered in these model tests is available at
https://innovation.cms.gov/initiatives/HPI.
Some stakeholders have expressed to CMS the potential for the improvements in quality in
these models to favorably influence the Star Ratings of contracts with participating plans, as
compared to the performance of those ineligible to participate. The goal is to not penalize
participants or non-participants. As the model tests are implemented, we will closely monitor
performance trends of participating plans across individual measures and determine if any
changes are warranted. We welcome any comments on how to address any potential
differences in performance between participating and non-participating plans.
The Part D plans participating in the Part D Enhanced MTM model test will be waived from
the MTM requirements under Section 1860D–4(c)(2) and 42 CFR 423.153(d) and the Part D
reporting requirements for MTM. However, Part D sponsors will not be waived from
establishing MTM programs in compliance with current requirements and reporting data for
the remaining plans under each Part D contract. Therefore, the MTM Program CMR
Completion Rates will be calculated using available plan-reported data from the remaining
plans under the Part D contract.
H. Measurement and Methodological Enhancements
CMS is committed to continuing to improve the Part C and D Star Ratings by identifying new
measures and methodological enhancements. Feedback or recommendations can help CMS’
continuing analyses, as well as our collaboration with measurement development entities
such as NCQA and PQA. We welcome comments and input on issues not described in earlier
sections.
26
The Challenges of Pharmacy Star Ratings • 101
Appendix
Improvement measures (Part C & D):
Part
C or D
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
D
D
D
D
D
D
D
D
D
D
D
D
D
D
Measure
Breast Cancer Screening
Colorectal Cancer Screening
Annual Flu Vaccine
Improving or Maintaining Physical Health
Improving or Maintaining Mental Health
Monitoring Physical Activity
Adult BMI Assessment
Special Needs Plan (SNP) Care Management
Care for Older Adults – Medication Review
Care for Older Adults – Functional Status Assessment
Care for Older Adults – Pain Assessment
Osteoporosis Management in Women who had a Fracture
Diabetes Care – Eye Exam
Diabetes Care – Kidney Disease Monitoring
Diabetes Care – Blood Sugar Controlled
Controlling Blood Pressure
Rheumatoid Arthritis Management
Reducing the Risk of Falling
Plan All-Cause Readmissions
Getting Needed Care
Getting Appointments and Care Quickly
Customer Service
Rating of Health Care Quality
Rating of Health Plan
Care Coordination
Complaints about the Health Plan
Members Choosing to Leave the Plan
Beneficiary Access and Performance Problems
Health Plan Quality Improvement
Plan Makes Timely Decisions about Appeals
Reviewing Appeals Decisions
Call Center – Foreign Language Interpreter and TTY Availability
Call Center – Foreign Language Interpreter and TTY Availability
Appeals Auto–Forward
Appeals Upheld
Complaints about the Drug Plan
Members Choosing to Leave the Plan
Beneficiary Access and Performance Problems
Drug Plan Quality Improvement
Rating of Drug Plan
Getting Needed Prescription Drugs
MPF Price Accuracy
Medication Adherence for Diabetes Medications
Medication Adherence for Hypertension (RAS antagonists)
Medication Adherence for Cholesterol (Statins)
MTM Program Completion Rate for CMR
Measure Type
Process Measure
Process Measure
Process Measure
Outcome Measure
Outcome Measure
Process Measure
Process Measure
Process Measure
Process Measure
Process Measure
Process Measure
Process Measure
Process Measure
Process Measure
Intermediate Outcome Measure
Intermediate Outcome Measure
Process Measure
Process Measure
Outcome Measure
Patients’ Experience and Complaints Measure
Patients’ Experience and Complaints Measure
Patients’ Experience and Complaints Measure
Patients’ Experience and Complaints Measure
Patients’ Experience and Complaints Measure
Patients’ Experience and Complaints Measure
Patients’ Experience and Complaints Measure
Patients’ Experience and Complaints Measure
Measures Capturing Access
Improvement Measure
Measures Capturing Access
Measures Capturing Access
Measures Capturing Access
Measures Capturing Access
Measures Capturing Access
Measures Capturing Access
Patients’ Experience and Complaints Measure
Patients’ Experience and Complaints Measure
Measures Capturing Access
Improvement Measure
Patients’ Experience and Complaints Measure
Patients’ Experience and Complaints Measure
Process Measure
Intermediate Outcome Measure
Intermediate Outcome Measure
Intermediate Outcome Measure
Process Measure
Weight
1
1
1
3
3
1
1
1
1
1
1
1
1
1
3
3
1
1
3
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
5
1.5
1.5
1
3
3
3
1
Improvement
Measure
Yes
Yes
Yes
No
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
No
Yes
Yes
No
Yes
Yes
Yes
Yes
27
102 • AIS’s Management Insight Series
February 19, 2016
Summary of Comments to the Request for Comments on 2017 Star Ratings and Beyond
On November 12, 2015, CMS released a memo, Request for Comments: Enhancements to the Star
Ratings for 2017 and Beyond, to Part C and D sponsors, stakeholders and advocates. The memo
described CMS’ proposed methodology for the 2017 Star Ratings for Medicare Advantage (MA) and
Prescription Drug Plans (PDP). We received approximately 90 comments representing plan sponsors,
associations, consumer groups, and measurement development organizations. Concerns about and
requests for clarification of specifications have been passed along to measure developers and
stewards. This document provides a summary of the comments received and how we addressed these
comments in the draft 2017 Call Letter.
A. Changes to Measures for 2017
1. Improvement measures (Part C & D).
Summary of Comments: Our proposal to use the 2014 CAHPS measure score (used in 2015 Star
Ratings) as the baseline for the 2017 improvement calculation for that measure if a contract’s
CAHPS measure score moved to very low reliability with the exclusion of the enrollees with less
than 6 months of continuous enrollment for the 2015 survey administration was not supported
by the majority of commenters. The following reasons were cited:

The proposal does not provide an accurate reflection of more recent efforts that may have
been made to impact CAHPS performance.

Sponsors may be disadvantaged by use of dated 2014 CAHPS measure scores.
These commenters were either against using prior year CAHPS data or proposed to exclude the
measure from the improvement measure. About half requested additional clarification.
A small number of additional comments related to the improvement measures included:

Excluding the Call Center measure or applying revisions due to transparency in the reporting
of plan performance or to increase the metric’s sample size or tailor the calls/ make test calls
to test availability of interpreters.

Including either the Part C or the Part D improvement measure to benefit the rating, as well
as reducing the current weight of 5 to 3.

Excluding the MTM measure from the improvement measure.

Considering achievement levels along with grading on the curve for some measures or
receiving the improvement measures above a 3-star rating.
Response: CMS appreciates these concerns. We will use the 2014 CAHPS data only if there is a
significant improvement from 2014 to 2016 when they do not have 2015 data due to very low
reliability. This policy would affect very few contracts, but this would hold contracts harmless
from missing CAHPS data.
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1. Reviewing Appeals Decisions/Appeals Upheld measures (Part C & D).
Summary of Comments: Almost all commenters supported the proposed change to include
appeal cases that are reopened and decided prior to May 1, 2016 in the upheld measure.
Additionally, some commenters suggested:

Extending the time frame to include reopened cases past May 1st.

Removing cases where the IRE obtains new or different information in making a decision,

Providing sponsors with the same reports that CMS receives.

Including reopening cases that occur in the following year’s data.

Accounting for the volume of cases appealed.

Adjusting the threshold for contracts to be excluded based on the contract’s membership .
Response: CMS will move forward with changing the reopening deadline to May 1. CMS will
review other suggestions.
2. Contract Enrollment Data (Part C & D).
Summary of Comments: Most commenters supported the proposed change. Some commenters
did not understand that we used the enrollment in the Special Needs Plans (SNP) Care of Older
Adults (COA) measures only for submissions that do not contain a valid eligible population
element.
Response: Further review by CMS has shown that the proposed change is no longer necessary
due to changes in the way enrollment data are processed over time.
3. Transition from ICD-9 to ICD-10 (Part C & D).
Summary of Comments: Almost all commenters suggested the transition to ICD-10 is
appropriate. Some suggested errors are likely because of the complexity of ICD-10 and that plans
should be held harmless for errors the transition might cause. Many noted NCQA’s guidance and
asked CMS to provide similar guidance and/or to prompt PQA to provide similar guidance. Some
suggested PQA has not anticipated likely challenges, while others worry PQA measures may
require reference to diagnostic codes that PDPs and pharmacies would not be able to access.
Response: PQA measures currently used in Star Ratings do not reference ICD-9 diagnostic codes, so
CMS will clarify that the transition to ICD-10 is not relevant to those measures at this time. CMS
will encourage measure stewards to provide guidance about the transition, if and as needed.
4. Appeals Upheld measure (Part D).
Summary of Comments: Several commenters disagreed with the proposal to again include cases
for beneficiaries enrolled in hospice in this measure.

Sponsors were concerned that data from hospice-enrolled beneficiaries are unreliable and
not reflective of plan performance.
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
Commenters also noted that appeals from members in hospice do not relate to services
rendered by the MA; including those in the calculation may result in a rate which does not
represents the true compliance of the MA.

Additionally commenters are concerned that they may be negatively impacted as they may not
have the visibility to hospice status at the time of the initial review due to the lag in timing of
receipt of hospice indicators and/or retroactive changes to hospice status as sent on the TRR.
A few commenters agreed with the proposed change. One commenter also suggested removing
cases where the IRE obtains new or different information in making a decision and to align time
frames and processes for plan sponsors and IREs to make a more equitable evaluation of plan
sponsor decisions.
Response: As noted in the 2016 Call Letter, this exclusion was only necessary for the 2016
measure as it was based on 2014 data that may have been affected by policy changes in 2014.
CMS policy has not changed since 2014, and there is no reason to exclude hospice appeal cases
from the 2017 Star Rating Appeals Upheld measure.
5. Medication Therapy Management (MTM) Program Completion Rate for Comprehensive
Medication Reviews (CMR) measure (Part D).
Summary of Comments: We received only positive feedback for CMS’ inclusion of more detailed
data during HPMS plan previews. Sponsors supported CMS program audits of MTM, but many
voiced concerns about the specific audit standards to be used, if sponsors could be penalized due
to MTM program variations, and how these audits would differ from the current data validation
activities for plan-reported data.
Response: In the Data Integrity section, CMS will clarify that more information about MTM audit
criteria will be released soon; questions should be directed by email to
[email protected]. We will also clarify that we will not apply any relevant MTM
program audit findings that could demonstrate data integrity issues for sponsors that participate
in the MTM audit during the pilot. We will also clarify that Data Validation standards assess
compliance to CMS’ reporting requirements and technical specifications while CMS program
audits are more comprehensive assessments of the contracts’ MTM programs.
B.
Removal of Measures from Star Ratings
1. Improving Bladder Control (Part C).
Summary of Comments: Most commenters expressed some doubt about the validity, reliability
or utility of this measure and supported removing the measure from Star Ratings, and giving
plans advance notice if the measure were to return to the Star Ratings. Some plans thought
expecting improvement in bladder control unrealistic for their (Special Needs) population or not
meaningful given the other conditions (e.g., receiving dialysis for kidney failure) their enrollees
may have. Many asked for clarification if CMS intends to return the measure to Star Ratings in
2018, which would be the normal course of action. Some stated they would prefer this measure
were dropped entirely. Some commenters thought the focus of the measure should move
beyond receipt of treatment, while others preferred the focus remains on receipt of treatment.
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There was also confusion about whether this measure was a cross-sectional measure or a twoyear change score.
Response: CMS will clarify that the HEDIS measures derived from the HOS survey, like Improving
Bladder Control, are cross-sectional and do not require comparison of responses from the same
cohort two years later. CMS will forward comments to the measure steward, NCQA.
2. High Risk Medication (Part D).
Summary of Comments: A majority of the commenters supported removing the High Risk
Medication (HRM) measure from Star Ratings and moving to the display measures for 2017. Over
one-quarter of the commenters supported removal of the HRM measure from Star Ratings, but
for 2018 or beyond, noting that plan sponsors have made significant investments to improve
HRM performance. Few commenters did not support this change. A number of commenters
recommended sufficient lead time before future updates to the measure specifications are
implemented to consider formulary and bid timelines. Some commenters suggested exclusion of
hospice patients from the measure calculation.
Response: CMS will move forward with the proposal to remove the HRM measure from the Star
Ratings and move to the display measures for 2017. We shared specification comments with the
PQA.
The timing of implementation of updates to the measure specifications in the future will provide
sufficient lead time ahead of the formulary and bid deadlines.
C.
Data Integrity
Summary of Comments: Many supported the development of program audits of Part D sponsors’
MTM programs, and voiced similar concerns as described in section A6 above. A few
commenters complained about CMS policy to reduce measures due to Data Validation failures at
an element level, or in general that this policy is unwarranted, and that reductions to 1 star
should only be made if sponsors intentionally made data errors. One commenter suggested that
if CMS or its contractors made errors, then affected sponsors should be assigned 5 stars, and/or
be able to reuse the prior year’s data.
Response: As noted in A6’s response, we will clarify that information about the MTM audit
criteria will be released soon, and that findings identified during pilots of the MTM audit criteria
would not be used. We will clarify that reductions are based on systemic failures. A reporting
section’s overall DV score may be high enough to consider the contract has passed, but specific
element-level failures show inaccurate data that would be used in the measure calculation. For
example, if the Data Validation found errors in the numbers of beneficiaries enrolled in the MTM,
or receiving CMR – but the overall MTM DV score was above 95, CMS would still have concerns
about the MTM CMR numerator and denominator.
CMS and its contractors also share in the responsibility for accurate collection and calculation of
Star Ratings. Each year, CMS reviews the quality of the data across all measures, variation among
organizations and sponsors, and the accuracy and validity of measures before making a final
determination about inclusion in the Star Ratings. Rarely, as a result of these reviews, CMS has
needed to exclude specific measures from the Star Ratings because systemic errors were found in
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the data; these errors may not have been caused by sponsors’ processes or actions. While CMS
considers all options prior to exclusion of a measure, it would be incorrect to infer contracts’
performances from historical data, or reuse prior years’ data as individual contract measure
performance changes from year to year. This would also unfairly disadvantage contracts, as use
of prior year scores may result in lower Star Ratings, versus if the measure was excluded. Using
data from a prior collection year for some but not all contracts (i.e., holding contracts harmless
for downward adjustment), or assigning 5 stars for all contracts could also appear arbitrary.
D. Impact of Socio-economic and Disability Status on Star Ratings
Summary of Comments: There was widespread appreciation of the attention and careful
examination of the LIS/DE/disabled effects that CMS has completed at this time and continues to
research. Respondents agreed with the overall approach and focus of the research conducted.
Many commenters applauded our efforts and were grateful for the acknowledgement of the
issue and the development of the two proposed interim analytical adjustments set forth in the
Request for Comments: a Categorical Adjustment Index or Indirect Standardization. Respondents
valued the numerous opportunities afforded for stakeholder input. In addition, many
commenters supported the engagement of the measure stewards and look to their research as
part of the answer to the long-term solution to address any sensitivity of the Star Ratings
measures to the enrollment of beneficiaries. Further, several re spondents complimented CMS for
maintaining the integrity of the core of the Star Ratings Program and the transparent manner in
which CMS approached the work related to the issue.
Many respondents mentioned the value of the information provided during the December 3rd
User Call, however, some still desired additional clarity of the methodologies. Most respondents
requested simulated results so that sponsors could better understand the methodologies
employed for the analytical adjustments and the impact of the adjustments on their scores.
Further, numerous respondents requested the additional details of the interim adjustments and
simulation results in advance of the draft 2017 Call Letter.
Overall, the reaction to the proposed analytical adjustments was mix ed. The comments received
did indicate a need for further outreach so that stakeholders would be comfortable supporting
one of the options proposed to address the LIS/DE/ disabled effect. Many respondents felt they
were unable to state a preference of one method over the other until they were able to review
simulation results. Of the respondents that did express a preference to a single analytical
adjustment, more commenters preferred the Categorical Adjustment Index (CAI) over the
method of Indirect Standardization (IS).
There was a request for the release of any research that focused on PDPs. Some commenters
expressed a need for details and discussion on the application of the analytical adjustments for
PDPs including the availability of the disability status of beneficiaries. Some respondents
expressed the need for immediate action and financial relief for plans that served vulnerable
populations. Several commenters wanted the interim adjustments to result in meaningful
differences in the ratings. Respondents were unsure of the mechanics of the application of the
adjustments for plans where beneficiaries were exclusively LIS/DE and others, requested the
minimum proportion of beneficiaries in the subgroups of LIS/DE and/or disabled status to qualify
for an adjustment. There were inquiries regarding the stability of the adjustments over time, the
details of operationalizing the methods, and the strengths and weaknesses of each method.
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There were a number of respondents that encouraged CMS to wait rather than to move forward
with either of the proposed interim adjustments. Some respondents who preferred a delay
referenced either looking to the work of the measure developers or the release of the Assistant
Secretary of Planning and Evaluation’s (ASPE) report due in the upcoming year as required by the
IMPACT Act. One commenter mentioned the need to ‘proceed with caution to avoid either
creating a double standard of care or lowering standards for chronic disease management.’ A
respondent questioned the value of an interim adjustment given the increase in the
administrative burden for both CMS and sponsors. Another reason cited for waiting for
implementation was that the proposed analytical adjustments did not adequately addre ss the
issue. In terms of the timing for a policy response, one commenter suggested optional
participation in 2017, while another suggested a two-year delay in implementation.
Numerous commenters believed that CMS should further investigate or control for factors
beyond LIS/DE and/or disabled status. The attributes that respondents mentioned for additional
examination and/or consideration included: age, race, health literacy, household income,
homelessness, hunger, transportation challenges, low literacy, unemployment, number of
providers, risk scores, medical complexity, chronic conditions, and geographical or regional
disparities. Some respondents mentioned that risk adjustment of quality measures would
penalize plans that deliver high quality of care irrespective of the population served.
There were a limited number of comments to help guide the selection of the measures to be
adjusted. Some commenters mentioned that only measures that revealed a meaningful withincontract difference in our research should be candidates for adjustment. Other commenters
believed all Star Ratings measures, regardless of whether they are already adjusted, should be
included as candidates for adjustment. A respondent did note that if all measures were adjusted,
it would still result in only a small proportion of the measures in the program. There was a
comment that stated that any risk adjustment must be rooted in evidence and not disincentivize
plans from enrolling vulnerable beneficiaries. Another respondent believed that some risk
adjustment done prudently is better than none. One commenter would not support adjusting for
medication adherence measures and believed that LIS beneficiaries in their plan do better and
thus, the plan would be negatively impacted by such an adjustment. There were several
commenters inquiring about the method of reporting – hybrid or census – and its impact on the
interim adjustment methodologies.
Some commenters expressed the need for accounting for LIS-look-alikes in the adjustments.
Respondents believe that there are beneficiaries that do not quality for LIS but share common
characteristics with LIS beneficiaries, such as community factors and income levels, and may in
fact experience worse outcomes due to their non-LIS status. The look-alikes therefore impact the
within-contract differences due to the modeling that uses a dichotomous variable for LIS status.
Many of the general comments related to the two options CMS is exploring for interim analytical
adjustments expressed concern about the possible bias an adjustment may introduce in the Star
Ratings program. A respondent expressed the need to capitalize on the heterogeneity of the
data. One commenter specifically discussed the importance of maintaining the quality signal that
the Star Ratings provide. To compensate for the perceived advantage plans with a high
percentage of LIS/DE/disabled enrollees may realize, many commenters supported a hold harmless provision. (Such a provision would ultimately result in only positive adjustments to the
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Overall and Summary Star Ratings.) Several commenters expressed concern regarding the use of
the pre-adjusted cut points for the conversion of the adjusted measure score to a measure -level
Star Rating and requested justification for this aspect of the methodology. One commenter felt
that mixing unadjusted and adjusted measure scores and stars would result in apple to orange
comparisons. A respondent asked for simulations using both adjusted and unadjusted cut points.
Numerous respondents believed that the adjustments would increase the complexity of the Star
Ratings and impinge on its transparency. In addition, there was concern about the possibility of a
shortened plan-preview period. Several commenters suggested an additional plan preview
period if CMS were to move forward with one of the interim adjustments. A number of
commenters wanted justification of the use of unadjusted measure cut points for the conversion
of the adjusted measures score to measure-level Star Ratings. Some commenters were unsure
how the adjustment would be applied to plans that were almost exclusively comprised of Dual
beneficiaries. Several respondents were unsure when the proposed adjustment would be
applied in relationship to the Reward factor. Further, several comments inquired about which
measures scores would be used for determining the integration factor – adjusted or unadjusted
measures scores.
Many of the comments received that were specific to the CAI were related to the number of
initial and final adjustment categories employed in the method. Commenters were concerned
about the collapsing of the initial groups and final adjustment categories and the impact of the
groupings on the adjustments and possible misclassification. Respondents who preferred CAI
over IS cited reasons such as: easier to understand, similarity to CAHPS, greater transparency,
ability to have the adjustment factors in advance of the plan preview, flexibility and accuracy of
the method. A number of commenters suggested using additional covariates in the model such as
race, gender, and community factors. Some commenters wanted to know more about the
stability of the adjustment factors over time.
A number of the comments received that were specific to IS noted the increased complexity of
the method. Many commenters expressed concern about the validation needed if the method
was employed and the impact on the plan preview period. Some respondents felt the
adjustment was more tailored to their specific plan and perhaps, more accurate. Several
commenters believe geographic comparisons instead of national comparisons should be used for
the standardization process. There were a number of comments regarding the determination of
the national means and the impact of its value on measures when the information is calculated
based on mixed reporting methods (census or hybrid).
There were a limited number of responses related to the additional response to address lack of
an LIS indicator for enrollees in Puerto Rico. Overall, there was appreciation to CMS for
addressing the unique circumstances and challenges in Puerto Rico. Respondents expressed
concern about the accuracy of the proposed LIS Indicator used for adjustment based on the
relationship developed using mainland data and modifying it for use in Puerto Rico. Further, the
commenters suggested an adjustment of the medication adherence measures for contracts
operating in Puerto Rico.
Response: While the measure stewards are undertaking a comprehensive review of their
measures used in the Star Ratings Program and ASPE is continuing its work under the IMPACT
Act, CMS is proposing to implement the CAI as an interim analytical adjustment for 2017 Star
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Ratings to take into account the impact of LIS/DE and/or disability status on Star Ratings
measures. The CAI is a factor that would be added or subtracted to a contract’s Overall and/or
Summary Star Rating to adjust for the average within-contract disparity. The proposed interim
solution adheres to certain core CMS principles, such as not permitting a lower standard of care
for vulnerable beneficiaries, proposing adjustments that reflect the actual magnitude of the
differences observed in the data, and recognizing the need for options that are both transparent
and feasible for the plans and CMS to implement. The proposal relies on an adjustment external
to the measure specifications, as well as, maintaining the integrity of the Star Ratings and the
core of its methodology. For contracts operating in Puerto Rico, we plan to proceed with
estimating an LIS Indicator, while other data sources continue to be explored.
E.
2017 CMS Display Measures
1. Timely Receipt of Case Files for Appeals (Part D) & Timely Effectuation of Appeals (Part D).
Summary of Comments: All commenters agreed to change the time frame of the Timely Receipt
of Case Files for Appeals (Part D) & Timely Effectuation of Appeals (Part D) from the first six
months of the current year to entire twelve months of the previous year.
Response: CMS will move forward with making this change.
2. Medication Reconciliation Post Discharge (Part C).
Summary of Comments: One third of the commenters were supportive of this measure being
included on the 2017 display page and 2018 Star Ratings. However, almost half of the
commenters had concerns about the timing of the measure and requested it delayed by either
leaving it on the display page for at least two years or delay it on the display page and Star
Ratings for at least a year. Many commenters wanted more clarification on the measure,
specifically on the roles to complete the measure (i.e., social workers, pharmacists), data
collection, and clarification or changes to technical specifications such as eligible members
included in the denominator. There were also a few comments questioning the measure’s
construction, assumptions and validity. Examples included difficulty in collecting accurate
information that medications were reconciled post discharge for D-SNP population, physicians
coding accurately and addressing where members are utilizing multiple providers. A few thought
the measure did not differ much from readmissions or the existent MRP measure required for
physicians. Two comments requested benchmarking and cut point proposals including case mix
and SES adjustments.
Response: CMS is planning to proceed to include this measure as part of the 2017 display page
and the 2018 Star Ratings. This measure has been collected by SNPs for a number of years.
Detailed specifications are available in HEDIS 2016, volume 2. We will monitor the 2016 data
submissions for any data issues and modify our plans if needed.
3. Hospitalizations for Potentially Preventable Complications (Part C).
Summary of Comments: Almost all commenters were not supportive of the timing of the
measure. They recommended it be delayed from the display page and Star Ratings or have it
remain on display page for an additional year or two. Some commenters wanted information
such as specifically what the ambulatory sensitive conditions are for this measure or requested
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narrowing the scope on ambulatory sensitive conditions. A few of the comments had validity
concerns about the measure specifically about the risk adjustment. One commenter had
concerns with comparing the ESRD population with a general Medicare Advantage population in
this measure.
Response: CMS is planning to proceed to include this measure as part of the 2017 display page
and the 2018 Star Ratings. Detailed specifications are available in HEDIS 2016, volume 2. We will
monitor the 2016 data submissions for any data issues and modify our plans if needed.
4. Statin Therapy for Patients with Cardiovascular Disease (Part C).
Summary of Comments: Almost all comments were negative, citing concerns with the measure’s
validity. Some noted a general lack of consensus with the 2013 ACC/AHA blood cholesterol
guidelines, with others identifying detailed methodological issues. Several commenters note d
that the measure does not account for members for whom statins are contraindicated, not well
tolerated, not recommended, or refused. Others stated the measure does not account for
alternate therapies or a wider range of statin dosages. A few commenters recommended moving
this to a Part D measure like the related Statin Use in Persons with Diabete s (SUPD) measure and
similarly excluding hospice beneficiaries. While a few agreed with the age ranges, just as many
disagreed. Some commenters requested more specifics from CMS for the diagnostic codes and
for “high or moderate statin.” Because of concerns with the measure’s validity, along with plans
having limited time to implement quality improvement, several asked CMS to omit from the
display page in 2017. Many others asked for the measure to stay on the display page for at least
two years and/or to hold off reporting measure in the 2018 Star Ratings. Very few commenters
agreed with CMS on this measure.
Response: Comments have been shared with NCQA. We are aware that treatments for
cardiovascular disease are evolving and we will continue to monitor best practices for standards
of care. We will keep the measure on the display page for an additional year to gain more
experience with new treatment guidelines and metric and then add to the 2019 Star Ratings.
5. Asthma Measures (Part C).
Summary of Comments: The majority of commenters argued against adding the two proposed
asthma measures as 2017 Star Rating display measures or as Star Rating measures in the future.
These two measures expand NCQA’s current asthma measures to include older adults and are
defined on the basis of medication utilization.
The reasons against included: 1) belief that these are inappropriate measures for the majority of
the Medicare population who, being ages 65 and over, are more likely to receive a COPD or other
pulmonary disease diagnosis rather than an asthma diagnosis and comments argue f or focusing
efforts on areas that impact greater numbers of members; 2) concern about the difficulty for
physicians to distinguish asthma from COPD in the senior population; 3) a few recent studies have
indicated that medication management for people with asthma has not been shown to correlate
with improved health outcomes, lower costs or lower utilization; 4) concern with the measures
being constructed on the basis of medication utilization rather than on diagnosis given that some
of the same medications are used for both asthma and COPD thus drug claims do not provide an
accurate picture of which members have persistent asthma; 5) difficulty distinguishing between
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‘seasonal’ versus ‘persistent’ asthma; 6) focusing on patients remaining on medications ‘during
the treatment period through the end of measurement year’ requires defining an appropriate
period of treatment for a condition which exhibits seasonality; 7) measures are not in line with
NIH recommendations for step-down controller therapy or management of patients who exhibit
seasonal variation in asthma symptoms; and 8) concern that for a population of persons often
with multiple health conditions (seniors and the disabled), there are considerations of possible
adverse medical consequences due to medication interactions.
A number of commenters requested CMS delay the addition of these 2 asthma measures for a
few years until: 1) the measures are fully specified; 2) there is some evidence that asthma
medication management is shown to correlate with improved health outcomes; 3) physicians are
more experienced using the ICD-10 coding system which is thought to better delineate asthma
from COPD; and 4) NCQA has fully specified, vetted and published results of these measures.
The only commenters arguing for the inclusion of the proposed asthma measures were
pharmaceutical organizations.
Lastly, a number of comments argued that those plans which serve large numbers of the under
age 65 Medicare population, the dual eligibles, would be further burdened by the inclusion of
these measures due to socioeconomic factors which cannot be controlled but impact the
frequency and severity of asthma events.
Response: CMS appreciates the comments received on this section. CMS shared the comments
with NCQA and will continue to monitor development of these measures. CMS is planning to
include these on the 2017 and possibly 2018 display page and will consider these for inclusion in
Star Ratings for future years.
6. Statin Use in Persons with Diabetes (SUPD) (Part D).
Summary of Comments: Comments similar to those received for the Part C Statin Therapy for
Patients with Cardiovascular Disease measure were submitted. There was mixed support to add
the SUPD measure to the 2017 display page and to the 2018 Star Ratings. While there was
support for this measure in general, a majority of commenters cited concerns with the measure’s
validity, or asked for the measure to stay on the display page for at least two years to gain
experience or until methodological issues could be resolved. Several commenters noted that the
measure does not account for members for whom statins are contraindicated, not well tolerated,
not recommended, or refused. Others stated that the specifications should account for or
exclude beneficiaries taking PCSK-9 therapies. Several commenters were concerned that
prescription claims, not diagnosis codes, are used to determine the presence of diabetes,
questioned the age criteria, or recommended excluding ESRD patients.
Response: Comments regarding the measure’s technical specifications have been shared with
the PQA. We will consider keeping the measure on the display page for an additional year to gain
more experience with new treatment guidelines and metric and then add to the 2019 Star
Ratings.
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Forecasting to 2018 and Beyond
F.
New Measures:
1. Care Coordination Measures (Part C).
Summary of Comments: Support for new care coordination measures was mostly positive,
although several commenters recommended against measures that involve chart review because
of increased administrative cost. A few commenters requested more detail and for CMS to put
specific proposed measures out for public comment before they become display measures. A
couple of commenters recommended that CMS take into account mental health issues and
dual/LIS/disabilities and consider a population-based approach. A few mentioned that measures
should consider multiple provider types or suggested that CMS use existing reporting
requirements related to care coordination. Several encouraged CMS to look at care coordination
measures that are linked to improved outcomes. Some stated that it is critical for CMS to
validate encounter data to ensure they are complete and accurate before relying on them.
Response: CMS appreciates the comments received on this section. We shared comments with
contractors developing care coordination measures and will continue to provide updates to the
industry as the work progresses.
2. Depression Measures (Part C).
Summary of Comments: Many commenters expressed concerns about privacy laws, as well as
readiness of electronic systems to transmit clinical data from behavioral health providers.
Several suggested CMS should first focus on depression screening measures before including a
depression outcome measure. A few requested that other depression or mental health screening
tools be included. A couple expressed concern that the 6 months measurement window is too
short to demonstrate impact. Several stated that the measure should be on display for several
years following HEDIS approval.
Response: CMS shared comments received on this topic with NCQA and will continue to monitor
development of the measure. NCQA is also working on a Depression Screening and Follow-Up
measure which may be proposed for HEDIS in the future.
3. Appropriate Pain Management (Part C).
Summary of Comments: NCQA is exploring opportunities to develop a new measure focusing on
appropriate pain management. The intent is to assess the quality of pain management and
treatment.
Commenters expressed appreciation for the exploration of this important topic. However,
commenters stressed that the experience of pain is subjective and varies across individuals,
conditions, and stages of a condition. Commenters stressed that these considerations need to be
addressed in specifying an appropriate pain management measure so that valid comparisons can
be made across plans and member populations.
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Commenters requested full measure specification to enable plans to provide meaningful
comment. Further, that if a measure is created and implemented, it remain on the display page
for at least 2 years.
One commenter suggested that a standardized pain screening tool be developed / employed to
assess, document, and monitor the experience of pain. Another commenter suggested that in
terms of pain control, the measure address not only medication use but also alternative
treatments for managing pain. Lastly, two commenters indicated that appropriate pain
management can be at odds with controlling/monitoring for opiate use.
Response: CMS appreciates the comments received on this section. CMS shared the comments
with NCQA and will continue to monitor development of these measures.
4. Use of Opioids from Multiple Providers or at High Dosage in Persons without Cancer (Part D).
Summary of Comments: There was general agreement on the importance of resolving opioid
overutilization and not adding the measures to the Star Ratings at this time. While there was
some support to add these three PQA opioid overutilization measures to the 2018 Part D display
page (using 2016 data), most commenters were opposed or expressed concerns with the
proposal. Concerns about the proposal included: 1) neither clinical guidelines nor experience
support the validity of the measures, 2) the measures do not measure and will not support plan
performance, particularly #1 and #2, 3) more detailed descriptions of the measure specifications
are needed in order to consider support, 4) some sponsors will be disadvantaged based upon the
characteristics of their enrollees (e.g., high numbers of disabled enrollees), 5) Part D sponsors
have limited ability to influence prescriber behavior, and 6) if the measures are not suitable for
Star Ratings, they should not be display measures.
Response: Due to concerns raised by commenters, CMS will implement the three PQA opioid
overutilization measures as Patient Safety measures, not display measures, for one year to gain
experience with the measures and pending new guidelines (e.g., from CDC) and current research
on opioid prescribing, overutilization, and interventions. We shared specification comments with
the PQA.
5. Antipsychotic Use in Persons with Dementia (APD) (Part D).
Summary of Comments: There was general agreement that this measure addresses an important
issue. Over half of the commenters agreed with the proposal, and one -third were neutral.
Changes to the proposal were suggested by two commenters, and over two-thirds of the
commenters noted specific concerns, including 1) lack of access to diagnosis data required for the
measure, 2) limitations on the ability of sponsors to intervene because antipsychotic drugs have
protected class status, 3) a desire to review the complete measure specifications, and 4) this
measure is primarily associated with nursing homes, the nursing home quality rating reporting
system includes a related measure, and the facilities are responsible, not plans.
Response: CMS will proceed as proposed. CMS will include a link to the CMS.gov webpage for an
APD measure analysis report that provides detailed specifications and testing results. We shared
specification comments with the PQA.
12
114 • AIS’s Management Insight Series
February 19, 2016
G. Changes to Existing Star Ratings and Display Measures and Potential Future Changes:
1. Colorectal Cancer Screening (Part C).
Summary of Comments: This measure is under consideration for revision. The USPSTF will
release its revised guidelines in late 2016. At that time, NCQA will consider revising the Star
Rating Colorectal Cancer Screening HEDIS measure.
The comments supported waiting for the USPSTF’s final evidence -based recommendations for
colorectal cancer screening methods. The commenters stressed the need for plans to be
provided, in advance of implementing any changes to the Star Ratings, additional detail of
specification changes to allow stakeholders to provide meaningful comment. The comments also
stressed the need for advance notice of the timeline for implementing changes so as to educate
providers and beneficiaries. It was suggested that any revised measure not be implemented until
the 2019 Star Rating year.
One commenter requested there be no change to the measure’s age limits. One commenter
requested the measure be broken down by age groups. Another commenter stressed that
universal colorectal cancer screening is not supported for persons with ESRD.
Response: CMS appreciates the comments received on this section. CMS shared the comments
with NCQA and will continue to monitor development of these measures.
2. Fall Risk Management (Part C).
Summary of Comments: Commenters were equally split between supportive, negative and
neutral comments. Many commenters would like more time for research or for plans to prepare
for changes. Some commenters would prefer CMS not use measures derived from surveys of
beneficiaries. A large number of commenters suggested that while it was appropriate to update
specifications to reflect changing guidelines, there is still not enough evidence to consider vitamin
D as a treatment to reduce falls. Others commented that specification changes can change the
focus of the measure and “eliminate its principal focus of prevention of falls among members by
eliminating physical barriers.” A few Special Needs Plans serving dialysis patients expressed
concerns that vitamin D is not appropriate treatment for patients also getting dialysis (it risks
leading to hypercalcemia) and therefore some exclusion is needed for those plans or for most of
their enrollees.
Response: CMS shared these comments to NCQA and highlighted the concerns commenters
have about the evidence for use of vitamin D as a treatment, as well as the concern that Special
Needs Plans that focus on End Stage Renal Disease may not have enrollees appropriate for this
measure.
3. Pneumococcal Vaccination Status for Older Adults (Part C).
Summary of Comments: Almost all comments were negative, citing concerns that the measure
relies on Medicare CAHPS survey data. Self-reports, according to commenters, are unreliable
because members may not recall getting a specific vaccine, especially if administered a long time
ago. Instead, most commenters recommended CMS use claims data instead. Still, a few
cautioned that claims data is imperfect and ask for lower cut points. Some plans asked CMS to
13
The Challenges of Pharmacy Star Ratings • 115
February 19, 2016
keep the measure as display and not add to Star Ratings until tested further, while a
pharmaceutical company encouraged CMS to include it the Star Ratings.
Response: We appreciate the concerns of commenters. We will monitor data during the display
period for issues with validity.
4. CAHPS measures (Part C & D).
Summary of Comments: Commenters were mostly positive about the proposed change to the
5.0 version of CAHPS. Several requested that the CAHPS survey be shortened in order to increase
response rates and stated that questions should focus on questions related to consumer
satisfaction. A few commenters expressed concern with CAHPS in general as they feel it is
subjective. One expressed concern about benchmark rate changes and CAHPS scores.
Comments on the sampling proposal were mixed.
Response: Patient experience surveys such as CAHPS focus on how patients experienced or
perceived key aspects of their care, not how satisfied they were with their care. CAHPS surveys
follow scientific principles in survey design and development. The surveys are designed to reliably
assess the experiences of a large sample of patients. They use standardized questions and data
collection protocols to ensure that information can be compared across healthcare settings.
CAHPS surveys are developed with broad stakeholder input, including a public solicitation of
measures and a technical expert panel, and the opportunity for anyone to comment on the
survey through multiple public comments period through the Federal Register. Regarding survey
length, analyses suggest that the relationship between survey length and response rate for the
MA CAHPS survey is only weakly negative. Specifically, the use of 12 supplemental items as
compared to none was associated with a 2.5% reduction in response rate (Beckett et al, Public
Opinion Quarterly, in press) 1.
To examine the impact of decreasing benchmarks on CAHPS measure scores, we conducted an
analysis of changes in CAHPS stars with changes in proxy standardized MA benchmarks at the
contract level. The benchmarks were developed as an average of plan-level BPT benchmarks
weighted by July enrollment for each year. Analyses on the impact on CAHPS scores did not find
a systematic relationship between CAHPS scores and declining benchmarks.
The table below includes a comparison of contracts changing their CAHPS measure star rating
from 2014 to 2015 comparing the quartile with the biggest drop in benchmarks ($81 or more)
with the quartile with the smallest changes in benchmarks (+$30 to -$47):
1
Beckett MB, Elliott MN, Gaillot S, Haas A, Dembosky JW, Giordano LA, Brown J. (In Press) “Establishing limits for
supplemental items on a standardized national survey.” Public Opinion Quarterly
14
116 • AIS’s Management Insight Series
February 19, 2016
Measure
Care Coordination
Quartile with largest drop in
benchmarks (% increasing
stars/% staying same/%
decreasing)
23%/51%/26%
Quartile with smallest
change in benchmarks (%
increasing stars/% staying
the same/% decreasing)
24%/51%/25%
Customer Service
Getting Appointments and Care Quickly
Getting Needed Care
Rating of Health Care Quality
22%/45%/33%
21%/61%/18%
23%/46%/31%
22%/54%/24%
30%/45%/25%
11%/68%/21%
23%/48%/29%
9%/69%/21%
Rating of Health Plan
Getting Needed Prescription Drugs
Rating of Drug Plan
18%/60%/22%
18%/45%/36%
21%/57%/21%
20%/56%/24%
20%/51%/29%
24%/59%/17%
5. Medication Adherence for Hypertension (RAS Antagonists) (Part D).
Summary of Comments: All commenters supported the proposed exclusion. One commenter
requested we exclude dual-eligible beneficiaries that have $0 copay. Another requested we
emphasize ESRD patients are excluded. A few requested CMS clarify which year this change
applies; two requested CMS set upper age limits for all 3 medication adherence measures.
Response: We will proceed as planned. We will clarify that this exclusion will be applied for the
2017 Star Ratings. We shared specification change suggestions with the PQA.
6. MPF Price Accuracy (Part D).
Summary of Comments: About one-quarter of commenters agreed with the proposed changes,
and the remaining were neutral or opposed. The most common comments included:

Broaden the cut points because the measure scores are tightly clustered resulting in
insignificant/negligible differences and therefore do not inform beneficiaries of any impactful
differences among the plans.

Retire or move the measure to the display page due to high scores.

Change the methodology for scoring this measure.

Clarify CMS’ decision making process that led to this change, and provide details of our
analysis of this change.

Provide best practices for how to achieve a high score.

Move to display page for one year due to methodology changes.
Other commenters commented that the different frequency of point of sale and MPF pricing
updates is a barrier to improving plan performance.
Also, if the measure has new scoring
methodology, commenters suggested temporarily removing the measure from the Improvement
15
The Challenges of Pharmacy Star Ratings • 117
February 19, 2016
Measure. Lastly, some commenters would like to be able to access detail reports of their scores
earlier and more frequently.
Technical comments included 1) the amount of difference between PDE prices and MPF prices
that constitute an inaccuracy should be broadened to more than one half of one cent, 2) only the
Formulary Reference File NDCs should be used when selecting the PDE claims that are being
measured because pricing for the same drug, strength, and dosage form can vary from
manufacturer to manufacturer, and 3) the “Patient Residence Code” should be used to determine
the retail claims from the PDEs.
Response: We will proceed with these changes as planned. CMS’ simulations found that the
accuracy scores using the new methodology were generally similar to scores calculated using the
current methodology. This measure will continue to be excluded from the Improvement
Measure. CMS uses accepted mathematical algorithms and practices to formulate the thresholds
(cut points) required to earn a particular rating. Currently the majority of contracts receive high
Accuracy scores. We do not believe options to further differentiate plans’ performances would
be supported by sponsors, as this could entail identifying price differences smaller than one half
of one cent. We continue to be open to other changes that will improve the impact of this
measure.
7. Drug-Drug Interactions (DDI) (Part D Display).
Summary of Comments: Most commenters were neutral, while a few voiced concern about the
implementation of future changes to PQA specifications including the timing of adoption by CMS
for the display measure.
Response: We will proceed as planned. Any future changes will be announced via the annual
Request for Comments and draft Call Letter process to provide advance notice.
8. Center for Medicare and Medicaid Innovation Model Tests.
Summary of Comments: Commenters appreciated CMS’ attention to the potential for
improvements in quality in the MA-VBID and Part D Enhanced MTM models to favorably
influence Star Ratings for contracts with participating plans and expressed a desire for contracts
not to be disadvantaged for either participating or not participating. Several requested that CMS
provide additional information about impact on plans. Several mentioned that only some
contracts are permitted to participate in the models, a few suggested that SNPs and territories
(e.g., Puerto Rico) should be allowed to participate. Some suggested that waiving MTM reporting
requirements for participating plans could impact cut points for this measure, and a few
requested that CMS suspend the MTM Star Rating during the model test years.
Response: CMS will closely monitor performance of contracts participating in the model to
evaluate any effect on Star Ratings. Our goal is to ensure that contracts are not penalized. Some
possible options are to establish different cut points for model participants and to case mix adjust
scores for the purpose of determining cut points. We will provide more information to
stakeholders as it is available and continue to engage with stakeholders on the impact of these
models.
16
118 • AIS’s Management Insight Series
February 19, 2016
H. Measurement and Methodological Enhancements.
Summary of Comments: Comments ranged in topics from general to measure-specific. They
included comments about specific Star Rating changes and measures, cut points, development of
outcome measures, the Reward Factor, as well as display measures.
Response: CMS appreciates all comments and will explore the feasibility of specific proposals for
possible future implementation. For example, we will continue to look at the issue of whether to
conduct call center monitoring in languages proportional to the prevalence of each language in
the 65 and older U.S. population.
17
The Challenges of Pharmacy Star Ratings • 119
2017 Part C & D Star Ratings Measures
2017
ID
C01
C02
C03
C04
C05
C06
C07
C08
C09
C10
C11
C12
C13
C14
C15
C16
C17
C18
C19
C20
C21
C22
C23
C24
C25
C26
C27
C28
C29
C30
C31
C32
2016
ID
C01
C02
C03
C04
C05
C06
C07
C08
C09
C10
C11
C12
C13
C14
C15
C16
C17
C18
C19
C20
C21
C22
C23
C24
C25
C26
C27
C28
C29
C30
C31
C32
Breast Cancer Screening
Colorectal Cancer Screening
Annual Flu Vaccine
Improving or Maintaining Physical Health
Improving or Maintaining Mental Health
Monitoring Physical Activity
Adult BMI Assessment
Special Needs Plan (SNP) Care Management
Care for Older Adults – Medication Review
Care for Older Adults – Functional Status Assessment
Care for Older Adults – Pain Assessment
Osteoporosis Management in Women who had a Fracture
Diabetes Care – Eye Exam
Diabetes Care – Kidney Disease Monitoring
Diabetes Care – Blood Sugar Controlled
Controlling Blood Pressure
Rheumatoid Arthritis Management
Reducing the Risk of Falling
Plan All-Cause Readmissions
Getting Needed Care
Getting Appointments and Care Quickly
Customer Service
Rating of Health Care Quality
Rating of Health Plan
Care Coordination
Complaints about the Health Plan
Members Choosing to Leave the Plan
Beneficiary Access and Performance Problems
Health Plan Quality Improvement
Plan Makes Timely Decisions about Appeals
Reviewing Appeals Decisions
Call Center – Foreign Language Interpreter and TTY Availability
HEDIS
HEDIS
CAHPS
HOS
HOS
HEDIS / HOS
HEDIS
Part C Plan Reporting
HEDIS
HEDIS
HEDIS
HEDIS
HEDIS
HEDIS
HEDIS
HEDIS
HEDIS
HEDIS / HOS
HEDIS
CAHPS
CAHPS
CAHPS
CAHPS
CAHPS
CAHPS
CTM
MBDSS
CMS Administrative Data
Star Ratings
IRE
IRE
Call Center
D01
D01
Call Center – Foreign Language Interpreter and TTY Availability
Call Center
D02
D03
D04
D05
D06
D07
D08
D09
D10
D11
D12
D13
D14
D15
D02
D03
D04
D05
D06
D07
D08
D09
D10
D11
D12
D13
D14
D15
Appeals Auto–Forward
Appeals Upheld
Complaints about the Drug Plan
Members Choosing to Leave the Plan
Beneficiary Access and Performance Problems
Drug Plan Quality Improvement
Rating of Drug Plan
Getting Needed Prescription Drugs
MPF Price Accuracy
High Risk Medication
Medication Adherence for Diabetes Medications
Medication Adherence for Hypertension (RAS antagonists)
Medication Adherence for Cholesterol (Statins)
MTM Program Completion Rate for CMR
Measure
Primary Data Source
Improvement
Measure Weight
Yes
1
Yes
1
Yes
1
No
3
No
3
Yes
1
Yes
1
Yes
1
Yes
1
Yes
1
Yes
1
Yes
1
Yes
1
Yes
1
Yes
3
Yes
3
Yes
1
Yes
1
Yes
3
Yes
1.5
Yes
1.5
Yes
1.5
Yes
1.5
Yes
1.5
Yes
1.5
Yes
1.5
Yes
1.5
No
1.5
No
5
Yes
1.5
Yes
1.5
Yes
1.5
Yes
1.5
IRE
Yes
1.5
IRE
Yes
1.5
CTM
Yes
1.5
MBDSS
Yes
1.5
CMS Administrative Data
No
1.5
Star Ratings
No
5
CAHPS
Yes
1.5
CAHPS
Yes
1.5
PDE data, MPF Pricing Files
No
1
Prescription Drug Event (PDE) data
Yes
3
Prescription Drug Event (PDE) data
Yes
3*
Prescription Drug Event (PDE) data
Yes
3*
Prescription Drug Event (PDE) data
Yes
3*
Part D Plan Reporting, Medicare
Yes
1
Enrollment Database (EDB) File
* Note: for contracts whose service area only covers Puerto Rico, the weights for these measures will be zero in the summary and
overall rating calculations and remain three for the improvement measure calculations.
The Challenges of Pharmacy Star Ratings • 121
Appendix D: Medicare 2016 Part C & D
Display Measure Technical Notes
Medicare
2016 Part C & D
Display Measure
Technical Notes
Updated – 12/17/2015
122 • AIS’s Management Insight Series
Document Change Log:
Previous Version
-
Description of Change
Initial Release of the 2016 Display Measure Technical Notes
(Last Updated 12/17/2015)
Revision Date
12/17/2015
Page i
The Challenges of Pharmacy Star Ratings • 123
Table of Contents
DOCUMENT CHANGE LOG:............................................................................................................................. I
GENERAL ......................................................................................................................................................... 1
CONTACT INFORMATION ............................................................................................................................... 1
PART C DISPLAY MEASURE DETAILS .......................................................................................................... 2
Measure: DMC01 - Follow-up Visit after Hospital Stay for Mental Illness (within 30 days of discharge) ........................... 2
Measure: DMC02 - Call Answer Timeliness ....................................................................................................................... 2
Measure: DMC03 - Antidepressant Medication Management (6 months) .......................................................................... 2
Measure: DMC04 - Continuous Beta Blocker Treatment.................................................................................................... 2
Measure: DMC05 - Appropriate Monitoring of Patients Taking Long-term Medications .................................................... 3
Measure: DMC06 - Osteoporosis Testing ........................................................................................................................... 3
Measure: DMC07 - Testing to Confirm Chronic Obstructive Pulmonary Disease .............................................................. 3
Measure: DMC08 - Doctors who Communicate Well ......................................................................................................... 4
Measure: DMC09 - Call Center – Beneficiary Hold Time ................................................................................................... 4
Measure: DMC10 - Pneumonia Vaccine ............................................................................................................................. 5
Measure: DMC11 - Access to Primary Care Doctor Visits.................................................................................................. 5
Measure: DMC12 - Calls Disconnected When Customer Calls Health Plan ...................................................................... 5
Measure: DMC13 - Pharmacotherapy Management of COPD Exacerbation – Systemic Corticosteroid .......................... 6
Measure: DMC14 - Pharmacotherapy Management of COPD Exacerbation – Bronchodilator ......................................... 6
Measure: DMC15 - Initiation of Alcohol or other Drug Treatment ....................................................................................... 6
Measure: DMC16 - Engagement of Alcohol or other Drug Treatment ................................................................................ 7
Measure: DMC17 - Reminders for Appointments ............................................................................................................... 7
Measure: DMC18 - Reminders for Immunizations .............................................................................................................. 7
Measure: DMC19 - Reminders for Screening Tests ........................................................................................................... 7
Measure: DMC20 - Computer Used during Office Visits .................................................................................................... 8
Measure: DMC21 - Computer Use by Doctor Helpful ......................................................................................................... 8
Measure: DMC22 - Computer Use Made Talking with Doctor Easier ................................................................................ 8
Measure: DMC23 - Improving Bladder Control ................................................................................................................... 9
PART D DISPLAY MEASURE DETAILS ........................................................................................................ 10
Measure: DMD01 - Timely Receipt of Case Files for Appeals ......................................................................................... 10
Measure: DMD02 - Timely Effectuation of Appeals .......................................................................................................... 10
Measure: DMD03 - Calls Disconnected When Customer Calls Drug Plan ....................................................................... 11
Measure: DMD04 - Call Center – Beneficiary Hold Time ................................................................................................. 11
Measure: DMD05 - Drug-Drug Interactions ...................................................................................................................... 12
Measure: DMD06 - Diabetes Medication Dosing .............................................................................................................. 12
Measure: DMD07 - Drug Plan Provides Current Information on Costs and Coverage for Medicare’s Website ............... 13
Measure: DMD08 - MPF – Stability................................................................................................................................... 14
Measure: DMD09 - Rate of Chronic Use of Atypical Antipsychotics by Elderly Beneficiaries in Nursing Homes ............ 14
Measure: DMD10 - Getting Information from Drug Plan ................................................................................................... 15
Measure: DMD11 - Call Center – Pharmacy Hold Time ................................................................................................... 16
Measure: DMD12 - Plan Submitted Higher Prices for Display on MPF ............................................................................ 16
Measure: DMD13 - Transition monitoring - failure rate for drugs within classes of clinical concern ................................ 17
Measure: DMD14 - Transition monitoring - failure rate for all other drugs ........................................................................ 18
Measure: DMD15 - Reminders to Fill prescriptions .......................................................................................................... 18
Measure: DMD16 - Reminders to Take Medications ........................................................................................................ 18
(Last Updated 12/17/2015)
Page ii
124 • AIS’s Management Insight Series
COMMON PART C & D DISPLAY MEASURE DETAILS ............................................................................... 19
Measure: DME01 - Enrollment Timeliness........................................................................................................................ 19
Measure: DME02 - Grievance Rate .................................................................................................................................. 19
Measure: DME03 - Disenrollment Reasons - Problems Getting Needed Care, Coverage, and Cost Information (MA-PD,
MA-only) ............................................................................................................................................................................ 20
Measure: DME04 - Disenrollment Reasons - Problems with Coverage of Doctors and Hospitals (MA-PD, MA-only) .... 21
Measure: DME05 - Disenrollment Reasons - Financial Reasons for Disenrollment (MA-PD, MA-only, PDP) ................ 22
Measure: DME06 - Disenrollment Reasons - Problems with Prescription Drug Benefits and Coverage (MA-PD, PDP) 22
Measure: DME07 - Disenrollment Reasons - Problems Getting Information about Prescription Drugs (MA-PD, PDP) .. 23
ATTACHMENT A: NATIONAL AVERAGES FOR PART C AND D DISPLAY MEASURES ........................... 24
Table A-1: National Averages for Part C Display Measures ......................................................................................... 24
Table A-2: National Averages for Part D Display Measures ......................................................................................... 24
Table A-3: National Averages for common Part C and D Display Measures ............................................................. 25
(Last Updated 12/17/2015)
Page iii
The Challenges of Pharmacy Star Ratings • 125
General
This document describes the metric, data source and reporting time period for each Medicare Part C or Part D
Display Measure. All data are reported at the contract level. The data do not reflect information for National
PACE, 1833 Cost contracts, Continuing Care Retirement Community demonstrations (CCRCs), End Stage
Renal Disease Networks (ESRDs), and Demonstration contracts. All other organization types are included.
These display measures are not part of the Star Ratings. Display measures may have been transitioned from
the Star Ratings. These can also be new measures being tested before inclusion into the Star Ratings. Lastly,
some measures are displayed for informational purposes only. As indicated in the 2015 Call Letter, CMS will
give advance notice if display measures are being considered for inclusion to the Star Ratings. Data for display
page measures will continue to be collected and monitored, and poor scores on display measures are subject
to compliance actions by CMS.
For 2016, CMS is

Transitioning one Star Rating measures to display:
a. Improving Bladder Control (Part C)

Reintroducing five display measures
a. Call Center Hold Time and Disconnection measures (Part C and D)
Contact Information
The contact below can assist you with various aspects of the Display Measures.

Part C & D Star Ratings: [email protected]
If you have questions or require information about the specific subject areas associated with the Display
Measures please write to those contacts directly and cc the Part C & D Star Ratings mailbox.

CAHPS (MA & Part D): [email protected]

Call Center Monitoring: [email protected]

Disenrollment Reasons Survey: [email protected]

HEDIS: [email protected]

HOS: [email protected]

Part C Plan Reporting: [email protected]

Part D Plan Reporting: [email protected]

Part C & D Plan Reporting Data Validation: [email protected]
(Last Updated 12/17/2015)
Page 1
126 • AIS’s Management Insight Series
Part C Display Measure Details
Measure: DMC01 - Follow-up Visit after Hospital Stay for Mental Illness (within 30 days of discharge)
Title
Description
HEDIS Label: Follow-Up After Hospitalization for Mental Illness (FUH)
Measure Reference: NCQA HEDIS 2015 Technical Specifications Volume 2, page 177
Metric: The percentage of discharges for members 6 years of age and older who were
hospitalized for treatment of selected mental health disorders (denominator) and who
had an outpatient visit, an intensive outpatient encounter or partial hospitalization with a
mental health practitioner within 30 days of discharge (numerator).
Data Source: HEDIS
Data Time Frame: 01/01/2014 - 12/31/2014
General Trend: Higher is better
Data Display: Percentage with no decimal point
Measure: DMC02 - Call Answer Timeliness
Title
Description
HEDIS Label: Call Answer Timeliness (CAT)
Measure Reference: NCQA HEDIS 2015 Technical Specifications Volume 2, page 251
Metric: The percentage of calls received by the organization’s member services call center
(during operating hours) during the measurement year that were answered by a live
voice within 30 seconds.
Data Source: HEDIS
Data Time Frame: 01/01/2014 - 12/31/2014
General Trend: Higher is better
Data Display: Percentage with no decimal point
Measure: DMC03 - Antidepressant Medication Management (6 months)
Title
Description
HEDIS Label: Antidepressant Medication Management (AMM)
Measure Reference: NCQA HEDIS 2015 Technical Specifications Volume 2, page 168
Metric: The percentage of members 18 years of age and older with a diagnosis of major
depression (denominator) who were newly treated with antidepressant medication, and
who remained on an antidepressant medication treatment (numerator).
Data Source: HEDIS
Data Time Frame: 01/01/2014 - 12/31/2014
General Trend: Higher is better
Data Display: Percentage with no decimal point
Measure: DMC04 - Continuous Beta Blocker Treatment
Title
Description
HEDIS Label: Persistence of Beta-Blocker Treatment After a Heart Attack (PBH)
Measure Reference: NCQA HEDIS 2015 Technical Specifications Volume 2, page 138
Metric: The percentage of members 18 years of age and older during the measurement year
who were hospitalized and discharged alive from July 1 of the year prior to the
measurement year to June 30 of the measurement year with a diagnosis of AMI
(Last Updated 12/17/2015)
Page 2
The Challenges of Pharmacy Star Ratings • 127
Title
Description
(denominator) and who received persistent beta-blocker treatment for six months after
discharge (numerator).
Data Source: HEDIS
Data Time Frame: 01/01/2014 - 12/31/2014
General Trend: Higher is better
Data Display: Percentage with no decimal point
Measure: DMC05 - Appropriate Monitoring of Patients Taking Long-term Medications
Title
Description
HEDIS Label: Annual Monitoring for Patients on Persistent Medication (MPM)
Measure Reference: NCQA HEDIS 2015 Technical Specifications Volume 2, page 202
Metric: The percentage of members 18 years of age and older who received at least 180
treatment days of ambulatory medication therapy for a select therapeutic agent
(denominator) during the measurement year and at least one therapeutic monitoring
event for the therapeutic agent in the measurement year (numerator).
Data Source: HEDIS
Data Time Frame: 01/01/2014 - 12/31/2014
General Trend: Higher is better
Data Display: Percentage with no decimal point
Measure: DMC06 - Osteoporosis Testing
Title
Description
HEDIS Label: Osteoporosis Testing in Older Women (OTO)
Measure Reference: NCQA HEDIS 2014 Specifications for The Medicare Health Outcomes Survey Volume
6, page 37
Metric: The percentage of Medicare women 65 years of age and older (denominator) who
report ever having received a bone density test to check for osteoporosis (numerator).
Exclusions: None listed.
Data Source: HEDIS / HOS
Data Source Description: Cohort 15 Follow-up Data collection (2014) and Cohort 17 Baseline data collection
(2014).
HOS Survey Question 52: Have you ever had a bone density test to check for
osteoporosis, sometimes thought of as "brittle bones"? This test may have been done to
your back, hip, wrist, heel or finger.
Data Time Frame: 04/18/2014 - 07/31/2014
General Trend: Higher is better
Data Display: Percentage with no decimal point
Measure: DMC07 - Testing to Confirm Chronic Obstructive Pulmonary Disease
Title
Description
HEDIS Label: Use of Spirometry Testing in the Assessment and Diagnosis of COPD (SPR)
Measure Reference: NCQA HEDIS 2015 Technical Specifications Volume 2, page 114
Metric: The percentage of members 40 or older with a new diagnosis or newly active Chronic
Obstructive Pulmonary Disease (COPD) during the measurement year (denominator),
(Last Updated 12/17/2015)
Page 3
128 • AIS’s Management Insight Series
Title
Description
who received appropriate spirometry testing to confirm the diagnosis (numerator).
Data Source: HEDIS
Data Time Frame: 01/01/2014 - 12/31/2014
General Trend: Higher is better
Data Display: Percentage with no decimal point
Measure: DMC08 - Doctors who Communicate Well
Title
Description
Metric: This case mix adjusted composite measure is used to assess how well doctors
communicate. The Consumer Assessment of Healthcare Providers and Systems
(CAHPS) score uses the mean of the distribution of responses converted to a scale
from 0 to 100. The score shown is the percentage of the best possible score each
contract earned.
CAHPS Survey Questions (question numbers vary depending on survey type):
• In the last 6 months, how often did your personal doctor explain things in a way that
was easy to understand?
• In the last 6 months, how often did your personal doctor listen carefully to you?
• In the last 6 months, how often did your personal doctor show respect for what you
had to say?
• In the last 6 months, how often did your personal doctor spend enough time with you?
Data Source: CAHPS
Data Time Frame: 02/15/2015 - 05/31/2015
General Trend: Higher is better
Data Display: Percentage with no decimal point
Measure: DMC09 - Call Center – Beneficiary Hold Time
Title
Description
Metric: This measure is defined as the average time spent on hold by the call surveyor
following the navigation of the Interactive Voice Response (IVR) or Automatic Call
Distributor (ACD) system and prior to reaching a live person for the “Customer Service
for Current Members – Part C” phone number associated with the contract. This
measure is calculated by taking the sum of the total time (mm:ss) it takes for a caller to
reach a Customer Service Representative (CSR) for all eligible calls made to that Part C
contract beneficiary customer service call center, divided by the number of eligible calls
made to the Part C contract beneficiary customer service call center. For calls in which
the caller terminated the call due to being on hold for greater than 10 minutes prior to
reaching a live person, the hold time applied is truncated to 10:00 minutes. Note that
total time excludes the time navigating the IVR/ACD system and thus measures only the
time the caller is placed into the “hold” queue.
Exclusions: Data were not collected from contracts that cover U.S territories, 1876 Cost,
Employer/Union Only Direct Contract PDP, Employer/Union Only Direct Contract PFFS,
National PACE, MSA, employer contracts, and organizations that did not have a phone
number accessible to survey callers.
Data Source: Call Center
Data Source Description: Call Center surveillance monitoring data collected by CMS. The “Customer Service for
Current Members – Part C” phone number associated with each contract was
monitored. This measure is based on calls to the current enrollee call center.
Data Time Frame: 01/19/2015 - 07/03/2015
(Last Updated 12/17/2015)
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Title
Description
General Trend: Lower is better
Data Display: Time
Compliance Standard: 2:00
Measure: DMC10 - Pneumonia Vaccine
Title
Description
Metric: The percentage of sampled Medicare enrollees (denominator) who reported ever having
received a pneumococcal vaccine (numerator). CAHPS Survey Question (question
number varies depending on survey type):
• Have you ever had a pneumonia shot? This shot is usually given only once or twice in
a person’s lifetime and is different from a flu shot. It is also called the pneumococcal
vaccine.
Data Source: CAHPS
Data Time Frame: 02/15/2015 - 05/31/2015
General Trend: Higher is better
Data Display: Percentage with no decimal point
Measure: DMC11 - Access to Primary Care Doctor Visits
Title
Description
HEDIS Label: Adults' Access to Preventive/Ambulatory Health Services
Measure Reference: NCQA HEDIS 2015 Technical Specifications Volume 2, page 233
Metric: The percentage of members 20 years and older (denominator) who had an ambulatory
or preventive care visit during the measurement year (numerator).
Exclusions: None listed.
Data Source: HEDIS
Data Time Frame: 01/01/2014 - 12/31/2014
General Trend: Higher is better
Data Display: Percentage with no decimal point
Compliance Standard: 85%
Measure: DMC12 - Calls Disconnected When Customer Calls Health Plan
Title
Description
Metric: This measure is defined as the number of calls unexpectedly dropped by the sponsor
while the call surveyor was navigating the IVR or connected with a customer service
representative (CSR) divided by the total number of calls made to the phone number
associated with the contract.
Exclusions: Data were not collected from contracts that cover U.S territories, 1876 Cost,
Employer/Union Only Direct Contract PDP, Employer/Union Only Direct Contract PFFS,
National PACE, MSA, employer contracts, and organizations that did not have a phone
number accessible to survey callers.
Data Source: Call Center
Data Source Description: Call Center surveillance monitoring data collected by CMS. The “Customer Service for
Current Members – Part C” phone number associated with each contract was
monitored. This measure is based on calls to the current enrollee call center.
Data Time Frame: 01/19/2015 - 07/03/2015
(Last Updated 12/17/2015)
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Title
Description
General Trend: Lower is better
Data Display: Percentage with 2 decimal points
Compliance Standard: 5%
Measure: DMC13 - Pharmacotherapy Management of COPD Exacerbation – Systemic Corticosteroid
Title
Description
HEDIS Label: Pharmacotherapy Management of COPD Exacerbation
Measure Reference: NCQA HEDIS 2015 Technical Specifications Volume 2, page 116
Metric: The percentage of COPD exacerbations for members 40 years of age and older who
had an acute inpatient discharge or ED encounter on or between January 1–November
30 of the measurement year and who were dispensed a systemic corticosteroid within
14 days of the event.
Data Source: HEDIS
Data Time Frame: 01/01/2014 - 12/31/2014
General Trend: Higher is better
Data Display: Percentage with no decimal point
Measure: DMC14 - Pharmacotherapy Management of COPD Exacerbation – Bronchodilator
Title
Description
HEDIS Label: Pharmacotherapy Management of COPD Exacerbation
Measure Reference: NCQA HEDIS 2015 Technical Specifications Volume 2, page 116
Metric: The percentage of COPD exacerbations for members 40 years of age and older who
had an acute inpatient discharge or ED encounter on or between January 1–November
30 of the measurement year and who were dispensed a bronchodilator within 30 days
of the event.
Data Source: HEDIS
Data Time Frame: 01/01/2014 - 12/31/2014
General Trend: Higher is better
Data Display: Percentage with no decimal point
Measure: DMC15 - Initiation of Alcohol or other Drug Treatment
Title
Description
HEDIS Label: Initiation and Engagement of Alcohol and Other Drug Dependence Treatment
Measure Reference: NCQA HEDIS 2015 Technical Specifications Volume 2, page 239
Metric: The percentage of members who initiate treatment through an inpatient AOD admission,
outpatient visit, intensive outpatient encounter or partial hospitalization within 14 days of
the diagnosis.
Data Source: HEDIS
Data Time Frame: 01/01/2014 - 12/31/2014
General Trend: Higher is better
Data Display: Percentage with no decimal point
(Last Updated 12/17/2015)
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The Challenges of Pharmacy Star Ratings • 131
Measure: DMC16 - Engagement of Alcohol or other Drug Treatment
Title
Description
HEDIS Label: Initiation and Engagement of Alcohol and Other Drug Dependence Treatment
Measure Reference: NCQA HEDIS 2015 Technical Specifications Volume 2, page 239
Metric: The percentage of members who initiated treatment and who had two or more
additional services with a diagnosis of AOD within 30 days of the initiation visit.
Data Source: HEDIS
Data Time Frame: 01/01/2014 - 12/31/2014
General Trend: Higher is better
Data Display: Percentage with no decimal point
Measure: DMC17 - Reminders for Appointments
Title
Description
Metric: The percentage of sampled Medicare enrollees (denominator) who reported that they
were reminded about appointments (numerator). CAHPS Survey Questions (question
numbers vary depending on survey type):
• In the last 6 months, did anyone from a doctor’s office or your health plan contact you
to remind you to make appointments for tests or treatment?
Data Source: CAHPS
Data Time Frame: 02/15/2015 - 05/31/2015
General Trend: Higher is better
Data Display: Percentage with no decimal point
Measure: DMC18 - Reminders for Immunizations
Title
Description
Metric: The percentage of sampled Medicare enrollees (denominator) who reported that they
were reminded about getting immunizations (numerator). CAHPS Survey Questions
(question numbers vary depending on survey type):
• In the last 6 months, did anyone from a doctor’s office or your health plan contact you
to remind you to get a flu shot or other immunization?
Data Source: CAHPS
Data Time Frame: 02/15/2015 - 05/31/2015
General Trend: Higher is better
Data Display: Percentage with no decimal point
Measure: DMC19 - Reminders for Screening Tests
Title
Description
Metric: The percentage of sampled Medicare enrollees (denominator) who reported that they
were reminded about getting a screening test (numerator). CAHPS Survey Questions
(question numbers vary depending on survey type):
• In the last 6 months, did anyone from a doctor’s office or your health plan contact you
to remind you about screening tests such as breast cancer or colorectal cancer
screening?
Data Source: CAHPS
Data Time Frame: 02/15/2015 - 05/31/2015
General Trend: Higher is better
Data Display: Percentage with no decimal point
(Last Updated 12/17/2015)
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Measure: DMC20 - Computer Used during Office Visits
Title
Description
Metric: The percentage of sampled Medicare enrollees (denominator) who reported their doctor
used a computer or handheld device during an office visit (numerator). CAHPS Survey
Questions (question numbers vary depending on survey type):
• Doctors may use computers or handheld devices during an office visit to do things like
look up your information or order prescription medicines. In the last 6 months, did your
personal doctor use a computer or handheld device during any of your visits?
Data Source: CAHPS
Data Time Frame: 02/15/2015 - 05/31/2015
General Trend: Higher is better
Data Display: Percentage with no decimal point
Measure: DMC21 - Computer Use by Doctor Helpful
Title
Description
Metric: This case-mix adjusted measure is used to assess how helpful providers’ computer use
is. The Consumer Assessment of Healthcare Providers and Systems (CAHPS) score is
the percentage of sampled Medicare enrollees (denominator) who reported that their
doctor’s use of a computer or handheld device was helpful “a lot” or “a little”.
CAHPS Survey Questions (question numbers vary depending on survey type):
• During your visits in the last 6 months, was your personal doctor’s use of a computer
or handheld device helpful to you?
Data Source: CAHPS
Data Time Frame: 02/15/2015 - 05/31/2015
General Trend: Higher is better
Data Display: Percentage with no decimal point
Measure: DMC22 - Computer Use Made Talking with Doctor Easier
Title
Description
Metric: This case-mix adjusted measure is used to assess whether providers’ computer use
made talking harder or easier. The Consumer Assessment of Healthcare Providers and
Systems (CAHPS) score is the percentage of sampled Medicare enrollees
(denominator) who reported that their doctor’s use of a computer or handheld device
made talking to them easier.
CAHPS Survey Questions (question numbers vary depending on survey type):
• During your visits in the last 6 months, did your personal doctor’s use of a computer or
handheld device make it harder or easier for you to talk to him or her?
Data Source: CAHPS
Data Time Frame: 02/15/2015 - 05/31/2015
General Trend: Higher is better
Data Display: Percentage with no decimal point
(Last Updated 12/17/2015)
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Measure: DMC23 - Improving Bladder Control
Title
Description
HEDIS Label: Management of Urinary Incontinence in Older Adults (MUI)
Measure Reference: NCQA HEDIS 2014 Specifications for The Medicare Health Outcomes Survey Volume
6, page 29
Metric: The percentage of Medicare members 65 years of age or older who reported having a
urine leakage problem in the past six months (denominator) and who received treatment
for their current urine leakage problem (numerator).
Exclusions: None listed.
Data Source: HEDIS / HOS
Data Source Description: Cohort 15 Follow-up Data collection (2014) and Cohort 17 Baseline data collection
(2014).
HOS Survey Question 42: Many people experience problems with urinary incontinence,
the leakage of urine. In the past 6 months, have you accidentally leaked urine?
Data Time Frame: 04/18/2014 - 07/31/2014
General Trend: Higher is better
Data Display: Percentage with no decimal point
(Last Updated 12/17/2015)
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Part D Display Measure Details
Measure: DMD01 - Timely Receipt of Case Files for Appeals
Title
Description
Metric: This measure is defined as the percent of case files that were requested by the IRE that
were received timely from the plan. (Timely is defined as files being received from the
plan within 48 hours for Standard appeals, and within 24 hours for Expedited appeals.)
Numerator = The number of case files requested that were received in the required time
frame.
Denominator = The number of case files requested by the IRE.
This is calculated as: [(The number of case files received in the required timeframe) /
(The number of case files requested by the IRE)] * 100.
Exclusions: None
Data Source: IRE
Data Source Description: Data were obtained from the IRE contracted by CMS for Part D reconsiderations.
These data are limited to appeal cases requested by beneficiaries and the IRE requests
files from the plans. Cases auto-forwarded to the IRE are excluded.
Data Time Frame: 01/01/2015 - 06/30/2015
General Trend: Higher is better
Data Display: Percentage with no decimal point
Measure: DMD02 - Timely Effectuation of Appeals
Title
Description
Metric: This measure is defined as the percent of appeals that required effectuation that the
plan effectuated in a timely manner (Timely is defined as within one day of decision
notification for Expedited appeals, or three days of decision notification for Standard
appeals.).
Numerator = The number of appeals that were effectuated timely.
Denominator = The number of the dispositions which required effectuation. Appeals with
a disposition of “Fully Reverse Plan” or “Partially Reverse Plan” require effectuation.
This measure looks at the most recent proceeding where effectuation is required in the
event of ALJ’s or Reopenings.
This is calculated as: [(The number of appeals that were effectuated timely) / (The
number of dispositions that required effectuation)] * 100.
Exclusions: None. These data are based on the report generation date. If the IRE does not receive
a notice of effectuation before the timeframe has elapsed, the IRE will count the appeal
as non-timely. Discrepancies may occur if the IRE receives the effectuation notice late,
despite the actual effectuation occurring timely. Re-openings and ALJ decisions may
also negate the need for effectuation.
Data Source: IRE
Data Source Description: Data were obtained from the IRE contracted by CMS for Part D reconsiderations.
Timely is defined as within one day of decision notification for Expedited appeals, or
three days of decision notification for Standard appeals. For appeals involving plans
(Last Updated 12/17/2015)
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Title
Description
making payments, timely is defined as payment being made within 30 calendar days of
decision notification.
Data Time Frame: 01/01/2015 - 06/30/2015
General Trend: Higher is better
Data Display: Percentage with 2 decimal points
Measure: DMD03 - Calls Disconnected When Customer Calls Drug Plan
Title
Description
Metric: This measure is defined as the number of calls unexpectedly dropped by the sponsor
while the call surveyor was navigating the IVR or connected with a customer service
representative (CSR) divided by the total number of calls made to the phone number
associated with the contract.
Exclusions: Data were not collected from contracts that cover U.S. territories, 1876 Cost,
Employer/Union Only Direct Contract PDP, Employer/Union Only Direct Contract PFFS,
National PACE, MSA, employer contracts, and organizations that did not have a phone
number accessible to survey callers.
Data Source: Call Center
Data Source Description: Call Center surveillance monitoring data collected by CMS. The “Customer Service for
Current Members – Part D” phone number associated with each contract was
monitored. This measure is based on calls to the current enrollee call center.
Data Time Frame: 01/19/2015 - 07/03/2015
General Trend: Lower is better
Data Display: Percentage with 2 decimal points
Compliance Standard: 5%
Measure: DMD04 - Call Center – Beneficiary Hold Time
Title
Description
Metric: This measure is defined as the average time spent on hold by a call surveyor following
the navigation of the Interactive Voice Response (IVR) or Automatic Call Distributor
(ACD) system and prior to reaching a live person for the “Customer Service for Current
Members – Part D” phone number associated with the contract. This measure is
calculated by taking the sum of the total time (mm:ss) it takes for a caller to reach a
Customer Service Representative (CSR) for all eligible calls made to that Part D
contract beneficiary customer service call center divided by the number of eligible calls
made to the Part D contract beneficiary customer service call center. For calls in which
the caller terminated the call due to being on hold for greater than 10 minutes prior to
reaching a live person, the hold time applied is truncated to 10:00 minutes. Note that
total time excludes the time navigating the IVR/ACD system and thus measures only the
time the caller is placed into the “hold” queue.
Exclusions: Data were not collected from contracts that cover U.S. territories, 1876 Cost,
Employer/Union Only Direct Contract PDP, Employer/Union Only Direct Contract PFFS,
National PACE, MSA, employer contracts, and organizations that did not have a phone
number accessible to survey callers.
Data Source: Call Center
Data Source Description: Call center monitoring data collected by CMS. The “Customer Service for Current
Members – Part D” phone number associated with each contract was monitored.
Data Time Frame: 01/19/2015 - 07/03/2015
General Trend: Lower is better
(Last Updated 12/17/2015)
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136 • AIS’s Management Insight Series
Title
Description
Data Display: Time
Compliance Standard: 2:00
Measure: DMD05 - Drug-Drug Interactions
Title
Description
Metric: This measure is defined as the percent of Medicare Part D beneficiaries who received a
prescription for a target medication during the measurement period and who were
dispensed a prescription for a contraindicated medication with or subsequent to the
initial prescription.
Numerator = Number of member-years of beneficiaries enrolled during the
measurement period who were dispensed a target medication with at least one day
overlap with a contraindicated medication.
Denominator = Number of member-years of beneficiaries enrolled during the
measurement period who were dispensed a target medication.
This is calculated as: [(Number of member-years of beneficiaries enrolled during the
measurement period who were dispensed a target medication with at least one day
overlap with a contraindicated medication) / (Number of member-years of beneficiaries
enrolled during the measurement period who were dispensed a target medication)]*100.
Exclusions: A percentage is not calculated for contracts with 30 or fewer beneficiary member years
(in the denominator).
Data Source: PDE data
Data Source Description: The Drug-Drug Interaction (DDI) measure is adapted from the measure concept that
was first developed by the Pharmacy Quality Alliance (PQA). The data for this measure
come from Prescription Drug Event (PDE) data files submitted by drug plans to
Medicare for dates of service from January 1, 2014-December 31, 2014, and processed
by June 30, 2015. Only final action PDE claims are used to calculate the patient safety
measures. PDE adjustments made post-reconciliation were not reflected in this
measure. The measure is calculated using the National Drug Code (NDC) lists updated
by the PQA. The complete NDC lists will be posted along with these technical notes.
Data Time Frame: 01/01/2014 - 12/31/2014
General Trend: Lower is better
Data Display: Percentage with 1 decimal point
Measure: DMD06 - Diabetes Medication Dosing
Title
Description
Metric: This measure is defined as the percent of Medicare Part D beneficiaries who were
dispensed a dose higher than the daily recommended dose for the following diabetes
treatment therapeutic categories of oral hypoglycemics: biguanides, sulfonlyureas,
thiazolidinediones, and DiPeptidyl Peptidase (DPP)-IV inhibitors.
Numerator = Number of member-years of beneficiaries 18 years and older enrolled
during the measurement period who were dispensed a dose of an oral hypoglycemic
higher than the daily recommended dose.
Denominator = Number of member-years of beneficiaries 18 years and older enrolled
during the measurement period who were dispensed at least one prescription of an oral
hypoglycemic.
(Last Updated 12/17/2015)
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The Challenges of Pharmacy Star Ratings • 137
Title
Description
This is calculated as: [(Number of member-years of beneficiaries 18 years and older
enrolled during the measurement period who were dispensed a dose of an oral
hypoglycemic higher than the daily recommended dose) / (Number of member-years of
beneficiaries 18 years and older enrolled during the measurement period who were
dispensed at least one prescription of an oral hypoglycemic)]*100.
Exclusions: A percentage is not calculated for contracts with 30 or fewer beneficiary member years
(in the denominator).
Data Source: PDE data
Data Source Description: The Diabetes Medication Dosing (DMD) measure is adapted from the measure concept
that was first developed by the Pharmacy Quality Alliance (PQA). The data for this
measure come from Prescription Drug Event (PDE) data files submitted by drug plans
to Medicare for dates of service from January 1, 2014-December 31, 2014, and
processed by June 30, 2015. Only final action PDE claims are used to calculate the
patient safety measures. PDE adjustments made post-reconciliation were not reflected
in this measure. The measure is calculated using the National Drug Code (NDC) lists
updated by the PQA. The complete NDC lists will be posted along with these technical
notes.
Data Time Frame: 01/01/2014 - 12/31/2014
General Trend: Lower is better
Data Display: Percentage with 2 decimal points
Measure: DMD07 - Drug Plan Provides Current Information on Costs and Coverage for Medicare’s
Website
Title
Description
Metric: This measure is defined as percent of pricing/formulary data file submissions that do not
result in suppression of pricing data on www.medicare.gov.
Numerator = Number of pricing data file submissions that do not result in suppression of
pricing data on www.medicare.gov
Denominator = Total number of pricing data submissions
This is calculated as: [(Number of pricing data file submissions that do not result in
suppression of pricing data on www.medicare.gov) / (Total number of pricing data
submissions)]*100.
Exclusions: None.
Data Source: CMS Administrative Data
Data Time Frame: 10/01/2014 - 09/30/2015
General Trend: Higher is better
Data Display: Percentage with no decimal point
(Last Updated 12/17/2015)
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138 • AIS’s Management Insight Series
Measure: DMD08 - MPF – Stability
Title
Description
Metric: This measure evaluates stability in a plan’s point of sale prices.
The stability price index uses final prescription drug event (PDE) data to assess
changes in prices over the contract year. It is defined as the average change in price of
a specified basket of drugs each quarter. A basket of drugs defined by quarter 1 PDEs
is priced using quarter 1 average prices for each drug first. The same basket is then
priced using quarter 2 average prices. The stability price index from quarter 1 to quarter
2 is calculated as the total price of the basket using the quarter 2 average prices divided
by the total price of same basket using quarter 1 average prices. This same process is
repeated using a quarter 2 basket of drugs to compute the quarter 2 to quarter 3 price
index and a quarter 3 basket of drugs to compute the quarter 3 to quarter 4 price index.
The overall stability price index is the average of the price index from quarter 1 to 2,
quarter 2 to 3, and quarter 3 to 4. A price index of 1 indicates a plan had no increase in
prices from the beginning to the end of the year. A stability index smaller than 1
indicates that prices decreased, while an index greater than 1 indicates that prices
increased.
To convert the index into the stability score, we use the formula below. The score is
rounded to the nearest whole number.
100 – ((stability index – 1) x 100).
Exclusions: A contract must have at least one drug with at least 10 claims in each quarter for the
price stability index. PDEs must also meet the following criteria:
• Pharmacy number on PDE must appear in MPF pharmacy cost file
• PDE must be for retail pharmacy
• Date of service must occur at a time that data are not suppressed for the plan on MPF
• PDE must not be a compound claim
• PDE must not be a non-covered drug
Data Source: PDE data, MPF Pricing Files, HPMS approved formulary extracts, and data from First
DataBank and Medi-span
Data Source Description: Data were obtained from a number of sources: PDE data, MPF Pricing Files, HPMS
approved formulary extracts. Post-reconciliation PDE adjustments are not reflected in
this measure
Data Time Frame: 01/01/2014 - 12/31/2014
General Trend: Higher is better
Data Display: Rate with no decimal point
Measure: DMD09 - Rate of Chronic Use of Atypical Antipsychotics by Elderly Beneficiaries in Nursing
Homes
Title
Description
Metric: This measure is defined as the percent of Medicare Part D beneficiaries 65 years and
older who are continuously enrolled in a nursing home and who received atypical
antipsychotic (AA) medication fills during the period measured.
Denominator = Number of beneficiaries who meet all of the following:
• Had Long-Term Institutional (LTI) status * for all months of the measurement period or
until death,
• Were alive for at least 90 days at the beginning of the measurement period,
• Were enrolled in Part D for all months of the measurement period that they were alive,
(Last Updated 12/17/2015)
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The Challenges of Pharmacy Star Ratings • 139
Title
Description
and
• Whose first reason for Medicare enrollment was aging-in.
Numerator = Number of Part D beneficiaries in the denominator who received at least a
90 day supply of AA medication(s) during the nursing home stay in the measurement
period
This rate is calculated using a list of AA National Drug Codes (NDC) maintained by
CMS. The complete medication list will be posted along with these technical notes.
* See Notes under Data Source for definition of LTI
Exclusions: A percentage is not calculated for contracts with 10 or fewer beneficiaries in the
denominator and will be shown as “No Data Available.”
Data Source: PDE data, Enrollment data, Minimum Date Set( (MDS) Assessments
Data Source Description: Data Source: Prescription Drug Event (PDE) data, Enrollment data, Minimum Data Set
(MDS) Assessments
Notes: Beneficiaries are defined as LTI for payment purposes under the Medicare Risk
Adjustment program. The algorithm that creates monthly flags for each LTI-defined
beneficiary is described below.
Monthly LTI flags are created to identify, by month, a beneficiary’s institutional versus
community status. The flags are used to determine the appropriate CMS- risk scores for
calculating Part C and Part D risk payments, and for resolving risk scores for analysis
purposes.
The monthly LTI flags are created based on an analysis of MDS assessments. A
nursing home resident (beneficiary) is stepped through their MDS assessments
chronologically. For each month, if a quarterly, annual, or significant change
assessment is encountered and the nursing home length of stay on the date of that
assessment is more than 90 days, then an LTI flag is turned on for the following month.
An LTI flag is established for all subsequent months until the beneficiary dies, a
discharge assessment is encountered, or if an assessment is not encountered within
150 days of a prior assessment.
Data Time Frame: 01/01/2014 - 12/31/2014
General Trend: Lower is better
Data Display: Percentage with 2 decimal points
Measure: DMD10 - Getting Information from Drug Plan
Title
Description
Metric: This case-mix adjusted composite measure is used to assess how easy it is for
members to get information from the plan about prescription drug coverage and cost.
The Consumer Assessment of Healthcare Providers and Systems (CAHPS) score uses
the mean of the distribution of responses converted to a scale from 0 to 100. The score
shown is the percentage of the best possible score each contract earned.
CAHPS Survey Questions (question numbers vary depending on survey type):
• In the last 6 months, how often did your health plan’s customer service give you the
information or help you needed about prescription drugs?
• In the last 6 months, how often did your plan's customer service staff treat you with
courtesy and respect when you tried to get information or help about prescription drugs?
(Last Updated 12/17/2015)
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140 • AIS’s Management Insight Series
Title
Description
• In the last 6 months, how often did your health plan give you all the information you
needed about which prescription medicines were covered?
• In the last 6 months, how often did your health plan give you all the information you
needed about how much you would have to pay for your prescription medicine?
Data Source: CAHPS
Data Time Frame: 02/15/2015 - 05/31/2015
General Trend: Higher is better
Data Display: Percentage with no decimal point
Measure: DMD11 - Call Center – Pharmacy Hold Time
Title
Description
Metric: This measure is defined as the average time spent on hold by a call surveyor following
the navigation of the Interactive Voice Response (IVR) or Automatic Call Distributor
(ACD) system and prior to reaching a live person for the “Pharmacy Technical Help
Desk” phone number associated with the contract. This measure is calculated by taking
the sum of the total time (mm:ss) it takes for a caller to reach a Customer Service
Representative (CSR) for all eligible calls made to that Part D contract pharmacy
technical help desk divided by the number of eligible calls made to the Part D contract
pharmacy technical help desk. For calls in which the caller terminated the call due to
being on hold for greater than 10 minutes prior to reaching a live person, the hold time
applied is truncated to 10:00 minutes. Note that total time excludes the time navigating
the IVR/ACD system and thus measures only the time the caller is placed into the “hold”
queue.
Exclusions: Data were not collected from contracts that cover U.S. territories, 1876 Cost,
Employer/Union Only Direct Contract PDP, Employer/Union Only Direct Contract PFFS,
National PACE, MSA, employer contracts, and organizations that did not have a phone
number accessible to survey callers.
Data Source: Call Center
Data Source Description: Call center data collected by CMS. The Pharmacy Technical Help Desk phone number
associated with each contract was monitored.
Data Time Frame: 01/18/2015 - 07/02/2015
General Trend: Lower is better
Data Display: Time
Compliance Standard: 2:00
Measure: DMD12 - Plan Submitted Higher Prices for Display on MPF
Title
Description
Metric: This measure evaluates the accuracy of drug prices posted on the MPF tool. A
contract’s score is based on the accuracy index.
The accuracy price index compares point-of-sale PDE prices to plan-reported MPF
prices and determines the magnitude of differences found. Using each PDE’s date of
service, the price displayed on MPF is compared to the PDE price.
The accuracy index considers both ingredient cost and dispensing fee and measures
the amount that the MPF price is higher than the PDE price. Therefore, prices that are
understated on MPF—that is, the reported price is lower than the actual price—will not
count against a plan’s accuracy score.
(Last Updated 12/17/2015)
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The Challenges of Pharmacy Star Ratings • 141
Title
Description
The index is computed as:
(Total amount that PF is higher than PDE + Total PDE cost) / (Total PDE cost).
The best possible accuracy index is 1. An index of 1 indicates that a plan did not have
PDE prices less than MPF prices.
A contract’s score is computed using its accuracy index as:
100 – ((accuracy index - 1) x 100).
Exclusions: A contract must have at least 30 claims over the measurement period for the price
accuracy index. PDEs must also meet the following criteria:
• Pharmacy number on PDE must appear in MPF pharmacy cost file
• Drug must appear in formulary file and in MPF pricing file
• PDE must be for retail and/or specialty pharmacy
• PDE must be a 30 day supply
• Date of service must occur at a time that data are not suppressed for the plan on MPF
• PDE must not be a compound claim
• PDE must not be a non-covered drug
• PDE must be for retail pharmacy (pharmacies marked retail and mail order/HI/LTC are
excluded)
Data Source: PDE data, MPF Pricing Files, HPMS approved formulary extracts, and data from First
DataBank and Medi-span
Data Time Frame: 01/01/2014 - 09/30/2014
General Trend: Higher is better
Data Display: Rate with no decimal point
Measure: DMD13 - Transition monitoring - failure rate for drugs within classes of clinical concern
Title
Description
Metric: The numbers of failures (numerator) were divided by the number of claims sampled
(denominator) to calculate an overall compliance score.
If the number of failures resulted in more than a 10% failure rate, CMS determined that
an overall compliance failure occurred for this area.
Exclusions: Contracts with fewer than 15 claims sampled; Contracts not listed in active status in
HPMS; MMPs that did not have a start date on or before January 2015; Contracts that
are involved in other transition oversight activities; Contracts that do not offer Part D
coverage or did not utilize a formulary.
Data Source: Part D Sponsor, PDE data, CME data and HPMS approved formularies
Data Source Description: Data was obtained from the Part D Sponsor, PDE data, CME data and HPMS approved
formulary extracts.
Data Time Frame: January 4 – 24, 2015
General Trend: Lower is better
Data Display: Percentage with 1 decimal point
Compliance Standard: >10%
(Last Updated 12/17/2015)
Page 17
142 • AIS’s Management Insight Series
Measure: DMD14 - Transition monitoring - failure rate for all other drugs
Title
Description
Metric: The numbers of failures (numerator) were divided by the number of claims sampled
(denominator) to calculate an overall compliance score.
If the number of failures resulted in more than a 20% failure rate, CMS determined that
an overall compliance failure occurred for this area.
Exclusions: Contracts with fewer than 15 claims sampled; Contracts not listed in active status in
HPMS; MMPs that did not have a start date on or before January 2015; Contracts that
are involved in other transition oversight activities; Contracts that do not offer Part D
coverage or did not utilize a formulary.
Data Source: Part D Sponsor, PDE data, CME data, and HPMS approved formularies
Data Source Description: Data was obtained from the Part D Sponsor, PDE data, CME data, and HPMS
approved formulary extracts.
Data Time Frame: January 4 – 24, 2015
General Trend: Lower is better
Data Display: Percentage with 1 decimal point
Compliance Standard: >20%
Measure: DMD15 - Reminders to Fill prescriptions
Title
Description
Metric: The percentage of sampled Medicare enrollees (denominator) who reported that they
were reminded about filling or refilling a prescription (numerator). CAHPS Survey
Questions (question numbers vary depending on survey type):
• In the last 6 months, did anyone from a doctor’s office, pharmacy or your prescription
drug plan contact you to make sure you filled or refilled a prescription?
Data Source: CAHPS
Data Time Frame: 02/15/2015 - 05/31/2015
General Trend: Higher is better
Data Display: Percentage with no decimal point
Measure: DMD16 - Reminders to Take Medications
Title
Description
Metric: The percentage of sampled Medicare enrollees (denominator) who reported that they
were reminded about taking medications as directed (numerator). CAHPS Survey
Questions (question numbers vary depending on survey type):
• In the last 6 months, did anyone from a doctor’s office, pharmacy or your prescription
drug plan contact you to make sure you were taking medications as directed?
Data Source: CAHPS
Data Time Frame: 02/15/2015 - 05/31/2015
General Trend: Higher is better
Data Display: Percentage with no decimal point
(Last Updated 12/17/2015)
Page 18
The Challenges of Pharmacy Star Ratings • 143
Common Part C & D Display Measure Details
Measure: DME01 - Enrollment Timeliness
Title
Description
Metric: Numerator = The number of plan generated enrollment transactions submitted to CMS
within 7 calendar days of the application date
Denominator = The total number of plan generated enrollment transactions submitted to
CMS
Calculation = [(The number of plan generated enrollment transactions submitted to
CMS within 7 calendar days of the application date) / (The total number of plan
generated enrollment transactions submitted to CMS)] * 100
Exclusions: 1. Contracts with 25 or fewer enrollment submissions during the measurement period,
when summed.
2. Election Types: ICEP, IEP, IEP2 and AEP.
3. Employer/Union enrollments.
4. 1876 Cost Contract MA-only members.
5. Special Needs Plans.
6. Transaction Reply Codes 1-5 (TRC1, TRC2, TRC3, TRC4, TRC5) equal to any of the
below: TRC’s: ('001', '002', '003', '004', '006', '007', '008', '009', '019', '020', '032', '033',
'034', '035', '036', '037', '038', '039', '042', '044', '045', '048', '056', '060', '062', '102', '103',
'104', '105', '106', '107', '108', '109', '110', '114', '116', '122', '123', '124', '126', '127', '128',
'129', '130', '133', '139', '156', '157', '162', '166', '169', '176', '184', '196', '200', '201', '202',
'203', '211', '220', '257', '258', '263', '600', '601', '602', '603', '605', '611') TRCs are
defined in the Plan Communication Users Guide Appendix Table I-2.
Data Source: Medicare Advantage and Prescription Drug System (MARx)
Data Source Description: The data timeframe is the monthly enrollment files for January - June, 2015, which
represents submission dates of 01/01/2015 - 06/30/2015.
Data Time Frame: 01/01/2015 - 06/30/2015
General Trend: Higher is better
Data Display: Percentage with no decimal point
Measure: DME02 - Grievance Rate
Title
Description
Metric: This measure is defined as the number of grievances filed with the health plan per
1,000 enrollees per month.
Numerator = (Quarter 1 Total Grievances + Quarter 2 Grievances + Quarter 3
Grievances + Quarter 4 Grievances) * 1,000 * 30
Denominator = Average Enrollment * Number of days in period
For MAOs, Total Grievances includes grievances reported per the Part C Reporting
Requirements. For PDPs, Total Grievances includes grievances reported per the Part
D Reporting Requirements. For MA-PDs, Part C and Part D grievances are combined
in order to report a single contract-level rate.
Exclusions: Part C grievances reported in the “CMS issues” category (Element 5.10: CMS issues
grievances) are excluded from the Total Grievances count.
Part D grievances reported in the “CMS issues” category (Element T: CMS issues
grievances) are excluded from the Total Grievances count.
A contract must have an average enrollment of 800 or more enrollees to have a rate
calculated. Contracts with fewer than 800 enrollees are listed as "Plan too small to be
(Last Updated 12/17/2015)
Page 19
144 • AIS’s Management Insight Series
Title
Description
measured.”
Contracts and plans with an effective terminate date on or before the deadline to submit
data validation results to CMS (June 30, 2014) are listed as “Plan not required to report
measure.”
Rates are not calculated for contracts that did not score at least 95% on data validation
for the Grievances reporting section(s). Rates are also not calculated for contracts that
scored 95% or higher on data validation for Grievance section(s) but that were not
compliant with data validation standards/sub-standards for at least one of the following
Grievance data elements:
Part C (MA only and MA-PDs)
• Fraud grievances (Element 5.1)
• Enrollment/disenrollment grievances (Element 5.2)
• Benefit package grievances (Element 5.3)
• Access grievances (Element 5.4)
• Marketing grievances (Element 5.5)
• Customer service grievances (Element 5.6)
• Privacy issue grievances (Element 5.7)
• Quality of care grievances (Element 5.8)
• Appeals grievances (Element 5.9)
• Other grievances (Element 5.11)
Part D (PDPs and MA-PDs)
• Enrollment, plan benefits, or pharmacy access – Total number of grievances (Element
A)
• Customer Service – Total number of grievances (Element C)
• Coverage determinations and Redeterminations process – Total number of grievances
(Element E)
• Other – Total number of grievances (Element I)
These contracts excluded from the measure due to data validation issues are shown as
“Data issues found.”
Data Source: Part C & D Plan Reporting
Data Source Description: Data were reported by contracts to CMS through the Health Plan Management System
(HPMS). Validation of these data was performed retrospectively during the 2014 Data
Validation cycle.
Data Time Frame: 01/01/2014 - 12/31/2014
General Trend: Lower is better
Data Display: Rate with 2 decimal points
Measure: DME03 - Disenrollment Reasons - Problems Getting Needed Care, Coverage, and Cost
Information (MA-PD, MA-only)
Title
Description
Metric: “Problems Getting Needed Care, Coverage, and Cost Information” is a composite of the
following survey questions (question numbers vary depending on survey type):
(a) Did you leave the plan because you were frustrated by the plan’s approval process
for care, tests, or treatment?
(b) Did you leave the plan because you had problems getting the care, tests, or
treatment you needed?
(c) Did you leave the plan because you had problems getting the plan to pay a claim?
(Last Updated 12/17/2015)
Page 20
The Challenges of Pharmacy Star Ratings • 145
Title
Description
(d) Did you leave the plan because it was hard to get information from the plan -- like
which health care services were covered or how much a specific test or treatment would
cost?
Each of these questions asked about a reason for disenrollment that was related to the
beneficiary’s experiences with getting needed health care services and cost information
and getting claims paid for these services. Scores range from 0 to 100 and a lower
mean indicates that problems getting needed care, coverage and cost information
reasons were endorsed less frequently by disenrollees from your contract.
Exclusions: Contracts with less than 30 responses are excluded.
Data Source: Disenrollment Reasons Survey
Data Source Description: Survey of members who disenrolled from the contract during the measurement time
frame with the following disenrollment reason codes: disenrollment reason codes:
11 - Voluntary Disenrollment through plan, 13 - Disenrollment because of enrollment in
another Plan, 14 - Retroactive or 99 - Other (not supplied by beneficiary).
Data Time Frame: 01/01/2014 - 12/31/2014
General Trend: Lower is better
Data Display: Percentage with no decimal point
Measure: DME04 - Disenrollment Reasons - Problems with Coverage of Doctors and Hospitals (MA-PD,
MA-only)
Title
Description
Metric: “Problems with Coverage of Doctors and Hospitals” is a composite of the following
survey questions (question numbers vary depending on survey type):
(a) Did you leave the plan because the doctors or other health care providers you
wanted to see did not belong to the plan?
(b) Did you leave the plan because clinics or hospitals you wanted to go to for care were
not covered by the plan?
Each of these questions asked about a reason for disenrollment that was related to the
coverage of doctors and hospitals by the plan. Scores range from 0 to 100 and a lower
mean indicates that problems with coverage of doctors and hospitals reasons were
endorsed less frequently by disenrollees from your contract.
Exclusions: Contracts with less than 30 responses are excluded.
Data Source: Disenrollment Reasons Survey
Data Source Description: Survey of members who disenrolled from the contract during the measurement time
frame with the following disenrollment reason codes: disenrollment reason codes:
11 - Voluntary Disenrollment through plan, 13 - Disenrollment because of enrollment in
another Plan, 14 - Retroactive or 99 - Other (not supplied by beneficiary).
Data Time Frame: 01/01/2014 - 12/31/2014
General Trend: Lower is better
Data Display: Percentage with no decimal point
(Last Updated 12/17/2015)
Page 21
146 • AIS’s Management Insight Series
Measure: DME05 - Disenrollment Reasons - Financial Reasons for Disenrollment (MA-PD, MA-only,
PDP)
Title
Description
Metric: “Financial Reasons for Disenrollment” is a composite of the following survey questions
(question numbers vary depending on survey type):
(a) Did you leave the plan because the monthly fee that the health plan charges to
provide coverage for health care and prescription medicines went up?
(b) Did you leave the plan because the dollar amount you had to pay each time you
filled or refilled a prescription went up?
(c) Did you leave the plan because you found a health plan that costs less?
(d) Did you leave the plan because a change in your personal finances meant you could
no longer afford the plan?
Each of these questions asked about a reason for disenrollment that was related to the
cost or affordability of services. Scores range from 0 to 100 and a lower mean indicates
that financial reasons were endorsed less frequently by disenrollees from your contract.
Exclusions: Contracts with less than 30 responses are excluded.
Data Source: Disenrollment Reasons Survey
Data Source Description: Survey of members who disenrolled from the contract during the measurement time
frame with the following disenrollment reason codes: disenrollment reason codes:
11 - Voluntary Disenrollment through plan, 13 - Disenrollment because of enrollment in
another Plan, 14 - Retroactive or 99 - Other (not supplied by beneficiary).
Data Time Frame: 01/01/2014 - 12/31/2014
General Trend: Lower is better
Data Display: Percentage with no decimal point
Measure: DME06 - Disenrollment Reasons - Problems with Prescription Drug Benefits and Coverage
(MA-PD, PDP)
Title
Description
Metric: “Problems with Prescription Drug Benefits and Coverage” is a composite of the
following survey questions (question numbers vary depending on survey type):
(a) Did you leave the plan because they changed the list of prescription medicines they
cover?
(b) Did you leave the plan because the plan refused to pay for a medicine your doctor
prescribed?
(c) Did you leave the plan because you had problems getting the medicines your doctor
prescribed?
(d) Did you leave the plan because it was difficult to get brand name medicines?
(e) Did you leave the plan because you were frustrated by the plan’s approval process
for medicines your doctor prescribed that were not on the plan’s list of medicines that
the plan covers?
Each of these questions asked about a reason for disenrollment that was related to
prescription drug benefits and coverage. Scores range from 0 to 100 and a lower mean
indicates that problems with prescription drug benefits and coverage reasons were
endorsed less frequently by disenrollees from your contract.
Exclusions: Contracts with less than 30 responses are excluded.
Data Source: Disenrollment Reasons Survey
Data Source Description: Survey of members who disenrolled from the contract during the measurement time
frame with the following disenrollment reason codes: disenrollment reason codes:
11 - Voluntary Disenrollment through plan, 13 - Disenrollment because of enrollment in
(Last Updated 12/17/2015)
Page 22
The Challenges of Pharmacy Star Ratings • 147
Title
Description
another Plan, 14 - Retroactive or 99 - Other (not supplied by beneficiary).
Data Time Frame: 01/01/2014 - 12/31/2014
General Trend: Lower is better
Data Display: Percentage with no decimal point
Measure: DME07 - Disenrollment Reasons - Problems Getting Information about Prescription Drugs
(MA-PD, PDP)
Title
Description
Metric: “Problems Getting Information about Prescription Drugs” a composite of the following
survey questions (question numbers vary depending on survey type):
(a) Did you leave the plan because you did not know whom to contact when you had a
problem filling or refilling a prescription?
(b) Did you leave the plan because it was hard to get information from the plan -- like
which prescription medicines were covered or how much a specific medicine would
cost?
(c) Did you leave the plan because you were unhappy with how the plan handled a
question or complaint?
(d) Did you leave the plan because you could not get the information or help you
needed from the plan?
(e) Did you leave the plan because their customer service staff did not treat you with
courtesy and respect?
Each of these questions asked about a reason for disenrollment that was related to the
beneficiary’s experiences with getting information about prescription drugs. Scores
range from 0 to 100 and a lower mean indicates that problems with getting information
about prescription drug reasons were endorsed less frequently by disenrollees from
your contract.
Exclusions: Contracts with less than 30 responses are excluded.
Data Source: Disenrollment Reasons Survey
Data Source Description: Survey of members who disenrolled from the contract during the measurement time
frame with the following disenrollment reason codes: disenrollment reason codes:
11 - Voluntary Disenrollment through plan, 13 - Disenrollment because of enrollment in
another Plan, 14 - Retroactive or 99 - Other (not supplied by beneficiary).
Data Time Frame: 01/01/2014 - 12/31/2014
General Trend: Lower is better
Data Display: Percentage with no decimal point
(Last Updated 12/17/2015)
Page 23
148 • AIS’s Management Insight Series
Attachment A: National Averages for Part C and D Display Measures
The tables below contain the average of the numeric values for each measure reported in the 2016 Display
measures.
Table A-1: National Averages for Part C Display Measures
Measure ID
Measure Name
Average
DMC01
Follow-up Visit after Hospital Stay for Mental Illness (within 30 days of discharge)
55%
DMC02
Call Answer Timeliness
82%
DMC03
Antidepressant Medication Management (6 months)
56%
DMC04
Continuous Beta Blocker Treatment
90%
DMC05
Appropriate Monitoring of Patients Taking Long-term Medications
91%
DMC06
Osteoporosis Testing
75%
DMC07
Testing to Confirm Chronic Obstructive Pulmonary Disease
36%
DMC08
Doctors who Communicate Well
91%
DMC09
Call Center – Beneficiary Hold Time
0:20
DMC10
Pneumonia Vaccine
69%
DMC11
Access to Primary Care Doctor Visits
DMC12
Calls Disconnected When Customer Calls Health Plan
DMC13
Pharmacotherapy Management of COPD Exacerbation – Systemic Corticosteroid
72%
DMC14
Pharmacotherapy Management of COPD Exacerbation – Bronchodilator
80%
DMC15
Initiation of Alcohol or other Drug Treatment
33%
DMC16
Engagement of Alcohol or other Drug Treatment
DMC17
Reminders for Appointments
59%
DMC18
Reminders for Immunizations
45%
DMC19
Reminders for Screening Tests
39%
DMC20
Computer Used during Office Visits
85%
DMC21
Computer Use by Doctor Helpful
94%
DMC22
Computer Use Made Talking with Doctor Easier
53%
DMC23
Improving Bladder Control
35%
95%
1.62%
3%
Table A-2: National Averages for Part D Display Measures
Measure ID
Measure Name
Average
DMD01
Timely Receipt of Case Files for Appeals
DMD02
Timely Effectuation of Appeals
DMD03
Calls Disconnected When Customer Calls Drug Plan
DMD04
Call Center – Beneficiary Hold Time
0:20
DMD05
Drug-Drug Interactions
5.7%
DMD06
Diabetes Medication Dosing
0.66%
DMD07
Drug Plan Provides Current Information on Costs and Coverage for Medicare’s Website
100%
DMD08
MPF – Stability
DMD09
Rate of Chronic Use of Atypical Antipsychotics by Elderly Beneficiaries in Nursing Homes
DMD10
Getting Information from Drug Plan
82%
DMD11
Call Center – Pharmacy Hold Time
0:09
DMD12
Plan Submitted Higher Prices for Display on MPF
DMD13
Transition monitoring - failure rate for drugs within classes of clinical concern
2.0%
DMD14
Transition monitoring - failure rate for all other drugs
3.2%
DMD15
Reminders to Fill prescriptions
38%
DMD16
Reminders to Take Medications
22%
(Last Updated 12/17/2015)
86%
92.73%
1.65%
99
17.54%
97
Page 24
The Challenges of Pharmacy Star Ratings • 149
Table A-3: National Averages for common Part C and D Display Measures
Measure ID
Measure Name
Average
DME01
Enrollment Timeliness
DME02
Grievance Rate
2.97
DME03
Disenrollment Reasons - Problems Getting Needed Care, Coverage, and Cost Information (MA-PD, MA-only)
17%
DME04
Disenrollment Reasons - Problems with Coverage of Doctors and Hospitals (MA-PD, MA-only)
26%
DME05
Disenrollment Reasons - Financial Reasons for Disenrollment (MA-PD, MA-only, PDP)
28%
DME06
Disenrollment Reasons - Problems with Prescription Drug Benefits and Coverage (MA-PD, PDP)
11%
DME07
Disenrollment Reasons - Problems Getting Information about Prescription Drugs (MA-PD, PDP)
12%
(Last Updated 12/17/2015)
95%
Page 25
News and Analysis of Medicare Advantage, Medicare Part D and Managed Medicaid
March 27, 2014
Volume 20, Number
6
Medicaid
D and Managed
age, Medicare Part
is of Medicare Advant
News and Analys
Contents
Senate Passes
Patients
Deal to Serve MA
CareMore-Emory erg’ in New Linkages
a Welliceberg” and that
May Be ‘Tip of Iceb
3 Oklahoma
Bare-Bones Medicaid
Medicare Advantage News is your most reliable source for
valuable strategic information to boost revenues, increase
enrollees, cut costs and improve outcomes.
calls the “tip of the
System unit,
industry observer
In a move that one
for its CareMore Health
serve
e terms a “new strategy” 19 that they will work together to
Point, Inc. executiv
tells MAN
Healthcare said March
r, CareMore’s CEO
CareMore and Emory
Georgia. Moreove
ents and exge beneficiaries in
similar arrangem
Medicare Advanta
other states about
negotiations in five
weeks.”
coming
“the
in
that her unit is in
place
not like
additional deal in
Leeba Lessin are
pects to have one
by CareMore CEO
plans
MA
outlined
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provider
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which insurers helped
alliance is
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deals that surfaced
Lessin, the understa
three existing
1). Indeed, notes
be working with
(MAN 4/25/13, p.
and
Emory instead will
of Georgia unit —
start an MA plan.
that Emory won’t
Cross and Blue Shield
with it.
g WellPoint’s Blue
share risk and savings
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when it agreed to
MA plan paymen
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3), it makes sense
care Spe-insurer
for close provider
institutional or chronic
heightened need
starting new MA
tells MAN.
lead to CareMore
as early as 2016, Lessin
agree. And it could
next January,
with provider systems
to get its first patients
cial Needs Plans (SNPs)
ent, which is slated
Emory does
ints.
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She says
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continued on p. 6
Emory is advantag
with highly regarded
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Managed Care Pilot
Bill
Suggests Employer
4 MedPAC
Group MA Plans Should
Bid Like Other MA
Plans
n of
Compariso
Plans
4 Table:
Employer Group MA
And Nonemployer
Plans
Plan Uses Many
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5 Tufts
Stars Improvement
With Providers
CMS Pullback,
PDPs
6 Despite
Second Enhanced
May Nearly Disappear
8 News Briefs
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James Gutman
om
[email protected]
Associate Editor
BJ Taylor
Executive Editor
Jill Brown
Duals
yed OK for CMS
Mich. Awaits DelaSlowly in Starting Its Own
Demo; Ariz. Goes of programs for Medicare-Medicaid dual eligi-l
a Michigan proposa
future direction
An indicator of the
whether to approve
care despite the
when CMS will decide
from physical health
bles could come soon
al health care separate Michigan selected eight health plans
g”
that would keep behavior
, p. 6). When
the process of “finalizin
care (MAN 11/21/13
goal of integrated
state said it was in
months
last November, the
But more than four
CMS.
with
for its duals initiative
(MOU)
obstacle has
of Understanding
tell MAN the major
its Memorandum
industry insiders
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MOU,
no
later, there has been
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plan executive says.
by summer.
significant risk,” one
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date, CMS site visits
new Michigan Medicaid
that to make the October
complicated by a
the situation is further to beneficiaries, with the aid of health
In the meantime,
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Charges will appear as Atlantic Information Services, Inc.
❏ Bill Me $636
11PUB/0616
Atlantic Information Services • 1100 17th Street, NW, Suite 300 • Washington, DC 20036 • 800-521-4323 • www.AISHealth.com