Download Using Demographic Data to Provide Patient

Using Demographic Data to
Provide Patient-Centered Care:
Why Data Collection is Important
Romana Hasnain-Wynia, PhD
Health Research and Educational Trust/AHA
November 3, 2006
Focus on data is good only
insofar that we remember:
“It is not the data, it is what you do with it”
-------Maryland Hospital Indicator Project
“ We can not manage what we can not measure.”
---David Kindig, M.D., M.P.H., University of Wisconsin School of
Medicine
Health Care Should Be
•
•
•
•
•
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Safe
Effective
Patient-Centered
Timely
Efficient
Equitable
Patient-Centered Care
• Incorporates respect for patients’ values,
preferences, and expressed needs
• Is highly customized and incorporates
cultural competence
Equitable
• Providing care that does not vary in quality
because of personal characteristics such
as gender, ethnicity, geographic location
and socio-economic status
Disparities in Health Care
STUDY CHARGE
• Assess the extent of racial and ethnic
differences in healthcare that are
not otherwise attributable to known
factors such as access to care
• Evaluate potential sources of racial
and ethnic disparities in healthcare,
provide recommendations regarding
interventions to eliminate healthcare disparities.
A National Problem
• African Americans are:
– Less likely to have a kidney transplant, surgery for
lung cancer, bypass surgery.
– More likely to have a foot amputation.
– More likely to die prematurely
• Latinos/Hispanics are:
– Less likely to receive pain medications
What about other groups? Chinese? Vietnamese
Pakistanis? Nigerian? Somali? Haitian, etc….
Evidence of Racial and
Ethnic Disparities in
Healthcare
• Disparities consistently found across a wide
range of disease areas and clinical services
• Disparities are found even when clinical
factors, such as stage of disease
presentation, co-morbidities, age, and
severity of disease are taken into account
…..Continued
• Disparities are found across a range of clinical
settings, including public and private hospitals,
teaching and non-teaching hospitals, ambulatory
care settings, etc…
• Disparities in care are associated with higher
mortality among minorities (e.g., Bach et al.,
1999; Peterson et al., 1997; Bennett et al., 1995)
Questions
• WHY and HOW disparities occur
• Which interventions are effective at
reducing or eliminating disparities
• What proportion of observed
disparities are amenable to
improvements in health care
• HOW to collect relevant data
CHANGING DEMOGRAPHICS:
CHANGING NEEDS
Demographic Changes
• The U.S. population grew by 13% between 1990 and 2000.
(Andrulis et al. 2003)
•
Foreign born population living in the US increased by 44%
to 28.4 million people during this period. (U.S. Census Bureau
2002).
•
In 2000, the foreign born population comprised 10 percent of
the total population, its highest since 1930. (U.S. Census Bureau
2002)
•
Over 300 different languages are spoken in the U.S. and nearly
52 million people (19% of the U.S. population) speak a language
other than English at home. (U.S. Census Bureau 2005)
Encounters with LEP Patients
• 80% of hospitals encounter patients with
LEP frequently
• 43% daily, 20% weekly, 17% month
HRET, 2006
Languages That 20% or More of
Hospitals Encounter Frequently
Spanish
Chinese
Vietnamese
Japanese
Korean
Russian
German
French
Arabic
Italian
Laotian
Hindi
Polish
Tagalog
Thai
93%
47%
39%
37%
37%
37%
36%
31%
26%
26%
23%
22%
22%
21%
20%
Source: HRET, 2006
Race/Ethnicity Data
• Why Collect It
• Current Practices
• Barriers
Why Collect Data?
• To monitor quality of care for all
populations
• Target interventions appropriately to
improve health care delivery
Equity
•Domain of “Equity” is not “top of mind” for senior
administrative and clinical leaders.
•Disparities is “not our issue.” They happen “before” and
“after” the hospital.
•Great concern that addressing disparities somehow
acknowledges discrimination or otherwise bad behavior.
Source: 42 key informant interviews:
Bruce Siegel, MD, MPH Planning Grant
for Robert Wood Johnson for Expecting Success, 2004
Equity
Clinical Leadership
N. Lurie, et al. Circulation (2005)
344 Cardiologists:
-34% agree disparities exist overall
-12% believe disparities exist in own hospital
-5% believe disparities exist in own practice
S. Taylor, et al. Annals of Thoracic Surgery (2005)
208 Cardiovascular Surgeons:
-13% believe disparities occur often or very often
-3% believe disparities occur often or very often in own
practice
Why Collect Data On Patient
Race/Ethnicity
Internal Factors
• Valid and reliable data are fundamental building blocks for
identifying differences in care and developing targeted
interventions
• Being responsive to communities: Pressing community
health problems such as disparities in care can be addressed
more effectively if health care organizations and health
professionals build the trust of the community by documenting
accomplishments
• Link race and ethnicity information to quality measures to
examine disparities and undertake targeted interventions
• Ensure the adequacy of interpreter services, patient
information materials, and cultural competency training for staff
Why Collect Data continued…
External Factors
• Reporting to the Joint Commission on
Accreditation of Healthcare Organizations
• Reporting to CMS (payer, purchaser
regulator, insurer, works through QIOs)
• State mandates
Current Practices:
National Survey of Hospitals
80
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40
20
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Use data for QI
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Clerk Eyeballs
Drawbacks to data coll
Who, When, and How: The Current State of Race, Ethnicity, and Primary Language Data Collection in Hospitals, 2004 CMWF
Nuts and Bolts of Data Collection
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•
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Addressing Discomfort
Categories
Staff training
Start the dialogue with the community
before implementing systematic data
collection on race/ethnicity/language
Recommendations For
Standardization
• Who provides the information
• When to collect
• Which racial and ethnic categories to use
• Where and how data are stored
• Address Patients’ Concerns
• Provide Staff training
Common Barriers To
Collecting Data
• Validity and reliability of
data
• Legal concerns
• System/organizational
barriers
• Appropriate categories
• Patients’
perceptions/language and
culture
• Staff discomfort in explicitly
asking patients to provide
this information. *
A Project in Chicago
Using Health Information Technology to
Provide Patient-Centered Care, Improve
Quality and Reduce Disparities
• Valid measures of hospital and physician clinical
performance
• Coordination of care
• Exchange of information between
providers/practitioners and patients
• Improve safety
Project: Adding Race/Ethnicity and other
Patient Demographic Information to Chicago
Community Health Center Clinical
Performance Information Systems
The Partnership:
-Health Research and Educational Trust
-Alliance of Chicago Health Services
-American Medical Association
Funded by the Commonwealth Fund and the Robert Wood
Johnson Foundation
American Medical Association
Convened the Physician Consortium for
Performance improvement, which aims to
provide performance measurement
resources to facilitate clinical quality
improvement programs. The Consortium
developed the Physician Performance
Measurement Sets:
Diabetes, Asthma, Coronary Artery Disease, Heart Failure,
Hypertension, Prenatal Care, Prevention and Immunizations
Alliance of Chicago Health
Services
A group of community health centers with
24 clinical sites throughout Chicago
serving 65,000 clients in 305,000
encounters annually. The Alliance was
chosen by the Bureau of Primary Health
Care to implement EHRs. The Alliance is
integrating the Performance Measures into
the EHRs and creating a data warehouse
through funding from AHRQ.
ADVANCE
The project covers three critical areas
in improving health care delivery:
Adoption of health information technology
(Electronic Health Record Systems) as a tool
to monitor and improve quality of care.
Patient Centered Care (such as respect for patient
values, preferences and needs,
information/education, emotional support and
involvement of family to remove fear and anxiety).
Improving the quality of care for vulnerable
populations through targeted interventions.
What Do We Mean by Linking
Demographic Data to Clinical Data?
Clinical Performance Measures will be linked with
demographic data in the EHRs
A. Will utilize the extract, transfer, and load software developed
by General Electric. (Extraction will occur on a nightly
basis.)
B. The data will be loaded in a clinical data warehouse, which
will be used to generate the clinical performance measure
reports.
C. The reporting process will include the transfer, linking, and
aggregation of the patient demographic data with clinical
data.
Goals:
• Standardize a process for collecting patient
demographic data on patient race, ethnicity,
language, health literacy (education), acculturation
(years lived in the US), and socioeconomic status
(family size, insurance, income).
• Link patient demographic data with national clinical
performance measures in an electronic health record
system.
• Show health care processes and outcomes for
specific conditions stratified by key patient
demographic information (to identify targeted
opportunities for QI).
Adult Diabetes Performance MeasuresCurrent System Captures the following:
Performance
Measure
Hemoglobin A1c
Lipid profile
Fasting
Total Cholesterol
HDL-C
LDL-C
Triglycerides
Influenza Vacc
Foot Examination
Dilated Retinal Eye
Exam
Smoking
Aspirin Use
Provider
Number
Birth Date
Gender
Adult Diabetes Performance Measures-New
System Would Capture the following:
Performance
Measure
Hemoglobin A1c
Lipid profile
Fasting
Total
Cholesterol
HDL-C
LDL-C
Triglycerides
Influenza Vacc
Foot
Examination
Dilated Retinal
Eye Exam
Smoking
Aspirin Use
Provider
number
Birth
Gender
Race
Ethnicity
Lang
Educ
Years in
US
Fam
Size
Contributions
• IOM report, Crossing the Quality Chasm, calls for
“national consensus on comprehensive standards for
the definition, collection, coding, and exchange of
clinical data.”
• IOM report, Unequal Treatment, calls for the
collection and reporting of data on health care
access and utilization by patients’ race, ethnicity,
socioeconomic status, and where possible,
primary language;
Benefits
• Standardize patient demographic data collection.
• Collect clinical performance measures.
• Link patient demographic data to clinical performance measures
in an electronic health record system at clinical sites.
• This work speaks to the growing consensus that clinical quality
improvement efforts should include key patient demographic
data that allow for more targeted and efficient quality
improvement interventions within health care organizations. In
addition, this work will assess the feasibility of using electronic
health record systems as a tool in quality improvement efforts in
community health centers.