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volume nine • number six
november/december 2003
Peer-reviewed Journal of the Academy
of Managed Care Pharmacy
JMCP
JOURNAL OF MANAGED CARE PHARMACY®
Page
513 Retrospective Drug Utilization Review: Incidence of
Clinically Relevant Potential Drug-Drug Interactions
in a Large Ambulatory Population
544 Determinants of the Cost-Effectiveness of Statins
552 Longitudinal Assessment of a Diabetes Care
Management System in an Integrated Health Network
523 Financial Risk Relationships and Adoption of
Management Strategies in Physician Groups for
Self-Administered Injectable Drugs
534 Unmet Needs in the Treatment of Allergic Asthma:
Potential Role of Novel Biologic Therapies
559 Examination of the Evidence for Off-Label Use of
Gabapentin
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■ ORIGINAL RESEARCH
513 Retrospective Drug Utilization Review: Incidence of Clinically Relevant
Potential Drug-Drug Interactions in a Large Ambulatory Population
Catherine C. Peng, PharmD, BCPS; Peter A. Glassman, MBBS, MSC; Iny R. Marks, PharmD;
Curtis Fowler, PharmD; Brenda Castiglione, PharmD; and Chester B. Good, MD, MPH, FACP
523 Financial Risk Relationships and Adoption of Management Strategies
in Physician Groups for Self-Administered Injectable Drugs
Jonathan D. Agnew, PhD; Marilyn R. Stebbins, PharmD; David E. Hickman, PharmD;
and Helene Levens Lipton, PhD
■ SUBJECT REVIEW
534 Unmet Needs in the Treatment of Allergic Asthma: Potential Role
of Novel Biologic Therapies
William W. Storms, MD
■ FORMULARY MANAGEMENT
544 Determinants of the Cost-Effectiveness of Statins
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JMCP
Journal of Managed Care Pharmacy 507
ORIGINAL RESEARCH
Retrospective Drug Utilization Review: Incidence of Clinically Relevant
Potential Drug-Drug Interactions in a Large Ambulatory Population
CATHERINE C. PENG, PharmD, BCPS; PETER A. GLASSMAN, MBBS, MSc; INY R. MARKS, PharmD;
CURTIS FOWLER, PharmD; BRENDA CASTIGLIONE, PharmD; and CHESTER B. GOOD, MD, MPH, FACP
ABSTRACT
OBJECTIVE: To determine the incidence of clinically relevant potential drug-drug
interactions (DDIs) in a large population of ambulatory patients utilizing a computerized, retrospective drug utilization review (DUR) program followed by clinical
pharmacist audit.
METHODS: The drug claims database included approximately 2.9 million patients
with more than 30 million prescriptions dispensed in the 12-month period from
September 2001 through August 2002. Cases were identified by a computerized,
retrospective DUR program with embedded triggers to detect 69 prespecified
potentially serious DDIs, with "serious" defined as an interaction that would likely require a change in therapy or use of additional clinical or laboratory monitoring. Two types of automated, computerized assessments were conducted: the
first simply detected coprescribed drug pairs, and the second assessment used
more sophisticated filters to reduce false positive alerts for coprescribed drug
pairs. Clinical pharmacist audit then determined the final incidence of clinically
relevant warnings; in this audit, coprescribed drug pairs were defined as clinically relevant if they could cause potentially serious DDIs.
RESULTS: Eighteen drug pairs had insufficient cases for inclusion, leaving 51
drug pairs for evaluation. A total of 244,703 cases of potential DDIs were identified (0.8% of total prescription claims) by simple automated screens. More
sophisticated DDI filters reduced the 244,703 potential DDIs by 70.8%, to a total
of 65,544 pairs (0.2% of total prescription claims). Clinical pharmacist review
reduced the number of potential DDIs by an additional 80.6%, to 12,722 drug
pairs (0.04% of total prescription claims) deemed clinically relevant. The combination of sophisticated DDI filters and clinical pharmacist review reduced the
incidence of potentially serious DDIs by 94.3%.
CONCLUSION: The incidence of potentially serious DDIs is relatively low (less than
1%) among ambulatory patients; however, the incidence depends on the method
of case finding. Retrospective DUR programs, especially those with additional
automated filters or that utilize additional pharmacist review, appear to be important screening tools in determining true rates of coprescribed drug pairs that can
lead to potentially serious DDIs.
T
he Institute of Medicine’s report, “To Err Is Human,
Building a Safer Health System,” heightened awareness
of reducing preventable medical errors.1 One important
subset is medication errors, in part, because they are relatively
common,2-3 and, in part, because they increase the risk for
adverse drug events.2 The latter is thought to be responsible for
nearly 7,000 lives lost and up to an estimated $136 billion
spent annually in additional health care costs.1,4
Studies evaluating medication errors have taken a broadbased approach at case finding and usually have limited the
evaluations to hospitalized patients or a small cohort of outpatients.5-13 While the relevance of this type of research should not
be underestimated, it does not address concerns about medication errors that might occur in large outpatient populations,
where most prescribing occurs in daily practice.
One such group of errors receiving increased focus involves
potentially serious drug-drug interactions (DDIs). However, little has been done to categorize the incidence of potential DDIs
of any severity in large outpatient populations. Currently available estimates of incidence vary widely, depending on the
method of defining and finding potential DDIs and the method
of defining the population assessed. Published studies have
reported proportions of potential DDIs ranging from 2.2% to
30% in hospitalized patients and from 9.2% to 70.3% in ambulatory patients,14,15 although evaluations yielding the highest
estimates have sometimes included theoretical interactions in
addition to documented interactions.
Authors
KEYWORDS: Drug utilization review, Drug-drug interactions, Medication errors,
Ambulatory care
J Managed Care Pharm. 2003;9(6):513-22
CATHERINE C. PENG, PharmD, BCPS, is clinical specialist; INY R. MARKS,
PharmD, is clinical product development specialist; CURTIS FOWLER, PharmD, is
manager of clinical product development; and BRENDA CASTIGLIONE, PharmD,
is director of clinical services, Clinical Services Department, Eckerd Health Services,
Pittsburgh, Pennsylvania. PETER A. GLASSMAN, MBBS, MSc, is staff physician,
Division of General Internal Medicine, VA Greater Los Angeles, West LA Campus,
Los Angeles, California, and associate professor of medicine, University of
California Los Angeles School of Medicine; CHESTER B. GOOD, MD, MPH,
FACP, is chairperson of the Medical Advisory Panel, Department of Veterans Affairs
and staff physician, Division of General Internal Medicine, VA Pittsburgh Health
Care System, Pittsburgh, Pennsylvania, and associate professor of medicine and
pharmacy, University of Pittsburgh School of Medicine.
AUTHOR CORRESPONDENCE AND REPRINT REQUESTS: Iny Marks,
PharmD, Eckerd Health Services, 620 Epsilon Dr., Pittsburgh, Pennsylvania 15238.
Tel: (800) 814-6600, ext. 5023; Fax: (412) 968-2691; E-mail: [email protected]
Copyright© 2003, Academy of Managed Care Pharmacy. All rights reserved.
www.amcp.org Vol. 9, No. 6 November/December 2003
JMCP
Journal of Managed Care Pharmacy 513
Retrospective Drug Utilization Review:
Incidence of Clinically Relevant Potential Drug-Drug Interactions in a Large Ambulatory Population
The main issues in accurately determining the incidence of
DDIs in ambulatory patients are primarily 2-fold. First, evaluations should be prospective and based on a prespecified set of
drug pairs. Second, large populations of patients are required to
find sufficient DDIs to establish incident rates. In addition to
these 2 necessary factors, sufficient technology is required to
preliminarily evaluate and categorize potential cases of DDIs.
Moreover, some type of secondary audit should occur to confirm the findings of preliminary assessments.
Claims-based analysis using computerized, retrospective
drug utilization review (DUR) offers a powerful tool to better
understand the incidence of potential DDIs as well as other
types of potential medication errors.16 Yet, despite the popularity of such programs in both the private and public health care
sectors, very little data are available on the detection of potential DDIs in ambulatory patients.17
Several studies have attempted to assess the effectiveness of
small and focused DUR programs.9,10,12,13,18 For instance, one
recent study by Curtis et al.19 looked at overlapping prescriptions
of drugs that may prolong the cardiac QT interval, a measure of
the ventricular refractory period on an electrocardiogram associated with life-threatening ventricular arrhythmias. Still, there are
little available data on specific DDIs found in various populations. Sharing these data would not only assist in determining
which coprescribed drug pairs to target for intervention but also
would assist in developing and tracking the success of DUR intervention programs across the United States.
Our study presents data on more than 50 potentially serious
DDIs found in a subset of approximately 2.9 million persons,
covered mainly by self-funded employer groups and health
plans, over the course of 1 year. The study describes the case
finding rates for potential drug interaction pairs, generated by a
computerized, retrospective DUR system using programmed
criteria, before and after pharmacist assessment. It is our hope
that detailing the data on case findings of potential DDIs at various steps in the detection process will assist others in determining how to develop and optimize such DUR programs.
■■ Methods
The Retrospective DUR Program
A pharmacy benefits management (PBM) company used a computerized, retrospective DUR program to monitor and intervene
in cases of potentially serious DDIs. This DUR program was
established in 1999 and continues as an ongoing program within the PBM; however, for the purposes of this study, a 1-year
period of time was chosen to determine the incidence of potentially serious DDIs. This program does not involve electronic or
other alert messages sent to dispensing pharmacies at the point
of sale and is separate from such concurrent alerts. The database
for the retrospective DUR program included claims submitted
for prescription medications dispensed from more than 56,000
community pharmacies and 3 mail-service facilities in the PBM’s
514 Journal of Managed Care Pharmacy
JMCP
November/December 2003
pharmacy network. Claims data were updated daily. The DUR
program assessed prescription claims each night, allowing for
case review within 1 business day after claims were submitted.
Available data on prescriptions included selected patient demographics, physician identification, and the name, strength, and
quantity of the medications dispensed.
Interventions on potential DDIs were routinely conducted
by mail, with alert letters sent to the prescribing clinicians. The
alert letter not only described the potential interaction but also
the underlying mechanism of that interaction, the possible consequent adverse drug event(s), and recommendation(s) on how
the interaction may be avoided or managed. For example, the
alert letter on the potential interaction between amiodarone and
warfarin informs providers that amiodarone can increase the
hypoprothrombinemic response by decreasing the hepatic
clearance of warfarin and, hence, the addition of amiodarone to
existing warfarin therapy can increase the prothrombin time by
50% to 100%. The letter continues with a recommendation to
reduce the warfarin dose by 30% to 50%.
Clinically relevant coprescribed drug pairs were defined as
those that could cause a potentially serious DDI. A DDI was
defined by the following standard: a “pharmacological or clinical response to the administration of a drug combination different from that anticipated from the known effects of the
2 agents when given alone. The clinical result of a DDI may
manifest as antagonism, synergism, or idiosyncratic.”20
For this DUR intervention program, we utilized standard
references20-24 to determine possible clinically relevant coprescribed drug pairs, with specific drug pairs then chosen for
inclusion into the restrospective DUR program by PBM clinical
pharmacists in collaboration with an independent advisory
board of practicing physicians and external clinical pharmacists. The advisory board consisted of 5 physicians with
specialties in general internal medicine (one of whom had a
background in pharmacology), gastroenterology, and endocrinology and 2 external clinical pharmacists. Priority was given to
coprescribed drug pairs that were either absolutely contraindicated or that, when an interaction occurred, were more likely to
cause a serious interaction.
A “serious” interaction was defined as potentially life or
organ threatening, as described in at least 1 commonly used
standard drug safety reference.20-24 Additionally, a “serious”
interaction would likely require a change in therapy or require
additional clinical or laboratory monitoring.
Although the underlying mechanisms of interactions and
subsequent harm varied among the drug pairs, the common
theme in choosing drug pairs was to include those that have the
potential to result in emergency treatment, hospitalization,
permanent harm, or death. The general classification and
definition of the categories of coprescribed drug pairs are
shown in Table 1. Classification into the 6 categories was based
on the management of the potential DDI.
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■■ Case Finding of Drug Pairs
Case finding of potentially interacting drug pairs proceeded
through 3 assessments. The initial 2 assessments were automated, and the third was a manual review conducted by 4 trained
clinical pharmacists. The pharmacists were trained by a senior
pharmacist who was also the clinical program operations manager. The training included a structured curriculum that utilized
standardized reference materials on identifying, classifying, and
managing DDIs as well as a proprietary manual on DUR protocols.20-24 Pharmacists were also specifically trained to evaluate the
automated alerts to look for specific inclusion or exclusion criteria for further intervention, as discussed below.
The automated software first searched the claims database to
preliminarily identify instances where patients may have been
receiving overlapping prescriptions for the 2 specified medications in a given drug pair. In practical terms, this first step of
automation provided an initial incidence of 2 potentially dangerous coprescribed drugs. For instance, one system check
reviewed individuals with active prescriptions for warfarin and
fluconazole, a drug pair with a known DDI.
Second, for each possible concomitant drug pair, a set of
additional automated filters was used to help improve accuracy
by determining which pairs were likely to be clinically relevant
(i.e., have a true potential to cause a clinically relevant interaction). For example, 1 basic filter ensured that there were at least
5 days of potential overlap for specific drug pairs. Therefore,
this filter would exclude any patient who was taking warfarin
chronically and received only a single dose of fluconazole for
the treatment of candidiasis.
These systematic filters varied depending on the drug pair
targeted, but the goal of each set of filters was to reduce clinically irrelevant cases (i.e., to increase specificity). Other filters at
this stage included assessing total drug dose (e.g., methotrexate
of at least 15 mg per week with a nonsteroidal anti-inflammatory drug, or simvastatin of at least 20 mg daily with amiodarone) and duration of drug therapy (e.g., carbamazepine with
a duration of therapy for at least 90 days and a macrolide antibiotic, or warfarin with a duration of therapy for at least 90 days
and a thyroid product).
After the automated filters identified potentially relevant
drug pairs, a clinical pharmacist reviewed the remaining cases.
The goal was to ensure that any intervention requiring clinician
contact involved a high likelihood of a true positive warning.
Common reasons for cases to result in a subsequent pharmacist
intervention or no pharmacist intervention (i.e., sending an
alert letter or not sending an alert letter to clinicians on a potential DDI) may be found in Table 2. As a matter of due diligence,
the reviewing pharmacist confirms the duration of overlap for
the coprescribed drug pairs as well as identifies any prior concomitant use of a drug pair and prior warnings to the relevant
clinician(s) concerning that drug pair. Thus, an alert letter
would not be sent if a prescribing clinician had already been
TABLE 1
Classification of Drug-Drug
Interaction Pairs
Category Definition
Examples
I
Drug-drug interaction pairs are
contraindicated in at least 1
reference or product package insert.
Sildenafil – Nitrate
Ritonavir – Quinidine
II
Avoid combination of drugs, if possible,
unless benefits outweigh risks or neither
drug can be discontinued.
HMG CoAs* – Gemfibrozil
Clonidine – Beta-blocker
III
Drug-drug interaction is not specific to
all drugs in a therapeutic class; therefore,
may use an alternative drug in the same
class.
Macrolide antibiotics –
HMG CoAs
Warfarin – Sulfonamides
IV
At least 1 of the drugs requires regular
Digoxin – Loop diuretics
monitoring of serum levels or laboratory Warfarin – Amiodarone
tests; dosage adjustment may be required.
V
Drug-drug interaction that may cause
increased levels in 1 drug, which may
or may not reach toxic levels. Therefore,
therapy requires monitoring for signs of
toxicity or lack of efficacy; dosage
adjustment may be required.
Verapamil – Beta-blockers
Rifampin – Oral
contraceptives
VI
Monitor for changes when initiating or
discontinuing drug therapy as likelihood
of an interaction is increased during
such times; dosage adjustment may
be required.
Warfarin – Thyroid
products
Digoxin – Propafenone
*HMG CoAs = HMG CoA reductase inhibitors.
informed of the potential interaction for the same patient within a period of 3 months.
Data on results of pharmacist interventions are maintained
in a longitudinal database that is part of the DUR system. For
those interventions that were considered clinically relevant
based on pharmacist review, an alert letter was sent by regular
mail within 24 hours of review. The pharmacist review provides
the closest estimation of a gold standard for the true incidence
of clinically relevant coprescribed drug pairs within the pertinent patient population.
■■ Data Analysis
There were 69 active drug pairs in the retrospective DUR program during the study period; however, for the present study,
18 drug pairs were excluded for the following reasons: (1) there
were no initial case finding of the coprescribed drug pairs in the
claims database, (2) there were fewer than 10 initially identified
cases and no pharmacist interventions, or (3) the drug pairs had
been in the system for less than 1 year and had fewer than 100
initial case findings. Excluded drug pairs, along with the reason
for exclusion, are shown in Table 3.
Incidence of clinically relevant potential interactions in the
study population was assessed in 3 ways, utilizing 2 denomina-
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TABLE 2
Common Examples of Why Alert Letters
Were Sent or Not Sent to Physicians
Alert Letter Sent to Physician(s)
(Pharmacist Intervention)
No Alert Letter Sent to Physician(s)
(No Pharmacist Intervention)
Multiple physicians involved with
the prescribing of medications with
potential DDIs
Patient has been maintained on both
medications in a drug pair for an
extended period of time, with time
periods specific for each drug pair
Multiple pharmacies involved with
the dispensing of potentially
interacting medications
Prior intervention (alert letter sent to
the relevant clinician) within the past
3 months
Greater than a specified number of
days overlap between potentially
interacting medications, with days
overlap specific to each drug pair
Past response from a clinician that
indicates the patient is being closely
monitored for a potential DDI
No previous history of an intervention Past response from clinician that
(alert letter sent to physician) for a
indicates the combination is
potential DDI in a patient
medically necessary (benefits outweigh risks)
TABLE 3
Drug-Drug Interaction Pairs
Excluded From Analysis
Drug Pairs With No Initial Case Findings
MAOIs* – Anorexiants
Penicillins – Tetracyclines
Protease inhibitors – Ergot alkaloids
Ritonavir – Amiodarone
Ritonavir – Clozapine
Ritonavir – Bepridil
Ritonavir – Quinidine
Methotrexate – Penicillins
Bosentan – Cyclosporine
Warfarin – Clofibrate
Drug Pairs With <10 Initial Case Findings and No Pharmacist
Intervention
Cyclosporine – Rifampin
Meperidine – MAOIs
Protease inhibitors – Rifabutin
Protease inhibitors – Rifampin
Selegiline – Meperidine
Drug Pairs With <100 Initial Case Findings and <1-Year-Old in the
Retrospective DUR System
Protease inhibitors – Oral contraceptives
Methotrexate – Probenecid
Bosentan – Glyburide
*MAOIs = monoamine oxidase inhibitors.
tors. First, we evaluated incidence as the number of cases
(i.e., detected drug pairs) per 1,000 paid prescription claims for
all medications and per 1,000 utilizing members (patients).
Claims that were rejected or were reversed within 1 business
day were not included. Second, we evaluated the incidence as
the number of drug pairs, following automated filtering by the
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retrospective DUR program, using the same denominators.
Finally, we evaluated the number of potential interactions
deemed clinically relevant by clinical pharmacist review and
used the same denominators to calculate the incidence.
Paid prescription claims, which included both new and
refilled drugs for eligible members in the study population,
were reviewed for potential inclusion during the 1-year study
period from September 1, 2001, through August 31, 2002.
We calculated an average for the number of eligible members
and for the number of utilizing members (patients) over the
course of the study period because the actual population varied
by month, depending on enrollment changes among the various
pharmacy benefit plans.
■■ Results
The study population contained an average of 2,889,000 members (48% male) that were eligible for the retrospective DUR
program during the 12-month study period from September 1,
2001, through August 31, 2002; of those individuals,
2,026,000 members (70% of eligible members) had utilized
their prescription benefits at least once over the study time
period and, thus, were included for screening of clinically relevant potential DDIs. The total number of prescription claims
utilized by those individuals was 30,174,549.
Over the course of 1 year, the first automated assessment
found 244,703 cases of potential interactions for the 51 prespecified drug pairs out of a total of 30,174,549 prescription
claims (0.8%) and for 2,026,000 patients (12.1%) (Table 4).
Systematic software filters reduced this count from 244,703 to
65,544 cases (27% of those drug pairs initially identified), giving a revised overall incidence of 2 per 1,000 prescriptions
(0.2%) and 32 per 1,000 patients (3.2%).
Pharmacist reviewers evaluated the 65,544 cases and, of
those, 12,722 cases (6% of those drug pairs initially identified)
were considered to be potentially clinically relevant (i.e., true
positive alerts), requiring an intervention with the relevant prescriber(s). Thus, the final incidence was 0.4 per 1,000 claims
(0.04%) and 6.3 per 1,000 patients (0.6%) (Table 4).
Among all drug pairs, the overall true positive case finding
rate (percentage of cases resulting in intervention divided by
cases reviewed by a pharmacist) was 19% (12,722 of 65,544
cases; range 0% to 100% for each specific drug pair), which led
to 22,364 alert letters sent to relevant prescribing clinicians over
the course of the year. The true positive case finding rates by
individual drug-pair categories for cases reviewed by a pharmacist (see Table 1 for definition of categories) were as follows:
65% for Category I drug pairs, 21% for Category II drug pairs,
50% for Category III drug pairs, 10% for Category IV drug
pairs, 21% for Category V drug pairs, and 9% for Category VI
drug pairs. Table 5 shows the top 10 drug interaction pairs by
the incident rate per 1,000 prescription claims, after clinical
pharmacist review.
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Incidence of Clinically Relevant Potential Drug-Drug Interactions in a Large Ambulatory Population
TABLE 4
Results of Investigation of Potential Drug-Drug Interactions From September 1, 2001, to August 31, 2002
Coprescribed Drug Pairs
Drug 1
Digoxin
Warfarin
HMG CoAs
Verapamil
Warfarin
Potassium-sparing diuretics
Digoxin
Digoxin
Clonidine
Macrolide antibiotics
Sumatriptan
Methotrexate
Digoxin
Digoxin
Warfarin
Warfarin
Lithium
Warfarin
Verapamil
Warfarin
Warfarin
Theophylline
Warfarin
Warfarin
Warfarin
TCAs
Methotrexate
Sildenafil
Verapamil
Selegiline
Sibutramine
Carbamazepine
Digoxin
Theophylline
Warfarin
Theophylline
Allopurinol
Cyclosporine
Methotrexate
Rifampin
Ketoconazole
Amiodarone
Selegiline
Lovastatin
Warfarin
Rifampin
Ergot alkaloids
MAOIs
MAOIs
MAOIs
MAOIs
Category
Drug 2
Loop diuretics
Thyroid products
Gemfibrozil
Beta-blockers
Amiodarone
Potassium
Verapamil
Amiodarone
Beta-blockers
HMG CoAs
SSRIs
NSAIDs
Propafenone
Quinidine
Sulfonamides
Quinidine
NSAIDs
Fluconazole
Carbamazepine
Barbiturates
Cimetidine
Fluoroquinolones
Metronidazole
Zafirlukast
Erythromycin
Clonidine
Sulfonamides
Nitrates
Quinidine
SSRIs
SSRIs
Macrolide antibiotics
Cyclosporine
Macrolide antibiotics
Capecitabine
Cimetidine
Azathiopurine
Phenytoin
Salicylates/aspirin
Oral corticosteroids
H2RAs
Quinidine
Venlafaxine
Cyclosporine
17-akyl androgens
Oral contraceptives
Macrolide antibiotics
SSRIs
Amphetamines
Sumatriptan
TCAs
Total
HMG CoAs = HMG CoA reductase inhibitors.
MAOIs = monoamine oxidase inhibitors.
IV
VI
II
V
IV
II
IV
IV
II
III
V
V
VI
IV
III
IV
IV
IV
II
VI
III
II
II
III
IV
II
V
I
V
II
II
II
V
III
IV
VI
II
IV
II
V
V
IV
I
V
IV
V
III
I
I
II
I
Number of
Number of
Number of
Coprescribed
Coprescribed
Initial
Drug Pairs
Coprescribed Drug Pairs
After
Clinically Relevant
Drug Pairs
Automated
by Pharmacist
Identified by
Filters
Review
DUR System
True
Positive
Rate of
Case
Finding
(%)*
Incidence
per 1,000
Patients†
Incidence
per
1,000
Prescription
Claims†
77,237
36,733
14,627
13,959
13,654
13,306
13,108
11,166
10,393
9,459
6,210
4,289
2,802
2,390
2,286
1,295
1,187
910
908
775
772
767
746
565
496
463
447
444
372
342
335
326
276
226
222
220
182
147
134
129
89
83
73
37
31
30
20
18
12
4
1
10,872
12,475
1,937
2,225
6,141
4,579
834
4,001
1,735
7,955
3,083
256
799
534
1,714
337
523
612
312
269
319
548
644
200
360
185
350
373
40
24
224
246
109
91
137
80
85
63
3
88
74
45
4
2
16
12
10
9
7
2
1
853
1,095
628
413
602
533
73
335
278
4,453
695
31
64
18
547
28
284
138
52
29
54
200
224
30
162
25
120
242
8
9
115
169
8
52
24
8
12
5
0
27
24
12
1
1
6
11
10
7
4
2
1
8
9
32
19
10
12
9
8
16
56
23
12
8
3
32
8
54
23
17
11
17
36
35
15
45
14
34
65
20
38
51
69
7
57
18
10
14
8
0
31
32
27
25
50
38
92
100
78
57
100
100
0.4210
0.5404
0.3100
0.2038
0.2971
0.2630
0.0360
0.1653
0.1370
2.1977
0.3430
0.0153
0.0316
0.0089
0.2700
0.0138
0.1402
0.0681
0.0256
0.0143
0.0267
0.0987
0.1106
0.0148
0.0799
0.0124
0.0592
0.1194
0.0039
0.0044
0.0567
0.0834
0.0039
0.0257
0.0118
0.0039
0.0060
0.0025
0.0000
0.0133
0.0118
0.0060
0.0004
0.0004
0.0029
0.0054
0.0049
0.0034
0.0020
0.0010
0.0004
0.0283
0.0363
0.0208
0.0137
0.0200
0.0177
0.0024
0.0111
0.0092
0.1476
0.0230
0.0010
0.0021
0.0006
0.0181
0.0009
0.0094
0.0046
0.0017
0.0010
0.0018
0.0066
0.0074
0.0010
0.0054
0.0008
0.0040
0.0080
0.0003
0.0003
0.0038
0.0056
0.0003
0.0017
0.0008
0.0003
0.0004
0.0002
0.0000
0.0009
0.0008
0.0004
0.0000
0.0000
0.0002
0.0004
0.0003
0.0002
0.0001
0.0001
0.0000
244,703
65,544
12,722
19
6.2779
0.4216
H2RAs = histamine-2 receptor antagonists.
NSAIDs = nonsteroidal anti-inflammatory drugs.
SSRIs = selective serotonin reuptake inhibitors.
TCAs = tricyclic antidepressants.
* Case finding was determined by the number of coprescribed drug pairs considered clinically relevant by pharmacist review. The true positive rate of case finding was defined as the percentage of
cases resulting in an intervention divided by total number of cases reviewed by a pharmacist for each drug pair (i.e., number of cases found by automated filters).
† The incidence was calculated by dividing the case finding rate, per pharmacist review, by eligible patients (2,026,000) or by prescription claims (30,174,549).
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TABLE 5
Top 10 Drug-Drug Interaction Pairs by Incidence per 1,000 Prescription Claims*
Coprescribed Drug Interaction Pairs
Number of Cases
Found by Pharmacist
Review† (n)
Incidence
per 1,000
Prescription Claims*
True Positive Rate
of Case Finding‡ (%)
Macrolide antibiotics
HMG CoAs
4,453
0.1476
56
Warfarin
Thyroid drugs
1,095
0.0363
9
Digoxin
Loop diuretics
853
0.0283
8
Sumatriptan
SSRIs
695
0.0230
23
HMG CoAs
Gemfibrozil
628
0.0208
32
Warfarin
Amiodarone
602
0.0200
10
Warfarin
Sulfonamides
547
0.0181
32
Potassium-sparing diuretics
Potassium
533
0.0177
12
Verapamil
Beta-blockers
413
0.0137
19
Digoxin
Amiodarone
335
0.0111
8
HMG CoAs = HMG CoA reductase inhibitors.
SSRIs = selective serotonin reuptake inhibitors.
* The incidence was calculated by dividing the case finding rate, after pharmacist review, by total prescription claims (30,174,549).
† Case finding was determined by the number of coprescribed drug pairs considered clinically relevant by pharmacist review.
‡ The true positive rate of case finding was defined as the percentage of cases resulting in an intervention divided by total number of cases reviewed by a
pharmacist for each drug pair (i.e., number of cases found by automated filters).
■■ Discussion
Medication errors may have significant clinical and economic
impact. While a medication error does not necessarily lead to an
adverse drug event,25 it is estimated that 28% to 56% of adverse
drug events are preventable.5,26-28 Among such errors, there is little doubt that the coprescribing of potentially interacting drugs
can have devastating consequences.29 However, the incidence of
such potential DDIs serious enough to lead to hospitalization or
another measurable and serious adverse event remains unclear.
Composite estimates of serious DDIs have been around 2%
to 3%,14,27 although a review by Jankel et al. found that the incidence may vary widely, with estimates from 2% to 17%,
depending on the population assessed.14 The incidence of overlapping QT-interval-prolonging drugs found by Curtis et al. was
9.4%, but that figure, as pointed out by the authors, includes
pairs with questionable clinical importance, and the assessment
did not involve manual audit.19 Among the large and diverse
outpatient population we assessed, we found that the incidence
of clinically relevant potential DDIs was most likely between
6 and 32 cases per 1,000 patients (0.6% to 3.2%), depending
on the type of audit method utilized (automation with and
without pharmacist review).
Unfortunately, there are little supportive data on the incidence of potential DDIs in other large ambulatory populations.
Few published studies have determined such errors exclusively,
with most aggregating various types of potential medication
errors. Many times, the determination of medication errors
found in studies has been part of a planned intervention that
might include medication selection or dosage assessment,30-32
laboratory monitoring,13,33,34 or inappropriate prescribing.12-13
Moreover, most studies on medication errors have involved
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interventions in hospitalized or institutionalized patients, but
not in outpatients.2,7,13,29,31,35-37
The available studies that have focused on potential DDIs in
the outpatient setting have had methodological problems or
other limitations that prevent epidemiological assessment.38,39
The study by Landorf et al. used retrospective case finding to
assess 276 emergency room patients and found that 15% had a
potential for a DDI.39 The study, while intriguing, was too small
to be generalizable.
Research on ambulatory patients has often focused on either
one or relatively few types of interactions.33,40-43 For instance,
McMullin et al. assessed the incidence of dangerous coprescribed drug pairs involving cisapride, before and after a DDI
screening program,42 and Schiff et al. looked at the prescribing
of potassium to patients with high serum potassium levels.33
These assessments found the incident rates of DDIs to be
around 2%. More recently, Curtis et al. studied the overlap of
coprescribed QT-interval-prolonging agents in approximately
5 million outpatients and found an incidence of 9.4%.19 This
important study, which also used a claims database and retrospective utilization review, included at least some interactions
that would not be listed as “serious” in standard references.
Thus, it is difficult to compare our results to those findings.
The lack of reliable population data has implications for
drug safety improvement programs since, logically, intervention
protocols should first and foremost focus on the most common
serious coprescribing errors in a population. Clearly, it is difficult to optimize existing technology and methods of intervention without understanding how often a problem, or a potential
problem, occurs. Surprisingly, there are little data from private
or public health care sectors on the incidence of potential med-
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ication errors that cause concern even though reliance on retrospective DUR programs is widespread.
As Schulman et al. euphemistically noted, the literature on
the benefit of DUR is “underdeveloped,”44 echoing the findings
of Soumerai and Lipton, who found that computer-based DUR
programs have been “implemented without satisfactory evidence
of . . . efficacy and safety.”17 Even so, DUR programs rapidly
expanded into general use after 1990, when the Omnibus Budget
Reconciliation Act (OBRA ’90) mandated states to provide such
reviews for ambulatory Medicaid patients.45,46 Programs vary
widely not only by the types of interventions performed but also
by the frequency of reviews. These differences mitigate the potential for improving drug safety because, if for no other reason,
there are little shared data among DUR users.
One of the most comprehensive assessments of medication
errors in a large outpatient population has been the work by
Monane et al.12 That study attempted to determine whether a
computerized DUR intervention system could improve quality
of pharmaceutical care in an elderly population. The intervention alerted pharmacists, trained in geriatrics, of potentially
inappropriate medication use. The pharmacists subsequently
contacted the prescribing physicians to inform them of the alert
and discuss possible treatment alternatives. Based on their
results (24% rate of change), Monane et al. concluded that
interventions driven by an integrated DUR computer system
and pharmacists contacting physicians improved prescribing
patterns and increased quality of care.
We hope that our research, along with findings already published by Monane et al.,12 and, most recently by Curtis et al.,19
will increase awareness about the utility of using claims-based
DUR programs to catalog the type and severity of various prescribing errors among ambulatory populations. We obviously
would encourage other health care systems and PBM companies
to release data on the incidence of coprescribing errors, however determined. Without such data, it is difficult to assess the
success of various programs and intervention methods.
The present study has other important implications for
those who wish to develop and optimize targeted DDI warning
systems, regardless of whether or not utilization review is
prospective, concurrent, or retrospective. As Peterson and Bates
have noted, a high number of warnings that are not clinically
relevant, or “noise,” may lead to alert fatigue.27
Our data show how threshold points for sending an alert can
change the proportion of clinically relevant alerts. More specifically, if an alert letter or an automated electronic warning, such
as those found in some physician order-entry systems, were to
be triggered at our highest sensitivity point, providers would be
likely to receive many irrelevant warnings.
For example, the retrospective DUR program’s simplest
automated system on active coprescriptions for digoxin and
quinidine would have sent warnings to clinicians 2,390 times,
while the more sophisticated automated system decreased the
warnings by 78% to 534. Furthermore, if the true positive
warning “signal” was best approximated by the pharmacist
review, the number of true alerts was 18 (99% reduction of the
initial 2,390 warnings). Put another way, pharmacist review in
addition to the sophisticated automated DUR system resulted in
a “signal”-to-“noise” ratio of nearly 1 in 30 (534 divided by 18)
instead of a ratio of nearly 1 in 130 (2,390 divided by 18) with
the simplest automated system.
Additionally, in order to decrease “noise” to providers, an
alert letter would not be sent if one had already been generated
for the same potential DDI case over the past 3 months. Hence,
the importance of programs and protocols that identify relevant,
potential DDIs while decreasing false positive alerts cannot be
overemphasized. One concern that our study raises is that studies depending only on computerized systems to determine incidence may overestimate potential DDIs or other medication
errors. Clearly, further research is required in this regard.
This raises the obvious question of what constitutes a true
positive—or even a false positive—warning. Although a complete discussion is beyond the scope of the current paper, evidence suggests that clinicians often ignore or override serious
and potentially life-threatening DDI alerts.13,37,47 Thus, clinical
relevance, from a safety perspective, cannot be solely determined by a clinician’s perspective, and we would argue that an
alert is clinically relevant based on the potential severity and/or
incidence of an actual subsequent adverse event from a DDI and
not on whether the receiving clinician concurs with the warning. For instance, warnings about the coadministration of sildenafil and a nitrate, tranylcypromine and an amphetamine, or
ritonavir and amiodarone are relevant, regardless of the subsequent clinical action because of their absolute contraindications
and subsequent adverse events.
Even so, in many circumstances, the actual clinical significance of a warning will depend on patient comorbidities, preferences for treatment, provider characteristics, and a balancing
of risks and benefits of particular drug combinations. For example, in some instances involving severe vascular disease, the
provider and patient may concur that the potential benefit of
combining an HMG CoA reductase inhibitor and a fibric acid
derivative to adequately address a severe underlying dyslipidemia and, thus, reduce the risk of subsequent vascular events,
outweighs the risk of myopathy and rhabdomyolysis when the
2 medications are taken together.
Therefore, our definition of clinical relevance of an alert is
predicated primarily on potential severity and incidence of an
interaction and not on the clinical significance. For instance,
our top 10 potential DDIs by incidence (Table 5) might not correspond to the top 10 potential DDIs that prescribing physicians perceive as most relevant. Clinical significance would perhaps be better assessed by evaluating clinical actions in
response to a warning. Thus, we can only speculate until further studies on this issue are available.
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Nonetheless, using our perspective on clinical relevance, the
true positive warning rates after a pharmacist’s review varied by
both drug pairs (Table 4) and drug pair classification scheme
(Table 1). One concern when developing such categorizations is
that there is no singular consensus about a standardized classification scheme.48 Indeed, while clinicians will no doubt disagree about clinical significance, there is also a lack of uniformity about potential severity of DDIs across commonly used
reference materials,49 making classifications of such interactions
even more difficult. In any case, our data suggest that there may
be differences in the clinical relevance of automated alerts and
that varying levels of manual input are needed to ferret out the
true positive from the false positive warnings. In fact, the benefit of retrospective claims-based analysis is that such programs
allow clinical pharmacists to reduce the number of irrelevant
alerts.45 We expect that such findings can ultimately guide technological improvements in automated case finding.
wanted to know how many prescription claims and how many
patients might require an intervention. Thus, it is important to
note that the incidence would change if we defined our population differently, such as in patients who filled at least 2 prescriptions, in patients who filled 2 or more overlapping drugs,
or in patients who used at least 1 of the target drugs in a given
drug pair during the course of the year.
Our study did not assess clinical outcomes such as changes
in drug therapy or therapies that resulted from alert letters to
the prescribing physician(s) or whether or not interventions we
assessed as clinically relevant were indeed clinically significant
based on patient outcomes. The scope of our study did not
address actions taken by prescribers in response to drug interaction alert letters, and we did not use certified mail to determine if all the letters were actually received by the prescribers
at their offices. We also did not determine to what extent or frequency prescribers reviewed the information.
■■ Limitations
We acknowledge certain study limitations. We included only
submitted, paid claims for dispensed, prescription medications.
Our methodology would therefore undercount coprescribing
errors when a claim for at least 1 of the drugs in a pair was purchased without the submission of a claim through a prescription benefit plan. This would not be a common occurrence for
most prescription medications but could occur, for example, in
a prescription for lithium and coincident use of a nonsteroidal
anti-inflammatory drug since many nonsteroidal anti-inflammatory drugs can be purchased over the counter. We also did
not formally assess the pharmacist audits against a secondary
blinded review or otherwise verify the reliability of clinical
pharmacist review. Therefore, we cannot be certain that variations in case finding are not at least partially attributable to variations in the individual pharmacist method. However, case
finding was performed by a small group of 4 trained pharmacists who often conferred with each other.
We also did not assess the relevance of coprescribed pairs
that were dropped by the second automated review; it is possible that a few cases may have been clinically relevant, but we do
not know how often this occurs. However, the filters were built
over time to account for many of the false positives that were
observed by the clinical pharmacists, and, as our data show, the
automated filters provided far more alerts than were considered
relevant by pharmacists.
As is common in prescription drug plan populations, activity in enrollment and disenrollment required that we calculated
an average enrolled study population over the 12-month study
period. Moreover, we defined incidence by using an eligible
population of those members who had prescription claims
throughout the year; this was done because we were interested
in the incidence of potential DDIs across a large, covered population from the perspective of a PBM firm. Put another way, we
■■ Conclusion
We found that the use of more sophisticated, electronic comparison of clinically relevant potential DDIs identified by simple
drug pairs reduced the incidence of DDI alerts by 70.8%.
Additional clinical pharmacist review reduced the incidence of
potentially serious DDIs by an additional 80.6%. Combination
of the 2 methods reduced the incidence of apparent serious DDI
by 94.3%.
It is important that private and public health plan sponsors
and PBM firms share available data on the types and incidence
of clinically relevant potential medication errors and their methods used to make these determinations. Doing so will assist in
better understanding the fundamentals of retrospective DUR
intervention programs in ambulatory populations.
Future research is needed to determine how often and to
what extent prescribers respond to such alerts about apparent
medication errors. In addition, future research is needed to
determine the methods and procedures that will make DUR
warning systems most effective in obtaining acceptance and
cooperation from prescribers in reducing the incidence of
adverse drug events.
520 Journal of Managed Care Pharmacy
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ACKNOWLEDGMENTS
We would like to acknowledge Evelyn Chiao, Kimberly Kasper, Kelly Makay,
Sandy Rowlands, and David Stillman, of Eckerd Health Services, for their significant
contributions to this study by providing administrative and technical support.
DISCLOSURES
No outside funding supported this study. Author Catherine C. Peng served as principal
author of the study. Study concept and design and analysis and interpretation of data
were contributed by Peng and authors Peter A. Glassman, Iny R. Marks, Curtis Fowler,
Brenda Castiglione, and Chester B. Good. Drafting of the manuscript was primarily the
work of Peng, Glassman, and Marks, and its critical revision was the work of all
authors. Statistical expertise was contributed by Peng, Marks, Fowler, and Glassman.
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46. The U.S. Pharmacopeia Drug Utilization Review Advisory Panel. Drug
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Vol. 9, No. 6
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ORIGINAL RESEARCH
Financial Risk Relationships and Adoption of Management Strategies
in Physician Groups for Self-Administered Injectable Drugs
JONATHAN D. AGNEW, PhD; MARILYN R. STEBBINS, PharmD;
DAVID E. HICKMAN, PharmD; and HELENE LEVENS LIPTON, PhD
T
RESULTS: We found that the level and locus of SAI financial risk were related to
the adoption of management strategies. Physician groups with higher financial
risk for SAIs adopted more strategies than lower-risk groups. Groups with SAI
financial risk in the medical services capitation (MSC) adopted 9.2 strategies
per group. In contrast, groups with SAI financial risk in the pharmacy-risk budget
(PRB) averaged 1.5 strategies per group. Groups with SAI financial risk in both
the MSC and PRB fell in-between, averaging 4.5 strategies per group. The most
frequently adopted strategy was designing evidenced-based therapeutic guidelines, i.e., protocols based on evidence from the peer-reviewed literature used to
guide physicians in the treatment of typically chronic conditions (9 groups, 45%
of sample). The second most common strategy involved adapting the existing
utilization management system to process SAIs (7 groups, 35%) and the establishment of office procedures for internal authorization (5 groups, 25%). The least
frequently used strategies were determining amount paid to out-of-group physician providers (1 group, 5%) and hiring personnel (e.g., pharmacists) in claims
or utilization management departments to implement and manage SAI programs
(1 group, 5%). We also identified potential factors that increased the likelihood
of strategy adoption and that could slow the rate of SAI cost increases.
he advent of high-cost, self-administered injectable
drugs (SAIs) represents an important emerging issue
within one of the fastest-growing subcomponents of
drug costs. An SAI is defined as a prescription for an injectable
medication written by a provider, filled by a pharmacy, and
administered at home by the patient or caregiver. (While these
drugs also may be administered in a variety of settings [physician’s office or clinic], this study focuses on those drugs selfadministered at home.)
Injectable drugs that can be self-administered have made
possible the treatment of conditions for which there were formerly very limited or no therapeutic options. For example, selfadministered injectable interferons, especially in combination
with ribavirin, have dramatically increased the percentage of
hepatitis C patients with positive clinical and virological outcomes.1 The Medical Advisory Board of the National Multiple
Sclerosis Society recommends initiation of the self-administered
injectables beta interferons or glatiramer acetate, following a
diagnosis of multiple sclerosis with a relapsing course.2
Rheumatoid arthritis (RA) can be treated with etanercept, adalimumab, or anikinra, all of which are SAIs.3,4 SAIs are now also
used to treat, anemia, neutropenia, deep-venous thrombosis
previously requiring hospitalization for treatment, infertility,
growth hormone deficiency, migraines, and diabetes.5-11
These medical advances, however, come at a price. Table 1
shows the average monthly cost for commonly used SAI medications. Expenditures for biotechnology products such as SAIs
are expected to grow faster than oral prescription drug costs,
which are projected to increase by 70% over the next 5 years.12,13
CONCLUSION: Our findings suggest that adoption of SAI drug-use management
strategies may be more likely to occur when there is a minimum level of risk for
SAI drug costs. Likewise, both the adoption of strategies and the opportunity to
slow the rate of SAI cost increases may be more likely to occur when 3 additional factors are present: a contractual environment conducive to controlling SAI
drug costs, the ability to implement SAI drug-use management strategies, and
power in negotiations with drug manufacturers to reduce SAI prices. A sustainable and affordable SAI financial risk management program maximizing these
factors while minimizing the financial burden for patients will require collaboration among all stakeholders, payers, providers, drug manufacturers, and patients.
JONATHAN D. AGNEW, PhD, is a post-doctoral fellow, Centre for Health Services
and Policy Analysis, University of British Columbia, Vancouver, B.C., Canada;
MARILYN R. STEBBINS, PharmD, is associate clinical professor of pharmacy,
Department of Clinical Pharmacy, School of Pharmacy, University of California,
San Francisco; DAVID E. HICKMAN, PharmD, is director, Outpatient Pharmacy
Services, Clinical Integration Department, Sutter Health, Sacramento, California;
HELENE LEVENS LIPTON, PhD, is professor of health policy and pharmacy;
Institute for Health Policy Studies and Department of Clinical Pharmacy, Schools
of Pharmacy and Medicine, University of California, San Francisco.
ABSTRACT
OBJECTIVE: To consider the extent, nature, and range of risk arrangements
between physician groups and health maintenance organizations (HMOs) for
self-administered injectable (SAI) drugs; to examine types and frequencies of
SAI drug-use management strategies adopted by physician groups; and to
explore the relationship between locus and level of financial risk for SAIs and
physician group strategy adoption.
METHODS: We used a multiple case-study design to select physician groups and
their health maintenance organization (HMO) contractual partners in 4 markets in
the United States (Northwest, Northeast, Midwest, Southwest). Physician groups
in these markets were chosen based on size (≥50 physicians) and experience
with drug risk (≥1 year). Physician groups were asked to identify their 3 major
HMO contractual partners in each market. Telephone interviews were conducted
from January 2000 to June 2001, with the resulting purposive sample of 37 individuals representing 20 physician groups.
KEYWORDS: Self-administered injectable drugs, Physician group, Risk, Drug-use
management strategy
J Managed Care Pharm. 2003;9(6):523-33
Authors
AUTHOR CORRESPONDENCE: Helene Levens Lipton, PhD, Professor of Health
Policy and Pharmacy, Institute for Health Policy Studies and Department of
Clinical Pharmacy, Schools of Pharmacy and Medicine, University of California,
San Francisco, 3333 California St., Suite 265, San Francisco, CA 94118.
Tel: (415) 476-2964; Fax: (415) 476-0705; E-mail: [email protected]
Copyright© 2003, Academy of Managed Care Pharmacy. All rights reserved.
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TABLE 1
Average Monthly Costs and Indications
for Selected Self-Administered
Injectable Drugs
Medication
Avonex 30 mcg
Betaseron 0.25 mg
Copaxone
Quantity
4 vials
15 vials
1 kit of 30 prefilled syringes
Rebif 44 mcg/0.5cc 12 pack of prefilled syringes
8 vials
Enbrel 25 mg
Humira
2 vials
Peg-Intron 120 mcg
Pegasys 180 mcg
Procrit 20,000 units
Epogen 4,000 units
Lovenox 100 mg
4 kits
1 kit
4 vials
12 vials
20 x 1 ml
syringes
Indication
Multiple sclerosis
Multiple sclerosis
Multiple sclerosis
Average Cost
per Month*
$943.98
$1,099.99
$940.99
Multiple sclerosis $1,209.99
Rheumatoid
arthritis
Rheumatoid
arthritis
Hepatitis C
Hepatitis C
Anemia
Anemia
Deep venous
thrombosis
$1,089.99
$1,159.87
$1,223.96
$1,349.95
$1,003,92
$587.88
$1,081.89†
Source: www.drugstore.com on May 30, 2003.
* Price for a 4-week or 30-day supply.
† Price for 10 days of therapy.
Importantly for patients, the cost of an individual course
of treatment with SAIs far exceeds that of oral medications.
The average cost per prescription of the top 50 new drugs introduced between 1992 and 2000 was $86.48. Of those drugs, the
4 that were SAIs had an average cost of $900.12 per prescription.14 The average wholesale price for SAIs for multiple sclerosis
for 1 month ranges from $900 to $1,300. Etanercept (Enbrel), an
SAI used to treat RA, has an average wholesale price of more than
$1,100 for 1 month of treatment.15
Because SAIs are often used to treat chronic conditions,
these costs take on even greater significance for both patients
and the health care system. Depending on insurance coverage,
patient costs for SAIs can represent a significant burden.
For example, in mid-May 2002, federal health officials
announced that Medicare would cover interferon beta-1a
(Avonex) for multiple sclerosis but not 3 other commonly prescribed MS medications and not other injectable drugs that
Medicare beneficiaries self-administer more than 50% of the
time.16,17
SAI drugs have existed since the introduction of insulin, but
the more recent introduction of several high-cost SAIs highlight
the dilemma that advances in biotechnology pose to the health
care system, namely, how to balance cost and care. These challenges are not unique to SAIs since oral drugs represent the
524 Journal of Managed Care Pharmacy
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November/December 2003
fastest-growing component of health care costs, but the cost per
treatment with SAIs far surpasses the average cost per treatment
with most oral drugs.
Of particular concern is the appropriate distribution of financial risk among physician groups, insurers (e.g., health maintenance organizations [HMOs]), and patients. In the case of oral
prescription drugs, one method has been the transfer of risk for
drug costs from HMOs to physician groups. However, given the
potentially enormous financial losses involved, some physician
groups were less willing or less able to assume contracts carrying
risk for oral prescription drugs. Other groups, convinced that such
risk could be managed profitably with the adoption of specific
management strategies, were more willing to assume such contracts.18 Evidence suggests that physician groups in California had
been trying to shift back to HMOs their financial risk for injectable
drugs administered in the physician’s office,19 and, effective July 1,
2003, California law required HMOs to offer to take back the
financial risk from physician groups for injectables.20
As with oral prescription drugs, the rapid growth of SAI
drug costs has made the distribution of financial risk for SAIs a
contentious issue. In many cases, HMOs have transferred financial risk for SAIs to physician groups. However, there are no
empirical studies examining how physician groups have
responded to the cost pressures associated with existing
SAI drug-risk arrangements and the extent to which they have
adopted strategies to manage significant increases in SAI drug
costs and utilization. This is important given that a premise
underlying managed care is that assumption of financial risk
will spur changes in physician group behavior to manage the
risk,21 such as the adoption of innovations.
Some studies have examined risk arrangements for oral drugs
among health plans and physician groups.22,23 One case study of a
northern California multispecialty physician group found that
adoption of multiple SAI drug-use management strategies resulted
in cost-savings of $271,000 over the initial 6-month period, 32%
of the SAI drug budget.24 However, no study has looked exclusively at SAIs and management strategies across physician groups.
Studying current SAI drug-risk arrangements is central not
only for understanding the dynamics of this increasingly important area of health care spending but also for its potential to
shed light on the broader, critically important policy issue of
how financial risk for increasingly expensive prescription drugs
should be spread among key stakeholders in the health care system. Given the absence of any systematic analysis of SAI drugrisk arrangements in the literature, we undertook the current
study with 3 goals in mind: first, to consider the extent, nature,
and range of SAI-risk arrangements between physician groups
and HMOs; second, to examine the types and frequencies of SAI
drug-use management strategies adopted by physician groups;
and third, to explore the relationship between locus and level of
financial risk for SAIs and the number of strategies adopted by
the physician group.
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■■ Methods
Case-Study Methodology and Sample Selection
This study was conducted as part of a larger study conducted
from January 2000 through June 2001 that examined drug-risk
arrangements between physician groups and their HMO contractual partners.23 We used a multiple case-study design to
select physician groups and their HMO contractual partners in
a 2-stage process.
In stage 1, we selected 4 markets, each composed of a single
metropolitan area, within which the physician groups under
study were chosen. One goal was to identify markets with significant managed care penetration (i.e., greater than 30% of
market share). We accomplished this by reviewing markets
selected by the Center for Studying Health System Change for
its Community Tracking Studies and markets described by the
University Health System Consortium.25 We then considered
geographic diversity in selecting markets. To protect confidentiality, the markets are described by region of the country in
which they are located: Northwest (NW), Southwest (SW),
Midwest (MW), and Northeast (NE).
In stage 2, physician groups in these markets were chosen
based on size (≥50 physicians) and experience with drug risk
(≥1 year). Physician groups were then asked to identify their
3 major HMO contractual partners in each market.
Telephone interviews with the resulting purposive sample of
37 individuals representing 20 physician groups were conducted between January 2000 and June 2001. One or two individuals in each physician group were interviewed using a semistructured protocol that lasted an average of 60 to 90 minutes
and included both closed and open-ended questions (see
Survey). Interviewees included medical directors (12), pharmacy directors (14), clinical pharmacy specialists or managers (2),
finance officers (2), and chief executive officers or other physician group executives (7). Respondents reported the locus of
SAI drug risk in 3 categories (medical services capitation, pharmacy risk budget, or both—defined below), level of SAI drug
risk (full, shared, or none), strategies adopted to manage SAI
costs, and health insurance market characteristics (e.g., HMOphysician group relations, perceived level of competition or collaboration among physician groups). Table 2 defines the SAI
drug-use management strategies, which were divided into 6 categories: (1) quantify SAI drug costs (physician group’s
attempts), (2) establish a physician group authorization process
for SAIs, (3) negotiate price and monitor the price paid for SAIs,
(4) develop and monitor a pharmacy claims system for SAIs,
(5) establish SAI auditing processes, and (6) develop SAI contracting arrangements with HMOs, pharmacies, out-of-group
providers, and/or home health providers.
Calculation of Study Variables
SAI drug-use management strategies. The research team, comprising managed care pharmacists and health services
researchers, developed a list of SAI drug-use management
strategies based on the experience of a large, multipractice
physician group’s SAI drug utilization program.24 As noted earlier, these strategies, which had been developed, implemented,
and evaluated in this physician group, were found to have some
success in containing SAI drug costs. The list of strategies was
then pretested and refined in 4 additional northern California
physician groups, each with 50 or more physicians and at least
1 year of experience with SAI drug risk.
Locus of SAI drug risk. Physician groups reporting some
level of financial risk for SAI drug costs indicated whether
SAI drug risk was part of the medical services capitation (MSC)
or the pharmacy-risk budget (PRB). The MSC is the monthly
capitation payment (per member per month) that is paid to the
physician group by the HMO for all medical services. When
SAIs were part of the MSC, the physician group assumed
responsibility for all SAI drug costs. In contrast, the PRB is the
budget established by the physician group and the HMO for
outpatient prescription drug costs. When SAI drug costs were
part of the PRB, the level of SAI drug risk was equal to that of
oral medications. For example, in a physician group with
HMO-risk contracts placing the group at 50% risk for oral prescription drug costs, if the SAI drug costs were part of the PRB,
the SAI risk level also was considered equal to 50%. In some
cases, physician groups had a combination of contracts from
their HMO partners such that SAI drug-risk was placed in both
the MSC and the PRB.
Level of SAI drug risk. Physician groups were classified as
having one of 3 types of SAI drug risk: no risk, shared risk, or
full risk. Physician groups reporting that the HMO assumed full
risk for SAI drug costs were categorized as “no risk.” If the
physician group reported SAI drug risk in the MSC, then the
group was assumed by the researchers to have assumed responsibility for all SAI drug costs and was therefore categorized as
“full risk.” (In this study, when level of risk was 100%, risk
always resided in the MSC. However, it is possible that
risk could be at 100% and reside in the PRB, in which case, the
physician group assumed all of the risk for SAI costs. No physician group in the current study met this criterion.) The remaining physician groups were assigned to the “shared risk” category. These groups reported either: (1) a combination of individual “no-risk” and “full-risk” contracts, (2) contracts stating that
risk was to be shared between a particular HMO partner and the
physician group, or (3) a combination of (1) and (2).
Sample characteristics. Table 3 summarizes the individual
group and market-level characteristics of the study sample.
The sample included 5 physician groups in the NE and MW
markets, 4 groups in the SW, and 6 groups in the NW. The total
number of physicians in each group ranged from 55 to 1,200
(mean: 737, median: 500; 19 of 20 groups reporting). The
number of enrollees ranged from 50,000 to 630,000 (mean:
214,473, median: 215,000; 17 of 20 groups reporting).
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Financial Risk Relationships and Adoption of Management Strategies in Physician Groups for Self-Administered Injectable Drugs
TABLE 2
Definitions of SAI Drug-Use Management Strategies in Physician Groups
Number of Physician Groups
Adopting the Strategy
Strategy Type
Strategy Subtype
Definition of Strategy Subtype
1(a). Quantify SAI costs
Capitation deductions
Determine amount health plan deducts from
medical capitation payment for SAIs
1(b). Determine extent
of cost burden
Pharmacies, out-of-group
providers, home health providers
Determine amount physician group pays pharmacies,
out-of-group providers, and home health providers through
direct billing to claims department*
2.
Implement therapeutic guidelines
for authorizations
Utilize evidence-based guidelines for SAI prescribing
(e.g., multiple sclerosis and rheumatoid arthritis)†
9
Use existing utilization management
(UM) system
Adapt existing UM system to process requests for SAI
authorizations
7
Establish office procedures for
internal SAI authorization
Establish processes physicians and staff follow to
obtain authorization from the physician group’s UM
department for SAIs that are the physician group’s
financial responsibility
7
Hire personnel
Hire personnel in claims/UM department to implement
and manage SAI authorization program
1
Determine current price paid for
each SAI
Determine price paid for each SAI using HMO
capitation deductions
4
Pharmacy network
Develop network(s) of local pharmacies or contract with
a pharmacy vendor to supply SAIs at a lower price
4
Pharmacies
Negotiate lower SAI price with local pharmacy
(by physician group)
3
Home health providers
Negotiate lower SAI price by redirecting patients to the
selected home health provider (by physician group)
3
Pharmaceutical companies
Negotiate a lower price with SAI manufacturer directly
(by physician group)
3
Establish claims processing system
for direct billing to internal claims
department
Establish process by which pharmacies, out-of-group
providers, and/or home health providers bill and receive
reimbursement from the physician group directly for SAIs
3
Monitor individual SAI costs via
claims system
Establish a system to monitor each individual SAI cost
through internal claims processing system
4
Monitor overall SAI costs via claims
system
Establish a system to monitor overall SAI costs through
internal claims processing system
4
Monitor compliance with internal
guidelines and internal priorauthorization process
Monitor compliance with internal prior-authorization
process and guidelines for SAIs (by individual or
department within physician group)
3
Audit capitation deduction reports
for patient eligibility, and duplicate
and over-charges for medications
Review medical services capitation deductions related
to SAIs for verification of patient eligibility, duplicate or
over-charges for medications, and correct interpretation
of contracted financial responsibility
2
Audit bills from pharmacies, out-ofgroup providers, and home health
providers
Review outpatient pharmacy, out-of-group providers,
and home health bills related to SAIs for verification of
patient eligibility, duplicate or over-charges for
medications, and correct interpretation of contracted
financial responsibility
4
Prospective auditing of patient
eligibility by UM department
Verify patient’s insurance coverage (by UM department in
the physician group before SAI authorized)
4
Establish different SAI-risk
arrangements with HMO
Transfer risk for SAI costs to HMO (shared risk or no risk
for physician group)
2
3.
4.
5.
6.
Establish SAI
authorization
processes
Negotiate price
and monitor
amount paid
for SAI
Establish, monitor
pharmacy claims
system for SAIs
Establish SAI
auditing processes
Develop SAI
contracting
arrangements
2
3, 1, 5
* This strategy subtype represents 3 possible strategies: determine amount paid to pharmacies, out-of-group providers, or home health providers.
† Medical Advisory Board of the National Multiple Sclerosis Society. Disease Management Consensus Statement. Available at: www.nationalmssociety.org.
Accessed December 20, 2002. ACR guideline update. Arthritis Rheum. 2002;46(2):325-45.
526 Journal of Managed Care Pharmacy
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Financial Risk Relationships and Adoption of Management Strategies in Physician Groups for Self-Administered Injectable Drugs
TABLE 3
Sample Characteristics, SAI-Risk Relationships, and Number of Adopted Strategies
Number
of
Physicians
Enrollees
(thousands)
Locus
of SAI
Risk
Level
of SAI
Risk
Northeast
NE 1
NE 2
NE 3
NE 4
NE 5
≥1,000
≥1,000
≥1,000
500-999
>1,000
>200
>200
>200
missing*
missing†
PRB
PRB
PRB
PRB
PRB & MSC
shared
shared
shared
shared
shared
none
none
none
none
none
Southwest
SW 1
SW 2
SW 3
SW 4
<500
<500
≥1,000
500-999
100-199
<100
>200
100-199
MSC
MSC
MSC
MSC
full
full
full
full
4
3
16
16
Midwest
MW 1
MW 2
MW 3
MW 4
MW 5
<500
500-999
<500
<500
500-999
missing†
<100
>200
<100
100-200
N/A‡
PRB
PRB
missing*
PRB
none
shared
shared
shared
shared
none
1
10
none
1
Northwest
NW 1
NW 2
NW 3
NW 4
NW 5
NW 6
<500
<500
500-999
<500
500-999
<500
>200
>200
>200
<100
100-199
>200
MSC
N/A‡
PRB
PRB & MSC
PRB & MSC
PRB & MSC
full
none
shared
shared
shared
shared
7
2
none
3
10
5
ID
*
†
‡
§
Number
of Adopted
Strategies
Market Summary§
Dominated by 3 large, nonprofit insurers, 2 of which were locally
based. Collaborative working relationships between physician
groups and HMOs. Consolidated on delivery side and high degree
of horizontal cooperation between groups. All but 1 organization
had drug-risk contracts with a management service organization
(MSO) for the purposes of negotiating risk contracts. The characteristics of the risk contracts themselves varied considerably.
Most heavily capitated market, with more partial capitation than
any other market. Groups derived substantially higher percentages
of income from Medicare-risk contracts than in other markets.
Relations between groups and HMOs more adversarial than in other
markets, and physician groups were not as horizontally integrated.
Mix of shared and global drug-risk contracts.
Market witnessed a decline in HMO penetration over the course
of the study period. Unique market due to the presence of a large
coalition of health care purchasers who leveraged the size of their
combined enrollee populations to purchase health care. Drug-risk
arrangements for oral medications were almost exclusively various
forms of full-risk or global capitation contracts.
Market unique in that there were no Medicare-risk contracts. This
shift in risk generated increased interest for health plans to collaborate with physician groups in managing drug costs.
Collaboration among physician groups in creating standardized
clinical practice guidelines and in publishing a formulary guide.
Primarily global capitation or full-risk contracts for oral drug
costs.
No data provided.
Respondents could only report number of patient visits per year, not number of enrollees.
Because these groups have no SAI risk, the locus of risk is not applicable.
The descriptions of each market include information on the defining characteristics of that market rather than common attributes across markets.
Locus of SAI Risk:
PRB = Pharmacy risk budget.
MSC = Medical services capitation.
Level of SAI Risk:
No risk = HMO assumed full risk for SAI drug costs.
Shared risk = the physician group reported either: (1) a combination of individual “no-risk” and “full-risk” contracts; (2) contracts stating that risk was to be shared
between a particular HMO partner and the physician group; or (3) a combination of (1) and (2).
Full risk = the physician group assumed responsibility for all SAI drug costs.
■■ Results
Level of SAI drug risk. Out of a total of 20 physician groups,
18 assumed some financial risk for SAI drug costs. Table 4
shows that 5 physician groups (25% of sample) reported that
they were at full financial risk for SAIs. Thirteen groups (65%)
shared financial risk with their HMO contractual partners,
while the remaining 2 groups (10%) reported no financial risk
for SAIs. The level of SAI drug risk borne by the physician
group appeared linked to the number of strategies adopted,
with higher-risk groups adopting more strategies than lowerrisk groups. Groups with full financial risk adopted an average
of 9.2 strategies per group compared with 2.3 strategies per
shared-risk group and 1 strategy per no-risk group. The average
number of strategies for the entire sample was 3.9 per group.
There was also a clear regional variation in the distribution
of the level of SAI drug risk across physician groups. All of the
SW groups had full risk for SAIs, while all of the NE groups had
shared risk for SAIs. The majority of the groups in the NW and
MW markets had shared risk for SAIs. There did not appear to
be any relationship between level of managed care penetration
in each market and the level of SAI risk among physician groups
within each market: the markets with the highest and lowest
levels of managed care penetration included groups with primarily shared-risk contracts for SAIs.
Locus of SAI drug risk. Table 5 reveals that physician groups
were divided with respect to the locus of SAI drug risk. Eight
groups (40% of sample) reported that risk was in the PRB,
5 (25%) groups reported it in the MSC, and 4 (20%) reported
it in both the MSC and PRB. Two groups (10%) had no SAI risk,
and one group (5%) did not know where its SAI drug risk resided.
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Journal of Managed Care Pharmacy 527
Financial Risk Relationships and Adoption of Management Strategies in Physician Groups for Self-Administered Injectable Drugs
TABLE 4
Level of SAI
Financial Risk
Full risk
Shared risk
No risk
TABLE 5
SAI Drug-Use Management Strategies
by Level of SAI Financial Risk
Number of
Physician
Groups
Number of
Strategies
Average Number
of Strategies
per Physician
Group
5
13
2
46
30
2
9.2
2.3
1.0
SAI Drug-Use Management Strategies
by Locus of SAI Financial Risk
Locus of SAI
Financial Risk
Number of
Physician
Groups*
Number of
Strategies
Average Number
of Strategies
per Physician
Group
MSC
PRB and MSC
PRB
5
4
8
46
18
12
9.2
4.5
1.5
Locus of SAI Risk:
PRB = Pharmacy risk budget.
MSC = Medical services capitation.
Level of SAI Risk:
No risk = HMO assumed full risk for SAI drug costs.
Shared risk = the physician group reported either: (1) a combination of individual
“no-risk” and “full-risk” contracts; (2) contracts stating that risk was to be shared
between a particular HMO partner and the physician group; or (3) a combination
of (1) and (2).
Full risk = the physician group assumed responsibility for all SAI drug costs.
* Three groups not included in analysis: group MW 4 “not sure” of locus of SAI risk.
Locus of SAI risk is not applicable to MW 1 and NW 2 since these groups had no
SAI risk.
Strategy adoption appeared related to the locus of SAI drug
risk. Groups with SAI drug risk in the MSC, on average, adopted 9.2 strategies per group. In contrast, groups with SAI drug
risk in the PRB averaged 1.5 strategies per group. Groups with
SAI drug risk in both the MSC and the PRB fell in-between,
with an average of 4.5 strategies per group.
As with patterns of strategy adoption, the locus of SAI drug
risk also varied by market. All 4 of the SW physician groups
(100% of market) had risk in the MSC. In contrast, in the NE
and MW, the majority of physician groups had SAI drug risk in
the PRB (80% of groups in the NE and 60% of groups in the
MW). The locus of SAI drug risk appeared more evenly spread
in the NW: 3 groups (50%) had SAI drug risk in both the PRB
and MSC, 2 in the PRB (33%), and 1 in the MSC (16%).
Frequency and distribution of SAI drug-use management
strategies. Sixty percent (12 groups) of surveyed physician
groups adopted at least 1 strategy. Among those physician
groups that adopted any strategies, the average was 6.5 per
group. The most common category of strategies adopted was
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November/December 2003
establishing an SAI authorization process (11 groups, 55% of
sample). The next most common categories of strategies included strategies to negotiate and monitor SAI prices (7 groups,
35%), including negotiating directly with the drug manufacturer (3 groups, 15%), followed by establishment and monitoring
of a pharmacy claims system for SAIs (5 groups, 25%), establishment of SAI auditing processes (5 groups, 25%), efforts to
quantify SAI drug costs (5 groups, 25%), and changes to current SAI contracting arrangements (i.e., transferring risk for SAI
drug costs back to the HMO—2 groups, 10%).
With respect to individual strategies, the most frequently
used strategy was designing evidenced-based therapeutic guidelines that formed the basis for authorizations for SAIs.
For example, a guideline might suggest the use of etanercept in
the treatment of RA when a patient meets the following inclusion criteria: a diagnosis of RA by a rheumatologist (i.e, the
patient meets 4 out of 7 criteria listed by the ACR [American
College of Rheumatologists]); has inadequate response, failed
therapy, or has contraindications to specific alternative drugs;
and no history of tuberculosis (Table 6). This strategy was followed in frequency of use by measures to adapt the existing utilization management system to process SAI requests efficiently
(7 groups, 35% of sample), the establishment of office procedures for internal authorization (5 groups, 25%), and determining the amount the physician group paid for SAIs to home
health agencies (5 groups, 25%).
The least frequently used strategies were: determining the
amount the group paid to out-of-group physician providers
(1 group, 5% of sample) and hiring personnel (e.g., pharmacists) in the claims or utilization management departments to
implement and manage an SAI program (1 group, 5%). Every
strategy was adopted by at least 1 physician group. No group
described a drug-use management strategy beyond the 21
described in the survey protocol even though all were offered the
opportunity to do so in the open-ended portion of the survey.
The extent of SAI management strategy adoption varied by
market. No physician groups in the NE adopted any SAI management strategies, while 3 of 5 groups (60%) in the MW
adopted one or more strategies. In the NW, 5 of the 6 groups
(83%) adopted strategies, compared with all 4 (100%) of the
SW groups.
The dependent variable (number of management strategies
adopted) and the independent variables (locus and level of SAI
drug risk) were independently conceptualized and measured in
our study. The list of management strategies used in the survey
was selected from a list of strategies developed by the study
authors. The independent variables, “location” of SAI risk (MSC or
PRB), and “level” of SAI risk (full, shared, none), were
a priori hypothesized to influence management strategy adoption.
■■ Discussion
We found that level of SAI drug financial risk was positively relat-
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Financial Risk Relationships and Adoption of Management Strategies in Physician Groups for Self-Administered Injectable Drugs
ed to strategy adoption, with high-risk groups adopting more
strategies than lower-risk groups. This is consistent with the theory of risk that has motivated much managed care activity, namely,
that when drug-risk transfer occurs, physician groups will be
motivated to adopt drug-use management innovations.
Findings from the current study corroborate and extend
results from 2 prior studies that examined this relationship for
oral prescription drug risk in managed care organizations.22,26
Hillman et al. compared drug spending and prescribing patterns across 9 physician groups managed by a single health
plan. The authors concluded that physician prescribing behaviors and total drug expenditures could be influenced by direct
financial incentives for physicians to control drug use.26 Using
data from a physician-hospital organization from 1995 to 1999,
Chernew et al. compared drug-cost growth for patients receiving services from capitated physician groups and patients using
noncapitated physician groups and found that drug spending in
the capitated group increased as the risk transfer was diminished.22
Neither of these studies addressed the extent to which financial incentives influenced adoption of drug-use management
innovations in physician groups. Further, in selecting physician
groups from only 1 managed care organization, Hillman et al.26
and Chernew et al.22 limited their potential to explore the range
of existing drug-risk arrangements and their differential effects
on innovation at the physician group level. Therefore, our current findings, which are based on the experiences of multiple
physician groups across multiple managed care markets, represent important empirical support for the hypothesis that the
assumption of financial responsibility for drug costs results in
changes in adoption of drug-use management innovations for
SAIs, the fastest-rising component of drug budgets.
Our findings revealed that strategy adoption was influenced
by locus of risk. When the locus of risk for SAI drug costs
resided in the MSC, the number of strategies adopted was higher (mean: 9.2 strategies per group) compared with groups
where the locus of risk was located in the PRB (mean: 1.2 strategies per group). We would suggest that placement of risk in the
MSC permitted physician groups to capitalize on their ability to
implement SAI drug-use management strategies.
Locus in the MSC increased strategy adoption because, once
in the MSC, physician groups could adapt available drug utilization strategies to their management of risk for SAI costs,
namely, establishing an SAI authorization process, developing
and monitoring a claims adjudication process for SAIs, and
negotiating and monitoring the prices paid for SAIs. Physician
groups were less able to implement strategies if the locus was in
the PRB because the pharmacy benefit was controlled by the
health plans, reducing the ability of medical groups to change
the authorization or claims processes or prices paid for SAIs.
Despite pressure to control SAI drug costs, 40% of groups
in the sample did not adopt any SAI drug-use management
TABLE 6
Guideline for Approval of Etanercept
(Enbrel) Therapy
Please include the following information to expedite the approval
process for Enbrel.
1. Request by rheumatologist:
______Yes
2. Inclusion criteria:
Patient has diagnosis of rheumatoid arthritis (RA) by American
College of Rheumatology (ACR) criteria (see guideline) ______Yes
Patient has moderate to severe RA
______Yes
Patient has inadequate response, failed therapy, or contraindications
to the following medications:
____Imuran ____Methotrexate ____Ridaura ____Plaquenil
____Cupramine____Azulfidine ____Gold Therapy
Patient does not have history of TB or a positive PPD
______Yes
Source: MedClinic 2003: http://www.medclinicmedgroup.org/cgi/home.pl.
Guideline derived from research literature on rheumatoid arthritis.
strategies. Among the 60% of groups that did adopt at least
1 strategy, the average number of adopted strategies was 6.5 per
group, well below the 21 possible strategies presented in the
survey. We posit 3 reasons for fairly low levels of strategy adoption. First, prescription drugs, which have accounted for a
smaller portion of health care organizations’ budgets than hospital and physician services, have, until recently, received less
attention from medical group management.27 The lack of
observed strategy adoption in our study may reflect a similar
phenomenon with respect to SAI drug costs in physician
groups, which may receive less attention from management
despite potentially rapid increases in utilization, because SAI
drug costs constitute such a small portion of the total drug
budget. Indeed, several groups stated in their open-ended
responses that SAI drug costs were simply “not on our radar
screen.”
A second explanation for low adoption rates may be related
to the physician groups’ lack of power to negotiate better
injectable medication prices with drug manufacturers or better
risk arrangements with HMOs. Only 3 groups (15% of the sample) negotiated better prices with manufacturers, and only
2 groups (10%) negotiated different contractual arrangements,
i.e., transferred SAI risk to HMOs. We did not determine how
many physician groups attempted to negotiate risk sharing with
HMOs.
An effective financial risk-management strategy for physician groups would involve risk sharing of SAI drug costs with
HMOs, but this strategy is, of course, part of the ongoing tug of
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Financial Risk Relationships and Adoption of Management Strategies in Physician Groups for Self-Administered Injectable Drugs
SURVEY
Principal Items in Survey of Physician Groups and Self-Administered Injectable Drugs
1. Who is at risk for SAIs?
a. HMO
b. Physician organization
c. Shared
d. Other
2. What kind of risk arrangement do you have
for SAIs?
a. None, HMO at full risk
b. Physician group cap
c. Pharmacy cap
d. Pharmacy carve-out for SAIs
e. Other
If group is at risk for SAIs:
3. When did you first assume risk for SAIs?
4. What were your SAI costs for the last fiscal
year?
5. Since assumption of risk for SAIs, has your
drug PMPM
a. Increased
b. Decreased
c. Remained the same
d. Not applicable because SAI in med cap
e. Other
6. Since assumption of risk for SAIs, have your
total SAI costs…
a. Increased
b. Decreased
c. Remained the same
d. Other
7. Where do you project your SAI costs are
going?
8. Why?
If group not currently at risk for SAIs:
9. Have you been at risk for SAIs in the past?
a. No
b. Yes
c. Other
10. Why was the risk arrangement dropped?
11. Do you anticipate assuming risk for SAIs in the
future?
a. No
b. Yes
c. Other
12. Why?
Strategies to manage SAI cost and use
13. Do you have strategies for containing costs of
SAIs?
a. No
b. Yes
c. Other
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Strategies to quantify SAI costs
14. Quantify costs from cap deducts
a. No
b. Yes
c. Other
15. Quantify costs from out-of-group providers via
claims department
a. No
b. Yes
c. Other
Physician group authorization process
16. Designing therapeutic guidelines for authorization
a. No
b. Yes
c. Other
17. Establishing process to use existing utilization
management
a. No
b. Yes
c. Other
18. Establishing office procedures for internal
authorization
a. No
b. Yes
c. Other
Auditing
19. Monitor compliance with guidelines and internal prior-authorization process
a. No
b. Yes
c. Other
20. Audit cap deduct detail reports for patient eligibility, duplicates, and overcharges
a. No
b. Yes
c. Other
21. Audit contracted pharmacy bills for patient eligibility, duplicates, and overcharges
a. No
b. Yes
c. Other
22. Prospective auditing of patient eligibility by
UM department
a. No
b. Yes
c. Other
Pharmacy network
23. Contract for price and service with local pharmacies
a. No
b. Yes
c. Other
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Measures to monitor and negotiate price
24. Determine current price paid for each selfinjectable drug
a. No
b. Yes
c. Other
25. Contract with home health provider for best
price
a. No
b. Yes
c. Other
26. Contract with pharmacy for best price
a. No
b. Yes
c. Other
27. Contract with drug company for best price
a. No
b. Yes
c. Other
28. Evaluate ability to use “own-use” pricing with
attached hospital system
a. No
b. Yes
c. Other
Claims
29. Establish claims-processing system for direct
billing to internal claims department
a. No
b. Yes
c. Other
30. Monitor SAI expense via claims data
a. No
b. Yes
c. Other
31. Monitor costs via claims system (monitoring
out-of-group expenses, home health agency
expenses)
a. No
b. Yes
c. Other
Contracting
32. Contract different risk arrangements with
health plans
a. No
b. Yes
c. Other
33. Contract different risk arrangements with
pharmacy, home health provider, and drug
industry
a. No
b. Yes
c. Other
Financial Risk Relationships and Adoption of Management Strategies in Physician Groups for Self-Administered Injectable Drugs
war between HMOs and contracted medical providers.
Financial risk that can be managed by physician groups can be
transferred. Less manageable financial risk should be shared,
and financial risk that is not manageable by the physician medical group should be retained by the HMO and affected through
benefit design and adequate premiums.
A third possibility is that adoption of strategies was related
to the ability of physician groups to develop and implement
strategies through possession of adequate expertise, infrastructure, and resources. The groups attempted to deal with SAI drug
financial risk by adapting tools already at their disposal in the
management of oral medications and other services. For example, groups were more likely to adopt strategies to establish
authorization processes for SAIs using existing utilization management departments, which had experience in implementing
prior-authorization procedures for other diagnostic and medical
services. The physician groups also implemented strategies
related to monitoring and negotiating SAI price, relying on their
existing contracting departments’ experience in negotiating
contracts for pharmacy budgets and services.
Fewer groups quantified their SAI drug costs—something
that might be considered an obvious first step to managing SAI
expenditures. This may represent the perception that quantifying costs is not necessary to control SAI expenditures or that the
magnitude of the SAI cost threat was not recognized. It may also
demonstrate the lack of expertise and resources within physician groups to quantify drug costs, particularly if risk for
SAI drug costs is in the MSC, where tracking and itemizing drug
costs from multiple sources (e.g., pharmacies, home health
providers, HMOs, out-of-network providers) is difficult.
In our study, 25% of the groups quantified SAI drug costs
related to home health agencies, but only 1 group attempted to
quantify SAI drug costs from out-of-network providers. In addition, several of the SAI drug-use management strategies were
employed by only 1 physician group, and no unique strategies
were offered by the groups during the open-ended portion of
the interview. Further, while some physician groups shifted
resources toward the management of SAI drug costs, as evidenced by adapting their existing utilization management
processes, only 1 group (NW1) actually extended resources by
hiring additional personnel to manage SAI costs. NW1 was
unique among its NW market counterparts in that it had a history of using pharmacists to manage oral prescription drug risk.
This group’s decision to hire a pharmacist might also be
explained by its acknowledgment that it “saw medical care
[including SAIs] as a complete pie which needs to be managed
and can be best controlled at the medical group level,” and hiring a pharmacist was seen as a step toward that goal.
Our findings suggest that adoption of SAI drug-use management strategies may be more likely to occur when there is at
least a minimum level of risk for SAI drug costs. Likewise, both
the adoption of strategies and the opportunity to slow the rate
of SAI cost increases may be more likely to occur when 3 additional factors are present: a contractual environment conducive
to controlling SAI drug costs, the ability to implement SAI druguse management strategies, and power in negotiations with
drug manufacturers to reduce SAI prices.
First, the responsible parties should be at some level of
financial risk (either shared or full) for SAI drug costs. Although
limited by the small sample size of the study, the findings support the hypothesis that increased risk is accompanied by
increased levels of strategy adoption. Specifically, physician
groups implemented more cost-control strategies when increasing levels of financial risk were assumed.
Second, financial risk-bearing for SAI drug costs should
occur in a contractual environment in which the responsible
party has the necessary control to manage the risk. In our study,
the physician groups were able to manage the risk when SAI
drug costs were embedded within the MSC, and more strategies
were adopted due to this increased level of control. As noted in
the discussion, placement of SAI drug-risk in the MSC permitted the physician groups to have control over key aspects of
SAI drug utilization, such as drug authorization, price, and,
potentially, formulary selection. In contrast, when SAI risk
resided in the PRB, SAI authorization, price, and formulary
selection were controlled by the HMO, thus limiting the group’s
implementation of cost-control strategies even when needed
infrastructure and expertise existed.
Third, the organization must possess the ability—adequate
expertise, infrastructure, and resources—necessary to develop
and implement the strategies. The most frequently used strategy, establishing SAI prior authorization, could be implemented
in physician groups by drawing on existing utilization management expertise, infrastructure, and staff.
Further, the processes for negotiating and monitoring
SAI prices should build upon an existing contracting department
with expertise in HMO risk arrangements and drug price negotiation. In contrast, very few groups quantified SAI drug costs or
hired personnel, reflecting their overall lack of expertise and
resources to develop a viable SAI drug management program.
Finally, power in negotiating with drug manufacturers is key
for organizations wishing to obtain discounts and rebates from
manufacturers and, therefore, manage SAI drug-cost increases.
In our sample, most price negotiations occurred between the
physician groups and pharmacy providers, not with drug manufacturers, presumably because of the relatively small portion of
market share that physician groups could leverage with the
manufacturers. By giving physician groups the power to transfer risk for SAI drug costs to HMOs, which command significantly larger market share, lower SAI prices could be obtained
from manufacturers by the HMOs.
■■ Limitations
Our study has several limitations. First, we did not consider the
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Financial Risk Relationships and Adoption of Management Strategies in Physician Groups for Self-Administered Injectable Drugs
extent to which the length of a medical group’s experience with
risk contracting was an explanatory variable.
Second, we relied upon self-report data to measure SAI
drug-risk levels and innovation, and we did not pursue interviews with physician group representatives to determine qualitative characteristics and differences in the financial risk
arrangements with HMOs.
Third, we did not obtain detailed information regarding the
management or administration of the physician groups or query
respondents about various SAI distribution methods; for example, we did not obtain information on the extent to which physician groups used group purchasing organizations to minimize
SAI costs when patients received SAIs directly from physicians.
Fourth, we considered all strategies equal in importance,
even though it is likely that some strategies have a larger impact
on SAI drug management than others.
Fifth, the characteristics of our sample limit the generalizability of our findings. The sample itself was too small to validate results through the use of statistical hypothesis testing.
Because we surveyed large physician organizations with experience of 1 year or more in managing drug risk, our results are
not generalizable to smaller physician groups or those with less
experience with financial risk contracting.
In addition, the variations in market characteristics among
the 4 cities we studied were large and create uncertainty about
the extent to which findings from these locations are applicable
to other markets. For example, there may exist other contractual arrangements between physician groups and HMOs that were
not found among our sample. Similarly, medical groups and
HMOs operate in other states where legislation may restrict or
prohibit drug-risk transfer entirely. Nonetheless, ours remains
the first systematic study of SAI drug risk and the first analysis
of the number and types of SAI drug-use management strategies
showing a pronounced link between strategy adoption and
locus and level of risk for SAIs.
We did not measure the effectiveness of any of these management strategies on actual SAI drug utilization or spending.
We did not assess the extent to which HMOs negotiated purchase discounts or rebates with manufacturers on behalf of
contract physician groups. Future research will also need to
assess the extent to which physician groups use group purchase
organizations to affect the average price of SAI drugs and how
physician medical groups and HMOs use specialty pharmacies
to manage SAI drug cost and care outcomes.
■■ Conclusion
Policymakers intent on maximizing the benefit of each of these
4 factors: risk, environment, ability to implement, and power in
negotiations (REAP) should consider whether the physician
group—or any single entity—is the optimal party to bear financial responsibility for SAI costs. Physician groups, while most
knowledgeable regarding the clinical factors related to
532 Journal of Managed Care Pharmacy
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November/December 2003
SAIs, may not have the infrastructure or resources necessary for
successful implementation of SAI drug-use management strategies. Physician groups certainly can assume some financial risk;
indeed, we believe that their clinical expertise means they can
(and should) adopt some strategies to manage risk, including
authorizations and clinical guidelines, without becoming the
primary bearer of financial risk.
Further, even the largest physician groups lack adequate
power since they generally represent only a fraction of the covered lives needed to secure significant rebates and discounts
from drug manufacturers. A sustainable and affordable SAI drug
financial risk-management program—one that maximizes the
REAP factors while managing the financial burden for
patients—ultimately will require collaboration among public
and private purchasers, health plans, providers, patients, and
drug manufacturers.
DISCLOSURES
Funding for this research was provided by the Robert Wood Johnson
Foundation and was obtained by authors Jonathan D. Agnew, Marilyn R.
Stebbins, and David E. Hickman. Agnew served as principal author of the
study, and study concept and design were contributed by Stebbins, Hickman,
and author Helene Levens Lipton. Drafting of the manuscript was primarily
the work of Agnew. Critical revision of the manuscript, analysis and interpretation of data, and statistical expertise were the work of all authors. An
abstract of this article was accepted as a poster at the AcademyHealth Annual
Research Meeting 2003, Nashville, Tennessee.
REFERENCES
1. McHutchinson J, Gordon S, Schiff E. Interferon alfa-2b alone or in combination with ribavirin as initial treatment for chronic hepatitis C. N Engl J Med.
1998;339:1485-92.
2. Medical Advisory Board of the National Multiple Sclerosis Society. Disease
Management Consensus Statement. New York: National Multiple Sclerosis
Society; 2002. Available at: http://www.nationalmssociety.org/SourcebookEarly.asp. Accessed October 17, 2003.
3. American College of Rheumatology. Guidelines for the Management of
Rheumatoid Arthritis. Arthritis Rheum. 2002;46(2):325-45.
4. Shanahan J, Moreland L, Carter R. Upcoming biologic agents for the treatment of rheumatic diseases. Curr Opinion Rheum. 2003;15(3):226-36.
5. Humulin [package insert]. Indianapolis, IN: Eli Lilly; 2002.
6. Humatrope [package insert]. Indianapolis, IN: Eli Lilly; 2002.
7. Epogen [package insert]. Thousand Oaks, CA: Amgen; 1999.
8. Neupogen [package insert]. Thousand Oaks, CA: Amgen; 2002.
9. Lovenox [package insert]. Bridgewater, NJ: Aventis Pharmaceuticals; 2003.
10. Gonal F [package insert]. Rockland, MA: Serono; 2002.
11. Imitrex [package insert]. Philadelphia, PA: GlaxoSmithKline; 2003.
12. Centers for Medicare and Medicaid Services. Prescription Drug Expenditures
Aggregate and Per Capita Amounts, Percent Distribution and Average Annual
Percent Change by Source of Funds: Selected Calendar Years 1980-2011. Bethesda,
MD: CMS Office of the Actuary; 2003.
13. Saikami D. Shifting the Risk for Injectable Drugs: Implications for Heath Plans
and Providers. Washington, DC: Atlantic Information Services; 2001:27.
14. Express Scripts. 2000 Drug Trend Report. 2001:152.
15. Drug Prices and Information, 2003. Available at: Drugstore.com. Accessed
July 10, 2003.
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16. Centers for Medicare and Medicaid Services. CMS Moderately Expands
Medicare Coverage for Injected Drugs. Bethesda, MD: CMS Office of Public
Affairs; 2003.
22. Chernew M, Cowen ME, Kirking DM, Smith DG, Valenstein P, Fendrick
AM. Pharmaceutical cost growth under capitation: a case study. Health Aff.
2000;19(6):266-76.
17. Centers for Medicare and Medicaid Services. Medicare Coverage of
Prescription Drugs Not Usually Self-Administered by the Patient. Baltimore, MD:
CMS Office of Public Affairs; 2003.
23. Lipton HL, Agnew JD. Managing the unmanageable: the nature and
impact of drug risk in physician groups. Paper presented at: Annual Meeting
of the Academy for Health Services Research and Health Policy; June 23-25,
2003; Washington, DC.
18. Carroll J. Physicians reconsider taking on pharmacy risk. Managed Care.
July 2000:9(7).
19. Rubinstein E, Saikami D, Nee C. Managing prescription drug costs in
medical groups. Med Group Manage J. 1992;39(3):62, 64, 72-73.
20. Chapter 798, California Statutes of 2002. Available at: http://www.leginfo.ca.gov/statute.html. Accessed October 17, 2003.
21. Robinson JC. Theory and practice in the design of physician payment
incentives. Milbank Q. 2001;79(2):149-77.
24. Hickman D, Stebbins M. Why are self-administered injectable medications
important? Paper presented at: Academy of Managed Care Pharmacists
Midyear Clinical Meeting; September 17-19, 2001; Phoenix, AZ.
25. University HealthSystem Consortium, 2000.
26. Hillman AL, Pauly MV, Escarce JJ, et al. Financial incentives and drug
spending in managed care. Health Aff. 1999;18(2):189-200.
27. Berndt ER. The U.S. pharmaceutical industry: why major growth in times
of cost containment? Health Aff. 2001;20(2):100-14.
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Journal of Managed Care Pharmacy 533
SUBJECT REVIEW
Unmet Needs in the Treatment of Allergic Asthma:
Potential Role of Novel Biologic Therapies
WILLIAM W. STORMS, MD
ABSTRACT
OBJECTIVE: To provide a review of the current status of the treatment of asthma
and introduce new and developing forms of therapy by means of a review of
published literature on asthma and publications on new and emerging therapies.
Increased public awareness of asthma, improved patient and provider education,
implementation of national treatment guidelines, and availability of safe and
effective therapies have combined to provide an effective response to the
increase in asthma prevalence. However, the number of persons with poorly
controlled asthma and asthma-related complications remains unacceptably high.
This is particularly true for the relatively small cohort of patients with moderateto-severe asthma that is poorly controlled with inhaled corticosteroids and other
standard-of-care medications. Consequently, these patients often experience frequent exacerbations, leading to a disproportionate consumption of asthma health
care resources and a poor quality of life. The National Committee on Quality
Assurance suggests that the negative impact of asthma can be minimized if
health care providers implement aggressive asthma management programs that
include patient education and appropriate medications. Newer therapies such as
injectable anti-IgE may provide a benefit for many patients.
SUMMARY: Currently available asthma medications have been proven to be generally safe and effective for most asthma patients. However, the subset of patients
with difficult-to-treat asthma who experience frequent exacerbations requiring
emergency department visits or hospitalizations may benefit from novel therapies
designed to target specific mechanisms underlying airway inflammation.
CONCLUSIONS: New therapies may help in the treatment of patients whose asthma is not controlled. These include anti-immunoglobulin E (IgE) antibodies,
cytokine modulators, and DNA vaccinations. Future research will determine if
these targeted biologic therapies are a cost-effective means to improve the clinical and economic outcomes of asthma management.
KEYWORDS: Airway inflammation, Allergic asthma, Asthma management,
Biologics, IgE blockers, Managed care
J Managed Care Pharm. 2003;9(6):534-43
Author
WILLIAM W. STORMS, MD, is clinical professor of medicine, University of
Colorado Health Sciences Center, and a practicing allergist at Asthma and
Allergy Associates, Colorado Springs, Colorado.
AUTHOR CORRESPONDENCE: William W. Storms, MD, Asthma and
Allergy Associates, 2709 North Tejon St., Colorado Springs, CO 80907.
Tel: (719) 473-0872, Fax: (719) 630-3658; E-mail: [email protected]
Copyright© 2003, Academy of Managed Care Pharmacy. All rights reserved.
534 Journal of Managed Care Pharmacy
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A
sthma is a chronic inflammatory disease of the airways
characterized by episodic symptoms such as coughing,
dyspnea, wheezing, chest tightness, variable obstruction
of the tracheobronchial tree, and increased bronchial hyperresponsiveness to various stimuli.1 Several therapeutic advancements over the past decade have yielded a variety of safe and effective medications that allow the majority of patients with asthma to
lead productive lives. In addition, comprehensive asthma treatment guidelines such as the National Asthma Education and
Prevention Program (NAEPP) Expert Panel Report1 outlines the
need for aggressive asthma management in order to improve both
clinical and economic outcomes of the disease.
As a result of these efforts, the estimated number of persons
with asthma attacks has declined slightly since 1997.2 However, a
small subset of asthma patients, in particular those with moderateto-severe persistent disease that is difficult to treat and poorly controlled with current standard of care medications, remain at risk
for frequent exacerbations, which require emergency department
visits or hospitalizations to treat. In addition, these patients miss a
substantial number of work or school days as a result of asthma
and generally have a poor quality of life (QOL).2
Although difficult-to-treat patients represent less than 20%
of the asthma patient population,3 they consume a disproportionate share of asthma care resources.3-5 Consequently, these
patients can potentially derive significant benefit from a simultaneous effort by health care practitioners, government agencies, and managed care plans to teach self-management techniques, improve adherence to prescribed therapy, increase compliance by health care professionals to national asthma treatment guidelines, and enhance QOL.6,7 In addition, these
patients may be candidates for treatment with novel biologic
agents designed to target specific steps in the inflammatory cascade that contribute to persistent airway inflammation.
■■ Epidemiology and Impact
Prevalence
According to the Centers for Disease Control (CDC), the estimated annual prevalence of self-reported asthma increased from 31.4
per 1,000 population in 1980 to 55.6 per 1000 in 1995.2 In 1996,
there was a slight decrease in the self-reported prevalence (to 54.6
per 1,000). This downward trend continued through 1999, with
38.4 persons per 1,000 reporting an episode of asthma or an asthma attack during the preceding 12 months. However, this trend
may reflect a change in the methodology used by the CDC to
measure asthma prevalence. Since 1997, the CDC includes only
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Unmet Needs in the Treatment of Allergic Asthma: Potential Role of Novel Biologic Therapies
Unplanned Use of Medical Resources
Although asthma in the majority of patients is well controlled, it
appears as if up to 20% of asthma patients consume a disproportionate share of asthma health care resources.3 These patients frequently require unplanned medical attention and seek care in
emergency departments (ED) and other urgent care facilities.
From 1980 through 1999, the number of ED visits for asthma
increased by 36%,2 and in 2000, there were 1.8 million ED visits
for asthma (Figure 210). The hospitalization rate for asthma peaked
in the mid-1980s and has gradually declined since then2; in 2000,
there were 465,000 asthma-related hospitalizations (Figure 311).
FIGURE 1
Classification of Asthma Severity Based
on NAEPP Classification of Symptoms
Mild Intermittent
60
Percent of Patients*
Mild Persistent
40
51.0
Moderate Persistent
50
Severe Persistent
39.0
34.2
30
24.2
22.1
20
15.7
22.1
19.1
16.8
16.0
15.0
11.6
10
0
Total
Adults
Children
*Survey of 2,509 asthma patients: 1,788 Adults, 721 children.9
NAEPP = National Asthma Education and Prevention Program.
FIGURE 2
Asthma Emergency Department Visits, 2001
120
104
100
Per 10,000 Population
those patients with a medical diagnosis of asthma as opposed to
an unconfirmed self-report of asthma.2 Despite this change, it
appears as if the trend is toward a decreasing prevalence of asthma in the United States.
Clear estimates of the distribution of asthma severity among
those diagnosed with asthma are not widely available. Fuhlbrigge
et al. used a survey to identify the overall (global) impact of asthma.8 Global asthma burden was composed of short-term
(1 month) symptom burden, long-term (12 months) symptom
burden, and functional impact of asthma-related activity limitations. This study identified only 10.7% of individuals as having a
global asthma burden consistent with mild intermittent disease
and 77.3% with moderate-to-severe persistent disease. The most
recent effort to classify asthma prevalence by disease severity was
generated by the Asthma in America Survey conducted in 1998.9
For this survey, researchers interviewed 2,509 adults and children
with asthma and classified their asthma severity using the symptom-based NAEPP severity classification scheme. As illustrated in
Figure 1, the Asthma in America Survey results suggest that 39.0%
of patients are classified with mild intermittent asthma, 15.7%
with mild persistent, 22.1% with moderate persistent, and 19.1%
with severe persistent disease.9
75
80
67
60
54
58
40
20
0
0-17
Years
18+
Years
Male*
Female*
Total
*Age adjusted to the 2000 population.
FIGURE 3
Asthma Hospitalizations, 2001
35
30
Per 10,000 Population
Mortality
Although the number of deaths and death rates from asthma
increased gradually from 1980 to 1995, it appears as if the mortality rates have started to plateau or decrease.2 In 1995, 5,637
deaths were attributed to asthma. This number fell to 4,487 by
2000.2 As with ED visits and hospitalizations, disparities exist with
higher mortality rates documented among African Americans,
women, and the elderly, with significant regional differences.2
Asthma mortality may be preventable in a significant number
of patients. In 1996, the National Institutes of Health published
the Working Group Report on the Quality of Asthma Care, which
suggested that nearly 50% of asthma mortality is preventable and
that asthma mortality is associated with inadequate or poor-quality medical care.12 Mortality rates, hospital admission rates, and
ED utilization rates are greatest among low-income and minority
populations. For example, in the New York City area, asthma hospitalization rates were found to be 3.6 times greater for children
30
25
19
20
17
15
15
12
10
5
0
0-17
Years
18+
Years
Male*
Female*
Total
*Age adjusted to the 2000 population.
living in low-income areas than for those residing in higher-income
areas.13 The difference noted in this survey may be attributed to an
enhanced ability to identify, avoid, and control asthma triggers and
better adherence to therapy in the higher-income groups.
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Unmet Needs in the Treatment of Allergic Asthma: Potential Role of Novel Biologic Therapies
Economic Burden
In 2000, direct and indirect costs associated with asthma reached
almost $12.7 billion in the United States.14 Direct costs such as hospital and physician services, medications, and diagnostic tests
account for 60%, or $7.62 billion, of the total amount spent on asthma care.14 Hospitalizations account for 47% of the direct medical
expense, followed by medications (30%), hospital outpatient visits
(15%), and ED visits (8%).12 Indirect costs account for the remaining $5.08 billion of the total expenditure and reflect the value of
asthma-related absence from work, school, and other daily activities
and loss of future potential earnings due to premature death.14
Morbidity costs are the largest component of indirect costs, contributing up to 75% of the total indirect costs for asthma.15,16 Loss of
QOL also adds to the indirect costs; patients with the lowest scores
on a health-related QOL scale have been shown to have the highest
asthma-related health care utilization and cost.17
Asthma Severity and Health Care Resource Utilization
A close relationship exists between the severity of asthma and the
costs associated with the disease. The volume of health care
resources utilized and the number of lost days of school or work
all increase as the severity of asthma increases.3-5 In particular, estimated costs associated with moderate disease are nearly twice
those of mild asthma, and health care expenditures associated
with severe asthma are more than 6 times those of mild asthma.4
In one study, patients considered “high cost” required a greater
number of ED visits, hospitalizations, medications, and office/clinic visits; 80% of asthma-related health care resources were used by
20% of the population.5 High users of health care resources also
have the highest risk of asthma-related morbidity and mortality.15,16
It is believed that high users of health care resources have persistent airway inflammation that is poorly controlled by current standard-of-care medications, suggesting that either these medications
are not taken, are taken incorrectly, or are ineffective.18
A recent review of a database of privately insured individuals
indicated that approximately 15% of asthma patients experience a
moderate-to-severe exacerbation annually. The mean total annual
direct costs associated with the cohort of patients with diagnoses of
moderate-to-severe exacerbations (15% of overall asthma patients)
was estimated to be $10,900. Direct costs are influenced by asthma-related and nonasthma-related health care utilization.
Additionally, asthma patients who experience serious exacerbations
tend to have more comorbidities, contributing to higher rates
of hospitalization and ED visits compared with patients who do
not have a diagnosis related to a moderate-to-severe exacerbation.19
Findings from the Epidemiology and Natural History of
Asthma: Outcomes and Treatment Regimens (TENOR) study in
severe and difficult-to-treat asthma confirm the observation that
patients with inadequately controlled moderate-to-severe disease
consumed a disproportionate share of health care resources.
TENOR enrollees, a 3-year observational study of more than
4,500 patients with moderate-to-severe and/or difficult-to-treat
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disease, experienced more asthma-related hospitalizations and
ED visits and had significantly lower asthma-related QOL compared with those with less-severe disease.20 Additionally, TENOR
patients who used multiple medications reported more problems
with asthma control, higher rates of asthma-related hospitalizations and ED visits, and lower QOL compared with those who
took fewer controller medications.20
Asthma and Quality of Life
In general, patients with asthma experience decreased classroom
and workplace productivity,21,22 social maladjustment,23 and sexual
dysfunction.24 Impairment in the health-related quality of life
(HRQOL) in asthma patients has been demonstrated to contribute
to rates of health care utilization. Eisner et al.17 conducted a random sample of 3,842 members of a staff model health maintenance organization (HMO) who completed an HRQOL survey.
Patients were stratified for disease severity. The results of the survey indicated that better baseline asthma-specific HRQOL scores
were associated with lower risk of asthma-related ED use or hospitalization. More favorable HRQOL scores were also associated
with decreased asthma-related health care costs during the following year.17
Impaired QOL can also have a substantial impact on attendance and productivity at work and school. CDC data published
in 2002 reveals that school absence days among children
increased from 6.6 million in 1980 to 14.6 million in 1992.
However this number dipped to 14 million in 1996. Among
adults with asthma, work absence days increased from 6.2 million
in 1982 to 14.5 million in 1996.2
■■ Trends in the Treatment of Asthma
Undertreatment of Asthma
To favorably improve both clinical and economic outcomes, an
asthma management strategy must include accurate diagnosis,
appropriate classification of disease severity, and therapeutic interventions designed to minimize or prevent the underlying airway
inflammation. According to the 2001 report of The National
Committee on Quality Assurance (NCQA7), approximately two
thirds of patients enrolled in nongovernment managed care organizations were being treated with the appropriate asthma medications, representing an approximately 4% increase across all age
groups over the previous year. With continued implementation of
aggressive management strategies, this number will continue to
rise and thus improve clinical and economic outcomes and
enhance QOL. This is particularly critical for patients who fail to
receive appropriate asthma care.
Several factors have been identified that may contribute to
the undertreatment of asthma, including poor compliance with
national asthma guidelines by physicians, pharmacists, and
other caregivers,25 poor adherence by patients to prescribed
therapeutic regimens,26-31 confusion regarding diagnosis due to
the presence of comorbid conditions,32,33 unidentified exacer-
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Unmet Needs in the Treatment of Allergic Asthma: Potential Role of Novel Biologic Therapies
bating factors or triggers,34 and medical or social conditions
(e.g., depression, anxiety disorders, mental impairments, etc.)
that limit the ability of the patient to understand the importance
of adhering to prescribed therapies.35,36
Effect of Medical Guidelines
Evidence-based medicine is a movement away from reliance on
professional judgment toward a more structured assessment of
clinical knowledge. This approach provides a method of weighing
health effects, economic impact, and patient preferences. The
validity of clinical findings in the literature, including the effectiveness, applicability, and potential adverse effects of interventions,
can be critically assessed and then evaluated by use of this decisionmaking tool. The majority of the recommendations in the current
NAEPP asthma treatment guidelines are based on an evidencebased analysis of the literature. For example, the recommendation
that inhaled corticosteriods (ICSs) form the basis of long-term asthma management is derived from an analysis that revealed that longterm regular use of these agents reduced asthma mortality.37
The first Expert Panel Report on the Management of Asthma
was published in 1991 and recognized the role of airway inflammation in the pathogenesis of asthma. Subsequent editions of the
Expert Panel Report were published in 19971 and 2002.38
Although the NAEPP strives to keep clinical practice guidelines
up-to-date, the continual emergence of new data on medications,
asthma-monitoring techniques, and prevention programs makes
this task challenging. For example, in 2002, the NAEPP Expert
Panel published an extensive review of data published since 1997
on the long-term use of ICSs in children with asthma. Data
describing the effect of combination therapy and use of antibiotics
in the treatment of asthma as well as the impact of written asthma
action plans and prevention programs are also reviewed.38
Much progress has been made in the implementation of the
recommendations provided in the NAEPP guidelines, but deviations from the guidelines in the care of asthma has been observed
in several patient groups, including pediatric, inner-city, and managed care patient populations.39-42 Donahue et al. analyzed 19961997 claims data to compare baseline pharmacotherapy in children with asthma at 3 managed care organizations.40 Of the
13,352 children included in the study, fewer than than 40% were
given controller medications during the study interval, leading the
investigators to conclude that the pattern of asthma therapy in this
pediatric population does not reflect the recommendations of the
guidelines.40 Lang et al. performed a cross-sectional analysis of
monthly bronchodilator and ICS prescription rates and demographic factors such as race, ethnicity, poverty, educational levels,
and ZIP code and noted the existence of a gap between optimal
asthma drug prescribing as recommended by the guidelines and
actual prescribing patterns.41 This gap was greatest in asthma
patients living in the ZIP codes assigned to inner-city regions of
Philadelphia. Legorreta et al. surveyed 5,580 members of a large
California HMO to compare the status of asthma disease manage-
ment with treatment recommendations found in the NAEPP
guidelines.42 These authors reported that 72% of survey respondents reported having a steroid inhaler, but only 54% used it daily.
Similarly, 26% reported having a peak-flow meter, but only 16%
used it daily.42 Doerschug et al. reported that practitioner training
and specialization significantly influenced understanding and subsequent compliance with the NAEPP guidelines.39 These investigators observed that asthma specialists as well as generalists with
more advanced training in asthma had a greater understanding of
the guidelines.39
Additional barriers to compliance with practice guidelines in
general include disagreement with the recommendations,43-45 lack
of familiarity and training,43-45 economic disincentives,46 and inadequate time.47 These results suggest a need for more and better
educational programs that address asthma diagnosis and treatment targeted to health care professionals and patients regarding
the importance of national guidelines.
Impact of Managed Care Intervention
Managed care organizations have contributed to the improvement
observed in asthma outcomes via the initiation of asthma management programs that identify high-risk patients, motivate
providers to comply with national treatment guidelines, educate
patients about their disease, and monitor clinical and economic
outcomes. One of the most successful programs implemented by
managed care plans uses comprehensive asthma management
clinics that enlist the support of pharmacists, primary care physicians, asthma specialists, and case managers. Specifically, pharmacist-managed asthma care programs have been demonstrated to
improve compliance with treatment guidelines, increase patient
understanding of the disease and adherence to therapy, enhance
QOL, and improve clinical and economic outcomes.
A pharmacist-provided comprehensive education program in
conjunction with care provided by a pulmonologist improved the
economic, clinical, and humanistic outcomes in adults with asthma compared with patients receiving care from a pulmonologist
alone.48 Patients receiving combined care reported significantly
more information about asthma self-management, were more likely to monitor peak-flow readings, and had increased satisfaction
with care than those treated exclusively by the specialist. Fischer
et al. reported that pharmacist intervention at the point of sale
appeared to increase the information given to patients about their
medications, increase awareness of side effects, and promote
adherence compared with usual care.49
Narhi et al. conducted a 12-month prospective study to determine the impact of community pharmacist intervention on severity of asthma symptoms, changes in peak-flow rates, changes in
daily medications, and the number of patients requiring oral corticosteroids.50 A positive change was noted in all outcome measures, particularly in the severity of asthma symptoms, with 79% of
patients having a net improvement in one or more indicators of
asthma severity.50
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Unmet Needs in the Treatment of Allergic Asthma: Potential Role of Novel Biologic Therapies
A drug therapy monitoring clinic established by the pharmacy
department of a large military hospital was highly effective in
improving clinical and economic outcomes for asthma patients.51
A chart review following implementation of the program indicated that compliance with national treatment guidelines was significantly improved when patients were followed by a pharmacist
compared with a primary care physician.51
A recently reported randomized controlled clinical trial indicates that 12 months after implementation of an aggressive pharmacist-managed intervention program, asthma patients demonstrated increased peak-flow rates and satisfaction with care compared with usual care, but they also increased the amount of
breathing-related medical care sought. Consequently, the program
increased the overall cost of care. However, disease severity and
patient awareness of available treatment options may explain the
apparent lack of cost savings with this intervention.52
Referral to an asthma specialist (usually an allergist or pulmonologist)—particularly for patients with severe asthma—may help
improve medical adherence to asthma management guidelines
and patient QOL.53-55 Westley et al.56 reviewed the charts of
70 moderate-to-severe asthma patients enrolled in a large staff
model HMO before and after referral to an asthma specialist (either
allergist or pulmonologist). Following consultation with the
specialist, there was a 45% decrease in the number of office visits
for asthma, a 55% decrease in acute care visits, a 67% decrease in
hospitalizations, and a cost savings of $2,100 per patient.56
Similar findings were reported by Wu et al.,57 who conducted
a survey of asthma outcomes among 1954 adult asthma patients
treated either by a specialist or generalist. Compared with patients
treated by generalists, patients treated by an allergist reported
fewer cancelled activities, hospitalizations, and ED visits and
greater physical functioning. Patients treated by pulmonologists
reported that their symptom control was improved compared with
those treated by generalists.57 Frieri et al.58 reported that asthma
patients evaluated by allergists had more severe disease and thus
had more office visits and were prescribed more medications than
those seen by a primary care physician. However, it was also noted
that, despite the increased cost to treat the more severe patients,
their care was more closely aligned with the NAEPP treatment
guidelines.
■■ Adherence to Asthma Therapy
Patients who adhere closely to therapy tend to do well clinically.59
Conversely, poor adherence to a therapeutic regimen has been
identified as a major factor contributing to suboptimal asthma control.60-62 Nonadherence exacts multiple consequences, including
increased hospitalization, ED visits, detrimental changes in clinical
status, and asthma-related mortality.63-65 For example, Suissa et al.
have reported the hospitalization rate and incidence of asthmarelated death are lower in patients who persist with continuous
low-dose asthma therapy compared with those who do not.66,67
Adherence rates for all medications prescribed for asthma ther538 Journal of Managed Care Pharmacy
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November/December 2003
apy range from 30% to 70%.64 In several reports, fewer than half
of all patients prescribed inhaled medications adhered to their prescribed regimens.65,68 Adherence to ICS therapy has been reported
to decrease by 1.6% a week,62 possibly because patients perceive
ICS therapy to be time-consuming, inconvenient, and difficult to
use.62 Alternatively, the reduction in patient adherence may be
explained by the efficacy of current treatments such as ICS therapy as patients become complacent in the absence of recurrent
asthma symptoms.
Strategies to Improve Adherence
There is no single reason for poor adherence to therapy, and nonadherence can occur with both symptomatic and asymptomatic
diseases. However, adherence is a learned behavior and can be
improved with practice and reinforcement. Therefore, it appears
that some form of ongoing intervention from pharmacists or other
health care practitioners is imperative to increase adherence to
prescribed treatment regimens. Strategies should include methods
that both health care professionals and patients can implement.
Educating patients is a cost-effective way to improve asthma
outcomes, particularly among high-risk patients.69,70 Patients who
are knowledgeable about their disease and the treatments being
used to manage it are also more motivated to adhere to the treatment plan.71 An educational dialogue founded on open communication between clinician and patient is critical for a successful partnership in asthma care.61
Educating patients about asthma self-management begins at
the time of diagnosis and is integrated into each clinician-patient
interaction. All patients with moderate-to-severe asthma should be
enrolled in an ongoing, intensive asthma education program.
Primary caregivers should be enrolled for those whose care must be
delegated to others. Patients should receive instruction on the
appropriate use of medication delivery devices and should be able
to demonstrate their self-administration technique to the satisfaction of their health care provider. In addition, patients should be
educated about asthma pathophysiology, environmental control
and avoidance measures, asthma action plans, medications, drug
interactions and side effects, self-management, and adherence techniques. Educational mediums include discussions with health care
professionals, brochures, videos, and information acquired via the
Internet or support groups.
As part of the educational effort, each patient should be given
a written asthma “action plan” that outlines the asthma management program design in partnership with the patient and family.72
A sound action plan is easy to understand and implement, consistent with the patient’s personal goals and daily activities, and outlines how variations in symptoms impact dosing of medication.
Specifically, the asthma action plan includes a diary for recording
peak expiratory flow-rate measurements and therapeutic guidelines to follow when peak-flow measurements decline or symptoms worsen. The plan should also clearly outline when it is
appropriate to seek emergency help. Pertinent phone numbers
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Unmet Needs in the Treatment of Allergic Asthma: Potential Role of Novel Biologic Therapies
(clinic, hospital, pharmacy, urgent care center, etc.) should
be clearly written in a prominent place in the action plan. An
excellent example of an asthma action plan is found in the
NAEPP guidelines.1,38
■■ Biologic Therapies for the Treatment of Asthma
Pharmacologic therapy is used to prevent and control asthma symptoms, reduce frequency and severity of exacerbations, and reverse airflow obstructions. Choosing the best
medication for individual patients requires knowledge of the
severity of the airway inflammation, familiarity with the
mechanism of action of the drug(s), the likelihood of patient
adherence, and expected impact on QOL and economic
outcomes resulting from the use of each medication.
Current therapies are safe and effective for the vast majority of
asthma patients and lead to improved clinical and economic outcomes. However, as noted earlier, a relatively small proportion of
asthma is poorly controlled on current therapies. It is these patients
who may benefit from therapies developed as a result of recent
advances in the understanding of the pathogenesis of asthma.
The novel therapies reviewed briefly below have the potential to
inhibit the allergic inflammatory process or modify the natural history of the asthma, although many of these benefits have yet to be
proven beyond small clinical studies. An anti-immunoglobulin E
(IgE) antibody has recently been approved for use in patients with
moderate-to-severe asthma poorly controlled on ICS therapy.
Therapies under development, but not currently available outside of
clinical trials, include cytokine modulators, immunostimulatory
DNA sequences, and monoclonal antibodies targeted against Th2
cytokines and mediators.
Anti-IgE Antibodies
The anti-IgE antibody (or IgE blocker) omalizumab is the first biologic therapy to be approved by the U.S. Food and Drug
Administration (FDA) for the treatment of allergic inflammation in
asthma. Specific FDA approval was granted for adults and adolescents aged 12 years and older with moderate-to-severe persistent
asthma who have a positive skin test or in vitro reactivity to a
perennial aeroallergen and whose symptoms are inadequately controlled with ICSs.73
IgE blockers inhibit binding of free IgE to receptors on the proinflammatory mast cells and basophils, thus attenuating the cascade of events that leads to airway inflammation and subsequent
symptoms in patients with moderate-to-severe allergic asthma. 1,38
Once- or twice-monthly subcutaneous administration of omalizumab to patients who remained symptomatic on a constant dose
of ICSs resulted in a significant (P≤0.005) reduction in the frequency of exacerbations compared with ICS therapy alone
(Table 174,75). An exacerbation was defined as an episode severe
enough to require either a doubling of baseline ICS dose or addition of a course of systemic corticosteroids, based on the treating
physician’s clinical judgment. The addition of omalizumab to ICS
TABLE 1
Placebo-Controlled Trials of Omalizumab
in Moderate-to-Severe Asthma:
Frequency of Exacerbations
Busse et. al74
Soler et. al75
Omalizumab Placebo Omalizumab
(N=274)
(N=257)
(N=268)
Placebo
(N=272)
Stable Steroid Phase (16 weeks)
Mean no. exacerbations
per patient
P Value
0.28
0.54
0.28
0.66
<0.001
0.009
Steroid Reduction Phase (12 weeks)
Mean no. exacerbations
per patient
0.39
0.66
0.03
P Value
0.36
<0.001
0.75
therapy also increased forced expiratory volume in 1 second
(FEV1) from baseline (P<0.05) and improved daytime and nocturnal asthma symptom scores compared with the control
(P<0.05).74,75
Anaphylaxis or an anaphylactoid reaction has been reported
within 2 hours of administration of omalizumab in <0.1% of all
patients receiving omalizumab without other identifiable allergic
triggers. No adverse drug interactions or antibodies to omalizumab have been reported. Among all completed studies, malignant
neoplasms (excluding nonmelanoma skin cancers) occurred in 16
of 4,127 patients exposed to the drug and 2 of 2,236 controls. The
most frequent adverse events included injection site reaction
(45%), viral infections (23%), upper respiratory tract infection
(20%), sinusitis (16%), headache (15%), and pharyngitis (11%).
These events were observed at similar rates in omalizumab-treated patients and control patients.73
Due to the need for subcutaneous administration, cost, and
narrow indication, biologic therapies such as omalizumab, while
promising, are not currently recommended for use in large numbers of asthma patients. Rather, their use should be targeted to the
approximately 30% of asthma patients with a documented allergic
component that experience frequent exacerbations, have a history
of high health care resource utilization, have a poor record of
adherence to therapy, and in whom therapy may be complicated
by IgE-mediated comorbidities. This new drug therapy is costly
compared with existing therapies but may be cost effective if targeted to the most appropriate patients. A thorough description of
the cost-effectiveness of omalizumab awaits further investigation.
Agents Targeting Cytokine Activity
The effects of key inflammatory cytokines can be attenuated by
several experimental monoclonal antibodies currently in development. These antibodies have their effects by blocking the cytokine
receptor or by binding to the cytokine in a way that renders them
inactivate.76 Soluble IL-4 (interleukin) receptor antagonists
(IL-4R) are reported to improve lung function and reduce corticosteroid and B2-agonist use in moderate asthma, possibly via a
mechanism that attenuates the production of IgE and expression
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Journal of Managed Care Pharmacy 539
Unmet Needs in the Treatment of Allergic Asthma: Potential Role of Novel Biologic Therapies
of IgE receptors.77,78
Initial phase 1 and phase 2 studies with soluble IL-4R were
performed in subjects with mild-to-moderate persistent asthma
who were withdrawn from ICS therapy and then randomly
assigned to placebo or a single dose of nebulized IL-4R.76,78
Nebulized IL-4R therapy improved asthma symptom scores,
decreased rescue B2-agonist use, improved FEV1, and decreased
methacholine airway responsiveness. No significant side effects
were noted. A subsequent phase 2 study in subjects with moderate persistent asthma compared the longer-term effect of administering weekly doses of nebulized IL-4R for 3 months as opposed
to a single dose. Withdrawal of ICSs in subjects treated with placebo resulted in a significant decline in FEV1 that did not occur in
the treatment group. Although much work remains, these studies
suggest the potential of IL-4R therapy in asthma.
Initial studies with anti-IL-5 were performed in patients with
mild asthma exposed to an inhaled allergen to determine if
anti-IL-5 provided protection against eosinophilia and airway
responsiveness to methacholine.79 A single intravenous infusion of
anti-IL-5 antibody reduced blood and sputum levels of
eosinophils by more than 90%. However, despite this reduction,
patients treated with anti-IL-5 were not protected against the latephase decline in FEV1 and did not develop reduced airway
responsiveness.79
A second study demonstrated that while anti-IL-5 is very effective in inhibiting eosinophils in blood and sputum (i.e., >90%), it
is less effective in inhibiting airway eosinophils (only 60%). This
level of eosinohil reduction may be insufficient to attenuate or prevent airway hyperreactivity.
Studies conducted in IL-5 and eotaxin-deficient mice demonstrated that eosinophil recruitment to the airway and development
of airway hyperreactivity is maximally inhibited in the combined
IL-5/eotaxin-deficient mice as opposed to the individual mutant
mice. These results suggest that the combination of anti-IL-5 with
an inhibitor of eosinophil chemoattraction may be a more effective
strategy than inhibiting IL-5 or eotaxin alone.80
Another approach to altering cytokine activity includes the
administration of anti-inflammatory cytokines. IL-10 has several
anti-inflammatory properties that may make it important in the
treatment of asthma. Reduced levels of IL-10 have been noted in
asthma patients, and patients with severe asthma are more likely
to exhibit gene expression associated with lower production of
IL-10.78,81 However, some studies have demonstrated increased
IL-10 mRNA (messenger RNA) expression in allergy and asthma.82
Clearly, additional research is required to determine the role of
IL-10 in asthma and its potential as a therapy for asthma.
The cytokine IL-12 plays a role in regulating Th1 cell differentiation and in blocking the expansion of Th2 cell lines by stimulating Th0 cells to release IFN-g (interferon).77 There are reports
that recombinant IL-12 reduces eosinophils in blood and sputum
but has little or no effect on bronchial hyperresponsiveness.83
Although these experimental therapies hold some promise, it is
540 Journal of Managed Care Pharmacy
JMCP
November/December 2003
believed that modifying individual cytokines may not ultimately
prove to be an effective strategy because of the significant redundancy in the immune response to inhaled allergens.76 A novel soluble receptor for IL-13 may also have therapeutic potential for the
treatment of asthma.76
The cytokine modulator suplatast tosilate is a nonspecific Th2
inhibitor that has been shown to suppress IL-4 and IL-5 synthesis
and attenuate eosinophilic airway inflammation when used as an
adjunct to corticosteroid therapy in patients with mild asthma.84
Suplatast inhibits Th2-type cytokines, which are purportedly
involved in the pathogenesis of asthma. Sano et al. compared outcomes in 15 patients with mild asthma treated with suplatast tosilate for 6 weeks and 13 control patients. The treatment group
showed a significant improvement in the concentration of histamine following a challenge while the control patients did not.
Similarly, significant improvements in peak expiratory flow and in
symptom scores were observed in patients in the treatment group,
but not in controls. Treatment with suplatast was associated with
a reduction in average number of infiltrating eosinopils. The average number of CD4+ (clusters of differentiation) and CD25+
T cells also dropped with suplatast therapy. These outcomes were
not observed in controls.85
DNA Vaccination
It has been proposed that one potentially effective strategy for
modifying the asthma disease process is to use immunostimulatory DNA sequences to bias the immune system away from a Th2
response and toward a Th1 response.86 Using a mouse model,
Horner et al. noted that airway and systemic eosinophilia were significantly suppressed following administration of a vaccination
containing DNA sequences and noted a suppressed airway and
systemic eosinophilia in response to an inhaled allergen.86
Inhibition of airway inflammation and eosinophilia has also been
noted in mice using a vaccine that induces an immune response
directed at IL-5. Immunotherapy with vaccinations appears to be
effective in animal models, but extensive further research is
required to demonstrate their applicability in humans.
In summary, biologic agents under development for the treatment of asthma offer the promise of therapies that target specific
steps in the pathogenesis of the disease. However, with the exception of the IgE blocker omalizumab, these experimental therapies
are several years away from potential use in regular clinical practice.
Because of their experimental status, no data exist comparing the
cost-effectiveness of these agents with more conventional therapies.
As novel biologic therapies become available, the most appropriate
use will need to be determined, particularly considering the current
availability of many safe and effective pharmacotherapies that provide sufficient asthma control in the majority of patients.
■■ Conclusions
Asthma care remains suboptimal despite major therapeutic
advances over the past decade and the widespread dissemination
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Unmet Needs in the Treatment of Allergic Asthma: Potential Role of Novel Biologic Therapies
of asthma management guidelines. Asthma is associated with significant morbidity and mortality, and, clearly, the primary goals of
therapy are to decrease the number of exacerbations, reduce the
severity of symptoms, reduce ED use and hospital admissions, and
improve QOL. While progress has been made in reducing the
rates of adverse outcomes of asthma, there remain unacceptably
high rates of adverse outcomes, particularly in patients with poorly controlled moderate-to-severe disease. It is these patients who
are suboptimally controlled on current standard-of-care medications and who consume a disproportionate percentage of the
health care resources used in asthma care.
Patients with poorly controlled asthma stand to benefit from
management strategies that guide clinicians and managed care
organizations in making appropriate treatment decisions.
Numerous observational studies have shown that practitioner
compliance with national treatment guidelines and patient adherence to treatment regimens is less than optimal. Targeted educational initiatives for pharmacists and other health care professionals, as well as for patients, may help improve clinical and economic outcomes.
Asthma patients will also benefit from the continuing development of novel biologic therapies that specifically target the mechanisms responsible for persistent airway inflammation. The
recently approved IgE blocker omalizumab and the numerous
cytokine modulators and other biologically engineered agents still
in development offer patients with poorly controlled, moderateto-severe asthma promising alternatives to currently available
treatments. However, the cost-effectiveness of these agents has yet
to be determined.
5. Godard P, Chanez P, Siraudin L, et al. Costs of asthma are correlated with
severity: a 1-yr. prospective study. Eur Respir J. 2002;19:61-67.
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Global Initiative for Asthma: Global Strategy for Asthma Management and
Prevention. Bethesda, MD: National Institutes of Health; 2002. NIH Publication
No. 02-3659.
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2002. Use of appropriate medications for people with asthma. Available at:
http://www.ncqa.org/sohc_2002_asthma.html. Accessed August 16, 2003.
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Accessed March 23, 2003.
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ACKNOWLEDGMENT
The research and editorial support of Keith Engelke is greatly appreciated.
DISCLOSURES
Funding for this research was provided by an unrestricted educational grant
from Genentech Inc. and Novartis Pharmaceuticals Corporation, and was
obtained by author William W. Storms. The author discloses participation in
speakers’ bureaus or paid consultant work for AstraZeneca, Aventis, Genetech,
Merck, Novartis, and Schering-Plough and work as principal investigator in
research funded by 3M, Adams Labs, Aerogen, AstraZeneca, Aventis, Bayer,
Immunex, Ivax, Merck, Novartis, Pfizer, Schering-Plough, Sepracor, and others. Administrative and technical support for this study was provided by Keith
Engelke, Dover Communications, Blue Bell, Pennsylvania.
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Unmet Needs in the Treatment of Allergic Asthma: Potential Role of Novel Biologic Therapies
72. Hunt LW. How to manage difficult asthma cases. An action plan for physicians and patients. Postgrad Med. 2001;109:61-68.
80. O’Byrne PM, Inman MD, Parameswaran K. The trials and tribulations of
IL-5, eosinophils, and allergic asthma. J Allergy Clin Immunol. 2001;108:503-08.
73. Omalizumab [prescribing information]. San Francisco, CA: Genentech, Inc.,
and East Hanover, NJ: Novartis Pharmaceuticals Corporation; 2003. Available at:
http://www.gene.com/gene/common/inc/pi/xolair.jsp. Accessed August 15, 2003.
81. Tomita K, Lim S, Hanazawa T, et al. Attenutated production of IL-10 and
IL-12 in monocytes from patients with severe asthma. Clin Immunol. 2002;
102:258-66.
74. Busse W, Corren J, Lanier BQ, et al. Omalizumab, anti-IgE recombinant
humanized monoclonal antibody, for the treatment of severe allergic asthma.
J Allergy Clin Immunol. 2001;108:184-90.
82. Lim S, Crawley E, Woo P, Barnes PJ. Haplotype associated with low interleukin-10 production in patients with severe asthma. Lancet. 1998;352:113.
75. Soler M, Matz J, Townley R, Buhl R, et al. The anti-IgE antibody omalizumab
reduces exacerbations and steroid requirement in allergic asthmatics. Eur Respir J
2001;18:254-61.
76. Barnes PJ. Cytokine modulators as novel therapies for asthma. Ann Rev
Pharmacol Toxicol. 2002;42:81-98.
77. Barnes PJ, Chung KF, Page CP. Inflammatory mediators of asthma: an update.
Pharm Rev. 1998;50(4):515-96.
78. Borish LC, Nelson HS, Lanz MJ, et al. Interleukin-4 receptor in moderate
atopic asthma: a phase I/II randomized, placebo-controlled trial. Am J Respir Crit
Care Med. 1999;160:1816-23.
83. Bryan SA, O’Connor BJ, Matti S, et al. Effects of recombinant human interleukin-12 on eosinophils,airway hyper-responsiveness, and the late asthmatic
response. Lancet. 2000;356:2149-53.
84. Tamaoki J, Kondo M, Sakai N, et al. Effect of suplatast tosilate, a Th2
cytokine inhibitor, on steroid-dependent asthma: a double-blind randomised
study. Lancet. 2000;356:273-78.
85. Sano Y, Suzuki N, Yamada H, et al. Effects of suplatast tosilate on allergic
eosinophilic airway inflammation in patients with mild asthma. J Allergy Clin
Immunol. 2003;111:958-66.
86. Horner AA,Van Uden JH, Zubeldia JM, et al. DNA-based immunotherapeutics for the treatment of allergic disease. Immunol Rev. 2001;179:102-18.
79. Leckie MJ, ten Brinke A, Khan J, et al. Effects of an interleukin-5 blocking
monoclonal antibody on eosinophils, airway hyperresponsiveness, and the late
asthmatic response. Lancet. 2000;356:2144-48.
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JMCP
Journal of Managed Care Pharmacy 543
F O R M U L A RY M A N AG E M E N T
Determinants of the Cost-Effectiveness of Statins
ALAN MORRISON, PhD, and HELENE GLASSBERG, MD
ABSTRACT
OBJECTIVE: To examine the cost-effectiveness of statins in relation to different
measures of effectiveness, differences in efficacy among individual statins, and
the risk of coronary heart disease. Efficacy is defined here as the magnitude of
the effect produced by a given amount of drug, as demonstrated in placebocontrol trials; i.e., the effectiveness per unit dose.
DATA SYNTHESIS: Treatment guidelines categorize patients by their risk of coronary events and set lower target cholesterol levels for patients at higher risk.
Statins vary in their efficacy. If effectiveness is expressed as percent lowering
in low-density lipoprotein cholesterol (LDL-C) and relatively little cholesterol lowering is required—as in low-risk patients—even statins of low efficacy provide
adequate cholesterol lowering, and drug price is the determining factor of costeffectiveness. For patients at high risk—the primary target group, which has
been expanded in recent guidelines—high-efficacy statins are required to meet
the more aggressive cholesterol goals, and efficacy is the important determinant
of cost-effectiveness. When effectiveness is expressed in terms of life-years
saved, the cost-effectiveness of statins as a class for treatment of high-risk
patients compares favorably with the cost-effectiveness of generally accepted
medical treatments.
CONCLUSION: In order to optimize cost-effectiveness, the level of effectiveness
required to treat the specific patient or patient group must be considered. Statin
efficacy is the major determinant of cost-effectiveness when greater cholesterol
lowering is required, i.e., for high-risk patients, who make up the primary target
group. Statin price is the more important factor if only limited cholesterol lowering (e.g., 35% or less reduction in LDL) is required.
KEYWORDS: Hydroxymethylglutaryl-CoA reductase inhibitors, Cost-effectiveness
analysis, Drug therapy, Economics, Coronary disease
J Managed Care Pharm. 2003;9(6):544-51
Authors
ALAN MORRISON, PhD, is senior consultant, SCRIBCO, Blue Bell, Pennsylvania;
HELENE GLASSBERG, MD, is assistant professor of medicine and director of
Prevention Cardiology and Lipid Center, Temple University Hospital, Philadelphia,
Pennsylvania.
AUTHOR CORRESPONDENCE: Alan Morrison, PhD, Senior Consultant,
SCRIBCO, P.O. Box 1525, Blue Bell, PA 19422. Tel: (610) 239-0701;
Fax: (610) 239-0712; E-mail: [email protected]
Copyright© 2003, Academy of Managed Care Pharmacy. All rights reserved.
544 Journal of Managed Care Pharmacy
JMCP
November/December 2003
H
igh blood cholesterol is a major modifiable risk factor
for coronary heart disease (CHD), the primary cause
of illness-related death in the United States.1,2 Every
10% reduction in total cholesterol decreases the risk of coronary death by 15%.3 Hence, cholesterol-lowering treatments,
including statins (inhibitors of hydroxymethylglutaryl-CoA
reductase), have been recommended in national guidelines for
an ever-widening section of the population.
The guidelines issued by the National Cholesterol Education
Program (NCEP) Adult Treatment Panel (ATP) III placed
patients in 3 risk categories: (1) those with established CHD
and those with a 10-year risk of coronary events equivalent to
that of CHD, (2) those with hypercholesterolemia and 2 or
more risk factors, and (3) those with hypercholesterolemia and
less than 2 risk factors. The guidelines set low-density lipoprotein cholesterol (LDL-C) treatment goals of <100 mg/dL,
<130 mg/dL, and <160 mg/dL, respectively, for patients in
these 3 groups (Table 1).4
These categories and LDL-C treatment goals are similar to
those in the ATP II guidelines published in 1993 except that in
the earlier guidelines, only patients with established CHD were
included in the first risk category.5 The broadened indications
for treatment in the ATP III guidelines increased the number of
people in the United States who require cholesterol-lowering
drugs to about 36 million, up from about 12.7 million in the
ATP II guidelines.6
Outcomes studies have revealed a considerable gap between
NCEP recommendations and clinical practice in the United
States.7-9 Sixty-two percent of patients receiving lipid-lowering
therapy in the L-TAP study, a study of 4,888 patients in
5 regions of the United States, did not meet their LDL-C goal.7
Similarly, in a retrospective study of 7,619 patients treated with
statins at 27 managed care plans, 37% did not reach their
LDL-C goal.8 Consistently in these and other studies, the percent of patients achieving their ATP treatment goals was lowest
in the highest-risk groups—i.e., those patients most in need of
effective treatment.7-10
Statins are established as first-line cholesterol-lowering
drugs and are the pharmacologic treatment of choice because of
their effectiveness and safety.10,11 The expanded indications for
treatment in the ATP III guidelines and evidence of widespread
undertreatment increase the need for statin therapy and will
increase demand (Table 1). For managed care, this raises questions about the costs and cost-effectiveness of statins. In particular: What determines the cost-effectiveness of statins? Are
there differences among the statins in cost-effectiveness? Are
statins as a class “cost effective”? For which patients are statins
most cost effective? In order to address these questions, we
Vol. 9, No. 6
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Determinants of the Cost-Effectiveness of Statins
reviewed the statin pharmacoeconomic literature and examined the
factors that determine the cost-effectiveness of statin treatment.
■■ Incremental Cost-Effectiveness
The cost-effectiveness ratio usually referred to in pharmacoeconomics is the incremental cost-effectiveness ratio, which compares
the costs and effects of one treatment (here, statins) with those
of another (typically patients’ usual care). The incremental costeffectiveness ratio is defined as the difference in the cost of the
2 treatments (statin and usual care) divided by the difference in
their effectiveness:
Cost/Effectiveness =
Cost (statin) – Cost (usual care)
Effectiveness (statin) – Effectiveness (usual care)
Alternative treatments typically vary both in their cost and
in their effectiveness. The goal is to find the treatment with the
least cost for the greatest effectiveness, i.e., the treatment with
the smallest (most favorable) cost-effectiveness ratio. It is evident from the above equation that the cost-effectiveness ratio can
be minimized by decreasing the cost or increasing the effectiveness. The equation does not, however, specify how costs and
effectiveness are to be defined. The cost is expressed in currency,
but effectiveness can be expressed in a number of ways. The
measures of effectiveness we shall consider are the average percent reduction in LDL-C per patient, the proportion of patients
reaching their LDL-C goal, and number of life-years saved (LYS).
These different measures imply different time horizons and corresponding differences in the costs that must be considered.
■■ Differences Among Statins in Efficacy and Price
Six statins—atorvastatin, fluvastatin, lovastatin, pravastatin,
rosuvastatin, and simvastatin—are currently marketed in the
United States. These statins vary considerably in price and efficacy. Efficacy is defined here as the magnitude of the effect—
or effectiveness—produced by a given amount of drug. It can
be understood as the inverse of potency, which is the amount
of drug required to produce a given effect.
Table 2 lists prices and effectiveness, expressed as percent
reduction in LDL-C, for different statin dosages. The effectiveness of statins increases with dosage, but efficacy is a fixed property for each statin. There are 2 ways of increasing the effectiveness: (a) increasing the dose of a given statin or (b) using the
same dose of another statin with greater efficacy. There are limits, however, to the extent to which the effectiveness of statins
with relatively low efficacy can be increased by raising the dose.
As an example, the effectiveness of pravastatin 80 mg (measured as percent reduction in LDL-C) is 65% greater than that of
pravastatin 10 mg but still less than that of rosuvastatin 5 mg
and considerably less than that of higher dosages of statins with
greater efficacy. Although it has been argued that the statins are
clinically interchangeable,12 the differences in efficacy and price
have important consequences in the determination of cost-
TABLE 1
LDL-C Goals and Cut Points for
Drug Therapy by Risk Category
in the NCEP III Guidelines*
10-Year
Risk of
LDL-C
Coronary
Goal
Events (mg/dL)
Description†
LDL-C Level at Which
to Consider Drug
Therapy (mg/dL)
CHD and CHD risk equivalents
>20%
<100
≥130 (100-129,
drug therapy optional)
≥2 Risk factors
≤20%
<130
≥130 if 10-year risk of
events = 10%-20%;
≥160 if 10-year
risk of events <10%
0-1 Risk factors
<10%‡
<160
≥190 (160-189,
drug therapy optional)
ATP = Adult Treatment Panel.
CHD = coronary heart disease.
LDL-C = low-density lipoprotein cholesterol.
NCEP = National Cholesterol Education Program.
* ATP III is based on the earlier ATP II and has the same LDL-C goals for the 3 risk
categories. The highest risk category in ATP III includes patients with a risk of major
coronary events equivalent to that of established CHD (in ATP II, only patients with
established CHD were in the highest risk category). CHD risk equivalents include
other forms of atherosclerotic disease, diabetes, and combinations of multiple risk
factors conferring a 10-year risk of CHD of >20%. By focusing more on the 10-year
risk of coronary events rather than simply on risk factors and placing more patient
groups in the higher risk categories, ATP III expands the indications for intensive
cholesterol-lowering therapy.4
† Major risk factors (exclusive of LDL-C) that modify LDL-C goals include cigarette
smoking, hypertension (blood pressure ≥140/90 mm Hg or use of an antihypertensive
medication), low HDL-C (<40 mg/dL), family history of premature CHD, age (men
≥45 years; women ≥55 years). Diabetes is considered as a CHD risk equivalent.
‡ Almost all people with 0-1 risk factors have a 10-year risk <10%; 10-year risk
assessment in these patients is not necessary.
effectiveness of statins, as demonstrated below.
■■ Relationship Between Efficacy and Cost-Effectiveness
The relationship between the efficacy and cost-effectiveness of
individual statins can be visualized in a scatter plot of the cost
versus the effect. Figure 1 shows such a plot, where effectiveness is expressed as percent lowering of LDL-C and costs are
expressed as annual drug costs, based on October 2003 prices
from an online pharmacy. The line in Figure 1 describes the
“efficient frontier,” consisting of those points representing the
lowest cost at any given level of effectiveness. Rosuvastatin and
generic lovastatin lie on the efficient frontier at higher and lower
levels, respectively, of effectiveness; fluvastatin 80 mg and atorvastatin 10 mg lie on the efficient frontier at intermediate levels
of effectiveness. If, for example, the level of effectiveness is set
at 45% reduction in LDL-C, rosuvastatin 10 mg has the lowest
cost; in the absence of rosuvastatin, atorvastatin 40 mg would
have the lowest cost at that level of effectiveness. At higher lev-
www.amcp.org Vol. 9, No. 6 November/December 2003
JMCP
Journal of Managed Care Pharmacy 545
Determinants of the Cost-Effectiveness of Statins
TABLE 2
Statin Dosages by Effectiveness
(Percent Reduction in LDL-C) and Price*
5 mg
10 mg
Daily dose
20 mg
40 mg
80 mg
Atorvastatin
-
39% / $2.04
43% / $3.07
50% / $3.07
60% / $3.07
Fluvastatin
-
-
22% / $1.56
25% / $1.56
35% / $1.97
Statin
Lovastatin†
-
21% / $0.96
27% / $1.11
31% / $1.97
-
Pravastatin
-
22% / $2.50
32% / $2.52
34% / $3.70
37% / $3.76
Rosuvastatin 45% / $2.22
52% / $2.22
55% / $2.22
63% / $2.22
-
Simvastatin
30% / $2.18
38% / $3.72
41% / $3.72
47% / $3.73
26% / $1.63
* Data presented as percent lowering of LDL-C / price per unit. Price per tablet based on price
of 90 tablets listed on drugstore.com on October 10, 2003. Values for the percent reduction in
LDL-C are as cited in the Physicians’ Desk Reference or at www.rxlist.com for patients with
primary hypercholesterolemia.13
† Prices are shown for generic lovastatin. Brand lovastatin prices are $1.28, $2.20, and $3.94
for 10, 20, and 40 mg, respectively.
FIGURE 1
Annual Statin Cost by
Percent Reduction in LDL-C
1,600
Atorvastatin 10, 20, 40, 80 mg
▲
Fluvastatin 20, 40, 80 mg
Lovastatin 10, 20, 40 mg
◆
1,400
●
● ●
Pravastatin 10, 20, 40, 80 mg
1,200
Annual Drug Cost ($)
Lovastatin generic 10, 20, 40 mg
■
Rosuvastatin 5, 10, 20, 40 mg
●
Simvastatin 5, 10, 20, 40, 80 mg
1,000
800
■
●
◆ ▲
R5
■
R10
■
R20
■
R40
A10
F80
600
●
▲ ▲
◆
400
◆
L20 generic
L10 generic
200
10
20
30
40
50
Percent Reduction in LDL-C
60
70
In this presentation of cost-effectiveness, drug acquisition costs are the only costs considered, and effectiveness is expressed as the percent reduction in LDL-C. The curve
approximates the “efficient frontier,” which tracks the lowest cost at any given level of
effectiveness. Statin dosages that lie on the efficient frontier are labeled: L10, L20,
and L40 generic, generic lovastatin 10 mg, 20 mg, and 40 mg; R5, R10, R20, and
R40, rosuvastatin 5 mg, 10 mg, 20 mg, and 40 mg. Annual drug costs are based on
prices for 90-pill packages, as listed on drugstore.com on October 10, 2003.
Effectiveness data are from the Physician’ Desk Reference or www.rxlist.com as
indicated in the legend to Table 2.13
els of effectiveness, the statin with the greatest efficacy (rosuvastatin) has the lowest cost-effectiveness ratio; i.e., is most cost
effective. At low levels of effectiveness (e.g., less than 30%
546 Journal of Managed Care Pharmacy
JMCP
November/December 2003
reduction in LDL-C) the lowest-priced statin has the
lowest cost-effectiveness ratio; i.e., is the most costeffective. The lowest-priced statin currently is generic
lovastatin.
Essentially the same results have been obtained in
several similar analyses set in the United States and
Canada.14-16 The effectiveness data (average percent
reduction in LDL-C per patient) for these analyses were
gleaned from published sources, and the costs were
annual drug costs, again expressed as average wholesale
prices (AWPs) for the U.S. study14 or as average reimbursements for the 2 Canadian studies.15,16 In each of
these studies, the efficient frontier was defined by the
statin with the greatest efficacy then available—simvastatin in one study16 and atorvastatin in 2 later studies,14,15
and by the least expensive statin, then fluvastatin.
■■ NCEP ATP III Risk Groups
When effectiveness is measured in terms of the proportion of patients reaching a target LDL-C threshold,
effectiveness is dependent on patients’ initial LDL-C level and
on their target level. Since the LDL-C target levels recommended by the NCEP are lower for patients at higher risk of CHD,
effectiveness (expressed as the percent of patients reaching their
LDL-C goal) and, therefore, cost-effectiveness, are dependent
on the risk of CHD. Figure 2 shows a scatter plot of annual
statin cost versus percent of patients achieving their ATP III
treatment goal for patients in the highest risk category (CHD
and CHD-risk equivalents). The picture is similar to that in
Figure 1 for the statins shown, which include the higher-efficacy statins (atorvastatin, rosuvastatin, and simvastatin) and
pravastatin. Again, atorvastatin 10 mg and rosuvastatin 5 mg,
10 mg, 20 mg, and 40 mg lie on the efficient frontier. The
lower-efficacy statins, including pravastatin, are not effective in
the high-risk patient group.
For patients in the lower ATP III risk groups, the data points
and the efficient frontier seen in Figure 2 are shifted to the right.
Table 3 shows the percent patients reaching their LDL-C goal
for each of the 3 ATP III risk categories. For patients in the lowest risk group (fewer than 2 CHD risk factors), even low-efficacy statins such as pravastatin can bring most patients to their
treatment goal (Table 3); under these circumstances, it is drug
price rather than efficacy that is the more important determinant of cost-effectiveness.
Table 3 illustrates the concept that, as CHD risk decreases,
statin efficacy is relatively less important. There are, however,
some caveats to the interpretation of these results. First,
the relationship between CHD risk and effectiveness seen in
Figure 2 is a consequence of the method of expressing effectiveness and the fact that the NCEP target LDL-C levels are set
lower for higher-risk groups. Second, it is generally not the case
that all low-risk patients reach their LDL-C treatment goal.
Vol. 9, No. 6
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Determinants of the Cost-Effectiveness of Statins
■■ Titration to LDL-C Treatment Goal
The situation illustrated in Figures 1 and 2, in which patients
continue with their initial statin dose, may, in fact, represent
reality for many patients. Outcomes studies indicate that many
patients—about half in some studies—do not receive LDL-C
level monitoring or appropriate statin dose adjustment.8,9
In contrast, the NCEP guidelines recommend drug titration
until patients reach their treatment goal (or the maximum dose)
if the initial dose is inadequate.4 In this scenario, effectiveness is
appropriately measured as the percent of patients reaching their
LDL-C treatment goal.
The costs that must be considered are all those associated
with measuring and remeasuring patients’ cholesterol levels,
including the costs of office visits and laboratory tests, as well as
drug acquisition costs. This scenario was examined in a pharmacoeconomic analysis based on a 54-week, randomized, multicenter trial in the United States, in which starting doses of
4 statins were titrated upwards until patients with and without
atherosclerosis reached the ATP II goal for LDL-C (or the maximum dose was reached).5,19 All related medical costs (drugs,
office visits, laboratory tests) were considered from the perspective of insurers and managed care organizations and were based
on national averages.19 The statin with the greatest efficacy—
atorvastatin, in that study—was “dominant,” i.e., it was both
more effective and less costly than dose titration with the other
statins. Note, however, that once drug titration has been completed, the costs of long-term maintenance therapy are principally the direct drug-acquisition costs.20
■■ Cost per Life-Year Saved
Since hypercholesterolemia is clinically silent, survival is the
ultimate measure of statin effectiveness, not cholesterol lowering. When effectiveness is measured in terms of survival as the
number of LYS, the costs that must be considered include not
FIGURE 2
Annual Drug Cost per Patient by Percent
of Patients Achieving LDL-C Treatment
Goal for Patients in the Highest ATP III
Risk Category
1,800
●
●
●
1,200
Annual Drug Cost ($)
Outcomes studies have shown that many patients in the lowrisk category do not reach their LDL-C goal.7-10 The failure to
reach LDL-C goal may be due, in part, to low adherence,17 but
inadequate treatment, due to failure to titrate and low-efficacy
therapies, also contributes to failure to reach LDL-C goal.7,9,10
Third, the use of the percent of patients reaching their LDL-C
treatment goal as a measure of effectiveness ignores any potential benefit of reducing LDL-C levels to below recommended
thresholds.
Preliminary data from the Heart Protection Study indicate
that statin treatment reduces the risk of coronary events in some
patient categories (those with a history of heart disease, stroke,
other occlusive vascular disease, or diabetes) even when their
cholesterol levels are normal.18 Furthermore, there appears to be
no threshold cholesterol value below which statin therapy is not
associated with a benefit, even among those with pretreatment
cholesterol levels below current national recommended targets.
R40
800
■
●
R5
■
R10
■■
R20
A10
400
0
0
20
40
60
80
100
% at LDL-C Goal
Atorvastatin 10, 20, 40, 80 mg
■ Rosuvastatin 5, 10, 20, 40 mg
Pravastatin 10, 20, 40 mg
● Simvastatin 10, 20, 40, 80 mg
The highest ATP III risk category contains patients with CHD and CHD-risk equivalents. The line shows the efficient frontier, defined as in the caption to Figure 1.
Statin dosages that lie on the efficient frontier are labeled: A10, atorvastatin 10 mg;
R5, R10, R20, and R40, rosuvastatin 5 mg, 10 mg, 20 mg, and 40 mg. The source
for drug costs is as in Figure 1. The sources of the effectiveness data are (except for
rosuvastatin 5 mg) the STELLAR trial,41 and mean values from the comparative
trials referenced as follows: rosuvastatin 5 mg,43-46 rosuvastatin 10 mg,41-45 atorvastatin 10 mg,41,42,45 simvastatin 20 mg,41,43,44 and pravastatin 20 mg.41,43,44
TABLE 3
Percent of Patients Achieving LDL-C
Treatment Goal by ATP III Risk
Category for Selected Statin Dosages
Statin Dosage
Percent of Patients at ATP III Treatment Goal*
CHD and CHD
≥2 Risk
0-1 Risk
Risk Equivalents
Factors
Factors
Pravastatin 20 mg
Simvastatin 20 mg
Atorvastatin 10 mg
Rosuvastatin 10 mg
6
23
25
62
40
74
79
89
89
90
92
98
*ATP III risk categories as defined in Table 1. Effectiveness data are mean values
from the comparative trials referenced as follows: rosuvastatin 10 mg,41-45
atorvastatin 10 mg,41,42,45 simvastatin 20 mg,41,43,44 and pravastatin 20 mg.41,43,44
just statin therapy and dose titration but also medical treatments for CHD (which are reduced for patients treated with
statins). More than 30 pharmacoeconomic analyses of the cost
www.amcp.org Vol. 9, No. 6 November/December 2003
JMCP
Journal of Managed Care Pharmacy 547
Determinants of the Cost-Effectiveness of Statins
TABLE 4
Cost Per Life-Year Saved for Patients With
and Without Preexisting Coronary Heart
Disease in the United States
Study
Statin
With Preexisting CHD
Ashraf, et al. (1996)36
Elliott 199937,38‡
Ganz 200039‡§
Goldman 199127
Grover 199940
Huse 199829
Johannesson 199741
Prosser 200026
Without Preexisting CHD
Goldman 199127
Hay 199128
Huse 199829
Prosser 200026†
Cost per LYS ($1,000s)*†
Pravastatin
Various
Pravastatin
Lovastatin
Simvastatin
Various
Simvastatin
Simvastatin
7.1 – 12.7
2.3 – 30.9
5.4 – 97.8
<0 – 310
4.4 – 21.7
8.2 – 63.6
3.8 – 27.4
1.8 – 40.0
Lovastatin
Lovastatin
Various
Pravastatin
13.0 – 1,500
6.0 – 297
4.3 – 468
54.0 – 1,400
LYS = life-years saved.
* Range of values (lower and upper) for the highest- and lowest-risk patient groups,
respectively (except where indicated).
† Costs are unadjusted for inflation and are expressed in $U.S. for 1989,27, 28
1995,35,40 1996,39 1997,26,29 1998,38 and 1999.36
‡ The lower and upper limits represent the most favorable and least favorable model
scenarios rather than patient risk groups.
§ Cost per quality-adjusted life-year reported.
TABLE 5
The Cost Per Life-Years Saved of
Statin Treatment Decreases as the
Risk Factors for Events Increase*
CostEffectiveness
($/LYS)
Risk Factors
LDL-C (mg/dL) Sex
≥300
250-299
≥300
≥300
≥300
≥300
<250
≥250
≥250
F
M
M
M
M
M
M
F
M
HTN
Obese
Smoker
CHD
+
+
+
+
+
+
+
+
+
130,000
93,000
58,000
28,000
17,000
15,000
17,000
8,100
1,600
CHD = coronary heart disease.
HTN = hypertension.
LYS = life-years saved.
* Data of Goldman et al. for people 55 to 64 years of age treated with lovastatin
20 mg.27 Definitions: hypertensive, diastolic blood pressure ≥105 mm Hg;
normotensive, diastolic blood pressure <95 mm Hg; obese, ≥130% of ideal weight;
nonobese, <110% of ideal weight.
of statins per LYS have been reported. In these analyses, the data
for the incidence of CHD, risk factors, and coronary events in
patient-lifetime projections typically comes from the
Framingham Heart Study, while the data for the effects of statins
548 Journal of Managed Care Pharmacy
JMCP
November/December 2003
on coronary events comes from long-term clinical event trials
with lovastatin, pravastatin, and simvastatin: the WOSCOPS
(West of Scotland Coronary Prevention Study)21 and
AFCAPS/TexCAPS (Air Force/Texas Coronary Atherosclerosis
Prevention Study)22 primary prevention trials and the 4S
(Scandinavian Simvastatin Survival Study),23 CARE (Cholesterol
and Recurrent Events),24 and LIPID (Long-Term Intervention
with Pravastatin in Ischaemic Disease)25 secondary prevention
trials. In some analyses, the cost per quality-adjusted life-year
(QALY) was determined; this adjustment for quality of life
increases cost-effectiveness ratios by about 10% to 20%.26
In most analyses of patients with preexisting CHD,26-29 the
ranges of lifetime incremental cost per LYS values lie in the
range of $1,800 to $40,000 (Table 4). The upper limits of the
ranges exceed $50,000 in some studies, but only for patients in
the lowest risk groups.27,29 For subjects without preexisting
CHD, the lifetime cost-effectiveness ratios vary over an extremely wide range—more than 100-fold in some studies27,29—from
lower limits generally below $15,000 to upper limits sometimes
exceeding $1 million per LYS (Table 4).26,27 The critical factor
is the risk of CHD: the cost-effectiveness ratio tends to decrease
as the risk of coronary events increases. This is illustrated in
Table 5, which shows data of Goldman et al.27 This relationship
holds because the effectiveness measure—LYS—depends on the
number of coronary events avoided, which is greater in a highrisk population.
The cost of statins per LYS for patients with preexisting
CHD, and for those without CHD but with multiple risk factors,
falls inside the threshold for an acceptable cost-effective ratio:
the value of this threshold was about U.S. $30,000 in the early
1990s and $40,000 to $50,000 more recently. The cost-effectiveness values for statins also generally fall within the range of
values for other currently accepted treatments: $7,700 to
$10,000 for single-vessel angioplasty in patients with severe
angina; $18,000 for annual screening for colorectal cancer with
a fecal occult blood test; $108,000 to $112,000 for single-vessel angioplasty in patients with mild angina; $15,000 to
$96,500 for treatment of hypertension in patients aged 35 to
64 years; and $150,000 for annual mammography in women
aged 55 to 65 years (cost-effectiveness ratios expressed as 1995
U.S.$ per QALY).26,30
■■ Specific Risk Groups
In addition to patients with CHD, several at-risk patient groups
have been subjected to cost-effectiveness analysis. Statin treatment of heterozygous familial hypercholesterolemia, which
affects approximately 0.5 million people in the United States, is
cost-saving for men and costs only $300 per LYS for women,
even without additional risk factors.31 Patients with type-2 diabetes have a risk of coronary events comparable to that of nondiabetic patients with a history of myocardial infarction.32 This
suggests that the cost-effectiveness of statin treatment of these
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Determinants of the Cost-Effectiveness of Statins
2 populations should be equivalent; this has not, however, been
demonstrated in the primary prevention cost-effectiveness literature, where diabetes has been treated as a risk factor for CHD
comparable to smoking or hypertension.29 Secondary prevention of coronary events in diabetic patients was studied in post
hoc analyses of patient subgroups of the 4S trial:33,34 The cost per
LYS of simvastatin treatment was substantially lower for diabetic than for nondiabetic patients with CHD.33
■■ Statin Pricing
In Figures 1 and 2, we presented cost-effectiveness data using
current statin prices from an online pharmacy. We note that
there have been changes in pricing policy by drug manufacturers over the past several years, such as a switch for some statins
from higher prices for higher doses to flat pricing, as well as the
introduction of new statins. Rosuvastatin has displaced atorvastatin at the upper end of the efficient frontier seen in Figure 1,
just as atorvastatin previously displaced simvastatin. Lovastatin,
which was the first statin to be marketed in the United States (in
1987), became available as a generic drug in 2002. Generic
lovastatin has replaced fluvastatin at the lower end of the efficient frontier shown in Figure 1. However, generic lovastatin
40 mg is comparable in effectiveness to simvastatin 10 mg
or pravastatin 20 mg, which bring less than 20% of highrisk patients to their LDL-C goal (Figure 2), so that generic
lovastatin can only compete (on the basis of price) at lower
levels of effectiveness. Outcomes studies indicate that the
majority of patients currently being treated with statins are in
the CHD or risk-equivalent category.7-9
■■ Limitations
Managed care organizations typically contract for statin prices at
discounts to the AWP. Discount prices for the statin drugs were
obtained from an online pharmacy Web site to help account for
the difference in AWP prices and the actual costs incurred by
managed care organizations (MCOs), prior to member cost
share. However, actual statin purchase costs will differ among
MCOs, and this may change the cost-effectiveness rankings of
statins at any given level of effectiveness. Nevertheless, in order
to optimize cost-effectiveness, MCOs must consider the level of
effectiveness that is required to treat individual patients or specific patient groups rather than simply the lowest purchase
price.
■■ Summary
In principle, the incremental cost-effectiveness ratio can be
reduced by decreasing the cost or by increasing the effectiveness
of the therapy. Both of these effects are evident in the comparisons of individual statins. When effectiveness is expressed as
percent reduction in LDL-C and cost as statin price, increasing
the efficacy (the effect per unit dose) decreases the cost-effectiveness ratio and, when greater LDL-C lowering is required
(as is the case with patients with CHD or CHD-equivalent risk),
the statins with the greatest efficacy have the lowest (most
favorable) cost-effectiveness ratios. If limited LDL-C lowering is
required (as may be the case for some low-risk patients), drug
price may be the more important factor.
The same relationships between the cost-effectiveness ratio
and statin efficacy and price are also seen when effectiveness is
expressed as the proportion of patients reaching LDL-C goal.
The inverse relationship between statin efficacy and the costeffectiveness ratio holds up under the circumstances of statin
titration to treatment goal and the inclusion of all related treatment costs. When effectiveness is expressed in terms of LYS and
all long-term medical costs are taken into account, the incremental cost-effectiveness ratio decreases as the risk of CHD
increases. For patients with preexisting CHD or CHD-equivalent risk of coronary events, the cost-effectiveness ratio of statins
as a class compares favorably with generally accepted medical
treatments.
The results suggest 3 strategies for minimizing the cost-effectiveness ratio of statin therapy. First, preferentially treat patients
with existing CHD or equivalent risk; second, use statins with the
greatest efficacy for these patients and for patients at low risk but
with high baseline LDL-C levels; and third, use a less-expensive
statin when less LDL-C lowering is needed, as in low-risk patients
with lower baseline LDL-C levels.
DISCLOSURES
Funding for this study was provided by AstraZeneca LP and was obtained by
author Alan Morrison. Morrison served as principal author of the study. Study
concept and design and analysis and interpretation of data were contributed
by Morrison. Drafting of the manuscript was the work of Morrison, and its
critical revision was the work of Morrison and author Helene Glassberg.
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25. Glasziou PP, Simes RJ, Hall J, Donaldson C. Design of a cost-effectiveness
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36. Elliott WJ, Weir DR. Comparative cost-effectiveness of HMG-CoA reductase inhibitors in secondary prevention of acute myocardial infarction. Am J
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of cardiovascular disease: forecasting the incremental benefits of preventing
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40. Johannesson M, Jonsson B, Kjekshus J, Olsson AG, Pedersen TR, Wedel
H. Cost-effectiveness of simvastatin treatment to lower cholesterol levels in
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41. McKenney JM, Jones PH, Adamczyk MA, et al. Comparison of the efficacy
of rosuvastatin versus atorvastatin, simvastatin and pravastatin in achieving
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42. Davidson M, Ma P, Stein EA, et al. Comparison of effects on low-density
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43. Paoletti R, Fahmy M, Mahla G, Mizan J, Southworth H. Rosuvastatin
demonstrates greater reduction of low-density lipoprotein cholesterol compared with pravastatin and simvastatin in hypercholesterolaemic patients:
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44. Brown WV, Bays HE, Hassman DR, et al. Efficacy and safety of rosuvastatin compared with pravastatin and simvastatin in patients with hypercholesterolemia: a randomized, double-blind, 52-week trial. Am Heart J. 2002;
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Journal of Managed Care Pharmacy 551
C O N T E M P O R A RY S U B J E C T
Longitudinal Assessment of a Diabetes Care
Management System in an Integrated Health Network
DAVID L. LARSEN, RN, MHA; WAYNE CANNON, MD; and STEVEN TOWNER, MD
ABSTRACT
OBJECTIVE: To describe the results of longitudinal assessment of the results of a
disease management process developed in a large integrated health care system
that successfully improved care for patients with diabetes. Outcome measures
included rates of testing of hemoglobin A1c (HbA1c) and low-density lipoprotein
(LDL), rate of annual eye exams, and LDL and HbA1c values.
METHODS: Intermountain Health Care (IHC) initiated the development of a Diabetes
Care Management System (DCMS) in early 1998. The DCMS was developed as a
comprehensive population-based disease management system. It includes provider
education programs; performance feedback to physicians; clinical quality performance incentives for physicians; patient education programs; patient incentive,
reminder systems to encourage compliance with best care process models; and
tracking of physician behavior change and patient compliance with diabetes therapy. A multifaceted intervention and education approach was chosen because of the
complexity of the diabetes treatment process.
RESULTS: The percentage of patients with at least one annual HbA1c test
increased from 78.5% in 1998 to 90.5% in 2002. During the same time period,
the percentage of patients whose most recent HbA1c was less than 7.0
increased from 33.5% to 52.8%, average HbA1c decreased from 8.1 to 7.3,
and the percentage of patients whose most recent HbA1c was greater than 9.5
decreased from 34.6% to 21.4%. The percentage of patients who had an LDL
cholesterol screening test within the prior 2 years increased from 65.9% in 1998
to 91.7% in 2002. During the same time period, the percentage of patients whose
most recent LDL cholesterol was less than 130 mg/dL increased from 39.9% to
69.8%. The percentage of diabetes patients who had an annual eye exam
increased from 52% in 1998 to 62% in 2002.
CONCLUSION: A multifaceted approach to improving diabetes management has
led to improved performance in clinical measures related to diabetes care that
have been shown to reduce the risk of patients with diabetes developing diabetes-related complications. All components of the diabetes management continuum of care, including primary care physicians, specialists, office staff, patients,
diabetes educators, and others, were involved in the care improvement activities.
KEYWORDS: Diabetes, Disease management, Clinical practice guideline, Care
process model, Integrated health system, Registry
J Managed Care Pharm. 2003;9(6):552-58
Authors
DAVID L. LARSEN, RN, MHA, is director, Quality Improvement Department,
IHC Health Plans, and data manager, Primary Care Clinical Program; WAYNE
CANNON, MD, is Primary Care clinical program leader; STEVEN TOWNER,
MD, is Diabetes team leader, Intermountain Health Care, Salt Lake City, Utah.
AUTHOR CORRESPONDENCE: David L. Larsen, RN, MHA, Director, Quality
Improvement Dept., IHC Health Plans, 4646 W. Lake Park Blvd., N-3, Salt Lake
City, UT 84120-8212. Tel: (801) 442-5863; Fax: (801) 442-4372;
E-mail: [email protected]
Copyright© 2003, Academy of Managed Care Pharmacy. All rights reserved.
552 Journal of Managed Care Pharmacy
JMCP
November/December 2003
A
ggressive management of diabetes is well known to
decrease both mortality and morbidity from complications related to the disease. From 1998 to 2003,
Intermountain Health Care (IHC) developed a system-wide initiative to improve care for patients with diabetes. This initiative is
known as the Diabetes Care Management System (DCMS). It is a
coordinated effort involving IHC senior management, IHCemployed physicians, network physicians not employed by IHC
who see IHC Health Plans patients, and IHC Health Plans, all of
which is coordinated through the Primary Care Clinical Program
of IHC. Specific goals of the DCMS include the following:
1. increase the annual testing rate of hemoglobin A1c (HbA1c)
in adult patients with diabetes,
2. increase the percentage of adult diabetes patients with favorable HbA1c values,
3. decrease the percentage of adult diabetes patients with unfavorable HbA1c values,
4. increase the percentage of adult patients with diabetes tested at least once every 2 years for low-density lipoprotein
(LDL) cholesterol,
5. increase the percentage of adult diabetes patients with favorable LDL values,
6. decrease the percentage of adult diabetes patients with unfavorable LDL values, and
7. increase the percentage of adult diabetes patients with an
annual diabetes eye exam.
IHC is an integrated health network with 400 employed
physicians, 100 outpatient clinics, 22 hospitals, and a health plan
that insures 467,000 members. There are also approximately 800
affiliated non-IHC-employed primary care physicians.
Disease management activities throughout the system are
led by “clinical programs.” Clinical programs established to date
include cardiovascular, women and newborn, neuromusculoskeletal, pediatric subspecialty, oncology, behavioral health,
intensive medicine, and primary care (Figure 1). Clinical programs are formed around like processes of clinical care such as
the Primary Care Clinical Program. Each clinical program
builds Care Management Systems (disease management programs) around the highest-volume clinical processes such as
asthma, diabetes, depression, hypertension, heart failure, otitis
media, and attention deficit hyperactivity disorder for primary
care. Each clinical program provides the resources necessary to
focus on the development, implementation, and outcomes
measurement of each clinical process.
Each clinical program has its own work group and develop-
Vol. 9, No. 6
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Longitudinal Assessment of a Diabetes Care Management System in an Integrated Health Network
ment team. The work group is a small core group of
approximately 10 physicians and staff members that develops the disease management system, which is then refined
by the larger development team. This is then coordinated
through central leadership and a large guidance council of
approximately 25 members, composed of primary care
medical directors and nurse managers, all under the direction of the Primary Care Clinical Program staff.
FIGURE 1
Diagram of IHC Clinical Program Structure
IHC Clinical Programs
Facility-based (Inpatient-focused)
Clinical Programs
Neuromusculoskeletal
Women &
Newborn
Community-based Clincial Programs
Cardiovascular
Primary Care
Behavioral
Health
Oncology
Diabetes
■■ Diabetes Care Process Model
The center of the DCMS is an evidence-based diabetes
best-care practice model (CPM). This detailed CPM is
based on nationally recognized guidelines from the
American Diabetes Association, with updates from current
scientific literature, and was developed by a multidisciplinary group of providers, including endocrinologists, primary care physicians, pharmacists, diabetes educators,
and nurses.1-11 Pharmacists are included on all development teams and in work groups, where appropriate, to provide
input on fundamental knowledge and expert advice in CPM
development. They also are valuable in providing input regarding drug formulary preferences and other health plan issues.
The diabetes CPM was distributed to physicians via academic
detailing of small groups of 6 to 8 primary care physicians, conducted by an endocrinologist, to discuss the science of the
CPM, and the regional medical director, to talk about implementation with the supporting programs described below.
Diabetes Performance Measurement
System and Diabetes Registry
The second part of the DCMS was the development of a measurement system founded on diabetes best-care practices.
A diabetes datamart (registry) was established by combining
data from 5 different data sources: electronic laboratory, health
plan claims, physician billing, clinical information system, and
case mix (from hospital/facility billing data). These 5 databases
comprise the available outpatient clinical information and
financial data used to identify patients with diabetes to populate
the registry and then match patients with the dates and results
of their lab tests, e.g., HbA1c and LDL cholesterol. These databases were also used to identify and match patients with their
primary care physician and specialist, if applicable. The registry
was initially populated in July 1999 with approximately 18,000
patients and has been updated quarterly; the most recent
update period ended June 30, 2003, and includes approximately 25,500 patients.
The 5 databases are updated each calendar quarter, and the
registry is refreshed using a multiple-step process to import the
new data into the registry. Of the 25,500 patients in the registry,
approximately 9,500 are members of IHC Health Plans (a multiproduct health plan with a health maintenance organization
and point-of-service options). The remaining 16,000 patients
Pediatric
Subspecialty
Intensive
Medicine
Asthma
Depression
ADHD
Hypertension
Heart Failure
Communityaquired
Pneumonia
consist of patients with diabetes not insured by IHC Health
Plans but treated by IHC-employed physicians from the IHC
Physician Division.
The 25,500 patients in the diabetes registry are treated by
approximately 750 primary care physicians. The primary care
physician with the most diabetes patients in the registry has
278 patients, and the registry is used to produce reports for
physicians who have as few as 1 or 2 patients.
Patient detail reports are produced quarterly for each primary care physician from the diabetes registry. The reports
include: (1) name, medical record number, and phone number
for each patient; (2) the most recent values for HbA1c, LDL,
and urine microalbumin; and (3) the date of the patient’s last
eye exam. Patients are sorted by risk (lack of needed test or
abnormal test result).
A Provider Summary Report (Figure 2) is included with this
patient detail report; it shows a physician his or her testing rates
compared with peers in both the physician’s geographical
region and the entire IHC system. The Provider Summary
Report also shows relative values of HbA1c and LDL in patients
cared for by the provider and how those values compare with
the region or system. These results are also available through a
password-protected site on the IHC intranet. On this Web site,
a physician can view his or her Provider Summary Report and
the same patient detail report that is distributed quarterly. The
patient detail report may be sorted by risk (HbA1c values higher than 9), or alphabetically. The intranet Web site also has performance reports for these same measures by quarter over the
last 4 years for the region or system.
Patient Education and Self-Management
The third part of the DCMS is a broad array of patient education programs. These include IHC-developed patient handouts,
outpatient programs that bring a certified diabetes educator and
www.amcp.org Vol. 9, No. 6 November/December 2003
JMCP
Journal of Managed Care Pharmacy 553
Longitudinal Assessment of a Diabetes Care Management System in an Integrated Health Network
FIGURE 2
Examples of Provider Summary Report for Diabetes Patient
Diabetes Summary Report
HbA1c mg/dL
Provider:
100
Period: January 2002-December 2002
92
Patients Tested (Proportion of Total Patients %) - All Patients
Provider
Region
81 78
80
System
HbA1c
190 (99%)
1,326 (90%)
18,987 (81%)
LDL/Trigl1
185 (96%)
1,357 (92%)
19,271 (82%)
Eye exam2
28 (78%)
156 (50%)
3,556 (38%)
172 (90%)
1,064 (72%)
10,747 (46%)
192
1,481
23,567
Microalbuminuria3
Total patients
Percent
73
60
56 55
40
25 24
1
LDL measures represent 2 years, ending in the chosen period.
2
Eye exam % calculated using IHC Health Plans patients only.
3
Includes spot microalbuminuria or 24-hour microalbuminuria or positive UA tests for
18
20
12 13
4
protein, within the reporting period, or any history of treatment for nephropathy.
7<HbA1c≤8
HbA1c≤8
8<HbA1c≤9
Microalbuminuria
Eye Exam Test
LDL mg/dL
100
8
90
6.79
87
80
77
78
80
56
47 47
40
60
52
50
38
40
Percent
71
72
7.19
7.25
6
60
46
40
HbA1c mg/dL
80
Percent
Percent
60
HbA1c>9
HbA1c mg/dL
100
94
80
7
0
HbA1c≤7
100
7
4
4
31 31 30
2
20
20
16 17
20
12
1
0
LDL<100
■ Provider
100≤LDL≤130
■ Region
LDL≤130
LDL>130
5
7
0
Trigl≥400
<1yr
<2yrs
0
0
Patients Tested
Average HbA1c Result
■ System
a registered dietician into physician offices, and Web-based
patient education programs. Patient handouts are available to
physicians through the electronic medical record used by IHCemployed physicians, the IHC intranet, or on the Internet
(www.IHC.com).12 Hard copies can be ordered for the cost of
shipping and handling. These materials are also available to
patients at the Diabetes Online Resource Center Internet site
(www.IHC.com).13 Telephone-based care management is provided for patients with diabetes who are high risk (HbA1c values higher than 9), and many large IHC-employed physician
clinics have on-site nurse care managers to assist with patient
self-management.
Pharmacists at IHC participate in the diabetes CMS in several ways. Clinical pharmacists from IHC Health Plans provide
routine consultation with disease state managers on complicated cases. IHC clinic-based pharmacists work closely with
patients to educate them on the importance of glucose testing
and medication compliance. Pharmacists in all IHC facilities
554 Journal of Managed Care Pharmacy
JMCP
November/December 2003
work to make sure all diabetics have glucose meters, understand how to use them, and provide additional training to supplement training received from diabetes educators. All pharmacists throughout the IHC system continually work to help
patients avoid drug interactions and adverse events.
Physician Office Implementation Tools
The fourth part of the DCMS includes tools that were developed
for physicians and their office staff to facilitate the implementation of the DCMS in their office. The tools include
1. templates on the electronic medical record (EMR) to make
charting easier for patients with diabetes;
2. a report, produced by the EMR, for patients with diabetes in
advance of their medical visit that provides an electronic
flowchart of all of the patient’s key diabetes management
parameters and alerts the physician to interventions that
need to occur at that medical visit;
3. manual diabetes data flowsheets that record lab values and
Vol. 9, No. 6
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Longitudinal Assessment of a Diabetes Care Management System in an Integrated Health Network
■■ Diabetes Quality Improvement Financial Incentive
A quality improvement (QI) financial incentive program was
also developed by IHC Health Plans to improve physician performance on the measured data elements. The QI financial
incentive represents 0.5% to 1% of total physician compensation, and one half of the total managed care QI financial incentive for physicians is based on diabetes measures. The 2 diabetes CPMs that are tied to the QI financial incentive are (1) the
percentage of diabetes patients who received an HbA1c test in
the past year and (2) the percentage of diabetes patients who
had an LDL test in the past 2 years.
FIGURE 3
Percent of Diabetes Patients With
HbA1c Test in Previous 12 Months —
Performance Compared With Benchmarks
100
90.0%
Percent of Patients
80
78.5%
91.0%
90.5%
90.6%
82.6%
83.0%
60
40
20
0
1998
FIGURE 4
1999
2000
2001
2002
2002
National
Average
2002
National
90th %ile
Percent of Patients With HbA1c Value ≤7
Jul 1998-Jun 1999
Oct 1998-Sept 1999
60
Jan 1999-Dec 1999
Apr 1999-Mar 2000
Percent of Patients
50
Jul 1999-Jun 2000
Oct 1999-Sept 2000
40
Jan 2000-Dec 2000
Apr 2000-Mar 2001
30
Jul 2000-Jun 2001
Oct 2000-Sept 2001
20
Jan 2001-Dec 2001
Apr 2001-Mar 2002
10
Jul 2001-Jun 2002
Oct 2001-Sept 2002
0
FIGURE 5
Jan 2002-Dec 2002
Average HbA1c Value in Diabetes Registry
8.2
Jul 1998-Jun 1999
Oct 1998-Sept 1999
8.0
Jan 1999-Dec 1999
Apr 1999-Mar 2000
7.8
HbA1c Value
clinical findings at each visit and can therefore be easily
trended across multiple visits;
4. patient self-history forms;
5. methods to alert the physician that the patient has diabetes;
6. monofilament fibers and training in their use for foot exams;
and
7. organized resources such as the American Diabetes
Association or the Juvenile Diabetes Foundation for patients
in financial need or with other socioeconomic problems.
To introduce and implement the DCMS, small-group meetings of 6 to 8 physicians were conducted, with separate smallgroup meetings for the physicians’ office staff. These meetings
allowed a physician-educator who was a diabetes expert to
present the CPM, answer questions, and then present to each
physician the diabetes Provider Summary Report related to that
physician’s practice. This report allowed each physician to compare his or her performance with the CPM. The first encounter
with the performance reports for many physicians resulted in a
predictable response—the physician-specific data did not
match the physicians’ perception of their level of testing and
control for their diabetic patients. Initial physician challenge of
the data in the performance reports evolved into familiarity and
confidence in the data and cooperation in using the reports to
improve their clinical performance.
After the initial DCMS implementation meetings, including
the important opportunity for physicians to challenge the data,
the diabetes Provider Summary Reports were distributed to
each physician on a quarterly basis. These reports became a
means of identifying patients that required direct physician contact and follow-up. Periodic small-group follow-up meetings
were held to introduce revisions to the CPM, introduce new
data included on the performance reports, and conduct more
detailed implementation education.
Jul 1999-Jun 2000
Oct 1999-Sept 2000
7.6
Jan 2000-Dec 2000
Apr 2000-Mar 2001
7.4
Jul 2000-Jun 2001
Oct 2000-Sept 2001
7.2
Jan 2001-Dec 2001
Apr 2001-Mar 2002
7.0
Jul 2001-Jun 2002
Oct 2001-Sept 2002
■■ Direct Patient Outreach
In addition to these aforementioned interactions with physicians, direct outreach to patients was initiated in 1998. Diabetes
patients who did not schedule routine diabetes-related office
visits or did not have an HbA1c test in the previous 12 months
were invited to diabetes screening clinics.
6.8
Jan 2002-Dec 2002
Diabetes calendars were distributed by mail to all IHC
Health Plan members with diabetes. The calendars focused on
a different diabetes self-management concept each month, with
www.amcp.org Vol. 9, No. 6 November/December 2003
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Journal of Managed Care Pharmacy 555
Longitudinal Assessment of a Diabetes Care Management System in an Integrated Health Network
TABLE 1
Performance
Measurement
Diabetes Management Performance Measures
1998
1999
2000
2001
2002
(n=5,785)*(n=6,187)* (n=7,196)*(n=7,988)* (n=9,436)*
P
Value‡
Annual HbA1c†
78.5%
83.0%
90.0%
91.0%
90.5%
0.002
HbA1c > 9.5†
34.6%
32.4%
24.3%
19.7%
21.4%
<0.001
Average HbA1c
8.1
7.9
7.7
7.5
7.3
<0.001
HbA1c < 7
33.5%
37.1%
42.0%
47.3%
52.8%
<0.001
Biannual LDL†
65.9%
73.7%
85.2%
87.8%
91.7%
<0.001
LDL < 130†
39.9%
49.6%
61.3%
65.5%
69.8%
<0.001
Annual eye exam†
52.0%
47.9%
56.0%
64.0%
62.0%
0.025
* Number of patients in the diabetes datamart (registry).
† HEDIS measure.
‡ A chi-square test of proportions with uncorrected P value was used to measure the statistical
difference between each of the listed performance measures in 1999 and 2002.
FIGURE 6
Percent of Patients in Diabetes Registry
Not Tested or WIth HbA1c Values >9.5
100
Percent of Patients
80
60
40
34.6%
33.9%
32.4%
24.3%
19.7%
21.4%
20.6%
20
0
1998
FIGURE 7
1999
2000
2001
2002
2002
National
Average
2002
National
90th %ile
Percent of Patients in Diabetes Registry
Who Had Lipid Profile Performed in
Previous 24 Months
100
85.2%
87.8%
91.7%
91.7%
85.1%
80
Percent of Patients
73.7%
65.9%
60
40
20
0
1998
1999
2000
2001
556 Journal of Managed Care Pharmacy
2002
JMCP
2002
2002
National National
Average 90th %ile
November/December 2003
reminders for appropriate self-management activities
indicated on various days throughout the month. Each
month, a reminder postcard that correlated to the diabetes self-management concept depicted on the calendar was mailed to each of the members with diabetes.
Patients with diabetes received a status report by
mail regarding their own compliance with appropriate
tests or exams to screen for diabetes complications.
The report contained dates and laboratory values for
the patient’s most recent HbA1c and LDL tests and the
date of the patient’s most recent eye exam.
To encourage eye exams, patients were offered a
60-minute, long-distance telephone debit card as an
incentive to complete their annual eye exam. During
the time the calling card incentive was in place, the eye
exam rates increased by approximately 5%, from 37%
to 42%.
■■ Results
The improvement in each of the key performance measures in
diabetes management is both clinically important and statistically significant (Table 1). This CPM was implemented for all
patients with diabetes in the IHC system. Thus, there is not a
control group. However, compared with national benchmarks,
currently, these results exceed the 90th percentile in all areas
except annual eye exam.14
The percentage of patients with at least one annual HbA1c test
increased from 78.5% in 1998 to 90.5% in 2002 (Figure 3). As
the DCMS was implemented, the first emphasis was on improving the percentage of patients with at least one HbA1c measurement. The rate of testing has leveled out at approximately 91%
over the last 3 years, without improvement, and is thought to be
reflective of a harder-to-reach population to improve beyond the
current level of performance. Accordingly, we have implemented
a new lab requisition program to address this challenge. This program is described in “Summary and Future Plans” below.
The percentage of patients whose most recent HbA1c value
was less than 7 increased from 33.5% in 1998 to 52.8% in 2002
(Figure 4), and the average HbA1c decreased from 8.1 to 7.3
(Figure 5). Improved HbA1c levels have been clinically proven to
result in reduction of diabetes complications.7-9 The percentage of
patients whose most recent HbA1c value was greater than
9.5 decreased from 34.6% in 1998 to 21.4% in 2002 (Figure 6).
The percentage of patients who had an LDL cholesterol screening
test within the last 2 years increased from 65.9% in 1998 to
91.7% in 2002 (Figure 7), and the percentage of patients whose
most recent LDL cholesterol was less than 130 mg/dL increased
from 39.9% in 1998 to 69.8% in 2002 (Figure 8). These achievements in quality improvement should significantly reduce the
risk of cardiovascular complications in these diabetes patients.7-9
The percentage of patients who had an annual eye exam
increased from 52.0% in 1998 to 62.0% in 2002 (Figure 9).
Vol. 9, No. 6
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Longitudinal Assessment of a Diabetes Care Management System in an Integrated Health Network
Percent of Diabetes Patients With
LDL Cholesterol <130 mg/dL
100
Percent of Patients
80
69.8%
65.7%
65.5%
61.3%
60
54.8%
49.6%
40
39.9%
20
0
1998
1999
FIGURE 9
2000
2001
2002
2002
National
Average
2002
National
90th %ile
Percent of Diabetes Patients
Who Received an Eye Exam
in Previous 12 Months
100
80
Percent of Patients
■■ Summary and Future Plans
A multifaceted approach to improving diabetes management
resulted in improved intermediate outcomes in diabetes care
(Figure 10) and should result in less risk of long-term diabetes
complications for these patients. A multispecialty diabetes work
group of 10 members, including primary care physicians,
endocrinologists, physician office staff, diabetes educators, and
pharmacists led by a physician diabetes champion, developed
and implemented the DCMS. Many of the interventions initiated
through the IHC DCMS are replicable in other managed care settings. Plans for the future include further enhancements to the
patient education materials for diabetes, expansion of the
resources devoted to diabetes education and care management,
and further development of the EMR system related to tracking
and monitoring diabetes patients. The diabetes registry will be
used to develop additional patient care management reports such
as medication compliance reporting and predictive modeling of
patients to identify those patients most likely to incur significant
future health care expenditures.
While our integrated health system has used physician-specific performance reports for diabetes care for several years,
many physicians have expressed concern regarding the time
and office resources that are necessary to schedule patients
for routine and follow-up testing and subsequent office visits.
In response to this concern, the health system has developed
a laboratory requisition direct-mailing process that includes
HbA1c, lipid profile, and microalbumin screening.
Diabetes laboratory requisition direct mailing has been
piloted in several physician offices. This new enhancement in
DCMS identifies diabetes patients who do not have a record of
receipt of the appropriate diabetes complication screening tests in
the time period specified. Laboratory requisition forms for direct
mailing are produced in bulk, aggregated, and then forwarded to
each primary care physician’s office. The laboratory requisition is
produced with prepaid postage and includes space for the physician to personalize the mailing with a signature. The patient
direct-mail letters include the list of locations where the lab tests
can be performed. The actual tear-off laboratory requisition
includes all of the required information necessary to process the
laboratory tests automatically. The primary care physician verifies
that the patient is active in the practice, personalizes the requisition with a signature, seals the trifold requisition, and either mails
FIGURE 8
68.1%
64.0%
62.0%
56.0%
60
51.7%
52.0%
47.9%
40
20
0
1998
1999
FIGURE 10
2000
2001
2002
2002
National
Average
2002
National
90th %ile
Diabetes Care Management System
(DCMS) Results, 1998-2002
100
80
♦
♦
60
50
40
*
•
30
*
•
*
•
*
•
70
♦
♦
90
Percent of Patients
Improving the rate of eye examinations for patients with diabetes proved to be one of the most difficult performance levels
to affect. We found that primary care physicians have relatively
little control over whether patients follow their advice to obtain
an eye exam. Also, primary care physicians may not focus on
this outcome because of the general lack of communication
between primary care and secondary care providers. These difficulties led to the development and implementation of the
patient incentive program for eye exams.
*
•
♦
20
2001
2002
10
0
1998
1999
♦
Annual HbA1c
HbA1c >9.5
www.amcp.org Vol. 9, No. 6 November/December 2003
2000
HbA1c <7
*
JMCP
Biannual LDL
LDL <130
•
Annual Eye Exam
Journal of Managed Care Pharmacy 557
Longitudinal Assessment of a Diabetes Care Management System in an Integrated Health Network
it to the patient directly or returns the requisitions in bulk to be
mailed to patients by the health system.
This laboratory requisition process allows for personalized
outreach to patients from each physician’s office while incurring
minimal use of office staff. This process is expected to reduce
the number of physician office visits, and the health system
plans to expand the laboratory requisition program to all primary care offices that have patients in the diabetes registry.
ACKNOWLEDGMENTS
The authors wish to acknowledge the following contributions in the preparation of this research and manuscript: Ilene Tippets for her input on study concept and design and analysis and interpretation of data, Matt Snell for his statistical expertise and analysis and interpretation of data, and Steven Barlow,
Jonathan Despain, and David Hale, for their administrative and technical support related to the building of the diabetes registry and the reports included in
this manuscript.
DISCLOSURES
No outside funding supported this study. Author David L. Larsen served as
principal author of the study. Study concept and design were contributed by
Larsen and authors Wayne Cannon and Steven Towner. Drafting of the manuscript and its critical revision were the work of Larsen and Cannon. Analysis
and interpretation of data was contributed by Larsen, Cannon, and Towner,
and statistical expertise was contributed primarily by Matt Snell.
REFERENCES
1. Pahor M, Psaty BM, Alderman M, Applegate WB, Williamson JD, Furberg
CD. Therapeutic benefits of ACE inhibitors and other antihypertensive drugs
in patients with type 2 diabetes. Diabetes Care. July 2000:23(7):888-92.
2. Grossman E, Messerl FH, Goldbourt U. High blood pressure and diabetes: are
all antihypertensive drugs created equally? Arch Intern Med. 2000:160(16):2447.
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3. White WB, Prisant LM, Wright JT. Management of patients with hypertension and diabetes mellitus: advances in the evidence for intensive treatment.
Am J Med. 2000:108(3):238-45.
4. National Heart, Lung, and Blood Institute. Treating Hypertension in the Patient
With Type 2 Diabetes [clinical advisory statement]. Available at:
http://www.nhlbi.nih.gov/health/prof/heart/ hbp/hbp_diab.htm.
5. Summary of revisions for the 2001 clinical practice recommendations.
Diabetes Care. 2001:24(suppl 1):53.
6. Laker RD. The Diabetes Control and Complications Trial—Implications for
policy and practice. N Engl J Med. 1993:329(14):1035-36.
7. Diabetes Control and Complications Trial Research Group: the effect of
intensive treatment of diabetes on the development and progression of longterm complications in insulin-dependent diabetes mellitus. N Engl J Med.
1993:329:977-86.
8. UK Prospective Diabetes Study Group. Intensive blood-glucose control with
sulphonylureas or insulin compared with conventional treatment and risk of
complications in patients with type 2 diabetes (UKPDS 33). Lancet. 1998:352:
837-53.
9. UK Prospective Diabetes Study Group. Effect of intensive blood-glucose
control with metformin on complications in overweight patients with type 2
diabetes (UKPDS 34). Lancet. 1998:352:854-65.
10. UK Prospective Diabetes Study Group. Tight blood pressure control and
risk of macrovascular and microvascular complications in type 2 diabetes
(UKPDS 38). BMJ. 1998:317:703-13.
11. UK Prospective Diabetes Study Group. Efficacy of atenolol and captopril
in reducing risk of both macrovascular and microvascular complications in
type 2 diabetes (UKPDS 39). BMJ. 1998:317:713-20.
12. http://www.ihc.com/xp/ihc/physician/clinicalprograms/primarycare/diabetes.xml.
13. http://www.ihc.com/diabetes.
14. National Committee for Quality Assurance. Health Plan Employer Data and
Information Set (HEDIS) 2003. vol.2.
Vol. 9, No. 6
www.amcp.org
C O N T E M P O R A RY S U B J E C T
Examination of the Evidence for Off-Label Use of Gabapentin
ALICIA MACK, PharmD
ABSTRACT
OBJECTIVES: (1) Describe the relevance of off-label use of gabapentin to managed care pharmacy; (2) summarize recent FDA warnings and media reports
related to off-label gabapentin use; (3) review medical information pertaining
to the off-label use of gabapentin; (4) outline alternatives to off-label use of
gabapentin in an evidence-based fashion, where literature exists to support such
alternatives; and (5) encourage key clinicians and decision makers in managed
care pharmacy to develop and support programs that restrict the use of
gabapentin to specific evidence-based situations.
SUMMARY: Gabapentin is approved by the U.S. Food and Drug Administration
(FDA) for adjunctive therapy in treatment of partial seizures and postherpetic
neuralgia. Various off-label (unapproved) uses have been reported, and the use
of gabapentin for off-label purposes has reportedly exceeded use for FDAapproved indications. Pharmaceutical marketing practices and physician dissatisfaction with currently available pharmacological treatment options may be key
factors that contribute to this prescribing trend.
Recently, the media has focused on these issues, noting that many cases of
reported safety and effectiveness of gabapentin for off-label use may have been
fabricated. A thorough review of the medical and pharmacy literature related to
off-label use of gabapentin was performed, and a summary of the literature for the
following conditions is presented: bipolar disorder, peripheral neuropathy, diabetic
neuropathy, complex regional pain syndrome, attention deficit disorder, restless
legs syndrome, trigeminal neuralgia, periodic limb movement disorder of sleep,
migraine headaches, and alcohol withdrawal syndrome. A common theme in the
medical literature for gabapentin is the prevalence of open-label studies and a lack
of randomized controlled clinical trials for all but a small number of indications.
CONCLUSIONS: In the majority of circumstances where it has reported potential
for “off-label” use, gabapentin is not the optimal treatment. The off-label use of
gabapentin for indications not approved by the FDA should be reserved for cases
where there is solid research support (e.g., diabetic neuropathy and prophylaxis
of frequent migraine headaches). Managed care pharmacists should develop
programs to restrict the use of gabapentin to these specific evidence-based situations, and key decision makers in managed care practice should feel confident
in supporting these use restrictions for gabapentin.
KEYWORDS: Neurontin, Gabapentin, Off-label, Comparison, Bipolar, Restless legs,
Trigeminal neuralgia, Migraine, Peripheral neuropathy, Diabetic neuropathy,
Complex regional pain syndrome, Attention deficit disorder, Periodic limb movement disorder of sleep, Alcohol withdrawal syndrome
J Managed Care Pharm. 2003;9(6):559-68
Author
ALICIA MACK, PharmD, is clinical pharmacy coordinator, Three Rivers
Administrative Services, LLC, Monroeville, Pennsylvania, and adjunct clinical
instructor, Department of Pharmacy and Therapeutics, University of Pittsburgh
School of Pharmacy, and Duquesne University, Mylan School of Pharmacy,
Pittsburgh.
AUTHOR CORRESPONDENCE: Alicia Mack, PharmD, Clinical Pharmacy
Coordinator, Three Rivers Administrative Services, LLC, 300 Oxford Dr.,
Monroeville, PA 15146. Tel: (412) 856-5108; Fax: (412) 457-1622;
E-mail: [email protected]
Copyright© 2003, Academy of Managed Care Pharmacy. All rights reserved.
G
abapentin (Neurontin) was approved by the U.S. Food
and Drug Administration (FDA) on December 30,
1993, for adjunctive therapy in the treatment of partial
seizures, with and without secondary generalization, in patients
above the age of 12 years. The FDA approved the indication for
adjunctive therapy for partial seizures in children aged 3 to
12 years in October 2000 and the indication for postherpetic
neuralgia in adults in May 2004.1
Gabapentin is an amino acid that is structurally related to the
inhibitory neurotransmitter gamma-amino butyric acid (GABA);
however, its antiepileptic activity appears unrelated to any direct
effects on the GABAergic system.2 The mechanism of action of the
drug has led to tremendous scientific speculation as to the potential merits of the drug in other clinical conditions.
Since its introduction to the market in 1993, gabapentin has
gained widespread use, and a significant portion of this use has
been for non-FDA approved uses (Figure 1). A retrospective
FIGURE 1
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
Reported Off-Label (Unapproved)
Uses of Gabapentin
Bipolar disorder
Neuropathic pain
Diabetic neuropathy
Complex regional pain syndrome
Attention deficit disorder
Restless legs syndrome
Trigeminal neuralgia
Periodic limb movement disorder of sleep
Migraine
Drug and alcohol withdrawal seizures
review of one managed Medicaid plan demonstrated that 95%
of patients were using gabapentin for off-label diagnoses.3
Gabapentin has also garnered unfavorable publicity because of
accusations that the manufacturer illegally promoted the agent
for at least 10 “off-label” medical conditions4,5 (Figure 1). The
FDA has issued various warning statements to the manufacturer as a result of these marketing practices.6,7
While various summaries of these issues are accessible in the
public domain, a more thorough evaluation of the issues from a
clinical standpoint is warranted. The intent of this review is to
tie the media concerns to clinical evidence obtained from a
thorough literature review so that managed care pharmacists
and physicians will be better prepared to address the subject of
appropriate use of gabapentin.
■■ Media Issues
The manufacturer of gabapentin has been accused of illegal promotion of the drug to prescribing physicians for at least 10 off-
www.amcp.org Vol. 9, No. 6 November/December 2003
JMCP
Journal of Managed Care Pharmacy 559
Examination of the Evidence for Off-Label Use of Gabapentin
TABLE 1
Summary of Open-Label Trials and Case Reports With Gabapentin in Bipolar Illness
Study
Treatment
Population
Results
Reference
Ghaemi SN,
Goodwin FK.
Open, prospective
chart review
8 patients
received
gabapentin
monotherapy;
13 received
adjunctive therapy
21 outpatients meeting DSM-IV
criteria for bipolar spectrum
disorder (type I, type II, NOS
cyclothymia) who were treated
with gabapentin
Alone, or as adjunct, gabapentin
appeared moderately effective in
treating depression. Using the CGIBP, gabapentin was moderately to
markedly effective in 43% of patients
for overall bipolar illness, 38% for
depressive symptoms, and 25% for
manic symptoms.
J Affect Disord.
2001;65(2):167-71.
Altshuler LL, Keck PE, Adjunctive
McElroy SL, et al.
therapy with
Open
gabapentin
600 mg-3,600 mg/
day
28 bipolar patients, 5 experiencing
manic symptoms, 5 experiencing
depressive symptoms, and 5
experiencing rapidly cycling
symptoms refractory to at least
1 mood stabilizer
As adjunctive therapy, gabapentin
appears to have acute antimanic and
antidepressant properties. Fourteen
of the 18 (78%) mania or hypomania patients had a positive response.
All of the patients treated for depression
had positive response. (Positive response
was a CGI response of much or very
much improvement.)
Bipolar Disord.
1999;1(1):61-65.
Carta MG,
Hardoy MC, Dessi I,
et al.
Open
Adjunctive
therapy with
gabapentin
300 mg-900 mg
10 patients with intellectual
disability and demonstrable
increases in symptomatology
during significant life events
that had interfered with or
induced interruption of their
rehabilitation programs
A positive response to therapy was
observed with subsequent improvement
of psychopathological conditions, particularly
for anxiety and depressive symptoms.
J Intellect Disabil Res.
2001;45(pt 2):I39-45.
Sokolski KN,
Green C, Maris DE,
et al.
Open label
Adjunctive
therapy for
1 month
10 bipolar patients with mixed
symptoms who had previously
demonstrated only partial
treatment responses
Decreases in Hamilton depression
(P<0.05) and Bech mania ratings
(P<0.01) were evident in the first week
of treatment and were sustained.
Potent early improvements were noted
in early, middle, and late insomnia.
Ann Clin Psychiatry.
1999; 11(4):217-22.
Young LT, Robb JC,
Hasey GM, et al.
Open
Adjunctive
treatment for
up to 6 months
37 patients with bipolar type I
or II with or without rapid
cycling course
Using HamD and YMS scales, mood symptoms
were assessed and both depressive and manic
symptoms were found to be significantly reduced
with gabapentin.
J Affect Disord.
1999;55(1):73-77.
Hatzimanolis J,
Lykouras, L,
Oulis P, et al.
Case report
Monotherapy
for 2 weeks
2 patients with acute mania
After 2 weeks of treatment, a moderate
improvement of both patients was observed.
Eur. Neuropsychopharma.
1999;9(3):257-9.
Erfurth A,
Kammerer C,
Grunze H, et al.
Open label
6 add-on cases
and 8 high-dose
monotherapy
cases; dose
range of 1,200 mg4,800 mg/day;
treatment for
up to 21 days
14 patients with acute mania
The study suggested that gabapentin
monotherapy may be useful in treating
modest but not severe manic states. In
conjunction with other mood stabilizers
such as lithium or depakote, it may be
useful. Of note, there was not a comparison
arm to the mood stabilizers alone, so any
advantage of the combination over monotherapy with these agents remains unproven.
J Psychiatr Res.
1998;32(5):261-64.
Soutullo CA,
Casuto LS, Keck PE.
Case report
Add-on to
carbamazepine
One boy, aged 13 years,
with bipolar disorder,
manic episode, and ADHD
Patient remained euthymic 7 months
after gabapentin was added. Young
Mania Rating Scale (YMRS) score
was 27 when gabapentin was added,
9 after 1 month, 15 after 4 months,
and 6 after 7 months.
J Child Adolesc
Psychopharmacol.
1998;8(1):81-85.
label conditions; company medical science liaisons were also
alleged to have been involved in this practice.4 The authors of
one news article noted that many reported cases of safety and
effectiveness with unapproved use of the drug appeared to be
fabricated by the manufacturer.
560 Journal of Managed Care Pharmacy
JMCP
November/December 2003
A follow-up story in January 2003 about a “whistle-blower”
lawsuit related to allegedly illegal marketing practices included
an explanation of some of the issues, with particular emphasis
on the clinically inappropriate promotion of gabapentin for
bipolar disorder.4 The lawsuit involves charges made by a for-
Vol. 9, No. 6
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Examination of the Evidence for Off-Label Use of Gabapentin
TABLE 2
Publication Type
Summary of Selected Primary and Tertiary References
Using Gabapentin in Management of Neuropathic Pain
Treatment or Method
Population
Results
Reference
Randomized,
double-blind,
placebocontrolled trial
Symptom-based, 8-week
study design of patients
receiving gabapentin in
doses up to 2,400 mg/day
or placebo
153 patients patients
randomized to gabapentin
and 152 patients
randomized to placebo
Over the study, the average daily pain
diary score improved by 1.5 (21%) in
gabapentin-treated patients and by
1.0 (14%) in placebo-treated patients.
(P=0.048, rank-based analysis of
covariance). Significant differences
were shown in favor of gabapentin
(P<0.05) for the clinician and patient
global impression of change and some
domains of the Short-Form McGill
Pain Questionnaire.
Serpell MG. Pain.
2002;99(3):557-66.
Pilot study
Gabapentin was administered
orally in gradually increasing
doses up to a maximum of
2,400 mg/day
18 patients with
peripheral nerve injuries
or central lesions
Gabapentin induced a moderate and
statistically significant relief of
ongoing or spontaneous pain and was
particularly effective in reducing
paroxysmal pain. A striking finding
was the significant effect on brushinduced cold allodynia. In contrast,
no effects were observed on detection
of pain thresholds to static mechanical
and hot stimuli.
Brasseur AN, Parker F,
Chauvin M, et al.
Eur Neurol. 1998;40(4):
191-200.
Retrospective
chart review
Patients receiving
gabapentin for
at least 30 days
were studied.
122 patients divided into
3 groups based on pain
diagnosis of low back,
myofascial, or neuropathic
pain
Significant decrease in pain scores
with gabapentin in the neuropathic
pain group but not in the low-backpain group. Patients with postherpetic
neuralgia had the greatest decrease in
pain scores. Patients who were taking
opiates had significantly less benefit
with gabapentin in terms of pain score.
Rosenberg JM, Harrell C,
Ristic H, et al. Clin J Pain.
1997;13(3):351-55.
Meta-analysis
Extensive search of
several electronic
databases for controlled
and uncontrolled studies.
Efficacy was assessed through
meta-analyses of randomized
controlled trials (RCTs).
Effectiveness of gabapentin
in uncontrolled studies was
assessed via a novel system of
dichotomous classification of
bad versus good results.
35 papers involving
727 patients with
multiple neuropathic
pain conditions
met inclusion
criteria
The meta-analysis of the 2 highquality placebo-controlled randomized
trials showed positive effect of
gabapentin in diabetic neuropathy
and postherpetic neuralgia. Addition
of 2 low-quality PC, RCTs did not
alter the magnitude or duration of the
observed effect. The uncontrolled
studies demonstrated positive effect
on pain in different neuropathic
syndromes as well as benefit for
different types of neuropathic pain;
highest dose administered and rate of
dose escalation showed wide variability
between prescribers. Fewer and lesssevere side effects were reported in the
uncontrolled studies.
Mellegers MA, Furlan AD,
Mailis A. Clin J Pain.
2001;17(4):284-95.
Randomized
controlled
clinical trial
Gabapentin 3,600 mg/day
(forced max) 67% achieved
max dose
Uncontrolled
diabetes
(75% type 2)
n=84 gabapentin,
n=81 placebo
Gabapentin versus placebo:
difference in mean pain score at
endpoint = -1.2 (P<0.001);
difference in mean sleep
interference score = -1.47 P<0.001).
Backonja M, Beydoun A,
Edwards K, et al.
JAMA. 1998;280: 1831-36.
Randomized
controlled
clinical trial
Gabapentin 3,600 mg/day
(65% achieved max dose)
versus placebo
Postherpetic
neuralgia
n=113 gabapentin,
n=112 placebo
Decrease in average daily pain score
= 33% gabapentin, 7% placebo
(P<0.001).
Rowbotham M, Harden N,
Stacey B, et al.
Ann Pharmacother.
2000;34:802-07.
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Journal of Managed Care Pharmacy 561
Examination of the Evidence for Off-Label Use of Gabapentin
TABLE 3
Drug
Price Comparisons for Gabapentin Versus Various Tricyclic Antidepressants
Used in the Management of Neuropathic Pain
Dose for Management of
Neuropathic Pain†*
FDA Approval
Cost per Unit†
Tablet or Capsules
per Month
Maximum Average
Cost per month
Gabapentin
300 mg/day up to
1,800 mg/day
No
100 mg cap ($0.51 ea)
300 mg ($1.23 ea)
400 mg ($1.47 ea)
600 mg ($1.98 ea)
800 mg ($2.38 ea)
up to 540
up to 180
up to 135
up to 90
up to 68
$275.40
$221.98
$199.48
$178.98
$162.44
Amitriptyline
10 mg-25 mg orally
at bedtime, up to
150 mg-200 mg/day
No
10 mg tab ($0.09 ea)
25 mg ($0.12 ea)
50 mg ($0.09 ea)
75 mg ($0.12 ea)
100 mg ($0.13 ea)
up to 600
up to 240
up to 120
up to 90
up to 60
$54.00
$28.80
$10.80
$10.80
$7.80
Nortriptyline
10 mg/day orally,
increase by 10 mg/day
every 3 to 5 days as needed;
doses up to 60 mg/day
have been reported
No
10 mg cap ($0.14 ea)
25 mg cap ($0.21 ea)
50 mg cap ($0.25 ea)
75 mg cap($0.28 ea)
up to 180
up to 60
up to 30
up to 30
$25.20
$12.60
$7.50
$8.40
† Gelman CR, Rumack BH, eds. DRUGDEX Information System. Denver, CO: Micromedex, Inc.; 1994.
‡ http://www.drugstore.com. Accessed September 7, 2003. Cost per unit based on 90 unit/month pricing.
mer salesman that the company used a systematic strategy to
promote gabapentin for various off-label uses. The extension of
potential uses of gabapentin contributed to the drug’s tremendous financial success, essentially creating a “blockbuster” drug
in terms of sales. In 2000 alone, gabapentin earned $1.3 billion
in sales, and as much as 78% of these sales were for uses without clinical evidence of safety or effectiveness.4
■■ Review of the Clinical Literature
Off-label use of gabapentin has been reported in bipolar disorder, peripheral neuropathy, diabetic neuropathy, complex
regional pain syndrome, attention deficit disorder, restless legs
syndrome, trigeminal neuralgia, periodic limb movement disorder of sleep, migraine headaches, and drug and alcohol withdrawal syndrome. A recurring theme in the literature, with the
exception of neuropathic pain and migraine, is a prevalence of
open-label studies with a lack of randomized controlled clinical
trials. It is important to consider that an inherent problem with
open-label trial design is the potential for introduction of bias
because the treatment assignment is known.
Gabapentin in the Treatment of Bipolar Disorder
Extensive review confirms that current published literature on
gabapentin is primarily based on open-label trials that evaluate
small numbers of patients (Table 1).8-15 The few randomized
controlled trials designed to investigate the efficacy of
gabapentin in treating bipolar disorder have concluded that
there is no significant difference in the effects of the drug compared with placebo.16,17 This supports the likelihood of bias in
the various open-label studies since these results have not been
confirmed in the randomized controlled trials. Various authors
562 Journal of Managed Care Pharmacy
JMCP
November/December 2003
of medical reviews on this subject have concluded that
gabapentin should not be recommended for treatment of bipolar disorder and that double-blind, randomized controlled trials
are needed to confirm any true efficacy of the drug in management of this condition.18-21
Real-life practice involves instances of refractory bipolar disorder
that exhaust the current treatment options. The Texas Medication
Algorithm Project (TMAP) lists lamotrigine or gabapentin only as
salvage therapy. Therefore, these 2 agents should be reserved for
unstable patients at the seventh stage of treatment in
hypomanic/manic episodes.22 In all other forms of bipolar disorder,
gabapentin is not recommended at any phase of therapy.
Although limited comparative data are available on the subject, results from a cross-over study suggest that lamotrigine
may be superior to gabapentin as well as placebo for the management of refractory mood disorders.23 The investigators studied 31 patients who had either bipolar I, bipolar II, or unipolar
disorder and failures of other mood stabilizing agents.
Lamotrigine was titrated to 300 mg–500 mg by weeks 5 and 6,
and gabapentin was titrated to 4,800 mg daily by week 6.
At week 6, based on the Clinical Global Impression Score, 52%
of patients responded to lamotrigine, 26% responded
to gabapentin, and 23% responded to placebo (P=0.011,
lamotrigine versus gabapentin). The results of this study suggest
that lamotrigine might be considered in cases of treatment
refractory to first-line agents in bipolar disorder.
Gabapentin in the Treatment of Pain Syndromes,
Peripheral Neuropathy, and Diabetic Neuropathy
The exact mechanism of action of gabapentin in managing neuropathic pain is unknown; however, it is speculated to work via
Vol. 9, No. 6
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Examination of the Evidence for Off-Label Use of Gabapentin
In the Morello study,34 the
agents were proven comparable
in clinical efficacy. In fact, these
Study
Treatment
Population
Results
Reference
authors suggested a slight advanCase study
Gabapentin
1 child
Satisfactory pain relief
Wheeler DS, Vaux KK , Tam DA.
tage to using amitriptyline over
was reported.
Use of gabapentin in the treatment
gabapentin, although the differof childhood reflex sympathetic
ence was not statistically signifidystrophy. Pediatr Neurol. 2000;
cant. Comparing prices of the
22(3):2201-11.
agents given in doses for the manCase study
Gabapentin
6 patients, aged Satisfactory pain relief was Mellick GA, Mellick LB. Reflex
agement of neuropathic pain,
42-68 years,
obtained in all patients.
sympathetic dystrophy treated
with severe,
with gabapentin. Arch Phys Med
amitriptyline and nortriptyline cost
refractory RSD
Rehabil. 1997;78(1):98-105.
only a small fraction of the significant direct drug cost associated
with gabapentin (Table 3).35
Therefore, the tricyclics appear to
voltage-activated calcium ion channels at the postsynaptic dor- offer a lower-cost therapeutically equivalent alternative to
sal horn, thereby interrupting the series of events that leads to gabapentin in many situations.
the sensation of neuropathic pain. Review of the various
hypotheses concerning these pharmacologic theories is beyond Gabapentin in the Treatment of
Complex Regional Pain Syndrome
the scope of this article but may be found elsewhere.24-26
While the clinical literature in support of gabapentin use for There are no reports that confirm efficacy of gabapentin in
conditions of neuropathic pain is more favorable than that con- management of complex regional pain syndrome, also known
cerning its use in various other disease states, there remain as reflex sympathetic dystrophy (RSD). The literature is sparse
issues concerning its merits in clinical practice. These involve and primarily anecdotal in nature, composed of 2 reports
variable doses, few direct comparisons to other agents, and, involving a total of 7 patients in addition to 2 letters (Table 4)
again, a number of open-label studies with the potential that offer little scientific value.36-40 From an evidence-based
for bias. Nonetheless, gabapentin does have proven efficacy for the standpoint, the available information is insufficient to support
treatment of diabetic neuropathy and postherpetic neuralgia.32,33 use of gabapentin in this condition. Recognized medical treatA summary of selected published studies on this subject ments for RSD include adrenergic blockers, nonsteroidal antiinflammatory drugs, calcium channel blockers, phenytoin, opiappears in Table 2.27-33
Morello et al. demonstrated that there is no statistically sig- oids, and calcitonin.39
nificant difference between amitriptyline and gabapentin in the
treatment of diabetics with peripheral neuropathic pain, as Gabapentin in the Treatment of Attention Deficit Disorder
measured by pain scales and global pain scores.34 In this study, There are 3 published reports related to behavioral disturbances
21 diabetic patients with stable glycemic control received either and the use of gabapentin, none of which were clinical trials.
gabapentin or amitriptyline for 6 weeks and then crossed over One case report is specific to the use of the drug in attention
to the other arm of therapy for 6 additional weeks, with a deficit hyperactivity disorder (ADHD). A second case report
1-week wash-out period between therapies. Dosage was adjust- involved 7 patients who experienced behavioral side effects
ed based on the patient’s response, with a mean gabapentin dose with gabapentin. The third citation was a letter (Table 5).41-43
of 1,565 mg and a mean amitriptyline dose of 59 mg. Both Thus, the evidence related to the use of gabapentin in ADHD is
medications were found to significantly decrease pain scores insufficient to warrant its use for this condition.
Stimulants have been the mainstay of ADHD therapy for
from baseline (P<0.001). Sixty-seven percent of amitriptyline
patients reported moderate or greater pain relief, and 52% of decades, but there is a rising trend in pediatric polypsychopharmacy with little or no research to support this phegabapentin patients reported such relief (P=0.26).
Current treatment guidelines favor using amitriptyline, nor- nomenon.44 Since there is no evidence to support the use of
triptyline, or gabapentin for the management of painful neuro- gabapentin in ADHD, alternative clinically appropriate and suppathic conditions. It is recognized that, in specific clinical cir- portable treatment options should be given primary consideracumstances, the adverse-effect profile of the tricyclics may tion when formulating treatment plans for cases refractory to
prove unacceptable, thus warranting consideration of therapeu- stimulants in ADHD. Current treatment guidelines suggest a
tic alternatives. However, in cases without tricyclic contraindi- trial with a stimulant along with diet, behavior management,
cations, cost should also be considered when selecting an initial special education, and perhaps psychotherapy in ADHD disease
management. 43
option for treatment.
TABLE 4
Published Reports Related to Use of Gabapentin
in Complex Regional Pain Syndrome I
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Examination of the Evidence for Off-Label Use of Gabapentin
TABLE 5
Published Reports of Gabapentin and Behavior in Children
Study type
Treatment
Results
Reference
Case report
Gabapentin 200 mg/day added
to methylphenidate 30 mg/day
1 boy, aged 12 years, with
ADD, reading disorder, mixed
receptive and expressive
language disorder,
encopresis, and
bipolar disorder II
Population
Within 3 weeks, mother,
teacher, and clinician noted
improvement and stabilization of mood symptoms as
remarkable; it remained so for
6 months of follow-up.
Hamrin V, Bailey K. Gabapentin
and methylphenidate treatment
of a preadolescent with attention
deficit hyperactivity disorder and
bipolar disorder. J Child Adolesc
Psychopharmacol. 2001;11(3):
301-09.
Case report
Gabapentin as adjunct
7 children with baseline
ADD and developmental
delay
Children consequentially
developed behavioral side
effects, including tantrums,
aggression toward others,
hyperactivity, and defiance.
All behavioral changes were
reversible and were managed
by dose reduction or discontinuation of gabapentin.
Lee DO, Steingard RJ, Casena M,
et al. Behavioral side effects of
gabapentin in children. Epilepsia.
1996;3(1):87-90.
Gabapentin in the Treatment of Restless Leg Syndrome
Restless leg syndrome (RLS) is an awake phenomenon characterized by an intense, irresistible urge to move the legs, usually
associated with sensory complaints, motor restlessness, worsening of symptoms at rest and relief with motor activation, and
increased severity in the evening or during the night. Sparse
case reports have suggested potential use of gabapentin in RLS,
but, again, there are no controlled clinical trials that assess its
safety and effectiveness in treatment of this condition.45-49
The Standards of Practice Committee of the American
Academy of Sleep Medicine (AASM), in conjunction with specialists and other interested parties, developed guidelines for
managing RLS that were subsequently approved by the Board of
Directors of AASM. The recommendations were identified as
standards, guidelines, or options, based on the strength of evidence from published studies that meet criteria for inclusion
(Table 6).
The AASM guideline classifies the following agents as having
sufficient evidence to support their use in RLS treatment:
(1) levodopa with decarboxylase inhibitor and pergolide,
(2) oxycodone and propoxyphene, or (3) carbamazepine. AASM
has reported that the dopaminergic agents are notably the best
studied and most successful agents for the treatment of RLS.50
Alternatively, they have commented that gabapentin has limited “Level V” evidence (case-series reports only), consisting of
only 2 case studies. For this reason, AASM has classified use of
gabapentin in RLS as a patient-care strategy that reflects uncertain clinical use. The members of the panel felt that there is
inconclusive data, conflicting evidence, or conflicting expert
opinion on the use of gabapentin for managing RLS. 50
Gabapentin in the Treatment of Trigeminal Neuralgia
Conclusive studies confirming the efficacy of gabapentin in the
treatment of trigeminal neuralgia are lacking. To date, literature
564 Journal of Managed Care Pharmacy
JMCP
November/December 2003
supporting the effectiveness of gabapentin in trigeminal neuralgia is limited to case studies in aggregate of less than
30 patients.51-53 Carbamazepine remains the drug of first
choice.54 If paroxysms of pain still occur with therapeutic blood
levels, phenytoin or baclofen should be added.54 Lamotrigine
was recently validated for use in refractory trigeminal neuralgia,
especially due to multiple sclerosis.51,52,55
Gabapentin in the Treatment of
Periodic Limb Movement Disorder of Sleep
Periodic limb movements of sleep occur as an asleep phenomenon and are characterized by periodic episodes of repetitive and
highly stereotyped limb movements. These patients typically
have complaints of insomnia or excessive sleepiness with no
other disorder to explain the symptoms.
RLS and periodic limb movement disorder (PLMD) of sleep
are distinct disorders by definition, but they have been reported to coexist in approximately 80% of cases. However, the treatment of the 2 conditions is not always the same. There is no reference to the use of gabapentin in PLMD, and there is no mention of gabapentin in recommendations of AASM.50 There is no
published evidence demonstrating efficacy of gabapentin in the
management of PLMD. Experts have reported that symptoms
may respond to correction of a coexisting iron deficiency anemia or to treatment with dopaminergic medication (such as levodopa or bromocriptine), benzodiazepines (diazepam or clonazepam), or opiates (codeine, propoxyphene, or oxycodone).56
Gabapentin in the Treatment of Migraine
Pharmacoeconomic analyses reveal that gabapentin is only cost
effective for migraine prophylaxis in patients who experience
very frequent migraine headaches. Adelman et al. studied the
costs for acute migraine care following initiation of prophylactic
medications. They reported that divalproex patients must have
Vol. 9, No. 6
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Examination of the Evidence for Off-Label Use of Gabapentin
TABLE 6A
Recommendation
Grade
A
American Academy of Sleep Medicine
Classification of Evidence
Evidence
Level
Study Design
I
Randomized, well-designed trials with
low alpha and low beta errors*
B
II
Randomized trials with high beta errors*
C
III
Nonrandomized controlled or
concurrent cohort studies
C
IV
Nonrandomized historical cohort studies
C
V
Case series
*Alpha error refers to the probability (generally set at 95% or greater) that a significant result (e.g., P<0.05) is the correct conclusion of the study or studies. Beta error
refers to the probability (generally set at 80% or 90% or greater) that a nonsignificant result (e.g., P>0.05) is the correct conclusion of the study or studies. The
estimation of beta error is generally the result of a power analysis. The power
analysis includes a sample size analysis that projects the size of the study population necessary to ensure that significant differences will be observed if actually
present.
Source: Chesson AL, Wise M, Davila D, et al. Practice parameters for the treatment of restless legs syndrome and periodic limb movement disorder. An American
Academy of Sleep Medicine Report. Standards of Practice Committee of the
American Academy of Sleep Medicine. Sleep. 1999;22(7):961-68.
TABLE 6B
Term
American Academy of Sleep Medicine
Recommendations for Restless Legs
Syndrome or Periodic Limb Movement
Disorder
Definition
Standard
This is a generally accepted patient-care strategy that
reflects a high degree of clinical certainty. The term
“standard” generally implies the use of Level I evidence,
which directly addresses the clinical issue or overwhelming Level II evidence.
Guideline
This is a patient-care strategy that reflects a moderate
degree of clinical certainty. The term “guideline”
implies the use of Level II evidence or a consensus of
Level III evidence.
Option
This is a patient care strategy that reflects uncertain
clinical use. The term “option” implies either
inconclusive or conflicting evidence or conflicting
expert opinion.
Source: Chesson AL, Wise M, Davila D, et al. Practice parameters for the treatment of restless legs syndrome and periodic limb movement disorder. An American
Academy of Sleep Medicine Report. Standards of Practice Committee of the
American Academy of Sleep Medicine. Sleep. 1999;22(7):961-68.
more than 10 migraine episodes per month while gabapentin
patients must have more than 24 migraine episodes per month
before these drugs can be considered cost effective.57-60
While there are clinical trials of gabapentin in migraine prophylaxis, outstanding questions remain regarding the drug’s
utility in clinical practice. One randomized, placebo-controlled
study of 63 patients showed that gabapentin in daily prophylactic doses of 1,200 mg is well tolerated and reduces headache
frequency and the use of drugs to produce symptomatic relief.61
While gabapentin appeared to be effective in this particular
trial, it is still unclear how gabapentin would compare to other
more-established pharmacotherapy for migraine prophylaxis.
Thus, gabapentin should be considered for use in migraine syndrome management only after failure of standard prophylaxis
regimens (Table 7).
Gabapentin in the Treatment of
Drug and Alcohol Withdrawal Seizures
Mayo-Smith published an evidence-based practice guideline for
the pharmacological management of alcohol withdrawal.62 He
completed a meta-analysis of prospective controlled trials only,
with methodologically sound endpoints (e.g., withdrawal severity, delirium, seizures, completion of withdrawal, entry into
rehabilitation, adverse events) corresponding to the Diagnostic
and Statistical Manual of Mental Disorders. Mayo-Smith concluded that benzodiazepines remain the gold standard for management of alcohol withdrawal and that dosage should be individualized based on withdrawal severity.
According to this analysis, the author notes that beta-blockers, clonidine, and carbamazepine may be considered as
adjunctive therapy.62 There was no mention of gabapentin in
this guideline since published reports of gabapentin for these
indications are limited to case reports, open-label studies, and
anecdotal letters.63-67 Thus, gabapentin cannot be recommended
for use in any aspect of the management of alcohol withdrawal
seizures, either as initial or add-on therapy.
■■ Conclusions
In the majority of circumstances where it has reported potential
for indications not approved by the FDA (i.e., off-label use),
gabapentin is not the optimal treatment. The reader should
remain cautious regarding claims that gabapentin offers any
benefit in treating conditions other than those with FDA
approval. Hamer et al. concluded, “While case reports and
open-label trials are valuable for directing further research, they
are generally not sufficient as the basis of treatment decisions.”
Gabapentin is not recommended in the clinical guidelines or
established treatment algorithms (e.g., American Academy of
Neurology or AASM guidelines or TMAP algorithm) for any of
the off-label indications. Considering the evidence, gabapentin
should be used almost exclusively for the FDA-approved indications—treatment of seizures and postherpetic neuralgia.
Off-label use of gabapentin should be reserved for patients who
have failed standard treatment options and in those cases where randomized controlled clinical trials have demonstrated gabapentin
efficacy (i.e., diabetic neuropathy and migraine headaches). Costeffectiveness ratios tend to be high (unfavorable) for the use of
gabapentin in diabetic neuropathy and migraine syndrome except
in those patients who experience a high frequency of acute episodes.
Pharmaceutical manufacturer marketing practices appear to
www.amcp.org Vol. 9, No. 6 November/December 2003
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Journal of Managed Care Pharmacy 565
Examination of the Evidence for Off-Label Use of Gabapentin
TABLE 7
AAA Migraine Prophylaxis Guidelines: Assessment of the Relative Value
of Preventive Therapies for Migraine Available in the United States
Group I*
Group II†
Efficacious Doses
in Clinical Trials
Group III‡
Group IV§
Drug
Efficacious Doses
in Clincial Trials
Drug
Amitriptyline 30 mg-150 mg/day
Aspirin¶
1,300 mg/day
Cyproheptadine
Divalproex
500 mg-1,500 mg/day
Atenolol
100 mg/day
Buproprion
Propranolol
80 mg-240 mg/day
Fenoprofen
1,800 mg/day
Diltiazem
Not established
Comipramine
Not established
Timolol
20 mg-30 mg/day
Flurbiprofen
200 mg/day
Doxepin
Not established
Clonazepam
Not established
Fluoxetine
20 mg every
other day to
40 mg/day
Fluvoxamine
Not established
Indomethacin
Not established
Gabapentin
900 mg2,400 mg/day
Ibuprofen
Not established
Lamotrigine
Not established
Not established
Drug
Efficacious Doses
in Clinical Trials
Group V||
Drug
Efficacious Doses
in Clinical Trials
Not established Methysergide
Not established
6 mg/day
Drug
Efficacious Doses
in Clinical Trials
Acebutolol
Not established
Carbamazepine Not established
Guanfacine
1 mg/day
Imipramine
Not established
Nabumetone
Ketoprofen
150 mg/day
Mirtazepine
Not established
Nicardipine
Not established
400 mg-600 mg/day Nortriptyline
Not established
Nifedipine
Not established
Pindolol
Not established
Magnesium
Mefanamic acid
1,500 mg/day
Paroxetine
Not established
Metoprolol
200 mg/day
Protriptyline
Not established
Nadolol
80 mg-240 mg/day
Sertraline
Not established
Naproxen sodium
1,100 mg/day
Tiagabine
Not established
Nimodipine
120 mg/day
Topiramate
Not established
Tolfenamic
acid
300 mg/day
Trazadone
Not established
Venlafaxine
Not established
Verapamil
240 mg/day
Vitamin B2
400 mg/day
Methylergonovine Not established
Phenelzine
Not established
* Group I = Medium to high efficacy, good strength of evidence, and a range of severity (mild to moderate) and frequency (infrequent to frequent) of side effects.
† Group II = Lower efficacy than those listed in the first column, or limited strength of evidence, and mild to moderate side effects.
‡ Group III = Clinically efficacious based on consensus and clinical experience, but no scientific evidence of efficacy.
§ Group IV = Medium to high efficacy, good strength of evidence, but with side concerns.
|| Group V = Evidence indicating no efficacy over placebo
¶ Does not include combination products.
Adapted from Limroth V, Michel MC. The prevention of migraine: a critical review with special emphasis on beta adrenoreceptor blockers. Br J Clin Pharmacol. 2001;52(3):237-43;
Adelman JU, Adelman RD. Current options for the prevention and treatment of migraine. Clin Ther. 2001;23(6):772-88; and Evidence-based Guidelines for Migraine Headache in the
Primary Care Setting. Guidelines on Migraine Headache Prophylaxis: Pharmacological Management for the Prevention of Migraine ( available at:
http://www.aan.com/professionals/practice/pdfs/gl0090.pdf; accessed September 9, 2003).
be a key contributor to the use of gabapentin in excess of its scientifically proven value. One additional factor is the perceived
need for treatment options among clinicians dissatisfied with
currently available therapies. The financial success of
gabapentin could be at least partially attributable to the placebo
effect since the majority of the off-label conditions are associated with an underlying psychological component.
ACKNOWLEDGMENTS
The author would first like to acknowledge Robert Mack for his patience and
encouragement throughout the process of developing and writing this manuscript. The author would also like to acknowledge the following individuals at
Three Rivers Administrative Services, LLC: Warren Carmichael, CEO, for the
opportunity to be a part of this organization and pursue this project; Robert
Baker, MD, MMM, FAAP, senior medical director, for thoughtful comments
that made a valuable contribution to this manuscript; Jessica Neely, PharmD,
clinical pharmacist; and Jim Hancovsky, RPh, MSIA, pharmacy director, for
helpful review of an earlier version of this manuscript.
DISCLAIMER
Since various disease states are discussed in this review, it is essential to note
that the references to treatment guidelines and algorithms are summary in
nature and are in no way intended to replace the various expert consensus
and more thorough reviews on the various subjects.
566 Journal of Managed Care Pharmacy
JMCP
November/December 2003
DISCLOSURES
No outside funding supported this study. The author discloses that she has no
financial affiliation with or interest in any company, product, or service that is
discussed in this article.
Vol. 9, No. 6
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Examination of the Evidence for Off-Label Use of Gabapentin
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bipolar spectrum: an open case series. J Affect Disord. 2001;65(2):167-71.
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10. Altshuler LL, Keck PE, McElroy SL, et al. Gabapentin in the acute treatment of refractory bipolar disorder. Bipolar Disord. 1999;1(1)61-65.
11. Sokolski KN, Green C, Maris DE, et al. Gabapentin as an adjunct to standard mood stabilizers in outpatients with mixed bipolar symptomatology.
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12. Young LT, Robb JC, Hasey GM, et al. Gabapentin as an adjunctive treatment in bipolar disorder. J Affect Disord. 1999;55(1):73-77.
13. Hatzimanolis J, Lykouras L, Oulis P, et al. Gabapentin as monotherapy in
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14. Erfurth A, Kammerer C, Grunze H, et al. An open label study of gabapentin
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15. Soutullo CA, Casuto LS, Keck PE. Gabapentin in the treatment of adolescent mania: a case report. J Child Adolesc Psychopharmacol. 1998;8(1):81-85.
16. Frye MA, Ketter TA, Kimbreel, TA, et al. A placebo-controlled study of
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17. Pande AC, Crockatt JG, Janny CA, Werth JL, Tsaroucha G. Placebo-controlled study of gabapentin treatment of panic disorder. J Clin Psychopharm.
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18. Macdonald KJ, Young LT. Newer antiepileptic drugs in bipolar disorder:
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21. Letterman L, Markowitz JS. Gabapentin: a review of published experience
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22. Dennehy EB, Suppes T. Medication algorithms for bipolar disorder.
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23. Frye MA, Ketter TA, Kimbreel TA, et al. A placebo-controlled study of
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24. Surges R, Fursten TJ. Mode of action of gabapentin in chronic neuropathic
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25. Rose MA, Kon PC. Gabapentin pharmacology and its use in pain management. Anaesthesia. 2002;57(5):451-62.
26. Dougherty JA, Rhone DH. Gabapentin, a unique antiepileptic agent.
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27. Serpell MG. Gabapentin in neuropathic pain syndromes: a randomized,
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28. Rose MA, Kam PC. Gabapentin: pharmacology and its use in pain management. Anesthesia. 2002;57(5):451-62.
29. Mellegers MA, Furlan AD, Mailis A. Gabapentin for neuropathic pain:
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30. Brasseur AN, Parker F, Chauvin M, et al. Effects of gabapentin on the different components of peripheral and central neuropathic pain syndromes:
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31. Rosenberg JM, Harrell C, Ristic H, et al. The effect of gabapentin on neuropathic pain. Clin J Pain. 1997;13(3):251-55.
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33. Rowbotham M, Harden N, Stacey B, Bernstein P, Magnus ML. Gabapentin
for the treatment of postherpetic neuralgia. A randomized controlled trial.
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34. Morello CM, Leckband SG, Stoner CP, et al. Randomized double-blind
study comparing the efficacy of gabapentin with amitriptyline on diabetic
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36. Wheeler DS, Vaux KK, Tam DA. Use of gabapentin in the treatment of
childhood reflex sympathetic dystrophy. Pediatr Neurol. 2000;22(3):2201-11.
37. Mellick GA, Mellick LB. Reflex sympathetic dystrophy treated with
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38. Mellick GA, Mellick LB. Gabapentin in the management of reflex sympathetic dystrophy. J Pain Symptom Manage. 1995;10(4):265-66.
39. Engstrom J, Martin JB. Disorders of the Autonomic Nervous System. In:
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40. Mellick LB, Mellick GA. Successful treatment of reflex sympathetic dystrophy with gabapentin. Am J Emerg Med. 1995;13(1):96.
41. Hamrin V, Bailey K. Gabapentin and methylphenidate treatment of a
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42. Lee DO, Steingard RJ, Cesena M, et al. Behavioral side effects of
gabapentin in children. Epilepsia. 1996;37(1):87-90.
43. Garcia-Borreguero D, Larrosa O, de la Llave Y. Treatment of restless legs
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44. Jellinik MS. Mirror-mirror on the wall. Are we prescribing the right psychotropic medications to the right children using the right treatment plan?
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Examination of the Evidence for Off-Label Use of Gabapentin
47. Stein MT, Perrin JM. Diagnosis and treatment of ADHD in school-age children in primary care settings: a synopsis of the AAP Practice Guidelines.
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48. Adler CH. Treatment of restless legs syndrome with gabapentin. Clin
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in migraine therapy. Cephalgia. 2000;20(6):533-37.
49. Mellick GA, Mellick LB. Management of restless legs syndrome with
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50. Chesson AL, Wise M, Davila D, et al. Practice parameters for the treatment
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63. Bozikas V, Petrikis P, Gamvrula K, et al. Treatment of alcohol withdrawal
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52. Khan OA. Gabapentin relieves trigeminal neuralgia in multiple sclerosis
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64. Chatterjee CR, Ringold AL. A case report of reduction in alcohol craving
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53. Sist T, Filadora V, Miner M, et al. Gabapentin for idiopathic trigeminal
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65. Bonnet U, Banger M, Leweke FM, et al. Treatment of alcohol withdrawal
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54. Joffroy A, Levivier M, Massager N. Trigeminal neuralgia. Pathophysiology
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SUGGESTED READING
57. Adelman JU, Adelman LC, Von Seggern R. Cost-effectiveness of antiepileptic drugs in migraine prophylaxis. Headache. 2002;42(10):978-83.
1. Diamond S, Wenzel R. Practical approaches to migraine management. CNS
Drugs. 2002;16(6):385-403.
58. Mathew NT. Antiepileptic drugs in migraine prevention. Headache.
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2002;15(5):595-603.
59. Mathew NT, Rapoport A, Saper J, et al. Efficacy of gabapentin in migraine
prophylaxis. Headache. 2001;41(2):119-28.
3. Louis ED. Clinical practice. Essential tremor. N Engl J Med.
2001;345(12)887-91.
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Vol. 9, No. 6
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Article Index by Subject Category
JMCP – July/August 1995 through November/December 2003
Adherence, Compliance, and Persistence
• Hypertension, prescription drug copayments and drug therapy
adherence. 2003;9(5):454-56.
• Patient adherence with amlodipine, lisinopril, or valsartan therapy in a usual-care setting. 2003;9(5):424-29.
• Measuring adherence and persistence in drug therapy. 2002;
8(3):204-46.
• Patient adherence with HMG reductase inhibitor therapy
among users of two types of prescription services. 2002;
8(3):186-91.
• Adherence, compliance, and persistence in drug therapy. 2002;
8(3):177-78.
• A team approach to address antiretroviral therapy adherence
barriers in a managed care organization. 2001;7(3):214-18.
• The Michigan pharmacists association patient persistency project. 2001;7(1):50-55.
• Evaluating medication adherence: which measure is right for
your program? 2000;6(6):499-504.
• Unclaimed prescriptions requisitioned through provider order
entry. 1999;5(6):498-502.
• Predicting adherence to prescription medication purchase
among HMO enrollees with diabetes. 1999;5(4):336-41.
• Analyzing variations in medication compliance related to individual drug, drug class, and prescribing physician. 1999;
5(1):47-51.
• A study on the characteristics of prescription transmittal
processes and the effect of a patient prescription reminder system on patient compliance. 1998;4(2):174-78.
• “Abandoned prescriptions”: a quantitative assessment of their
cause. 1995;1(6):193-99.
Adverse Drug Events
• Preventable drug-related morbidity (PDRM). 2003;9(2):178.
• Indicators of preventable drug-related morbidity in older adults.
2. Use within a managed care organization. 2003;9(2):134-41.
• Medical errors, adverse medical events, and PDRM. 2002;
8(5):400.
• Preventable drug-related morbidity indicators in the U.S. and
U.K. 2002;8(5):372-77.
• Preventable drug-related morbidity in older adults. 1. Indicator
development. 2002;8(5):365-71.
• Evaluation of resources used to treat adverse events of selective
serotonin reuptake inhibitor use. 2001;7(5):402-06.
• Adverse drug events: a plea for reporting and new rules to ease
the burden. 1998;4(4):364.
Behavioral Health
• Issues and trends in behavioral health and managed care.
2000;6(1):11, 12, 15-16.
Biotechnology
• Biotechnology and managed care. 2000;6(5):410-14.
• Biotechnology as a pharmacy specialty. 1998;4(5):465, 468-70.
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November/December 2003
Capitation and Risk-Financing Methods
• Contractual arrangements between HMOs and medical groups
to manage drug costs (editorial). 2003;9(6):572.
• Financial risk relationships and adoption of management strategies in physician groups for self-administered injectable drugs.
2003;9(6):523-33.
• Demographics and the cost of pharmaceuticals in a private
third-party prescription program. 2000;6(5):395-402, 407-09.
• Challenges to methods used in studying capitation reimbursement (letter). 2000;6(1):8.
• The impact of pharmaceutical capitation to primary medical
groups on the health care expenditures of Medicare HMO
enrollees. 1999;5(5):414-19.
• Managing pharmacy risk in physician groups. 1999;5(5):38284.
Clinical Pharmacy Interventions—
Quality, Service, and Cost Outcomes
• Assessment of clinical pharmacist management of lipid-lowering therapy in a primary care setting. 2003;9(3):269-73.
• A pharmacist-based screening program of octogenarians starting
new medications. 2003;9(1):13-18.
• Crossing the quality chasm—pharmacist prescribing, nontraditional interventions, and outcomes-based pharmacist reimbursement (OBPR). 2002;8(5):403-04.
• Determining the value of pharmacy services—the search for rigorous research designs. 2002;8(2):152-53.
• Quality and cost outcomes of clinical pharmacist interventions
in a capitated senior drug benefit plan. 2002;8(2):124-31.
• Community pharmacists and diabetes health care.
2002;8(1):56-57.
• Factors affecting pharmacist consultation services in a university health insurance plan. 2002;8(1):55-56.
• Effects of a community pharmacist-based diabetes patient-management program on intermediate clinical outcome measures.
2002;8(1):48-53.
• Collaborating with community pharmacists to improve the
quality of diabetes care in an IPA-model HMO. 2001;7(4):29296.
• Implementation and evaluation of a pharmacist-managed diabetes service. 2000;6(6):488-93.
• Impact of a diabetes disease management clinic on the total glycosylated hemoglobin of patients with type 2 diabetes mellitus.
1999;5(6):511-15.
• Using patient expectations and satisfaction data to design a new
pharmacy service model in a primary care clinic. 1997;3(5):
531-40.
• AIDS enters new era with pharmacists on the front lines.
1997;3(4):391-92, 395-96.
• Outcomes management: the why, what, and how of data collection. 1997;3(3):345-51.
Vol. 9, No. 6
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Article Index
Clinical Pharmacy—Patient Consultation
• Factors affecting pharmacist consultation services in a university health insurance plan. 2002;8(1):32-40.
• Providing patient-focused care within a managed care and pharmaceutical care environment: a person/situation interactionist
model for community practitioners. 2000;6(3):233-39.
• Counseling: where does the profession stand? 1998;4(1):78.
Clinical Pharmacy—Payment for Services
• Disease management, pay-for-performance and clinical pharmacist interventions in diabetes care (editorial). 2003;9(6): 574.
• Outcomes-based pharmacist reimbursement: reimbursing pharmacists for cognitive services. 2002;8(5):383-91.
• Reimbursement for pharmacy cognitive services: pharmacists’
assessment. 1999;5(5):420-424.
• Cost-benefit analysis of pharmaceutical care in a Medicaid population—from a budgetary perspective. 1998;4(3):303-08.
• Reimbursement for pharmacy cognitive services: insurance
company assessment. 1997;3(1):46-48, 50-51.
• Mississippi Medicaid waiver breaks new ground for pharmacists. 1996;2(6):564, 566.
• Community-based pharmacy: partnering with managed care to
provide value-added services. 1996;2(5):483, 487-88.
Clinical Pharmacy Quality Improvement—
Patient Safety and Prevention of ADEs
• Preventing medication errors and adverse drug events. 2003;
9(1):92-93.
• The role of managed care pharmacy in reducing medication
errors. 2003;9(1):62-65.
• Quality improvement, risk management, and patient education:
tools to reduce medication error. 2001;7(2):156-63.
• Adverse drug reaction tracking and management in an integrated health care system. 1997;3(6):644-47, 650.
Clinical Practice Guidelines (CPGs) and Quality Improvement
• Consensus panel, national guidelines, and other potentially misleading terms (editorial). 2003;9(6):575.
• Evidence-based medicine, practice guidelines, and disease management (editorial). 2003;9(6):573.
• Crossing the quality chasm—incremental change through clinical practice guidelines (CPGs) (editorial ). 2002;8(5):400-01.
• Actual prescribing versus guidelines. 2002;8(4):297-98.
• Relationship of clinical factors to the use of COX-2 selective
NSAIDs within an arthritis population in a large HMO.
2002;8(4):252-58.
• An assessment of the effectiveness of a nonsteroidal anti-inflammatory drugs algorithm in an integrated health care system.
2001;7(2):149-55.
Clinical Quality Improvement
• A prescription for change: bridges to cross the “quality chasm.”
2001;7(4):309-14.
• Designing a framework for pharmacy practice: a look at consumer reactions and expectations. 2001;7(3):193-200.
• The case for pharmacy report cards. 1999;5(3):176, 179-80,
182.
• Response-oriented patient evaluation survey (ROPES): an
administrator’s tool for identifying opportunities for service
quality improvement. 1998;4(3):311-20.
• Managing drug therapy decisions: pay me now or pay me later.
1998;4(3):242, 245.
• Performance reporting for managed care prescription programs.
1998;4(2):160-66.
• Do we measure up in reducing morbidity and mortality?
1997;3(6):651-52, 654-55, 658.
• Medical outcomes: creating new opportunities for pharmacy.
1997;3(3):289-92.
• Documenting indicators of pharmaceutical care in rural community pharmacies. 1996;2(6):659-66.
• Pharmaceutical care: needed now more than ever. 1995;1(1):
21-22, 25.
Collaboration—Pharmacists and Others
• Rear window: actuaries and pharmacists—toward a new competency. 2001;7(3):233-37.
• Physician attitudes toward pharmacist-run anticoagulation clinics in Department of Defense Health Services Region 5.
1998;4(4):413-19.
• Physician groups embrace pharmacists: collaborations that
work. 1997;3(5):526-28, 530.
• Blood pressure outcomes in a pharmacist-and-nurse managed
hypertension clinic: a team approach. 1997;3(3):307-12.
• Pharmacy practice in the long-term care environment.
1997;3(2):189-94.
Collaboration—Pharmacy Education
• A unique partnership: the Arkansas College of Pharmacy and
the Arkansas PRO. 2002;8(1):12,14.
• Oregon State University partners with Medicaid and a managed
care organization. 2001;7(3):185-86.
• The University of Colorado School of Pharmacy and the
University of Colorado Health Plan forge a PBM partnership.
1998;4(5):478, 480.
• Rutgers opens door to managed care. 1997;3(6):717-18.
Collaborative Practice—Pharmacists as Prescribers
• Collaborative pharmacy practice: an idea whose time has come.
1999;5(6):487-88, 491.
Database Analyses of Drug Utilization
(see also Research Methods)
• Oral isotretinoin: an analysis of its utilization in a managed care
organization. 2002;8(4):272-77.
• Claims data and drawing appropriate conclusions. 2002;8(2):
152.
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Article Index
• Cost and utilization patterns of fentanyl transdermal system and
oxycodone hydrochloride controlled-release in a California
Medicaid population. 2002;8(2):132-40.
• Administrative databases and outcomes assessment: an
overview of issues and potential utility. 1999;5(3):215-22.
• Basics of managed care claims processing: from claims payment
to outcomes management. 1995;1(6):200-05.
Decision Support Systems (DSS)
• Understanding decision support systems. 2002;8(2):96-101.
Direct-to-Consumer Advertising (DTCA)
(see also Drug Promotion and Advertising)
• Direct-to-patient advertising (DTPA) and direct-to-consumer
advertising (DTCA) of prescription drugs. 2002;8(6):521.
• Promotion of prescription drugs to consumers: case study
results. 2002;8(6):512-18.
• Responding to direct-to-consumer advertising. 2000;6(3):20102.
• Direct-to-consumer advertising provides challenge to managed
care. 1999;5(2):101-03, 106.
• The patient as a partner in prescribing: direct-to-consumer
advertising. 1998;4(1):15-16, 18-19.
Disease Management—ALS (Amyotrophic Lateral Sclerosis)
• Treatment of patients with ALS: implications for the managed
care pharmacist. 1996;2(6):599-604.
Disease Management—Angina, CHD, and CHF
• Congestive heart failure: a disease management approach in
long-term care patients. 1999;5(6):516-20.
• Direct medical costs of unstable angina pectoris in a defined
population. 1999;5(1):39-44.
• Managing congestive heart failure in a Medicare risk population.1999;5(1):14-16.
• Changing practices in home inodilator infusion therapy for
advanced congestive heart failure. 1998;4(1):73-77.
Disease Management—Arthritis and Joint Pain
• Cost-effective use of COX-2 drugs and NSAIDs. 2002;8(4):29596.
• Relationship of clinical factors to the use of COX-2 selective
NSAIDs within an arthritis population in a large HMO. 2002;
8(4):252-58.
• Economic considerations in the management of arthritis.
1999;5(6):476-78, 481-82, 484.
• New options in the treatment of arthritis. 1999;5(5):443-48.
• Pharmacoeconomics of NSAIDs: beyond bleeds. 1997;3(4):
425-30.
Disease Management—Asthma or Allergic Rhinitis
• Unmet needs in the treatment of allergic asthma: potential role
of novel biologic therapies. 2003;9(6):534-43.
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November/December 2003
• Exploring new frontiers in asthma management for optimal
therapeutic and economic outcomes. 2003;9(5):S1-S25.
• Optimizing clinical and economic outcomes in asthma management: individualizing drug therapy to address dual components
of asthma. 2002;8(5):S1-S25.
• Impacts of a PBM-based disease management program on asthma medication use. 2001;7(6):460-67.
• Costs and utilization patterns associated with persistent asthma:
a comparison of Texas Medicaid patients with and without continuous inhaled corticosteroid treatment. 2001;7(6):452-59.
• Evaluating asthma medication use before and after an acute
asthma-related event. 2001;7(4):303-08.
• An investigation of allergic rhinitis, asthma, and medication use
in a privately insured population. 2001;7(4):287-91.
• A claims data analysis of patient acquisition of drug therapies for
the treatment of asthma. 1999;5(4):342-46.
• Evaluating health-related quality of life in three disease management areas: asthma, diabetes, and hypertension. 1996;2(4):40813.
• Asthma disease management: integration of DUR, case management, and performance indicators. 1996;2(1):59.
Disease Management—Atopic Dermatitis
• Prevalence and costs of atopic dermatitis. 2002;8(5):404.
• The effect of atopic dermatitis on total burden of illness and
quality of life on adults and children in a large managed care
organization. 2002;8(5):333-42.
Disease Management—Attention Deficit
Hyperactivity Disorder (ADHD)
• Physician perceptions of the use of medications for attention
deficit hyperactivity disorder. 2003;9(5):416-23.
Disease Management—Cancer
• Oncology drugs and managed care. 1998;4(4):374-75, 378,
380.
Disease Management—Deep Vein Thrombosis
• Outpatient treatment of uncomplicated deep vein thrombosis:
an overview of program development. 1997;3(2):170, 173-74.
Disease Management—Depression
• Depression in managed care: costs of selective serotonin reuptake inhibitors. 2001;7(2):142-48.
• Documentation of indicators for antidepressant treatment and
response in an HMO primary care population. 2000;6(6):49498.
• Utilization patterns of antidepressant medications in a patient
population served by a primary care medical group. 1999;
5(3):243-49.
• SSRI-to-SSRI switching and associated dosing characteristics.
1999;5(2):138-43.
• The treatment of depression with newer antidepressants: pharVol. 9, No. 6
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Article Index
macology and efficacy versus clinical effectiveness. 1999;5(1):
57-62.
Disease Management—Diabetes
(see also Clinical Pharmacy Interventions)
• Longitudinal assessment of a diabetes care management system
in an integrated health network. 2003;9(6):552-58.
• Analysis of cost and utilization of health care services before and
after initiation of insulin therapy in patients with type 2 diabetes
mellitus. 2003;9(4):309-16.
• Real-world research in diabetes care and protocols for patient
privacy. 2003;9(3):275-76.
• Misadventures in insulin therapy: are your members at risk?
2003;9(3):S1-S13.
• Evaluating medication use for continuous quality improvement
in diabetes care. 2002;8(5):378-82.
• Importance of blood glucose monitoring to achieve short- and
long-term glycemic control. 1999;5(6):543-47.
• The cost of managing diabetes mellitus: focus on the oral pharmacologic management of type 2 diabetes. 1999;5(2):113-20.
• Use of glycosylated hemoglobin testing among patients with
diabetes mellitus. 1997;3(6):691-96.
• Diabetic nephropathy prevention and the role of managed care
pharmacists. 1997;3(6):682-87.
• Evaluating health-related quality of life in three disease management areas: asthma, diabetes, and hypertension. 1996;2(4):40813.
• Saving vision: an intervention for HMOs. 1996;2(2):178,180.
Disease Management—Heartburn
• Pharmacoeconomics—Determination of the cost-effectiveness of
Helicobacter pylori eradication. 2003;9(5):461-52.
• Validation of a single-patient drug trial methodology for personalized management of gastroesophageal reflux disease.
2002;8(6):459-68.
• Cost-benefit computer modeling of Helicobacter pylori testing
and treatment in patients on long-term H2-blocker prophylaxis. 2000;6(5):383-89.
• Gastroesophageal reflux disease in a managed care setting:
charges by place and type of service. 1998;4(3):336-43.
• Defining strategies for peptic ulcer treatment: a Helicobacter
pylori economic-cost model. 1998;4(2):205-20.
• Gastroesophageal reflux disease in a managed care setting: professional, facility, and pharmacy charges. 1998;4(1):64-70.
• Peptic acid disorders: developing a disease management program. 1996;2(5):569-75.
• AMCP’s annual meeting: controversies surrounding Helicobacter
pylori. 1996;2(4):377-79.
• Economic implications of self-treatment of heartburn/nonulcer
dyspepsia with nonprescription famotidine in a managed care
setting. 1996;2(3):263-71.
Disease Management—Hypercholesterolemia
• Optimizing dyslipidemia outcomes: a novel pharmacotherapy
pathway. 2003;9(1):S1-S28.
• Effective cholesterol management with fewer dollars. 2002;
8(6):519.
• High blood cholesterol and ATPIII: guidelines for health benefit
and health care providers. 2001;7(6):482-89.
• Comparative cost-effectiveness of fluvastatin and lovastatin in
patients with hypercholesterolemia. 2000;6(3):241-46.
• A comparison of hypercholesterolemia management in the secondary prevention of coronary heart disease by payor types: feefor-service, Medicare, and managed care organizations.
1998;4(5):483-87.
• The cost-effectiveness impact of a preferred agent HMG-CoA
reductase inhibitor policy in a managed care population. 1997;
3(5):548-53.
• Comparative cost-effectiveness of bile acid sequestering resins,
HMG Co-A reductase inhibitors, and their combination in
patients with hypercholesterolemia. 1995;1(6):188-92.
Disease Management—Hypertension
• Antihypertensive drug effects on renal function and myocardial
infarction and implications of the ALLHAT study results.
2003;9(1):93-95.
• Impact of the ALLHAT study results on managed care. 2003;
9(1):84-86.
• Risk of myocardial infarction with combination antihypertensive regimens including a dihydropyridine calcium channel
blocker in hypertensive diabetics. 2003;9(1):29-35.
• Evaluation of initial drug selection for newly medicated hypertensives at the Westinghouse Electric Corporation. 1999;
5(6):505-09.
• The clinical and economic implications of drug utilization patterns in the treatment of hypertension with ACE inhibitors and
calcium channel blockers in a managed care setting. 1998;
4(2):194-202.
• Trends in the treatment of hypertension within managed care
organizations: a national survey of HMO pharmacy directors.
1997;3(3): 317-22.
• Evaluating health-related quality of life in three disease management areas: asthma, diabetes, and hypertension. 1996;2(4):40813.
Disease Management—Multiple Sclerosis
• Paying for value in the management of multiple sclerosis. 2002;
8(6):520.
Disease Management—Obesity
• The efficacy and safety of anorexiant medication in the treatment of obesity: implications for managed care formularies.
1998;4(4):422-28.
• A cost-effective analysis of appetite suppressants for obesity
treatment in a managed care organization. 1998;4(3):293-300.
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Disease Management—Osteoporosis
• ERT, HRT, raloxifene, calcitonin, or bisphosphonates for osteoporosis. 2003;9(2):178-181.
• The cost of treating osteoporosis in a managed health care
organization. 2003;9(2):142-49.
• Prevention and treatment of osteoporosis in managed care settings. 2002;8(1):58-65.
• Alendronate use among 812 women: prevalence of gastrointestinal complaints, noncompliance with patient instructions,
and discontinuation. 1998;4(5):488-92.
Disease Management—Otitis Media and Infectious Disease
• The economic impact of acute exacerbations of chronic bronchitis in the United states and Canada: a literature review.
2003;9(4):353-59.
• Early switch and early discharge opportunities in intravenous
vancomycin treatment of suspected methicillin-resistant staphylococcal species infections. 2003;9(4):317-26.
• Evaluation of a rule-based program to describe antibiotic utilization for otitis media among three medical plans.
1999;5(3):232-40.
• Medication outcomes assessment of community-acquired infections. 1999;5(2):122-26.
• Fluoroquinolone-use evaluation by acute cystitis. 1996;
2(5):564-68.
Disease Management—Seizure Disorders
• The cost of treating seizure patients in a managed care organization. 1999;5(4):351-56.
Disease Pathology
• Influenza: a practical review. 2000;6(3):247-48.
Dose Optimization
• Dose-optimization intervention yields significant drug cost savings. 2002;8(2):146-51.
• Dose optimization: an opportunity for pharmacy administrative
services. 2002;8(2):81.
Drug Benefit Management—Benchmarks and Measures
• Finding the truth about health care cost drivers—price versus
utilization factors. 2003;9(3):274-75.
• Searching for drug benefit benchmarks—cost per day of therapy. 2002;8(1):54-55.
• The use of economic models in managed care pharmacy decisions. 1998;4(1):42-50.
Drug Benefit Management—Efficiency and Patient Safety
• Weight uniformity of split tablets required by a Veterans Affairs
policy. 2003;9(5):401-07.
• Mail-order prescriptions requiring clarification contact with the
prescriber: prevalence, reasons, and implications. 2003;
9(4):346-52.
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• Tablet splitting to improve the value-for-money equation in
cholesterol management. 2002;8(6):519.
• Effects of a tablet-splitting program in patients taking HMGCoA reductase inhibitors: analysis of clinical effects, patient satisfaction, compliance, and cost avoidance. 2002;8(6):453-58.
• A model to estimate drug plan cost savings from a trial prescription program. 2001;7(5):391-401.
• A model for comparing unnecessary costs associated with various prescription fill-quantity policies: illustration using VA data.
2001;7(5):386-90.
• The impact of a telephone care pharmacy program on health
care resource utilization. 2000;6(3):217-21.
• Pharmacy cost reduction imperative at United HealthCare.
1999;5(1):19-20.
• The evolution of best-in-class pharmacy management techniques. 1998;4(4):366-67, 370, 372-73.
• Practice guidelines, physician groups, and drug formularies.
1997;3(5):489-92.
• Maximizing generic substitution in managed care. 1996;
(2)6:557-60, 562-63.
• Pharmacy benefit administration options. 1996;2(3):272-78.
Drug Benefit Management—Employee Benefits and Coverage
• Pressure on pharmacy benefit managers for disclosure and
demonstration of value—rebates and drug benefit cost savings
(editorial). 2003;9(4):369-71.
• New generic and OTC drugs provide opportunities for drug
benefit managers. 2002;8(6):520.
• Analysis of the movement of prescription drugs to over-thecounter status. 2002;8(6):499-508.
• Employee benefits consulting: an essential role for pharmacy.
2001;7(4):268-71.
• Employer-sponsored health care services. 2001;7(3):189-92.
• Pharmacy benefit managers and unique customer segments:
large employers. 2000;6(5):342-44, 346.
• The history, philosophy, and principles of pharmacy benefits.
1999;5(6):525-31.
• Quality-of-life drugs: framing the issue. 1999;5(3):185, 189-90.
• Successful disease management programs for health and welfare
fund union groups. 1998;4(3):269-70, 272.
• Carve outs and pharmacy: fashion or fad? 1996;2(4):352, 35455, 359.
Drug Benefit Management—Patient Satisfaction,
Benefit Knowledge, and Consumer Behavior
• Unraveling the effects of tier-copayment drug benefit designs.
2003;9(2):177-78.
• Effects of a 3-tier pharmacy benefit design on the prescription
purchasing behavior of individuals with chronic disease. 2003;
9(2):123-33.
• Measuring outcomes of 3-tier copay drug benefit plans. 2002;
8(6):522.
• Impact of multi-tiered pharmacy benefits on attitudes of plan
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members with chronic disease states. 2002;8(6):477-91.
• Consumer preferences for types of cost containment in prescription drug programs. 2002;8(3):192-98
• Drugs, PPOs, tiered cost-share for beneficiaries, and consumer
preferences. 2002;8(3):177.
• Patient satisfaction with and knowledge of their prescription
drug coverage. 2001;7(1):34-42.
• The CIGNA Healthcare quality improvement and patient satisfaction project. 2000;6(4):312-15.
• Development of an interval-level scale to assess consumer satisfaction with prescription drug coverage. 2000;6(3):225-31.
• Drug-management strategies: consumers’ perspectives. 2000;
6(2):122-28.
• A comparison of satisfaction with mail versus traditional pharmacy services. 1997;3(3):327-37.
• Guide to consumers’ pharmaceutical purchasing behavior.
1996;2(5):489-90, 494, 498-99.
Drug Benefit Management—Pharmacy Providers
• Bargaining between community pharmacies and third-party
payers: influences on bargaining outcomes. 2001;7(1):43-49.
• The pharmacy audit: what is it and are you prepared?
1999;5(2): 93-94, 98.
Drug Benefit Management—
Quantity Limits and Prior Authorization (PA)
• The relative value of disease management programs versus drug
manufacturer rebates (editorial). 2003;9(6):573.
• Transparency needed for economic analyses of PA programs
(letter). 2003;9(6):576.
• Clinical, service, and cost outcomes of drug coverage edits and
quantity limits (editorial). 2003;9(4):368-69.
• Evaluation of a monthly coverage maximum (drug specific
quantity limit) on the 5-HT1 agonists (triptans) and dihydroergotamine nasal spray. 2003;9(4):335-45.
• Pharmacoeconomic modeling of prior-authorization intervention for COX-2 specific inhibitors in a 3-tier copay plan.
2003;9(4):327-34.
• Prior authorization to manage drug utilization and costs.
2003;9(1):95.
• Analysis of a prescription drug prior authorization program in a
Medicaid health maintenance organization. 2003;9(1):36-44.
• Managing care via prior-authorization (PA) programs? 2002;
8(4):296.
• A neurologist’s perspective on quantity limits. 2002;8(3):184.
• Triptan quantity limits. 2002;8(3):182-84.
• Medical and pharmacy cost and utilization outcomes of a quantity limit on 5-HT1 agonists (triptans) by a managed care
organization. 2001;7(6):468-75.
• Analysis of the effects of quantity limits. 2001;7(5):338,340.
• Prior-authorization programs: a critical review of the literature.
2001;7(4):297-302.
• Evaluating the operational performance and financial effects of
a drug prior-authorization program. 1997;3(6):699-706.
• Assessment of Medicaid prior-approval policies on prescription
expenditures: market-share analysis of Medicaid and cash prescriptions. 1996;2(6):651-56.
• Effect of a prior-authorization requirement on the use of nonsteroidal anti-inflammatory drugs by Medicaid patients.
1996;2(2):158-63.
Drug Benefit Management Methods—Benefit Design
• Benefit maximums versus drug benefit needs for Medicare beneficiaries. 2002;8(5):402-03.
• Prescription use behavior among Medicare beneficiaries with
capped prescription benefits. 2002;8(5):360-64.
• Effects of Medicare+Choice annual maximum dollar prescription drug benefits. 2002;8(3):178.
• A cost analysis of four benefit strategies for managing a COX-2
inhibitor. 2001;7(3):224-27.
• Three-tier copay systems and consumer-centric care. 2000;
6(5):351-53.
• Medicare-risk pharmacy benefit design: a new cost-effective
approach to pharmacy management. 1997;3(1):103-04, 106.
Drug Promotion and Advertising
(see also Direct-to-Consumer Advertising (DTCA))
• Common industry practices and OIG compliance guidance (letter). 2003;9(4):375.
• Health care communications agencies respond to managed care.
1998;4(1):9-12.
• Information requirements of health systems as drug purchasers:
does the FDA have a role in setting evidentiary standards?
1996;2(6):593-98.
Drug Spending, Utilization, and Cost Trends
• Prescription drug expenditures, financial burden, and health
plan satisfaction among Medicare beneficiaries. 2003;9(5):45354.
• Selected characteristics of senior citizen’s prescription drug payment and procurement in 1998 and 2001. 2003;9(5):408-15.
• Burden of prescription drug costs in the United States.
2003;9(1):91-92.
• Prescription drug use among elderly and nonelderly families.
2003;9(1):19-28.
• Trends in managed care pharmacy: responding to changing
environments. 2002;8(2):102-07.
• Drug costs out of control—check your assumptions.
2002;8(2):81.
• Trends in managed care pharmacy: preparing for the future.
2001;7(2):105-10.
• Too much or too little? The role of pharmaceuticals in the health
care system. 1999;5(4):296-97, 301-02.
• Local area market dynamics. 1998;4(2):115-17, 120.
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Drug Therapy and Therapeutic Selection
• Prescription drugs marketed in the United States should be
approved by the FDA. 2003;9(4):366-67.
• Cost and utilization comparisons among propensity scorematched insulin lispro and regular insulin users. 2003;
9(3):263-68.
• Improvements in glycemic control in type 2 diabetes patients
switched form sulfonylurea coadministered with metformin to
glyburide-metformin tablets. 2003;9(3):256-62.
• Modeling the annual costs of postmenopausal prevention therapy: raloxifene, aledronate, or estrogen-progestin therapy. 2003;
9(2):150-58.
• Pharmacoeconomics and considerations for injectable products:
Focus on colony-stimulating factors. 2003;9(2):S1-S25.
• Clinical and economic impact of glatiramer acetate versus beta
interferon therapy among patients with multiple sclerosis in a
managed care population. 2002;8(6):469-76.
• A pharmacoeconomic model comparing two long-acting treatments for overactive bladder. 2002;8(5):343-52.
• The search for better antipsychotics continues. 2002;8(4):298.
• Atypical antipsychotics and tardive dyskinesia. 2002;8(4):29192.
• Neuroleptic drug exposure and incidence of tardive dyskinesia:
a records-based case-control study. 2002;8(4):259-65.
• Ophthalmic agents and managed care. 2002;8(3):217-223.
• An in-home Synagis program for RSV prevention in high-risk
infants. 2001;7(6):476-81.
• An assessment of emerging patterns of etanercept use in the
treatment of rheumatoid arthritis. 2001;7(1):56-61.
• Using simple and relative difference to interpret changes in
health-related quality-of-life scores for salmeterol, ipratropium,
and placebo. 2000;6(6):483-87.
• Cost analysis of therapeutic interchange of calcium channel
blockers for the treatment of hypertension: unexpected results
from a conversion program. 2000;6(5):390-94.
• Outcomes analyses of the outpatient treatment of venous
thromboembolic disease using the low-molecular-weight
heparin enoxaparin in a managed care organization.
2000;6(4):298-304.
• Assessing the relevance of outcomes data for colony-stimulating
factors. 2000;6(2):144-50.
• Economic assessment of the relationship between disease exacerbations and the cost of multiple sclerosis. 2000;6(1):19-24.
• Calcium channel blockers and angiotensin-converting enzyme
inhibitors for hypertension in a multimarket managed care
organization. 1999;5(6):537-40.
• Criteria for the use of tramadol in adult patients: medication-use
evaluation guidelines. 1999;5(6):492-97.
• Safety and efficacy of a mandatory formulary switch from
nifedipine GITS to amlodipine. 1999;5(3):225-29.
• Evaluation of blood pressure and adverse effects in patients converted from lisinopril to benazepril. 1999;5(1):52-54.
• The NTI debate. 1998;4(3):289-90.
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• Human growth hormone: ethical and economic considerations
of use and misuse. 1997;3(4):448-52.
• Outcomes and cost savings of an ACE inhibitor therapeutic
interchange. 1997;3(2):219-23.
• Physicians’ perspectives of a therapeutic conversion with a staffmodel HMO. 1997;3(1):55-56, 65.
• Retrospective analysis of formulary transition at large metropolitan HMO: nifedipine GITS to felodipine ER. 1996;2(6):642-46.
Drug Therapy—Natural Products
• Managing natural products. 2001;7(5):414-19.
• Top-selling herbal supplements. 1999;5(4):357-66.
Drug Utilization Review (DUR) or Drug
Utilization Management—Appropriate Drug Use
• Use of drugs for off-label indications: living in the same world
(editorial). 2003;9(6):570-71.
• Gabapentin may be appropriate for off-label uses (editorial).
2003;9(6):569-70.
• Examination of the evidence for off-label use of gabapentin.
2003;9(6):559-68.
• Retrospective drug utilization review: incidence of clinically relevant potential drug-drug interactions in a large ambulatory
population. 2003;9(6):513-22.
• Analysis of medication use patterns: apparent overuse of antibiotics and underuse of prescription drugs for asthma, depression, and CHF. 2003;9(3):232-37.
• Gabapentin and indications of appropriate use. 2002;8(4):29394.
• Gabapentin use in a managed Medicaid population. 2002;8(4):
266-71.
• Better data for making better decisions: finger-pointing or useful drug use review (editorial). 2002;8(3):208-10.
• High frequency of itraconazole prescriptions with potentially
interacting medications in a large health care plan.
2002;8(3):199-203.
• DUR messages—better data needed for making better decisions
(editorial). 2002;8(3):178-79.
• Potentially inappropriate medication use in a Medicare managed care population: association with higher costs and utilization. 2001;7(5):407-13.
• A provincial program in Nova Scotia to decrease the use of wet
nebulization respiratory medications. 2000;6(6):457-58, 46061, 464.
• Incidence of anxiolytic/hypnotic therapy and its relationship to
duration of antidepressant therapy in a national managed care
organization. 2000;6(2):138-42.
• Medicaid drug utilization review and managed care: the perspectives and experiences of state program directors.
2000;6(2):131-36.
• Evaluation of online prospective DUR programs in community
pharmacy practice. 2000;6(1):27-32.
• The pharmacist’s assessment of second generation online
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prospective drug utilization review. 1998;4(2):183-191.
Ethics
• A question of ethics. 2001;7(6):436.
• Ethics and the use of drug formularies. 1996;2(2):76, 78, 8182.
Formulary Management—Methods and Effects—
Pharmacoeconomics
• Determinants of the cost-effectiveness of statins. 2003;9(6):
544-51.
• Formulary management methods and pharmacoeconomics.
2003;9(5):452-53.
• Using decision-analytic models wisely. 2003;9(5):449-50.
• Do decision-analytic models identify cost-effective treatments?
A retrospective look at Helicobacter pylori eradication. 2003;
9(5):430-40.
• Shortcomings in pharmacy benefit forecasting—interferon beta
products. And author response (letters). 2003;9(4):373-74.
• Alternate financial incentives in multi-tiered formulary systems
to improve accountability for outcomes. 2003;9(4):360-65.
• Pharmacy benefit forecast for a new interferon beta-1a for the
treatment of multiple sclerosis: development of a first-line decision tool for pharmacy-budget planning using administrative
claims data. 2003;9(2):168-74.
• Industry’s perception of presenting pharmacoeconomic models
to managed care organizations. 2003;9(2):159-67.
• Quality of Health Economic Studies (QHES—tool or mask?
2003;9(1):93.
• Summary quality scores for pharmacoeconomic studies: balancing validity with need. 2003;9(1):87-88.
• Assessing the value of the Quality of Health Economic Studies
(QHES). 2003;9(1):86-87.
• Examining the value and quality of health economic analyses:
implications of utilizing the QHES. 2003;9(1):53-61.
• Meta-analysis of oral triptan therapy for migraine: number
needed to treat and relative cost to achieve relief within 2 hours.
2003;9(1):45-52.
• Economic evaluation of citalopram use and expenditures
among recipients in the Texas Medicaid program. 2002;
8(6):494-500.
• Exploring the methodological challenges of investigating comparison groups with different underlying characteristics: a case
study. 2002;8(5):353-59.
• AMCP guidance for submission of clinical and economic evaluation data to support formulary listing in U.S. health plans and
pharmacy benefits management organizations. 2001;7(4):27282.
• The effect of a closed formulary in the face of real-life enrollment
and disenrollment patterns. 2000;6(4):293-97.
• The pros and cons of formularies. 2000;6(3):203-07.
• The role of pharmacoeconomic information in the formulary
decision-making process. 2000;6(2):108, 113-14, 117-18, 121.
• The impact of a therapeutic interchange program in a managed
care organization. 1999;5(5):438-41.
• Outcome analysis of a formulary transition from nifedipine to
felodipine at a Veterans Affairs Medical Center. 1999;5(5):42528.
• Managed care formularies in the United States.1999;5(4):28992,295.
• Formulary management by an on-site school of pharmacy faculty member in a Medicaid managed care organization.
1998;4(4):407-10.
• Innovative drug formulary management through computerassisted protocols. 1998;4(3):246-47,251-52.
• Applications of pharmacoeconomics for managed care pharmacy. 1997;3(6):720-26.
• DOD’s Pharmacoeconomic Center: translating research into
good patient care practices. 1997;3(6):662-64, 666.
• Managing the pharmacy benefit: the formulary system.
1997;3(5):565-73.
• Drug formularies: real opportunities to improve MCO efficiency. 1997;3(3):254, 375-76.
• Pharmacoeconomic analysis of hormone replacement therapy—implications for managed care. 1997;3(2):200-09.
• Pharmacoeconomic evaluations: guidelines for drug purchasers.
1996;2(6):671-77.
• A predictive cost analysis model for estimating formulary
impact of new products in managed care. 1996;2(6):585-90.
• Using outcomes as a tool to evaluate formulary selection decisions: hypercholesterolemia as a case example. 1996;2(4):396404.
• Development of a community-based formulary comparison
instrument. 1995;1(6):211.
Formulary Management—P & T Committees
• The pharmacy and therapeutics committee competition goes
national: building toward Tampa and beyond. 2001;7(6):44851.
• Pharmacy & therapeutics committees: a mock meeting at
AMCP. 1996;2(4):380,383-84.
Health Care Delivery
• A managed care stakeholder assessment of preventive medicine:
Practical applications, measurable results, evaluating success.
2002;8(4):S1-S13.
• Pharmacy: looking back to see the future. 1998;4(5):454-55,
459-60, 462.
• International markets offer new opportunities for MCOs and
PBMs. 1997;3(4):403-04, 409-10.
• Integration takes managed care in different directions: horizontal, vertical, and beyond. 1997;3(3):260, 263-64.
• Looking back: failed health care reform put managed care on
the map. 1997;3(2):159, 160, 163.
• Alternative medicine in managed care pharmacy. 1997;3(1):7780, 83-86.
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• Indian Health Service: paving the way for pharmaceutical care.
1997;3(1):36,41-43.
• While health care evolves, antitrust law endures. 1996;
2(6):679-86.
• Managed care cautiously embraces complementary medicine.
1996;2(6):626, 631-33.
• Rocky Mountain HMO. 1996;2(5):500, 502-04, 07.
• Veterans Affairs Health System: embracing new challenges, new
changes. 1996;2(2):111-12, 117-18.
Health Care Quality Improvement
• Information technology to cross the quality chasm. 2002;
8(5):401-02.
• Quality improvement opportunities in health care—making it
easy to do it right. 2002;8(5):394-99.
• Quality measures: looking in all the wrong places. 2001;
7(2):88.
• Medical and medication errors: a partial summary of reports by
the Institute of Medicine and the quality interagency coordination task force. 2001;7(1):62-68.
• Developing disease state management in the United Kingdom:
an obviously American conjecture finds export opportunities
abroad. 1998;4(3):275-76, 279-83, 287.
• How to evaluate disease state management programs. 1997;
3(3):270, 273-74, 277-78.
• Managed care and the quest for quality measures. 1997;
3(3):255, 258-89.
• Innovations in quality improvement: managed care leads the
way. 1996;2(1):20, 22, 24, 27-28.
• Successful CQI-based programs in a group-model managed
care setting. 1995;1(5):134, 137.
• Disease state management. 1995;1(5):128-33.
• Quality assessment and quality assurance of pharmacy services.
1995;1(4):40-51.
Health Care Spending and Health Economics
• Examination of resource use and clinical interventions associated with chronic kidney disease in a managed care population.
2003;9(3):248-55.
• Resource use and patient care associated with chronic kidney
disease in a managed care setting. 2003;9(3):238-47.
• Is there no prescription to decrease health care outlays in the
face of an aging population? 2000;6(6):450-51.
• Health economics II: some unique aspects of health economics.
2000;6(2):173-78.
• Health economics I: basic economic principles. Evaluation of
online prospective DUR programs in community pharmacy
practice. 2000;6(1):43-50.
Health Insurance and Health Care Finance
• The Health Insurance Portability and Accountability Act of
1996: the issue of portable health care coverage. 1999;5(2):81,
85-88.
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• Direct contracting: the next purchaser strategy. 1996;2(1):1112, 14, 16.
Institutional Managed Care
• Managed pharmaceutical care within a criminal justice system.
2001;7(3):182.
Internet Pharmacy
• Concern about foreign-source pharmacy Internet providers.
2001;7(5):335-36.
• The Internet and PBMs: new business model or business as
usual? 2000;6(2):102,105-07.
• With the click of a mouse. Evaluation of online prospective
DUR programs in community pharmacy practice. 2000;6(1):
73.
Lifestyle Drugs
• Enhancing life or eradication ugliness?: lifestyle drugs.
2002;8(1):15-16, 19-20.
Managed Care Pharmacy Practice
• John Ogden talks about managed care in the Veterans
Administration. 2002;8(2):91-93.
• The value of managed care pharmacy in an IPA setting.
2001;7(6):438-39.
• Innovative managed care pharmacy practice. 2001;7(2):90-92.
• Innovative managed care pharmacy practice. 2001;7(1):8, 9.
• Career changes in managed care pharmacy. 2000; 6(3):208,
210, 215.
• Managed care and the pharmacy profession revisited.
1999;5(2):78.
• Advancing outcomes research in managed care pharmacy: a call
to action. 1998;4(3):257-58, 261-63, 266-67.
• The importance of communication skills for the managed care
pharmacist. 1998;4(2):102.
• The evolution of pharmaceutical care into managed care environments. 1998;4(1):55-58.
• The changing face of managed care pharmacy and the role of
PBMs. 1997;3(5):494, 497-98.
• Managed care pharmacists: leading the way for a new millennium. 1997;3(4):383-85, 388.
• Consultant pharmacy and managed care: a partnership for the
future. 1997;3(2):164, 167-69.
• Managed care pharmacy: leading pharmaceutical care integration forward. 1997;3(2):139, 141-42, 145-47.
• Group Health Cooperative. 1996;2(6):634-36, 639-40.
• Internal marketing: essential challenge for managed care pharmacy. 1996;2(5):473-74, 479-80.
• Prescription solutions: managing pharmacy care through flexibility and innovation. 1996;2(4):385-86, 389-90, 395.
• Harvard Pilgrim Health Care: a new partnership in promoting
pharmaceutical care. 1996;2(3):249-50, 252, 254.
• Blue Cross and Blue Shield: making pharmaceutical care a key
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component of managed care. 1996;2(1):33-34, 36, 38.
• CIGNA HealthCare: a leader in pharmacy re-engineering.
1995;1(6):174-75, 178, 180.
• Issues and concerns of managed care pharmacy directors:
results of a national survey. 1995;1(5):116-20.
• Systemed: the future in PBMs. 1995;1(5):109-10, 113-14.
• Professional opportunities in managed care pharmacy.
1995;1(5): 80, 82, 86-87.
• Kaiser Permanente medical care program. 1995;1(4):26-28, 30.
Managed Health Care
• Medicare PPOs and managed care. 2003;9(1):91.
• Examining the managed health care continuum. 1997;
3(5):511-12, 515-16, 518.
• Physician-management companies: ready to make their move in
managed care. 1996;2(2):95-96, 98, 100, 106-07.
Manpower and Job Satisfaction
• A closer look at pharmacy technicians. 2003;9(1):84.
• 2002 White Paper on Pharmacy Technicians: needed changes
can no longer wait. 2003;9(1):72-83.
• How many pharmacists are in our future? The Bureau of Health
Professions projects supply to 2020. 2000;6(6):474-82.
• Charting the demand for pharmacists in the managed care era.
1999;5(4):324-28.
• Burnout in a sample of HMO pharmacists using the Maslach
Burnout Inventory. 1998;4(5):495-503.
Medicaid
• State-by-state look at Medicaid retail pharmacy delivery: trials
and triumphs. 1996;2(6):546-47, 551-52, 554.
Medicare (see also Drug Benefit Management Methods—
Benefit Design)
• Medicare and managed care update 2000. 2000;6(6):466, 468,
470, 472.
• Prescription coverage options for Medicare beneficiaries.
1999;5(3):250-54.
• Medicare and managed care: emerging partnerships. 1998;
4(2):105, 108-10, 112.
• Overview of Medicare for managed care professionals. 1996;
2(2):165-72.
Pain Management
• Fentanyl transdermal vs. oxycodone hydrochloride controlledrelease (letter). 2003;9(5):457-58.
• Patient-reported utilization patterns of narcotic drugs (letter).
2003;9(4):374-75.
• Patient-reported utilization patterns of fentanyl transdermal system and oxycodone hydrochloride controlled-release among
patients with chronic nonmalignant pain. 2003;9(3):223-31.
• Beyond narcotics for effective pain management. 2003;
9(2):175-76.
• Out of illness, into life: pain management and the need for triptans. 2003;9(1):89-90.
• It’s a pain. 1999;5(6):558.
Pharmaceutical Industry
• India’s pharmaceutical industry: a growing influential force in
the world pharmaceutical market. 2002;8(3):211-15.
• International movement of Japan’s pharmaceutical industry:
reform of Japanese health policies, Part III. 1998;4(6):567-68,
571-72, 555-57, 580, 582-83.
• International movement of Japan’s pharmaceutical industry:
reform of Japanese health policy, Part II. 1998;4(2):123-24,
127-28, 130, 135-37.
• International movement of Japan’s pharmaceutical industry:
health policy reform. 1997;3(6):667-68, 671-74.
• The drug approval process in the U.S., Europe, and Japan.
1997;3(4):459-65.
• Pharmaceutical privatization and reform program in
Kazakhstan. 1997;3(4):415-16, 418-19, 422.
• U.S. pharmaceutical firm prospects within the People’s Republic
of China. 1996;2(3):240-42, 245-48.
• Manufacturer-provided alliances: case studies of the nature of
and prospects for several model arrangements. 1996;2(3):227,
231, 235-36, 239.
• Industry partnerships: disease management programs flourish.
1995;1(6):164, 166, 170-72.
• Evaluating the pharmaceutical industry interface with managed
care. 1995;1(4):35-39.
Pharmacogenomics
• Drug therapy customized to individual patients. 2002;8(4):29697.
• Evaluating the potential impact of pharmacogenomics on ADRs.
2002;8(4):285-90.
• Health care professionals’ perceptions of the role of pharmacogenomic data. 2002;8(4):278-84.
Pharmacy Education
• The Society of Industrial Pharmacy Students: a new organization at the University of Houston (letter). 2003;9(4):372-73.
• Managed care and the University of Texas College of Pharmacy.
2001;7(6):490.
• University of Michigan College of Pharmacy and managed care
partner to enhance drug therapy. 2001;7(5):345-46.
• An inside look at the benefits of a student pharmacy and therapeutics (P & T) committee competition from the University of
Illinois at Chicago. 2001;7(4):259-60.
• Managed care concepts prominently featured in innovative
management programs at Duquesne University. 2001;7(2):
94,96.
• Managed care teaching and research in South Dakota.
2001;7(1):10, 11.
• Synergy between the University of Louisiana at Monroe and the
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Louisiana Drug Utilization Review Board. 2000;6(5):420.
• Virginia Commonwealth initiates combined graduate programs.
2000;6(4):327-28.
• College offers certified managed care pharmacist program.
2000;6(3):262-63.
• The University of Maryland’s Center on Drugs and Public Policy.
2000;6(2):184-85.
• Teaching managed care pharmacy and disease management in
Canada. Evaluation of online prospective DUR programs in
community pharmacy practice. 2000;6(1):71-72.
• Managed care pharmacy practice at the Texas Tech University
Health Sciences Center School of Pharmacy. 1999;5(6):556-57.
• Description of a formal affiliation between a school of pharmacy and a managed care organization. 1999;5(5):433-37.
• Students gain exposure to managed care principles at a new
school of pharmacy. 1999;5(4):371.
• Improving efficiency and effectiveness in managed care: ongoing efforts at the University of New Mexico College of Pharmacy.
1999;5(2):111.
• Cooperative learning in a required outcomes assessment course.
1998;4(4):431-32.
• First managed care pharmacy course at the University of Illinois
at Chicago. 1998;4(1):80-81.
• Draft criteria for residency programs in managed care pharmacy. 1997;3(3):363-64, 366, 368, 371.
• Internship takes classroom into the “real world.” 1997;3(2):234,
241.
• New degree program at Ole Miss: B.S. in pharmaceutical sciences/management major. 1997;3(1):112-113.
• Linking the ivory tower and real-world practice: building a synergy bridge in managed care pharmacy. 1997;3(1):107-08, 110.
• Pharmacy internship offers real-world exposure to managed
care pharmacy practice. 1996;2(6):605-06.
• Managed care pharmacy at the St. Louis College of Pharmacy.
1996;2(4):439, 442.
• Managed care pharmacy curriculum in pharmacy schools: the
Samford University perspective. 1996;2(3):320.
• Managed care pharmacy education at the University of
Washington School of Pharmacy. 1996;2(3):319-20.
• Managed care pharmacy education at MCP. 1996;2(1):53.
Physician Education-Intervention—Academic Detailing
• Effects of physician report cards, knowledge of drug prices, and
financial incentives in prescription drug costs (editorial).
2003;9(4):368.
• Physician education-intervention influenced prescribing for otitis media. 2002;8(2):141-45.
• Selection bias in physician education-intervention programs.
2002;8(2):82.
• Effect of physician profiles and academic detailing on cost and
utilization of selective serotonin reuptake inhibitors. 2002;
8(1):23-31.
• Driving market share in an integrated health system without
588
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therapeutic interchange. 2001;7(4):283-86.
• Effect of provider education and feedback on antihypertensive
prescribing in a department of Veterans Affairs primary care
clinic. 2000;6(4):307-10.
• Academic detailing to influence prescribing. 1997;3(6):631-33,
637-38.
• Academic detailing: methods and success stories in IPA-model
HMOs. 1996;2(5):586-88, 593-94, 596.
• Effectiveness of academic detailing in the managed care environment: improving prescribing of lipid-lowering agents.
1996;2(2):148-57.
• Academic detailing: what’s in a name? 1996;2(2):88-90.
• UIC students mobilize first student chapter of AMCP.
1995;1(6):185-86.
Population Health—Interventions and Prevention of ADEs
• Who bears responsibility for glucocorticoid-exposed patients in
a large health maintenance organization? 2001;7(3):228-32.
• An employee influenza initiative in a large university managed
care setting. 2001;7(3):219-23.
• Public health, managed care, and pharmacy: an evolving trifecta. 2001;7(1):12, 14-16.
Prior Authorization (PA) (see Drug Benefit Management—
Quantity Limits and Prior Authorization (PA))
Privacy of Health Information
• HIPAA effects on health research and PBM functions in drug utilization review. 2003;9(1):95-97.
• The Health Insurance Portability and Accountability Act of
1996 (HIPAA) and the pharmacy benefit: implications for health
plans, PBMs, and providers. 2003;9(1):66-71.
• Privacy just took on a whole new meaning: what HIPAA means
to pharmacists. 2001;7(5):342.
• Employer access to employee prescription records: dilemmas
for pharmacists. 1997;3(5):504-05, 508.
Quality Assurance
• Credentialing in pharmacy. 2001;7(1):22-27, 30-31.
Research Methods (see also Survey Methods)
• Single-patient trial (SPT) method—substitute for expert opinion? 2002;8(6):519.
• Statistical significance versus practical significance. 2002;
8(5):404.
• Conjoint analysis in pharmaceutical research. 2002;8(3):20608.
• Researching managed care pharmacy using Internet searches.
2001;7(3):201-04, 213.
• Research methodology: designing a research study. 1998; 4(5):
504-14.
• Research methodology: hypotheses, measurement, reliability,
and validity. 1998;4(4):382-88.
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• The vital role of pharmacy benefit management firms in health
services research. 1998;4(1):23-24, 26-28.
• Calculating risks and number-needed-to-treat: a method of data
interpretation. 1997;3(2):179-83.
• Method is everything: evaluating results by study design.
1997;3(1):66-68, 71-72, 75-76.
• Epidemiological techniques. 1997;3(1):30-32, 35.
• Research methodology: some statistical considerations. 1996;
2(6):617-21.
• Measuring quality of life: a primer for managed care pharmacists. 1996;2(4):415-22.
• Interface between pharmacoepidemiology and pharmacoeconomics in managed care pharmacy. 1996;2(3):282-89.
• Research in managed care: outcomes research in disease prevention and management. 1996;2(3):212, 214, 216, 221-22.
• Outcomes research, pharmacoeconomics, and the pharmaceutical industry. 1996;2(1):48-52.
• Drug-related morbidity and mortality: a cost-of-illness model.
1996;2(1):39-47.
Safety—Health Care Worker
• New standards to prevent needle-stick injury. 2001;7(5):34952.
Safety—Patient Care (see also Drug Utilization Review (DUR))
Specialty Pharmacy
• The emergence of specialty pharmacy. 2000;6(4):280-84.
Survey Methods (see also Research Methods)
• Constructing mail survey questionnaires to maximize the rates
of return and assure the validity and reliability of responses.
2002;8(3):225-31.
• Implementing mail survey questionnaires. 2002;8(2):157-61.
• Going to the source: a guide to using surveys in health care
research. 1999;5(2):150-59.
• The year 2000 in pharmacy—business as usual or disaster in
progress? 1999;5(4):305, 308-10.
• Technology and automation update. 1998;4(3):345-50.
• Gaining links: health information networks arise with integration challenges. 1995;1(5):96-98, 100.
• Automation aids prescription processing—but professional
judgment remains indispensable. 1995;1(5):90, 93-95.
Technology—Electronic Prescribing
• Extent of electronic prescribing implementation as perceived by
MCO pharmacy managers. 2002;8(1):41-47.
• Electronic prescribing in ambulatory care: a market primer and
implications for managed care pharmacy. 2001;7(2):115-20.
• Connecting physicians to pharmacies—and patients. 1998;
4(5):473-74, 477.
• Electronic prescribing: the next revolution in pharmacy?
1998;4(1):35-36, 39.
Therapeutic Interchange—Therapeutic Selection
• Utilization of pharmacy claims data to evaluate therapeutic
interchange programs. 1999;5(4):331-34.
• Risk-taking propensity and drug product selection behavior of
pharmacists. 1997;3(4):439-43.
Value of Pharmacotherapy
• RxHealthValue offers three recommendations and cost research.
2001;7(1):17-20.
Women’s Health
• Women’s health: issues and opportunities for managed care
pharmacy. 2001;7(4):263-67.
• Estimating the relative cost effectiveness of four contraceptive
methods in the prevention of unwanted pregnancies within the
Department of Defense active-duty women. 1999;5(2):131-36.
Technology—Automation
• Automated dispensing technologies: effect on managed care.
1995;1(5):212-17.
Technology—Education and Information
• Evaluation of personal digital assistant drug information databases for the managed care pharmacist. 2003;9(5):441-48.
• Use of technology throughout the curriculum. 2002;8(2):86.
• Critical evaluation of web sites: an example in osteoporosis.
2000;6(4):316-22.
• Adopting knowledge technology to “manage” care: issues and
status of physician use. Evaluation of online prospective DUR
programs in community pharmacy practice. 2000;6(1):35-41.
• The Internet: changing the managed pharmaceutical care environment. 1999;5(5):387-88, 390, 392.
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EDITORIALS
■■ Gabapentin May Be Appropriate for Off-Label Uses
In this issue, Alicia Mack, PharmD, discusses the clinical literature of the “off-label” uses of gabapentin (Neurontin) to prepare
managed care practitioners for the appropriate uses of
gabapentin.1 In the review, Mack examines several off-label uses
of gabapentin, leading her to the conclusion that patients
should only receive gabapentin when they have failed standard
treatment options and when efficacy has been demonstrated in
a randomized controlled trial.1
The methods by which gabapentin has become a drug with
more than a billion dollars in annual sales in the United States are
being examined in the federal court system.2 Regardless of the
outcomes of the federal investigation of marketing practices, the
use of gabapentin for off-label indications far surpasses its FDAapproved indications.3 Gabapentin may have become a “catchall” medication for practitioners because its exact mechanism of
action remains unknown and because it can be prescribed to
patients with hepatic and/or renal insufficiencies.4 Furthermore,
data ranging from case studies to randomized double-blind,
placebo-controlled studies suggest that gabapentin may have positive effects on patients with a variety of disease states.
Randomized double-blind studies are the gold standard
when researchers are trying to compare medication regimens.
However, the studies must be critically evaluated to ensure that
the results can be applied to a specific patient population.
Mack cites a study by Morello5 that was a randomized double-blind study comparing the efficacy of gabapentin to
amitriptyline on diabetic peripheral neuropathy pain. The
results state that there is no statistically significant difference
between the 2 medications. However, the study was conducted
in the Veterans Affairs (VA) San Diego Healthcare System.5
The demographics of the study—24 men and 1 woman—do
not accurately depict the American population of diabetics,
which is more than 50% female.6 The study was well designed
and the results are accurate, but they may not be generalized to
patient populations outside the VA system.
A similar study performed by Dallocchio et al. states that
gabapentin significantly reduced pain scores, improved paresthesia scores, and had a better safety profile when compared
with amitriptyline.7 The study was an open-label design, but the
authors lessened possible biases by randomizing the patients to
treatment arms.7 In addition, the patient population was also
more representative of the American diabetic population
(11 males, 14 females). Even though the study lacked blinding,
the results may be considered as more applicable based upon
the generalizability of the results. Moreover, all published data
must be assessed to determine their applicability to specific
patient cases.
The evidence-based practice of medicine allows therapies to
evolve in search of the optimal treatment. A recent example utilizes metformin as adjunctive therapy in adolescents with
type 1 diabetes.8 Another article by Gomez9 states that metformin adjunctive therapy may improve glycemic control in
type 1 diabetic patients. If several articles are published about
metformin use in type 1 diabetes, a meta-analysis can be performed to determine treatment effectiveness.
A meta-analysis, such as the one performed by Backonja and
Glanzman10 for gabapentin, provides an immense amount of
data on the treatment of painful diabetic neuropathy, postherpetic neuralgia, and other neuropathic pain syndromes. Metaanalyses of well-designed studies provide greater generalizability when compared with smaller well-designed, randomized
controlled trials, due to greater statistical power. Therefore, a
practitioner can confidently apply the data to treat a more
diverse patient population. Off-label uses may become clinically acceptable without having an FDA-approved indication.
Speculation arises concerning consistency of gabapentin offlabel use due to a lack of manufacturer prescribing guidelines.
A retrospective study in a managed Medicaid population
(N=105) by Hamer et al. demonstrated that 95% of patients
received gabapentin for off-label uses.11 Results indicated that
59% of patients receiving gabapentin continued treatment with
the initial prescriber; 47% of patients received gabapentin
3 times daily, the usual dosing frequency; 40% of patients had
no documented follow-up related to gabapentin; and 65% of
patients discontinued therapy by the end of the study period.11
Additionally, the average dose received was predominately at
the lower end of published dosage ranges.11 Based on the
review, Hamer concluded that patients did not appear to receive
benefit from gabapentin.11 Consequently, are the results due to
gabapentin ineffectiveness, improper titration and follow-up,
poor patient compliance, an atypical population, or a combination thereof? Health professionals choosing to practice evidence-based medicine must adhere to the published literature
in regard to dosing, titration, and follow-up to accurately medicate their patient population.
The medical community has helped to make gabapentin a
blockbuster drug, in part through prescribing for off-label uses.
Gabapentin is used to treat some patients with unexplainable
pathophysiologies; in patients with multiple, complex disease
states; and in patients who have demonstrated intolerance to
other therapies.
John Barbuto, MD, a practicing neurologist, observed in a
previous issue of the Journal that logic drives the use of
gabapentin because of its (a) few major side effects (and lower
risk of malpractice lawsuits); (b) few drug interactions, a consideration more important for this patient population that has a
relatively high incidence of affective disorders and chronic pain
and tends to be taking multiple drugs; (c) favorable tolerance
for these patients with affective disorders and chronic pain who
are more prone to complain of side effects; and (d) relative ease
of use (e.g., less need for follow-up laboratory monitoring).12
In many cases, practitioners are unable to pinpoint the
mechanism causing relief; critics refer to this as the placebo
effect and demand randomized controlled trials to justify the
cost of gabapentin. Is it financially responsible to conduct a randomized controlled study to demonstrate results beyond a rea-
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Journal of Managed Care Pharmacy 569
Editorials
sonable doubt when conclusions from a meta-analysis of all
published data suggest clinical effectiveness and certain patients
seem to respond favorably to gabapentin?
Limiting the use of gabapentin to an alternative status for
only times when the patient is intolerant of the standard treatment option(s) or only when it has been studied in randomized
controlled trials would be practicing “black and white” medicine in an environment that is actually various shades of gray.
Practicing evidence-based medicine requires the health care
professional to critically evaluate the literature, consider all possible therapeutic options, select therapy that will adequately
treat the patient, and properly follow the patient in order to
minimize the cost to the health care system.
Shawn Davis
PharmD Candidate, 2004
The Ohio State University College of Pharmacy
Columbus, Ohio
E-mail: [email protected]
The author discloses no financial interest or bias regarding
gabapentin or Pfizer, Inc.
REFERENCES
1. Mack A. Evidence-based use of gabapentin. J Managed Care Pharm.
2003;9(6)559-68..
2. Zimmerman R. A unit of Pfizer is target of lawsuit over its marketing. Wall
Street Journal. March 15, 2002:B3.
3. Lenzer J. Whistleblower charges drug company with deceptive practices.
BMJ. 2003;326(7390):620.
4. Prescribing information for Neurontin (gabapentin). New York: Pfizer Inc.;
2003. Available at: http://www.pfizer.com/download/
uspi_neurontin.pdf. Accessed September 22, 2003.
5. Morello CM, Leckband SG, Stoner CP, et al. Randomized, double-blind
study comparing the efficacy of gabapentin with amitriptyline on diabetic
peripheral neuropathy pain. Arch Intern Med. 1999;159:1931-37.
6. CDC’s Diabetes Program—Publications and Products. Centers for Disease
Control. Available at: http://www.cdc.gov/diabetes/pubs/women/index.htm.
Accessed September 17, 2003.
7. Dallocchio C, Buffa C, Mazzarello P, et al. Gabapentin vs. amitriptyline in
painful diabetic neuropathy: an open-label pilot study. J Pain Symptom Manage.
2000;20(4):280-85.
8. Hamilton J, Cummings E, Zdravkovic V, et al. Metformin as an adjunctive
therapy in adolescents with type 1 diabetes and insulin resistance. Diabetes
Care. 2003;26(1):138-43.
9. Gomez R, Mokhashi MH, Rao J, et al. Metformin adjunctive therapy with
insulin improves glycemic control in patients with type 1 diabetes mellitus:
a pilot study. J Pediatr Endocrinol Metab. 2002;15(8):1147-51.
10. Backonja M, Glanzman RL. Gabapentin dosing for neuropathic pain:
evidence from randomized, placebo-controlled clinical trials. Clin Ther.
2003;25(1):81-104.
11. Hamer AM, Haxby DG, McFarland BH, et al. Gabapentin use in a managed Medicaid population. J Managed Care Pharm. 2002;8(4):266-71.
12. Barbuto J. Gabapentin and indications of appropriate use. J Managed Care
Pharm. 2002;8(4):293-94.
570 Journal of Managed Care Pharmacy
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November/December 2003
■■ Use of Drugs for Off-Label Indications:
Living in the Same World
Learning is acquired by reading books; but the much more
necessary learning, the knowledge of the world, is only to be
acquired by reading man, and studying all the various editions of them.
—Philip Dormer Stanhope, statesman and writer (1694-1773)
In this issue Alicia Mack, PharmD,1 discusses a proposal that
gabapentin use be restricted to its label indications.1 While her
argument is based on perspectives of documented science, it may
miss the point. Medical care is based on serving patients. The
demands of this are a far cry from rigorous science. In the real
world, the perspectives of Mack are, in my opinion, impractical.
Scientifically, it would be ideal if medical care proceeded as
a rigorous science. Yet, it doesn’t. Ultimately, medical care is
about patient satisfaction. Patients do not go to the doctor to be
provided rigorous science. Patients go to the doctor to meet
their medical desires. There is only a partial correlation between
these and the interests of science. If you were to attempt to provide medical care based on rigorous science (and I, more or less,
have tried this), you would find that what you receive is patient
dissatisfaction, even hostility. The average patient is only interested in rigorous science when this happens to be consistent
with beliefs and desires.
What is the proof for this? The proof is plentiful indeed. Let’s
start with some very simple perspectives: smoking, obesity, narcotic addiction. Is there evidence that smoking is bad for
health? Do people continue to smoke? Do a lot of people continue to smoke? Or, is there evidence that obesity is bad for
health? Do people continue to overeat? Do a lot of people continue to overeat? Or, is there evidence that drug addiction is bad
for health? Do a lot of people abuse drugs? What do we learn
from these observations? What are these people doing? Are they
looking for the answers of rigorous science, or something else?
Now, let’s consider more subtle proof. There are countries of
the world that have life expectancies equal to ours but that also
have far lower health care costs. Widely available statistics (from
the U.S. Census Bureau’s International Data Base, for instance)
reveal that the United States is certainly not heading the list of
life expectancy. By some measures, we’re down around rank 20.
Yet, our health care costs are not only the highest in the world
in terms of percent GNP but also are about double the costs for
some other countries whose life expectancies are similar (or
greater) than ours, such as England and Japan.2 Why is this proof
for the tenet above? Science would dictate that all of our cost is
not necessary. Yet, people of America do seek and consume health
care to a greater extent than anywhere in the world. So, is this
meeting the needs revealed by science, or is this consumption
driven by something else? Information on heath care costs across
the world are widely available. If we are so interested in reducing
costs, why do we not, as scientists, look at outcomes across the
world? Part of the reason is simply that medical care is only partVol. 9, No. 6
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Editorials
ly interested in science.
In the real world of the doctor in the office, medical care is
about people who are ill or worried and who seek to assuage
their illness or fears. They come as humans, driven by emotion
and personal life needs or desires. They do not come as computers, satisfied with the best solution to the equation.
This then brings us to gabapentin. This is a drug that
patients find to “work” for them. How do we know this? They
buy it—or have an insurance company buy it for them. They
buy it not because they find taking pills an inherently joyful
activity. They buy it, and continue to buy it, because, at one
level or another, it proves itself to them. And, doctors provide it
because, at one level or another, the drug proves itself to them
also. For doctors in America, the keys to success of gabapentin
are few drug interactions and few major side effects. In other
words, providing the drug is not likely to get the patient or the
doctor in trouble. This is the key to its widespread use.
While these perspectives paint a sobering picture of the
practical use of gabapentin, we must also recognize that a great
deal of off-label use of medications later becomes on-label use.
Obtaining a specific indication for a drug is an economic decision. A manufacturer must decide whether the potential market
opportunities of the medication warrant the costs of the
research that might support it. The manufacturer must decide
whether the formal studies would generate more business or
simply provide a costly “I told you so.” And, yes, the company
must decide what would happen if science did not support their
current use patterns. This set of issues largely becomes a commentary on market economics, not scientific applicability. Yet,
we must recognize that when there is widespread use of a medication for a problem, it may be reasonably likely that there is
some foundation for the behavior. Just because a use is off-label
does not mean it is scientifically wrong.
The move to control a drug by demanding that its use be
limited to formal indications is a doomed strategy. There is very
extensive information supporting the perspective that very frequently a drug comes to be recognized as useful for a condition
via serendipity. Some physician somewhere either observes a
fortuitous effect or correctly guesses a probable applicability. In
the early stage of such use, the application is off-label.
For many drugs and many conditions, well-established uses
may stay off-label. So, the hope of curtailing use to those situations that have formal labeling is an approach that will be rejected. To recognize this truth is not to advocate “do whatever you
want.” Certainly, I do not believe nor support this. Rather, we
simply know that there is a large gray area where science has not
rigorously resolved questions. Where this is true, we would be
wrong to presume that science will be unsupportive of extant
behaviors.
I have no personal or economic interest in gabapentin or the
company that manufactures it. Support of the behaviors surrounding gabapentin is not about supporting the drug itself. It
is about recognizing how real medical care works. Real medical
care is about taking care of emotional, personally interested
human beings in a way that is satisfying to the patient and
allows the doctor a successful life. Real medical care is about
people. It is only about science as a secondary issue. Human
beings are drawn to science where it serves their desires; however, few humans are drawn to science truly as a life grail. This
should not surprise us—in spite of our trappings, we are barely emerged from the forest, so to speak.
So, as I have advocated before in the pages of this Journal,3
if we wish to control costs, we need to understand the real
dynamics of American health care. I deeply believe in science.
Yet, I also know the limits of its application to most human
beings. This is not a criticism. This is a science.
More wisdom is latent in things-as-they-are than in all the
words men use.
—Antoine-Marie-Roger de Saint Exupéry (1900-1944).
John P. Barbuto, MD
Neurology In Focus
An Outpatient Neurology Clinic at HealthSouth
Sandy, Utah
E-mail: [email protected]
REFERENCES
1. Mack A. Examination of the evidence for off-label use of gabapentin.
J Managed Care Pharm. 2003;9(6):559-68.
2. http://www.lippmannforcongress.us/universal_health care.htm
3. Barbuto J. Gabapentin and indications of appropriate use. J Managed Care
Pharm. 2002;8(4):293-94.
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Journal of Managed Care Pharmacy 571
EDITORIAL SUBJECTS—IN THIS ISSUE
■■ Contractual Arrangements Between HMOs
and Medical Groups to Manage Drug Costs
In the middle 1980s, a national for-profit health maintenance
organization (HMO) signed pharmacies, physicians, and hospitals to full-risk (capitation) financial arrangements that left
many of these contract providers bankrupt or financially devastated. Many medical and hospital providers have come to more
fully appreciate that financial risk can, in fact, be very risky.1
Several pharmacy administrative service organizations ceased to
exist in the swath of the lopsided risk-contracting methods.2
Financial-risk contracting between HMOs and provider
groups is an ongoing tug of war. From one perspective, financial risk that can be fully managed by the provider group
should be fully transferred (capitated) to that provider group
from the HMO. Ideally, financial risk that is less manageable by
the provider group should be retained by the HMO in increments proportional to the manageability of the financial risk,
including volume (units) and price per unit. In general, pharmacy providers have very little control over either price or volume and generally should not assume financial risk associated
with a prescription drug benefit.3 The HMO (insurer) controls
the drug benefit design, including scope of drug coverage,
copayment amounts, and days supply per copayment, etc.
The HMO (or health plan), not the pharmacy provider, controls
the rebates obtainable from pharmaceutical manufacturers, and
pharmacy providers have little opportunity to influence
(reduce) price except for small discounts earned through volume purchasing or through therapeutic selection if the HMO
administers a true low net-cost drug formulary.
Physician medical groups have some degree of control over
volume and price in prescription drug benefits of HMOs and
may, therefore, reasonably assume some degree of shared financial risk. Physicians can control price through therapeutic selection of generic drugs and lower-cost brand drugs.4 Physicians
also have a considerable amount of control over the volume of
prescription drugs provided to a given population of patients.5
Drug benefit financial risk is measurable and even predictable for large HMOs, and historical experience, measured
per member per month (PMPM) with defined populations of
continuously enrolled members-patients, can help reduce the
uncertainty of unknown future costs. However, physician medical groups are also dependent on HMOs to share reliable information to help predict future costs. In the 1990s, allegations
were made that some HMOs were setting PMPM capitation
rates, including drug benefit financial risk, as a percentage of
premium, using unadjusted historical costs and growing enrollment through artificially low monthly premium rates. A Texas
state court judge ruled in May 1998 that a given HMO must
stop immediately its practice of penalizing physicians who
exceeded their pharmacy risk-budgets, calling the policy “probably illegal.”6 An executive at the HMO acknowledged that the
first drug benefit capitation rate was “too low” (at 9.6% of premium).6
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In October 1998, a large medical service organization (MSO)
representing an independent practice association (IPA) of physicians in North Texas terminated its risk-contract with one of the
largest HMOs in the country for not providing claims data in a
timely and complete manner, making it impossible for the MSO
to manage financial risk.7 Subsequent negotiations between the
large HMO-insurer and the MSO resulted in some strong-arm
tactics that attracted national attention and the intervention of
the American Medical Association. The presidents of the Dallas
County Medical Society and the Texas Medical Association
(Austin) released a joint statement that included the following
assertion: “Remember, this is an HMO that cannot, on a daily
basis, tell its contracting doctors where or who its patients are,
what kind of medications they are taking, or even what hospital
they are in.”8 The dispute attracted the attention of the Texas
Department of Insurance and the U.S. Justice Department, which
penalized the insurer in a consent decree that required significant
asset divestures in key Texas markets.9 In early 1999, an independent practice association in San Mateo, California, notified
the same large national insurer that it would not renew its contract, in part because the IPA could not obtain accurate and timely medical claims data. The IPA claimed that “We could never
seem to get information on admissions, bed-days, etc.”10
Business practices that either leave provider groups with
unmanageable medical or drug costs or fail to provide the riskcontracted providers with the claims data necessary to manage
the financial risk may result in state restrictions on risk contract
terms. The Texas Department of Insurance, for example, prohibited HMOs from transferring financial risk for prescription
drugs to medical groups following the unfair capitation rates
and financial-risk practices for prescription drug benefits risk
that devastated several physician groups in North Texas in the
late 1990s.11,12 HMOs in Texas may provide financial incentives
to physician groups for managing prescription drug costs but
are not permitted to transfer financial risk for prescription drug
benefits to physicians.
In this issue of the Journal, Agnew, Stebbins, Hickman, and
Lipton describe the results of a survey of physician groups surrounding the subject of the management of financial risk associated with the growing use of self-administered injectable
(SAI) drugs.13 As the relative magnitude of cost of this category
of medical costs grows, more attention will be paid to the methods to manage these SAI drug costs effectively. The present survey, sponsored by a grant from the Robert Wood Johnson
Foundation, seemed to find that many physician groups under
contract with HMOs had not, as of early 2001, adopted a
sophisticated or thorough cost management strategy for
SAI drugs. This finding is really not surprising because the
utilization of SAI drugs has grown more dramatically since that
time, particularly in the categories of SAIs for hepatitis C virus
(e.g., interferon SAIs with ribavirin), multiple sclerosis
(e.g., beta interferons and glatiramer acetate,) and rheumatoid
arthritis (e.g., etanercept). What is surprising is that at the time
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of this survey, the 18-month period ended in June 2001, the
20 physician groups almost universally did not know their
actual SAI drugs costs, even for those medical groups that
reported risk contracts with HMOs for these costs.
Some readers may have difficulty understanding why and
how a physician group would agree to accept financial risk for
a cost center, in this case SAI drugs, that is poorly measured and
not clearly defined. However, a survey performed a year earlier,
in 1999, by Evergreen Re, a reinsurer based in Stuart, Florida,
produced results that may have predicted the results found by
Agnew, Stebbins, Hickman, and Lipton. As many as 30% of
hospital and physician medical group executives in markets
with considerable HMO penetration—at least 30%—had little
understanding of their level of exposure to financial risk
through their capitated contracts. The hospital and medical
groups in the survey reported an average 36% of revenues from
capitated contracts, and the average provider organization had
capitated agreements with 5 HMOs.14
Many of the SAIs have a monthly drug cost of more than
$1,000 per patient. There is probably the temptation for some
HMOs to consider the transfer of financial risk, in this case for
SAIs, to physician provider groups. This will also be a short-run
game if (a) the expenditures for SAIs become significant and
(b) the physician groups do not have control over benefit design
(e.g., out-of-pocket cost-share amount, scope of coverage, and
criteria for coverage). SAI drug cost is probably best managed
by a shared financial risk arrangement in which the physician
groups assume a relatively small portion (e.g., 20%) of the total
financial risk and also enjoy a reasonable financial cap on losses (i.e., aggregate or patient-specific stop-loss).
■■ Evidence-based Medicine, Practice Guidelines,
and Disease Management
Early in 2003, the Agency for Healthcare Research and Quality
launched the Web-based National Quality Measures Clearinghouse
to function as a repository for evidence-based quality measures and
measure sets.15 In January 2003, Kaiser Permanente announced that
it would make available on its Web site more than 100 clinical
practice guidelines (CPGs) that are used by Kaiser doctors for treatment of Kaiser HMO members.16 CPGs are the operational
(process) part of interventions to improve clinical, service and cost
outcomes. CPGs are necessary to operationalize the evidence that
results from the conduct of randomized controlled trials (RCTs).
Without CPGs, it is possible to systematically apply RCT evidence
to real-world clinical practice. When CPGs are defined clearly and
in sufficient detail, it is possible to use feedback from performance
measures to continually improve care in a disease management
program.
Disease management programs are difficult to design, implement, operate, and maintain,17 and, even today, there remains considerable frustration over the inability to reliably measure the financial value of disease management programs.18 In this issue of the
Journal, Cannon, Larsen, Towner, et al. describe a health system-
wide effort to improve clinical outcomes in diabetes.19 The authors
report statistically significant and clinically important improvement
in diabetes care according to 6 key performance measures: percentage of diabetics with at least 1 recorded hemoglobin A1c measurement per year, percentage of diabetics with hemoglobin A1c
greater than 9.5, percentage of diabetics with hemoglobin A1c less
than 7, percentage of diabetics with at least 1 recorded low-density lipoprotein (LDL) measurement per year, percentage of diabetics
with recorded LDL value less than 130 mg/dL, and percentage of
diabetics with at least 1 eye exam per year. The authors do not
report an estimated return on investment in the diabetes care management system (DCMS) at this integrated health system.
The investment in care process models (CPMs) at
Intermountain Health Care (IHC) is, in fact, large. Brent James,
MD, and his colleagues at IHC have worked for nearly 20 years to
create CPMs and measure their effects on clinical and service outcomes. James is fond of saying that clinical practice improvement
will result in greater efficiency and, therefore, have a favorable effect
on cost outcomes as well as clinical and service outcomes.
The results of the DCMS reported in this issue of the Journal
are nothing short of exciting. Yet, readers should recognize that
(a) this integrated health network (IHN) has been in the business
of producing, implementing, and continually improving CPMs for
nearly 20 years and (b) this is not just another integrated health
system. SMG Marketing, now Verispan, has found IHC to be
among the top integrated health systems in the United States since
it began the measurement of integrated health systems 5 years ago.
As of March 1999, this IHN ranked number 15 among all IHNs in
the United States.20 SMG Marketing ranked IHC number one
among 532 IHNs in 1999.21 In year 2000, Sentara Healthcare
(Norfolk, VA) edged out IHC as the most integrated health network in the United States by these measures,22 but IHC reclaimed
the top spot in 200123 and held on to the top spot among
472 IHNs assessed in 2002.24 IHC had about 2,000 beds among
21 hospitals in 2002, in addition to the physician division and
insurance division, including IHC Health Plans.
■■ The Relative Value of Disease Management
Programs Versus Drug Manufacturer Rebates
When the State of Florida in 2001 proposed a plan to extract
additional rebates from prescription drug manufacturers
through imposition of a preferred drug list (PDL) tied to a priorauthorization process, selected prescription drug manufacturers
made counter proposals to sponsor disease management programs in lieu of paying additional rebates. In September 2001,
Florida agreed to a proposal that projected savings of $16.3 million from establishment of 2 community-based disease management programs, one to hire health professionals and social
workers to attend to Hispanic and Mexican-American Medicaid
recipients with depression, HIV/AIDS, breast cancer, cervical
cancer, or lung cancer. The explicit goal of this disease management program was to improve compliance with health regimens, including drug regimen adherence.25 The second disease
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management program would hire and train community residents to help overcome language and cultural barriers to
obtaining access to care for Medicaid recipients with depression
and cardiovascular disease. The “savings” would apparently be
measured in reduced emergency room visits and hospitalizations. The Pharmaceutical Research and Manufacturers of
America (PhRMA) contested the Florida Medicaid program
efforts to extract “supplemental” rebates, but a federal judge in
the U.S. District Court in northern Florida (Tallahassee) ruled
on December 28, 2001, that the Florida Medicaid list of preferred drugs may influence patient and physician behavior but
did not prevent access to nonpreferred drugs, which would be
illegal under federal law.26 In September 2002, the Eleventh
Circuit Court of Appeals (Atlanta) upheld the lower court’s ruling regarding the Florida program, and the legality of Medicaid
supplement rebate programs based upon PDLs with prior
authorization was bolstered by the decision from Federal Court
Judge John Bates in Washington, DC, on March 28, 2003,
regarding a similar program in Michigan that employed a PDL
with prior authorization.27
The value of disease management programs in lieu of concessions in direct drug cost was disputed by a report from the Office
of Program Policy Analysis & Government Accountability (OPPAGA) of the Florida legislature in early 2003. OPPAGA found that
the disease management programs in Florida sponsored by prescription drug manufacturers saved the state about $35M in 2002,
about $30M short of the amount that the drug companies would
have paid in supplemental rebates. In 2001, Florida’s PDL saved
the state $123M, including $46M (37.4%) from supplemental
rebates. OPPAGA recommended to the Florida legislature that
supplemental rebates be required for all drugs on the PDL and
that the disease management programs be funded from a portion
of the supplemental rebate income.28 OPPAGA analysts also said
that the methodologies used by the drug companies to calculate
savings from the disease management programs were vague, and
some experts opined that the drug manufacturers had not been
able to show that their disease management programs save money
despite offering these programs to health insurers and others since
the mid-1990s.29
From another perspective, it is easy to see why the pharmaceutical manufacturers are opposed to the heavy-handed managed care method imposed by prior authorization (PA). The PA
process in Florida produced dramatic market share changes
that would be the envy of managed care pharmacists in the private sector. In just 90 days, the market share of lansoprazole
increased by an absolute 21 percentage points, or 55% in relative terms, from 38% of prescriptions for proton-pump
inhibitors in the second quarter of 2001 to 59% of prescriptions for proton-pump inhibitors in the third quarter of 2001.30
Lansoprazole market share increased further, to 67% of prescriptions in the fourth quarter of 2001. Stated another way, by
paying supplemental rebates, the manufacturer of lansoprazole
was able to nearly double its market share, a relative increase of
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76%, or 29 absolute percentage points, in just 6 months, at the
expense of competitor omeprazole, which experienced a market
share drop of 33 percentage points, from 49% in the second
quarter of 2001 and to 16% in just 90 days in the third quarter
of 2001. The market share erosion for omeprazole was essentially 100%, to a residual of 1% of prescriptions for proton-pump
inhibitors in the first quarter of 2002, a period of just 9 months.
■■ Disease Management, Pay-for-Performance,
and Clinical Pharmacist Interventions in Diabetes Care
The April 2003 issue of a business news magazine contained
2 articles on the same subject, but the editor did not make an
apparent connection between the articles and their common subject. More surprising, both articles were written by the same
author. Certainly, the titles of the articles were different and would
not suggest a connection: “Pay-for-performance plans seek to cut
costs,”31 and “Pharmacist oversight cuts cost of chronic disease.”32
One article touted the “unique” notion of paying physicians to
attain certain measures of disease management, in an employersponsored program called “Bridges to Excellence.” The separate,
front-page article, touted the value of pharmacists in managing
chronic disease, particularly diabetes; incidentally, the pharmacists were compensated for the professional interventions. The
former article reported that several large employers had invested
in a scheme, labeled Bridges to Excellence, with the intended purpose of reducing future costs of chronic disease, specifically diabetes. The (physician) pay-for-performance program had the same
expected outcomes as the pay-pharmacist program, the regular,
routine use by patients of measures to better control serum glucose and thereby delay the onset and reduce the magnitude of
complications of diabetes.
The pharmacist pay-for-outcomes program, the “Asheville
Project,” involved payment of $38 per monthly visit to participating pharmacists who monitor medication adherence and the
routine use of serum glucose measures and perform basic physical exams to detect foot care or other health problems that may
warrant a medical visit to a physician. The City of Asheville, a
primary sponsor of the pay-pharmacist disease management
program for diabetes, reported savings of $2,000 per diabetic
patient per year, largely as a result of reduced hospital costs.
Average total medical costs per diabetic patient were reported to
be $7,082 prior to implementation of the pharmacist disease
management program for diabetes, an average $5,210 (26%
less) in the first year and $4,651 in year 2, a 34% reduction compared to base-year costs. The Asheville Project included incentives for patient participation, including the elimination of copayments for visits to pharmacists and diabetes drugs and supplies,
and provided each participating patient with a glucose meter.
■■ Consensus Panel, National Guidelines, and
Other Potentially Misleading Terms
A recent article trumpeted in its title, “Consensus Panel
Recommendations” for “Asthma Treatment Guidelines.”33 The
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Editorial Subjects—In This Issue
panel of 16 physicians and 2 pharmacists appeared to have the
credentials necessary to adequately address the subject.
However, the work of the panel and the article that was derived
from this work were funded by the manufacturer of the drug
that the panel recommended for use in patients with moderate
to severe asthma that is “suboptimally controlled.” This observation gives the reader pause. Should not national treatment
guidelines be based upon evidence from randomized clinical
trials and developed by independent experts who do not benefit from or have a direct commercial interest in the recommendations that evolve from such panels?
What is the necessary amount of independence for these
experts? Some may argue that experts employed by health plans
are biased toward treatments and care processes that are concerned about cost. On the other hand, physicians and other
providers engaged in clinical practice generally want what is
best for their patients and may have little interest in cost, particularly for insured patients. Disclosure of potential conflicts of
interest and sources of funding is a fundamental tool to manage
bias, but most would agree that consensus panel guidelines
should not be developed by persons compensated by the company that stands to benefit from the use of these guidelines. For
busy readers, perhaps such treatment guidelines should include
titles such as “Consensus Panel Recommendations Sponsored
by XYZ Company.”
Frederic R. Curtiss, PhD, RPh, CEBS
Editor-in-Chief
E-mail: [email protected]
10. Wojcik J. Second doctors group parts ways with Aetna. Bus Insurance.
1999; Jan 25:2,21.
11. Ornstein C. Dallas physicians’ group will file for bankruptcy. Dallas
Morning News. July 28, 1999:17A.
12. Ornstein C. Fiscal losses strain top Dallas doctor groups. Dallas Morning
News. 1999 July 13, 1999.
13. Agnew JD, Stebbins MR, Hickman DE, Lipton HL. Financial risk relationships and adoption of management strategies in physician groups for selfadministered injectable drugs. J Managed Care Pharm. 2003;9(6):523-33.
14. Rauber C. Study: capitated risk not always understood. Mod Healthcare.
April 12, 1999:34.
15. Agency for Healthcare Research and Quality. National Quality Measures
Clearinghouse (NQMC). Available at: http://www.qualitymeasures.ahrq.gov/.
Accessed March 1, 2003.
16. Freudenheim M. Large HMO to make treatment guidelines public. John
Wennberg, MD, observed that “This sets a new standard for the competition
and the doctors.” New York Times. January 24, 2003. Available at:
http://www.nytimes.com/2003/01/24/business/24CARE.html. Accessed
January 26, 2003.
17. Curtiss FR. Lessons learned from projects in disease management in
ambulatory care. Am J Health-Syst Pharm. 1997;5(October 1):2217-29.
18. Greenwald J. Disease management value comparisons difficult. Bus
Insurance. February 24, 2003:T3-T5.
19. Larsen DL, Cannon W, Towner S. Longitudinal assessment of a diabetes
care management system in an integrated health network. J Managed Care
Pharm. 2003;9(6):552-58.
20. Appleby JM. Top 25 integrated health networks (IHNs). Man HeathCare.
October 1999:50.
21. Bellandi D. Intermountain tops list of best systems. Mod Healthcare.
January 31, 2000:30.
22. Galloro V. Putting the patient first—Sentara’s successful integration leads
to top spot in annual ranking. Mod Healthcare. February 19, 2001:18.
23. Moon S. Improving care through integration. Mod Healthcare. January 7,
2002:32.
REFERENCES
24. Reilly P. Still leader of the pack. Mod Healthcare. March 3, 2003:36.
1. Curtiss FR. Pricing HMO prescription drug benefits. Med Interface. August
1989:38-42, 45.
25. Gold R. Bristol-Myers signs Florida deal for Medicaid health initiatives.
Wall Street Journal. September 6, 2001:B2.
2. Curtiss FR. Managed Care [chapter 5]. In: Fincham JE, Wertheimer AI, eds.
Pharmacy and the U.S. Health Care System, 2nd ed. Binghamton, NY: Halworth
Press; 1988.
26. Gold R. Judge allows drug rebates in Florida law. Wall Street Journal.
January 3, 2002:A3.
3. Curtiss FR. Methods of providing prescription drug benefits in health
plans. Amer J Hosp Pharm. 1986;43:2428-35.
4. Curtiss FR. Pharmacy preferred-provider organizations. Am J Hosp Pharm.
1987;44:1797-801.
5. Patients and physicians are influenced by financial incentives in use of
pharmaceuticals. Man Healthcare. 1997;May:70.
6. Ornstein C. State judge tells Harris to stop fining doctors. Dallas Morning
News. May 12, 1998:1.
7. Denver doctors may quit HMO. Bus Insurance. November 1998:16:30.
8. Wojcik J. 400 Dallas doctors walk out on Aetna—dispute with managed
care giant leaves plan participants seeking alternative. Bus Insurance. October
26, 1998:1.
9. Decree directs Aetna to sell units. Bus Insurance. June 28, 1999:2.
27. Medicaid supplemental rebates upheld by D.C. federal court. Green Sheet.
April 14, 2003:2,3.
28. Florida disease management report: DM saves 11%; rebates save more.
Green Sheet. April 14, 2003:1,2.
29. Petersen M. Drug makers expand their Medicaid role. New York Times.
April 23, 2003.
30. Florida should implement competitive bidding for retail pharmacy—
report. Green Sheet. April 28, 2003:3,4.
31. Prince M. Pay-for-performance plans seek to cut costs—bonuses paid for
quality health care. Bus Insurance. April 28, 2003:4.16.
32. Prince M. Pharmacist oversight cuts cost of chronic disease. Bus Insurance.
April 28, 2003:1,22.
33. Rosenwasser LJ, Nash DB. Incorporating omalizumab into asthma treatment
guidelines: Consensus Panel recommendations. P & T. 2003;28(6):400-10.
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LETTERS
■■ Transparency Needed for
Economic Analyses of PA Programs
Dear Editor,
I am writing in response to the article “Pharmacoeconomic
Modeling of Prior-Authorization Intervention for COX-2
Specific Inhibitors in a 3-Tier Copay Plan” in the July/August
2003 issue of the Journal of Managed Care Pharmacy.1 While the
authors are to be commended for using an economic analysis to
assess the impact of a prior-authorization (PA) program, I have
some objections with the paper that I wish to express.
My primary objection addresses the lack of transparency in
methods used. When conducting pharmacoeconomic analyses,
it is essential that the methods be made explicit to the reader.
Otherwise, there is no way of knowing of the validity or applicability of the conclusions. In this study, there are several key
variables that are insufficiently explained or ignored entirely.
1. The model assumes a drug cost savings of $0.31 per member per month (PMPM) exclusive of the PA program. This
savings estimate was calculated based on the difference
between the plan’s market share of COX-2s to nonspecific
NSAIDs with that of other managed care populations across
the nation according to IMS Health. The assumption is that
the PA plan is responsible for that difference. This is a rather
weak assumption upon which to base an entire analysis
without additional substantiation. The discrepancy in COX2 use between this plan and that of other plans across the
nation could be explained by a variety of alternative causes
other than the PA program. The variance could just as easily
be explained by differences in population characteristics or
variations in practice patterns.
2. The paper fails to mention that a significant portion of the
savings resulted from denying care to 13% of people who
have a prescription from their doctor.
3. There was no information provided about how the cost of the
PA program was calculated. Readers were told that the PA
program cost $0.07 per call but were not told whether that
sum included costs due to start-up, office space and equipment, employee salaries and benefits, employee training,
computing, and administration or how those costs were allocated. At a minimum, 25% of all costs associated with the
PA plan-wide should be allocated toward this program since
25% of all calls were for COX-2 inhibitors.
4. There was no discussion about the possible relationship
between the PA requests for COX-2 inhibitors and PA for
proton-pump inhibitors (PPIs). Would a COX-2 PA request
to switch to a NSAID and PPI initiate another PA for the PPI?
If so, how many PAs for PPIs (20% of all PAs plan-wide) were
generated due to a switch from a COX-2 drug? Were these
costs included in the analysis?
5. The study only examined the cost of serious GI events and
ignored the costs of other less-serious events. Symptoms of
dyspepsia related to the treatment of arthritis have been associated with higher health care resource utilization (e.g., outpatient visits, inpatient admissions).2
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6. Insufficient details are provided regarding the PA process and
its impact on physician, pharmacist, and patient time. How
much time was spent by persons affected by the PA burden?
For example, how much time did patients, pharmacists, and
physicians spend in switching from a prescribed COX-2 to
an approved drug? There were no data or discussion relating
to these potential time costs.
7. The model does not address costs associated with the
requirement that a patient fail on 2 NSAIDs before becoming
eligible for a COX-2 drug.
8. Figure 3 suggests that sensitivity analyses were conducted for
all probabilities. However, they were not conducted on key
assumptions such as the PMPM drug cost, PMPM cost of the
PA, risk factors such as age or prior GI event, or percent compliance with medications. In addition, no 2-way or 3-way
sensitivity analyses were conducted on any variables,
although they are warranted.
9. The limitations section failed to acknowledge many of the
study’s limitations described above.
My primary concern with this paper is that it presents conclusions with insufficient transparency of methods. Outcomes
researchers can make a model agree with any conclusion they
desire. Therefore, it is critical that authors make their methods
and underlying assumptions as explicit as possible. Casual
readers of this paper may accept the conclusions on face value
without any understanding of their limitations. Worse, the conclusions may be cited by others to justify similar PA programs.
In conclusion, I want to express a final point relating to the
issue of bias or conflict of interest. In the disclosure section at
the end of the article, the authors “reported no biases or conflicts of interest in the preparation of this manuscript.” This
statement lacks credibility given the fact that the authors are all
employed by Humana, a health benefits company. Clearly, the
authors’ interests are advanced if their PA intervention is shown
to be cost effective. That does not imply that they are conducting biased research; it only suggests that their source of
employment makes it that much more important to be explicit
in their methods.
David Holdford, RPh, PhD
Department of Pharmacy, Medical College of Virginia
Richmond, Virginia
E-mail: [email protected]
REFERENCES
1. Stacy J, Shaw E, Arledge MD, Howell-Smith D. Pharmacoeconomic modeling of prior-authorization intervention for COX-2 specific inhibitors in a 3-tier
copay plan. J Managed Care Pharm. 2003;9(4):327-34.
2. Zhao SZ, Argulelles LM, Dedhiya SD, Morgan DG. Healthcare utilization
associated with dyspepsia in patients with arthritis. Am J Managed Care.
1999;5(10):1285-95.
For author response, see following page.
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Letters
The Authors Respond
Dr. Holdford raises some good questions regarding our study.1
Our point-by-point response is as follows:
1. It is reasonable that population differences or practice variation can contribute to utilization variance. However, the size
of the study population does represent broad geographic,
demographic, and treatment patterns.
2. There is strong evidence regarding overprescribing of
COX-2 specific inhibitors. The number of requests for
COX-2 drugs suggests that many prescriptions are written
for patients with no risk. The prior-authorization (PA)
process is put in place to provide COX-2 drugs based on
established risk criteria.
3. The administrative cost per call for the call center in 2000
reflected all costs, including office space and equipment,
employee salaries and benefits, training costs, etc. The stated cost savings for the PA program on COX-2 specific
inhibitors was adjusted for the entire operation of the call
center. If only 25% of all costs of the call center were used,
the cost savings of $0.24 per member per month (PMPM)
would be more favorable.
4. Concomitant use of proton-pump inhibitors (PPIs) with
COX-2 specific inhibitors and nonspecific nonsteroidal antiinflammatory drugs (NSAIDs) was reflected in the population of our model (see Figure 1). The membership is allowed
90-day PPI treatment without a PA. The actual influence of
PA rate change for PPIs was not in the scope of the study.
5. This study, along with many in the current literature regarding NSAID treatment, focuses on only serious GI events. The
study cited by Holdford used claims data from 1992-1993,
before the availability of COX-2 drugs. It would probably be
of value to repeat this analysis using more recent claims data.
6. The issues of PA impact on physician and patient time were
addressed in the second-to-last paragraph of the Results section. It was acknowledged that the value of PA might
decrease due to the level of patient and provider satisfaction
and its impact on member retention and burden of use (see
bottom of page 332).
7. We agree that the costs associated with treatment failure for
nonspecific NSAIDs were not measured in the scope of this
study.
8. Sensitivity analysis was conducted on the probabilities in
which the assumptions were made. The areas of PMPM drug
cost, cost of PA, and risk factors were calculated numbers
that we feel were very real estimates with a smaller range of
variability. Although this was only a preliminary study, a
2-way sensitivity analysis may prove valuable for future evaluations to determine how one variable affects the other.
Regarding the issue of bias or conflicts of interest, this study
was done to help make administrative decisions about benefit
design and the true value of PA to the health plan. The results
were not biased to sway the outcomes one way or the other.
Jane Stacy, PharmD
Clinical Pharmacist, Outcomes Analysis
Humana, Louisville, Kentucky
E-mail: [email protected]
REFERENCE
1. Stacy J, Shaw E, Arledge MD, Howell-Smith D. Pharmacoeconomic modeling of prior-authorization intervention for COX-2 specific inhibitors in a 3-tier
copay plan. J Managed Care Pharm. 2003;9(4):327-34.
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