Published Online: September 07, 2009
Allison B. Rosen, MD, MPH, ScD; Alicen B. Spaulding, MPH; Dan Greenberg, PhD; Jennifer A. Palmer, MS; and Peter J. Neumann, ScD
Background: Despite evidence that medication adherence can influence cost-effectiveness analysis (CEA) results, the extent to which published CEAs include adherence has not been fully characterized.
Objectives: To characterize inclusion of patient adherence in CEAs of self-administered medications and to examine whether industry sponsorship affects adherence inclusion, because adherence exclusion might overstate the interventions’ costeffectiveness.
Study Design: Systematic review of the Englishlanguage medical literature published between 1998 and 2003 identified 177 original CEAs of self-administered medications.
Methods: Two trained readers independently abstracted data. Adherence inclusion was estimated overall and by study characteristics. Predictors of inclusion were assessed with c2 tests and logistic regression.
Results: Among 177 CEAs, 30.5% explicitly modeled adherence; of these, only half modeled adherence in both base-case and sensitivity analyses. Only 21% of studies performed sensitivity analysis on adherence; fewer than half of these provided sufficient information to determine the impact on results. Of the remaining 20 studies, 9 were sensitive to adherence. Adherence inclusion varied across clinical areas (P = .022). Only 30% of chronic anticoagulation studies, 52% of cardiovascular risk reduction studies, 38% of neuropsychiatric studies, and 32% of HIV antiretroviral studies considered suboptimal adherence. Among 128 CEAs that disclosed study sponsorship, adherence was included in 25.4% of industry-sponsored and 35.1% of non–industrysponsored studies (P = .17).
Conclusions: Few CEAs modeled suboptimal medication adherence. As CEAs are meant to model “real world” costs and effects of interventions, investigators would do well to explicitly consider medication adherence in the future.
(Am J Manag Care. 2009;15(9):626-632)
Suboptimal medication adherence remains pervasive in the US healthcare system, resulting in substantial adverse health and economic effects. Despite a growing body of evidence that adherence can influence cost-effectiveness analyses (CEAs), the extent to which published CEAs include adherence has not been fully characterized.
- Fewer than one-third of published CEAs modeled suboptimal adherence.
- In the small subset of studies that varied adherence in sensitivity analyses, the impact on cost-effectiveness often was substantial.
- With payers and policymakers increasingly turning to these studies for guidance, failure to account for nonadherence may lead to suboptimal resource allocation strategies.
Medication adherence is perhaps the most important determinant of the therapeutic effectiveness of medications.1 Yet suboptimal adherence remains pervasive in the US healthcare system, resulting in substantial adverse health and economic effects.2,3 Overall, rates of nonadherence are high—fewer than 50% of patients with chronic diseases take their medications as prescribed.4 In turn, poor adherence is associated with disease progression, complications, avoidable hospitalizations, and death,1,2,5-7 as well as increased medical costs for some chronic diseases.6,8,9 Indeed, it has been estimated that suboptimal adherence is responsible for an estimated $177 billion in total direct and indirect health spending annually in the United States.1
Given the substantial impact of adherence on health and spending, inclusion of adherence in economic evaluations may be critical for informing policymakers about the value of therapies in actual practice. Indeed, past studies have shown that adherence can influence the results and recommendations of cost-effectiveness analyses (CEAs).10-12 Despite the importance of adherence, however, the extent to which published CEAs consider it has not been fully characterized. Our objective was to examine the inclusion of patient adherence in CEAs of self-administered medications. Because the exclusion of adherence might overstate the cost-effectiveness of evaluated interventions, we also examined the relationship between pharmaceutical company sponsorship and inclusion of adherence.
Cost-effectiveness analyses compare alternative approaches to a health problem to determine the relative costs and benefits of each. Cost-utility analyses, the subset of CEAs with health benefits measured in quality-adjusted life-years (QALYs), represent the gold standard for conducting and reporting of CEAs in medicine.13 For the remainder of this article, we use CEA to refer to cost/QALY studies.
Development of CEA Registry
We previously reported on the development of a comprehensive registry of CEAs published in the public health and medical literature from 1976 through 1997.14-16 The Tufts cost-effectiveness analysis registry is continuously updated and maintained on the Internet as a free, public use resource (http://www.cearegistry.org). As part of the updates to this registry, we conducted a systematic review of the English-language medical literature published between 1998 and 2003. We searched MEDLINE for the following medical subject headings and text keywords: “qualityadjusted,” “quality-adjusted life year(s),” “QALY,” “adjusted life year(s),” “cost-utility,” and several variations of these terms. To identify potentially overlooked studies, our search findings were validated to those of the Health Economic Evaluation Database maintained by the British Office of Health Economics.17 Our search identified 2528 candidate articles published between 1998 and 2003. We then screened titles and abstracts to remove noneligible articles, such as methodologic and review articles, and studies that did not use cost/QALY as their main outcome measure. A final list of 568 published cost-utility analyses were included in the registry for the years 1998 through 2003.
Study Selection and Data Abstraction
Of the 568 cost-utility analyses, 226 had a medication component in the intervention or comparator. To restrict analyses to studies in which patient adherence was applicable, we excluded studies in which medications were administered by injection or infusion (n = 27), in an acute-care setting (n = 14), or by someone else (often the physician) for other reasons (n = 8). The final sample included 177 CEAs of self-administered medications (available at https://research.tufts-nemc. org/cear/related/ajmcappendix.pdf). Each article was reviewed by 2 independent readers, who abstracted select data elements from each article; consensus meetings were held to review and resolve discrepancies. We collected data on a wide variety of elements related to the methods, results, and quality of reporting in the article, along with data on study inclusion of adherence to therapies. In addition, we abstracted data on the source of funding for each study (when reported).
Adherence. Readers recorded whether medication adherence was (1) included in the base-case analysis only, (2) included in sensitivity analyses only, (3) included in both the base-case and sensitivity analyses, (4) mentioned in the manuscript but not included in analyses, or (5) not mentioned. If the results of sensitivity analyses on adherence were reported in the text, tables, figures, or an appendix, they were considered “sufficient” to judge the impact of adherence. Of studies with sufficient data, we report whether the authors describe the results as sensitive to adherence. In practice, adherence has many different definitions, measurement approaches, and even names (eg, compliance, persistence).2 For the purposes of this analysis, we included any form of adherence regardless of whether or how it was defined.
Additional Covariates. Readers abstracted data from each study on the expected duration of intervention therapy, study sponsorship, and the clinical condition of interest. Intervention medications were classified as short term if therapy duration was expected to be less than 1 month. Study sponsorship was categorized as unknown if no funding source was listed, industry-sponsored if at least 1 funding source or 1 author’s affiliation was a pharmaceutical or medical device company, and non–industry-sponsored if all funding came from governments, foundations, or other nonindustry sources. Study settings included the United States, the United Kingdom, Canada, and an “other country” category that included any country that served as the CEA setting in 10 or fewer studies. Studies were grouped into the following clinical categories: cardiovascular risk factors and disease (CVD), cancers, HIV and AIDS, other infectious diseases, hepatitis, other gastrointestinal conditions, musculoskeletal conditions (including osteoporosis), neurologic conditions, psychiatric conditions, pulmonary diseases, and an “other disease” category that included any clinical conditions examined in fewer than 5 CEAs. Additionally, a separate anticoagulation category was included because of the large number of CEAs published in this area. To assess whether the inclusion of adherence in CEAs has improved over time, we also created a variable indicating whether the study was published earlier (1998-2000) or later (2001-2003) in the 6-year study window.
We examined the frequency with which adherence was included in CEAs, as well as the extent to which it was included. The kappa interrater reliability score for adherence inclusion was 0.84, representing strong agreement between reviewers.18 Associations between adherence inclusion and duration of therapy, study sponsorship, publication window, study setting (country), and disease categories were assessed with X2 tests. Logistic regression was performed with inclusion of adherence in either the base-case or sensitivity analyses as the dependent variable, and therapy duration, study sponsorship, publication window, and disease category as independent variables. Analyses were conducted using SAS version 9.1 (SAS Institute, Inc, Cary, NC).
Among the 177 CEAs of self-administered medications, only 30.5% (n = 54) explicitly modeled patient adherence to therapy, whereas an additional 16.4% mentioned but did not model medication adherence (Figure 1). Of the 54 studies that did model adherence, only half (14.7% of all studies, or 26 studies) modeled adherence in both the base-case and sensitivity analyses. In those studies that included adherence in the base case, the most common base-case assumption was that medication nonadherence and/or discontinuation rates were the same as those rates reported in clinical trials. Adherence was equally likely to be considered in CEAs of long-term versus short-term drug therapy (29.6% vs 30.3%; not significant).
Study inclusion of adherence varied significantly across clinical areas (P = .022). Only 30% of chronic anticoagulation studies, 52% of cardiovascular risk reduction studies, 38% of neuropsychiatric studies, and 32% of HIV antiretroviral studies included suboptimal adherence in either the base-case or sensitivity analyses. Figure 2 shows the extent to which adherence inclusion varied across clinical areas.
Eighty-four CEAs were set in the United States, 23 in the United Kingdom, 19 in Canada, and 10 or fewer in all other countries. In 35% of studies set in the United States, 30% of those set in the United Kingdom, 32% in Canada, and 25% of studies set in other countries, adherence was included in either the base-case or sensitivity analyses (differences were nonsignificant).
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