ArticleHealth services research2013
Potential bias in medication adherence studies of prevalent users.
Article in Health services research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Improvement of medication adherence in osteoporosis through telemedicine combined with email: a patient-reported experience and outcome measure-based prospective study.BMJ health & care informatics · 2025Trial
- Artificial intelligence approaches to predicting treatment non-adherence in chronic diseases: a narrative review.Frontiers in digital health · 2026Review
- Bias in pharmacoepidemiologic studies using secondary health care databases: a scoping review.BMC medical research methodology · 2019Article
- Article
- Real-World Clinical Effectiveness and Cost Savings of Liraglutide Versus Sitagliptin in Treating Type 2 Diabetes for 1 and 2 Years.Diabetes therapy : research, treatment and education of diabetes and related disorders · 2018Article
- Estimating Adherence Based on Prescription or Dispensation Information: Impact on Thresholds and Outcomes. A Real-World Study With Atrial Fibrillation Patients Treated With Oral Anticoagulants in Spain.Frontiers in pharmacology · 2018Article
- Article
- Adherence to Disease-Modifying Therapies for Multiple Sclerosis.Journal of managed care & specialty pharmacy · 2016Article
- Revisiting the washout period in the incident user study design: why 6-12 months may not be sufficient.Journal of comparative effectiveness research · 2015Article
- Real-world clinical and economic outcomes of liraglutide versus sitagliptin in patients with type 2 diabetes mellitus in the United States.Diabetes therapy : research, treatment and education of diabetes and related disorders · 2014Article
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Authors and funding
5 authors.
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Abstract
purposeWe examined how the choice of historic medication use criteria for identifying prevalent users may bias estimated adherence changes associated with a medication copayment increase.
methodsFrom pharmacy claims data in a retrospective cohort study, we identified 6,383 prevalent users of oral diabetes medications from four VA Medical Centers. Patients were included in this prevalent cohort if they had one fill both 3 months prior and 4-12 months prior to the index date, defined as the month in which medication copayments increased. To determine whether these historic medication use criteria introduced bias in the estimated response to a $5 medication copayment increase, we compared adherence trends from cohorts defined from different medication use criteria and from different index dates of copayment change. In an attempt to validate the prior observation of an upward trend in adherence prior to the date of the policy change, we replicated time series analyses varying the index dates prior to and following the date of the policy change, hypothesizing that the trend line associated with the policy change would differ from the trend lines that were not.
resultsMedication adherence trends differed when different medication use criteria were applied. Contrary to our expectations, similar adherence trends were observed when the same medication use criteria were applied at index dates when no copayment changes occurred.
conclusionTo avoid introducing bias due to study design in outcomes assessments of medication policy changes, historic medication use inclusion criteria must be chosen carefully when constructing cohorts of prevalent users. Furthermore, while pharmacy data have enormous potential for population research and monitoring, there may be inherent logical flaws that limit cohort identification solely through administrative pharmacy records.
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