Evidence map›Paper›PMID 23402554›Full record

ArticleHealth services research2013

Potential bias in medication adherence studies of prevalent users.

Matthew L Maciejewski, Chris L Bryson, Virginia Wang, Mark Perkins, Chuan-Fen Liu

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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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10citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Trial
  2. Review
  3. Article
  4. Article
  5. 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 · 2018
    Article
  6. Article
  7. Article
  8. Adherence to Disease-Modifying Therapies for Multiple Sclerosis.Journal of managed care & specialty pharmacy · 2016
    Article
  9. Article
  10. 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 · 2014
    Article
4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Matthew L MaciejewskiDivision of General Internal Medicine, Department of Medicine, Duke University, Durham, NC 27705, USA. matthew.maciejewski@va.gov
Chris L Bryson
Virginia Wang
Mark Perkins
Chuan-Fen Liu

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

BiasDrug MonitoringAgedAged, 80 and overDeductibles and CoinsuranceDrug CostsFemaleHealth Services ResearchHumansMaleMiddle AgedPrescription DrugsTime FactorsPrescription Drugscost sharinginclusion criteriaMedication adherencepharmaceutical policyresearch designveterans

Identifiers

PMID23402554
PMCPMC3725535

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.