Evidence map›Paper›PMID 28795170›Full record

ArticleJournal of health & medical economics2016

The High Cost-related Medication Non-adherence Rate Among Medicare-Medicaid Dual-Eligible Diabetes Patients.

James X Zhang, David O Meltzer

Abstract read
In one paragraph

Article in Journal of health & medical economics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

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  4. Observational
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

James X ZhangSection of Hospital Medicine, Department of Medicine (J.X.Z., D.O.M.); Department of Economics (D.O.M.); and the Harris School of Public Policy (D.O.M.); The University of Chicago.
David O MeltzerSection of Hospital Medicine, Department of Medicine (J.X.Z., D.O.M.); Department of Economics (D.O.M.); and the Harris School of Public Policy (D.O.M.); The University of Chicago.

Funding

Research Design, Data, and Analytics CoreP30DK092949 · NIDDK · UNIVERSITY OF CHICAGO · PI ELBERT S. HUANG · 2011 to 2026
$10.0M
NIDDK NIH HHS P30 DK092949
6 · The paper itself

Abstract

contextAccess barriers to effective medication treatment have been a persistent issue for millions of older Americans despite the establishment of Medicare Part D.

objectiveWe aimed to assess the prevalence rate of cost-related medication non-adherence (CRN) and the patterns of CRN behaviors in Medicare-Medicaid dual eligibles with diabetes. DESIGN SETTING PATIENTS INTERVENTIONS AND

main outcome measuresWe used data from the 2011 Medicare Current Beneficiary Survey, a nationally representative sample of Medicare beneficiaries. Multivariate logistic regression analysis was performed to assess CRN rate, controlling for demographics and types of Medicare Part D plans.

resultsThe CRN rate in dual-eligible diabetes patients was 21%, compared to 16% in non-dual-eligible diabetes patients (p<0.01). In 2011, the standardized prevalence rate of CRN in dual-eligible diabetes patients was 21%, of those with CRN 29% reported three or more types of CRN behaviors.

conclusionContrary to the common belief that dual eligibles have better insurance coverage for medication due to the assistance from Medicaid to pay some of the out-of-pocket payments, the CRN rate among dual eligibles is high and patients often report multiple types of CRN behaviors. This demonstrates that cost is a significant access barrier for dual-eligible diabetes patients. More research is needed to improve the insurance benefit design and expand insurance coverage for this high-need, high-cost subpopulation.

Indexed as

dual eligiblemedication adherence

Identifiers

PMID28795170
PMCPMC5546751

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

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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.