Evidence map›Paper›PMID 21751052›Full record

ArticleJournal of general internal medicine2011

Use of prescription drug samples and patient assistance programs, and the role of doctor-patient communication.

Walid F Gellad, Haiden A Huskamp, Angela Li, Yuting Zhang, Dana Gelb Safran, Julie M Donohue

Abstract read
In one paragraph

Article in Journal of general internal medicine, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
4.5field-weighted citation impact, top 7% of its field
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

12 citing papers in PubMed, 24 citations in OpenAlex.

  1. Trial
  2. Article
  3. Impact of Cost Conversation on Decision-Making Outcomes.Mayo Clinic proceedings. Innovations, quality & outcomes · 2021
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  9. Impact of rural residence on forgoing healthcare after cancer because of cost.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2013
    Article
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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

6 authors at 4 institutions in 1 country.

Walid F GelladPittsburgh Veterans Affairs Medical Center and the Center for Health Equity Research and Promotion, Pittsburgh, PA, USA. Walid.gellad@va.gov
Haiden A Huskamp
Angela Li
Yuting Zhang
Dana Gelb Safran
Julie M Donohue
University of Pittsburgh · USBlue Cross Blue Shield of Massachusetts · USHarvard University · USTufts Medical Center · US

Funding

Comparing Methods to Pay for Psychotropic Medications for Medicare BeneficiariesRC1MH088510 · NIMH · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI ZHANG, YUTING · 2009 to 2010
$912k
Racial and Ethnic Differences in Response to the Medicare Coverage Gap among PatiR01HS018657 · AHRQ · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI ZHANG, YUTING · 2010 to 2012
$676k
Impact of Medicare Part D on Racial Disparities in Diabetes Treatment and OutcomeR01HS017695 · AHRQ · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI DONOHUE, JULIE MARIE · 2009 to 2011
$628k
Racial Disparities in Older Adults: Impact of Medicare Part DR01AG034056 · NIA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI HANLON, JOSEPH T · 2009 to 2010
$451k
AHRQ HHS 1R01HS017695AHRQ HHS R01 HS017695AHRQ HHS R01 HS018657AHRQ HHS R01HS018657NIA NIH HHS 1R01AG034056NIA NIH HHS R01 AG034056NIMH NIH HHS RC1 MH088510NIMH NIH HHS RC1MH088510
6 · The paper itself

Abstract

backgroundCost-related underuse of medications is common among older adults, who seldom discuss medication costs with their physicians. Some older adults may use free drug samples or industry-sponsored patient assistance programs (PAP) in hopes of lowering out-of-pocket costs, although the long-term effect of these programs on drug spending is unclear.

objectiveTo examine older adults' use of industry-sponsored strategies to reduce out-of-pocket drug costs and the association between doctor-patient communication and use of these programs.

designCross-sectional analysis of a 2006 nationally representative survey of Medicare beneficiaries.

participants14,322 community-dwelling Medicare beneficiaries age ≥65. MAIN MEASURES: We conducted bivariate and multivariate analyses of the association between receipt of free samples and participation in PAPs with sociodemographic characteristics, health status, access to care, drug coverage, medication cost burden, and doctor-patient communication. KEY

results51.4% of seniors reported receiving at least one free sample over the last 12 months and 29.2% reported receiving free samples more than once. In contrast, only 1.3% of seniors reported participating in an industry-sponsored PAP. Higher income respondents were more likely to report free sample receipt than low-income respondents (50.8% vs. 43.8%, p < 0.001) and less likely to report participating in a PAP (0.42% vs. 2.2%, p < 0.001). In multivariate analyses, those who reported talking to their doctor about the cost of their medications had more than twice the odds of receiving samples as those who did not (OR 2.17, 95% CI 1.95-2.42).

conclusionsIn 2006, over half of seniors in Medicare received free samples, but only 1.3% reported receiving any medications from a patient assistance program. Doctor-patient communication is strongly associated with use of these programs, which has important implications for clinical care regardless of whether these programs are viewed as drivers of prescription costs or a remedy for them.

Indexed as

CommunicationPhysician-Patient RelationsAgedAged, 80 and overCross-Sectional StudiesFemaleHumansMaleMedical AssistanceMedicarePrescription DrugsPrescription FeesUnited StatesPrescription Drugs

Identifiers

PMID21751052
PMCPMC3235606
OpenAlexW1986844803

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.