Evidence map›Paper›PMID 32357873›Full record

ArticleBMC health services research2020

Eliciting patient views on the allocation of limited healthcare resources: a deliberation on hepatitis C treatment in the Veterans Health Administration.

Akbar K Waljee, Kerry A Ryan, Chris D Krenz, George N Ioannou, Lauren A Beste, Monica A Tincopa, Sameer D Saini, Grace L Su, Maria E Arasim, Patti T Roman and 2 more

Abstract read
In one paragraph

Article in BMC health services research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Building trust: public priorities for health care AI labeling.The American journal of managed care · 2026
    Article
  3. Article
  4. Article
  5. 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

12 authors.

Akbar K WaljeeVA Ann Arbor Health Services Research and Development Center of Clinical Management Research, 2215 Fuller Road, Mail Stop 152, Ann Arbor, MI, 48105, USA. awaljee@med.umich.edu.
Kerry A RyanCenter for Bioethics and Social Sciences in Medicine, University of Michigan Medical School, 2800 Plymouth Road, North Campus Research Complex, Bldg. 14, G016, Ann Arbor, MI, 48109-2800, USA.
Chris D KrenzCenter for Bioethics and Social Sciences in Medicine, University of Michigan Medical School, 2800 Plymouth Road, North Campus Research Complex, Bldg. 14, G016, Ann Arbor, MI, 48109-2800, USA.
George N IoannouVeterans Affairs Puget Sound Healthcare System, 1660 South Columbian Way, Seattle, WA, 98108, USA.
Lauren A BesteDivision of Gastroenterology, Department of Medicine, University of Washington, 1959 NE Pacific St., Box 356424, Seattle, WA, 98195-6424, USA.
Monica A TincopaMichigan Medicine, Department of Internal Medicine, Division of Gastroenterology and Hepatology, 3912 Taubman Center, 1500 East Medical Center Drive, SPC 5362, Ann Arbor, MI, 48109-5362, USA.
Sameer D SainiVA Ann Arbor Health Services Research and Development Center of Clinical Management Research, 2215 Fuller Road, Mail Stop 152, Ann Arbor, MI, 48105, USA.
Grace L SuVA Ann Arbor Health Services Research and Development Center of Clinical Management Research, 2215 Fuller Road, Mail Stop 152, Ann Arbor, MI, 48105, USA.
Maria E ArasimVA Ann Arbor Health Services Research and Development Center of Clinical Management Research, 2215 Fuller Road, Mail Stop 152, Ann Arbor, MI, 48105, USA.
Patti T RomanVA Ann Arbor Health Services Research and Development Center of Clinical Management Research, 2215 Fuller Road, Mail Stop 152, Ann Arbor, MI, 48105, USA.
Brahmajee K NallamothuVA Ann Arbor Health Services Research and Development Center of Clinical Management Research, 2215 Fuller Road, Mail Stop 152, Ann Arbor, MI, 48105, USA.
Raymond De VriesCenter for Bioethics and Social Sciences in Medicine, University of Michigan Medical School, 2800 Plymouth Road, North Campus Research Complex, Bldg. 14, G016, Ann Arbor, MI, 48109-2800, USA.

Funding

Advanced Prediction Models to Optimize Treatment and Access for Veterans with Hepatitis CI01HX002220 · VA · VETERANS HEALTH ADMINISTRATION · PI WALJEE, AKBAR K · 2018 to 2021
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HSRD VA I01 HX002220
6 · The paper itself

Abstract

backgroundIn response to the development of highly effective but expensive new medications, policymakers, payors, and health systems are considering novel and pragmatic ways to provide these medications to patients. One approach is to target these treatments to those most likely to benefit. However, to maximize the fairness of these policies, and the acceptance of their implementation, the values and beliefs of patients should be considered. The provision of treatments for chronic hepatitis C (CHC) in the resource-constrained context of the Veterans Health Administration (VHA) offered a real-world example of this situation, providing the opportunity to test the value of using Democratic Deliberation (DD) methods to solicit the informed opinions of laypeople on this complex issue.

methodsWe recruited Veterans (n = 30) from the VHA to attend a DD session. Following educational presentations from content experts, participants engaged in facilitated small group discussions to: 1) identify strategies to overcome CHC treatment barriers and 2) evaluate, vote on, and modify/improve two CHC treatment policies - "first come, first served" (FCFS) and "sickest first" (SF). We used transcripts and facilitators' notes to identify key themes from the small group discussions. Additionally, participants completed pre- and post-DD surveys.

resultsMost participants endorsed the SF policy over the FCFS policy, emphasizing the ethical and medical appropriateness of treating the sickest first. Concerns about SF centered on the difficulty of implementation (e.g., how is "sickest" determined?) and unfairness to other Veterans. Proposed modifications focused on: 1) the need to consider additional health factors, 2) taking behavior and lifestyle into account, 3) offering education and support, 4) improving access, and 5) facilitating better decision-making.

conclusionsDD offered a robust and useful method for addressing the allocation of the scarce resource of CHC treatment. Participants were able to develop a modified version of the SF policy and offered diverse recommendations to promote fairness and improve quality of care for Veterans. DD is an effective approach for incorporating patient preferences and gaining valuable insights for critical healthcare policy decisions in resource-limited environments.

Indexed as

Attitude to HealthAgedFemaleHealth Care RationingHepatitis C, ChronicHumansMaleMiddle AgedQualitative ResearchUnited StatesUnited States Department of Veterans AffairsVeteransDemocratic DeliberationHealth policyHepatitis CPublic deliberationQualitative researchVAVeterans

Identifiers

PMID32357873
PMCPMC7193376

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.