Evidence map›Paper›PMID 39562326›Full record

ArticleInternational journal of technology assessment in health care2024

A genuine need or nice to have? Understanding HTA representatives' perspectives on the use of patient preference data.

Evi Germeni, Simon Fifer, Mickaël Hiligsmann, Barry Stein, Mandy Tonkinson, Maya Joshi, Alissa Hanna, Barry Liden, Deborah A Marshall

Abstract read
In one paragraph

Article in International journal of technology assessment in health care, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. How Patients Can Contribute to the Assessments of Health Technologies.Journal of market access & health policy · 2025
    Article
  2. Review
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

9 authors.

Evi GermeniHealth Economics and Health Technology Assessment (HEHTA), School of Health and Wellbeing, University of Glasgow, Glasgow, UK.ORCID https://orcid.org/0000-0001-5576-8816
Simon FiferCommunity and Patient Preference Research (CaPPRe), Sydney, New South Wales, Australia.
Mickaël HiligsmannDepartment of Health Services Research, CAPHRI Care and Public Health Research Institute, Maastricht University, Maastricht, The Netherlands.ORCID https://orcid.org/0000-0003-4274-9258
Barry SteinColorectal Cancer Canada (CCC), Montreal, Quebec, Canada.
Mandy TonkinsonPublic Involvement Programme, National Institute for Health and Care Excellence (NICE), Manchester, UK.
Maya JoshiCommunity and Patient Preference Research (CaPPRe), Sydney, New South Wales, Australia.
Alissa HannaPatient Engagement, Edwards Lifesciences, Irvine, CA, USA.ORCID https://orcid.org/0000-0001-7246-2843
Barry LidenLeonard D. Shaeffer Center for Health Policy and Economics, University of Southern California, Los Angeles, California, USA.ORCID https://orcid.org/0000-0001-9228-8037
Deborah A MarshallDepartment of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThe roles and potential value of patient preference (PP) data in health technology assessment (HTA) remain to be fully realized despite an expanding literature and various efforts to establish their utility. This article reports lessons learned through a series of collaborative workshops with HTA representatives, organized by the Health Technology Assessment International's Patient Preferences Project Subcommittee.

methodsFive online workshops were conducted between June 2022 and June 2023, seeking to facilitate collaborative learning and reflection on ways that PP data can be integrated into HTA. Participants included nine HTA representatives from the United States, Canada, Australia, England, and the Netherlands. Workshops were recorded, transcribed, and thematically analyzed.

resultsDespite appreciating the value of PP data, participants were ambivalent about their use in HTA. Some felt that they were already getting the information they needed from the cost-effectiveness analysis or existing patient involvement processes. Others thought that PP data would be very helpful at the initial and final stage of the decision-making process and, particularly, in the following cases: (a) when technology has important non-health benefits; (b) when the clinical and/or cost-effectiveness evidence is marginal; and (c) when treatment is indicated for a large and heterogeneous population. Issues related to the validity and reliability of PP studies were frequently raised, with preference heterogeneity at the core of these concerns.

conclusionsCollaborating with HTA representatives in the "co-creation" of PP research can help address their concerns and facilitate mutual learning about how PP data can be used in HTA.

Indexed as

Patient PreferenceTechnology Assessment, BiomedicalCost-Benefit AnalysisDecision MakingHumansPatient ParticipationReproducibility of Resultshealth technology assessmentpatient participationpatient preferencesstakeholder engagement

Identifiers

PMID39562326
PMCPMC11579672

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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.