A Review of Web-Based Tools for Value-of-Information Analysis.


Journal

Applied health economics and health policy
ISSN: 1179-1896
Titre abrégé: Appl Health Econ Health Policy
Pays: New Zealand
ID NLM: 101150314

Informations de publication

Date de publication:
09 2021
Historique:
accepted: 11 05 2021
pubmed: 29 5 2021
medline: 26 11 2021
entrez: 28 5 2021
Statut: ppublish

Résumé

Value-of-information analysis (VOI) is a decision-theoretic approach that is used to inform reimbursement decisions, optimise trial design and set research priorities. The application of VOI analysis for informing policy decisions in practice has been limited due, in part, to the perceived complexity associated with the calculation of VOI measures. Recent efforts have resulted in the development of efficient methods to estimate VOI measures and the development of user-friendly web-based tools to facilitate VOI calculations. We review the existing web-based tools including Sheffield Accelerated Value of Information (SAVI), the web interface to the BCEA (Bayesian Cost-Effectiveness Analysis) R package (BCEAweb), Rapid Assessment of Need for Evidence (RANE), and Value of Information for Cardiovascular Trials and Other Comparative Research (VICTOR). We describe what each tool is designed to do, the inputs they require, and the outputs they produce. Finally, we discuss how tools for VOI calculations might be improved in the future to facilitate the use of VOI analysis in practice.

Identifiants

pubmed: 34046866
doi: 10.1007/s40258-021-00662-4
pii: 10.1007/s40258-021-00662-4
pmc: PMC7613968
mid: EMS158428
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

645-651

Subventions

Organisme : Medical Research Council
ID : G0601721
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_UU_00002/11
Pays : United Kingdom
Organisme : National Health and Medical Research Council
ID : GNT1121232

Informations de copyright

© 2021. The Author(s), under exclusive licence to Springer Nature Switzerland AG.

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Auteurs

Haitham Tuffaha (H)

Centre for the Business and Economics of Health, The University of Queensland, Brisbane, QLD, 4067, Australia. h.tuffaha@uq.edu.au.

Claire Rothery (C)

Centre for Health Economics, University of York, York, UK.

Natalia Kunst (N)

Department of Health Management and Health Economics, University of Oslo, Oslo, Norway.
Public Health Modeling Unit, Yale University School of Public Health, New Haven, CT, USA.

Chris Jackson (C)

Medical Research Council Biostatistics Unit, University of Cambridge, Cambridge, UK.

Mark Strong (M)

School for Health and Related Research, University of Sheffield, Sheffield, UK.

Stephen Birch (S)

Centre for the Business and Economics of Health, The University of Queensland, Brisbane, QLD, 4067, Australia.

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Classifications MeSH