Tuffaha, H., Rothery, C., Kunst, N. et al. (3 more authors) (2021) A review of web-based tools for value-of-information analysis. Applied Health Economics and Health Policy, 19 (5). pp. 645-651. ISSN 1175-5652
Abstract
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.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2021 The Author(s), under exclusive licence to Springer Nature Switzerland AG. This is an author-produced version of a paper subsequently published in Applied Health Economics and Health Policy. Uploaded in accordance with the publisher's self-archiving policy. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > School of Health and Related Research (Sheffield) > ScHARR - Sheffield Centre for Health and Related Research |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 25 May 2021 07:06 |
Last Modified: | 28 May 2022 00:38 |
Status: | Published |
Publisher: | Springer Nature |
Refereed: | Yes |
Identification Number: | 10.1007/s40258-021-00662-4 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:174105 |