Kunst, Natalia orcid.org/0000-0002-2409-4246, Wilson, Edward C F, Glynn, David orcid.org/0000-0002-0989-1984 et al. (11 more authors) (2020) Computing the Expected Value of Sample Information Efficiently:Practical Guidance and Recommendations for Four Model-Based Methods. Value in Health. pp. 734-742. ISSN 1524-4733
Abstract
Value of information (VOI) analyses can help policy makers make informed decisions about whether to conduct and how to design future studies. Historically a computationally expensive method to compute the expected value of sample information (EVSI) restricted the use of VOI to simple decision models and study designs. Recently, 4 EVSI approximation methods have made such analyses more feasible and accessible. Members of the Collaborative Network for Value of Information (ConVOI) compared the inputs, the analyst’s expertise and skills, and the software required for the 4 recently developed EVSI approximation methods. Our report provides practical guidance and recommendations to help inform the choice between the 4 efficient EVSI estimation methods. More specifically, this report provides: (1) a step-by-step guide to the methods’ use, (2) the expertise and skills required to implement the methods, and (3) method recommendations based on the features of decision-analytic problems.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020, ISPOR–The Professional Society for Health Economics and Outcomes Research. Published by Elsevier Inc. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. |
Keywords: | Decision Making,Decision Support Techniques,Humans,Policy Making,Research/economics,Research Design,Software |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Social Sciences (York) > Centre for Health Economics (York) |
Depositing User: | Pure (York) |
Date Deposited: | 16 Jul 2020 10:10 |
Last Modified: | 07 Feb 2025 00:28 |
Published Version: | https://doi.org/10.1016/j.jval.2020.02.010 |
Status: | Published |
Refereed: | Yes |
Identification Number: | 10.1016/j.jval.2020.02.010 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:163335 |
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