Affiliation:
1. Department of Statistical Science, University College London, London, UK (AH, IM, GB)
Abstract
In recent years, value-of-information analysis has become more widespread in health economic evaluations, specifically as a tool to guide further research and perform probabilistic sensitivity analysis. This is partly due to methodological advancements allowing for the fast computation of a typical summary known as the expected value of partial perfect information (EVPPI). A recent review discussed some approximation methods for calculating the EVPPI, but as the research has been active over the intervening years, that review does not discuss some key estimation methods. Therefore, this paper presents a comprehensive review of these new methods. We begin by providing the technical details of these computation methods. We then present two case studies in order to compare the estimation performance of these new methods. We conclude that a method based on nonparametric regression offers the best method for calculating the EVPPI in terms of accuracy, computational time, and ease of implementation. This means that the EVPPI can now be used practically in health economic evaluations, especially as all the methods are developed in parallel with R functions and a web app to aid practitioners.
Funder
MapI
Engineering and Physical Sciences Research Council
Reference35 articles.
1. Probabilistic sensitivity analysis for NICE technology assessment: not an optional extra
2. Methods for health economic evaluations: a guideline based on current practices in Europe (2nd draft). Diemen (The Netherlands): European Network for Health Technology Assessment;2014.
3. Guidelines for the economic evaluation of health technologies: Canada (3rd ed). Ottawa (ON): Canadian Agency for Drugs and Technologies in Health; 2006.
4. Guidelines for preparing submissions to the Pharmaceutical Benefits Advisory Committee: version 4.3. Canberra (Australia): Department of Health and Ageing; 2008.
5. Information Value Theory
Cited by
67 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献