Value of Information Analysis in Models to inform Health Policy

Christopher H Jackson, Gianluca Baio, Anna Heath, Mark Strong, Nicky J Welton, Edward C.F. Wilson

Research output: Contribution to journalArticle (Academic Journal)peer-review

Abstract

Value of Information (VoI) is a decision-theoretic approach to estimating the expected benefits from collecting further information of different kinds, in scientific problems based on combining one or more sources of data. VoI methods can assess the sensitivity of models to different sources of uncertainty, and help to set priorities for further data collection. They have been widely applied in healthcare policy making, but the ideas are general to a range of evidence synthesis and decision problems. This paper will give a broad overview of VoI methods, explaining the principles behind them, the range of problems that can be tackled with them, and how they can be implemented, and discuss the ongoing challenges in the area.
Original languageEnglish
JournalAnnual Review of Statistics and Its Application
Publication statusAccepted/In press - 30 Jul 2021

Keywords

  • decision theory
  • evidence synthesis
  • health economics
  • Bayesian
  • sensitivity analysis
  • design

Fingerprint

Dive into the research topics of 'Value of Information Analysis in Models to inform Health Policy'. Together they form a unique fingerprint.

Cite this