Literature DB >> 35415193

Value of Information Analysis in Models to Inform Health Policy.

Christopher H Jackson1, Gianluca Baio2, Anna Heath3, Mark Strong4, Nicky J Welton5, Edward C F Wilson6.   

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 article gives 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 discusses the ongoing challenges in the area.

Entities:  

Keywords:  Bayesian; decision theory; design; evidence synthesis; health economics; sensitivity analysis

Year:  2022        PMID: 35415193      PMCID: PMC7612603          DOI: 10.1146/annurev-statistics-040120-010730

Source DB:  PubMed          Journal:  Annu Rev Stat Appl        ISSN: 2326-8298            Impact factor:   7.917


  47 in total

1.  Dimensions of design space: a decision-theoretic approach to optimal research design.

Authors:  Stefano Conti; Karl Claxton
Journal:  Med Decis Making       Date:  2009-07-15       Impact factor: 2.583

Review 2.  Health impact assessment of active transportation: A systematic review.

Authors:  Natalie Mueller; David Rojas-Rueda; Tom Cole-Hunter; Audrey de Nazelle; Evi Dons; Regine Gerike; Thomas Götschi; Luc Int Panis; Sonja Kahlmeier; Mark Nieuwenhuijsen
Journal:  Prev Med       Date:  2015-04-18       Impact factor: 4.018

3.  Model parameter estimation and uncertainty: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force--6.

Authors:  Andrew H Briggs; Milton C Weinstein; Elisabeth A L Fenwick; Jonathan Karnon; Mark J Sculpher; A David Paltiel
Journal:  Value Health       Date:  2012 Sep-Oct       Impact factor: 5.725

4.  Expected value of sample information for Weibull survival data.

Authors:  Alan Brennan; Samer A Kharroubi
Journal:  Health Econ       Date:  2007-11       Impact factor: 3.046

5.  Calculating the Expected Value of Sample Information in Practice: Considerations from 3 Case Studies.

Authors:  Anna Heath; Natalia Kunst; Christopher Jackson; Mark Strong; Fernando Alarid-Escudero; Jeremy D Goldhaber-Fiebert; Gianluca Baio; Nicolas A Menzies; Hawre Jalal
Journal:  Med Decis Making       Date:  2020-04-16       Impact factor: 2.583

6.  An Efficient Estimator for the Expected Value of Sample Information.

Authors:  Nicolas A Menzies
Journal:  Med Decis Making       Date:  2015-04-24       Impact factor: 2.583

7.  Bayesian history matching of complex infectious disease models using emulation: a tutorial and a case study on HIV in Uganda.

Authors:  Ioannis Andrianakis; Ian R Vernon; Nicky McCreesh; Trevelyan J McKinley; Jeremy E Oakley; Rebecca N Nsubuga; Michael Goldstein; Richard G White
Journal:  PLoS Comput Biol       Date:  2015-01-08       Impact factor: 4.475

8.  The current and potential health benefits of the National Health Service Health Check cardiovascular disease prevention programme in England: A microsimulation study.

Authors:  Oliver T Mytton; Christopher Jackson; Arno Steinacher; Anna Goodman; Claudia Langenberg; Simon Griffin; Nick Wareham; James Woodcock
Journal:  PLoS Med       Date:  2018-03-06       Impact factor: 11.069

9.  Computing the Expected Value of Sample Information Efficiently: Practical Guidance and Recommendations for Four Model-Based Methods.

Authors:  Natalia Kunst; Edward C F Wilson; David Glynn; Fernando Alarid-Escudero; Gianluca Baio; Alan Brennan; Michael Fairley; Jeremy D Goldhaber-Fiebert; Chris Jackson; Hawre Jalal; Nicolas A Menzies; Mark Strong; Howard Thom; Anna Heath
Journal:  Value Health       Date:  2020-05-27       Impact factor: 5.725

10.  Estimating the expected value of partial perfect information in health economic evaluations using integrated nested Laplace approximation.

Authors:  Anna Heath; Ioanna Manolopoulou; Gianluca Baio
Journal:  Stat Med       Date:  2016-05-18       Impact factor: 2.373

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