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Computing the Expected Value of Sample Information Efficiently: Practical Guidance and Recommendations for Four Model-Based Methods.
Kunst, Natalia; Wilson, Edward C F; Glynn, David; Alarid-Escudero, Fernando; Baio, Gianluca; Brennan, Alan; Fairley, Michael; Goldhaber-Fiebert, Jeremy D; Jackson, Chris; Jalal, Hawre; Menzies, Nicolas A; Strong, Mark; Thom, Howard; Heath, Anna.
Afiliação
  • Kunst N; Department of Health Management and Health Economics, University of Oslo, Oslo, Norway; Yale University School of Medicine, New Haven, CT, USA; Department of Epidemiology and Biostatistics, Amsterdam UMC, Amsterdam, The Netherlands; LINK Medical Research, Oslo, Norway. Electronic address: natalia.ku
  • Wilson ECF; Health Economics Group, Norwich Medical School, University of East Anglia, Norwich, England, UK.
  • Glynn D; University of York, York, England, UK.
  • Alarid-Escudero F; Center for Research and Teaching in Economics, Aguascalientes, Mexico.
  • Baio G; University College London, London, England, UK.
  • Brennan A; School of Health and Related Research (ScHARR), University of Sheffield, Sheffield, England, UK.
  • Fairley M; Stanford Health Policy, Centers for Health Policy and Primary Care and Outcomes Research, Stanford University, Stanford, CA, USA.
  • Goldhaber-Fiebert JD; Stanford Health Policy, Centers for Health Policy and Primary Care and Outcomes Research, Stanford University, Stanford, CA, USA.
  • Jackson C; MRC Biostatistics Unit, University of Cambridge, Cambridge, England, UK.
  • Jalal H; University of Pittsburgh, Pittsburgh, PA, USA.
  • Menzies NA; Harvard TH Chan School of Public Health, Harvard University, Boston, MA, USA.
  • Strong M; School of Health and Related Research (ScHARR), University of Sheffield, Sheffield, England, UK.
  • Thom H; University of Bristol, Bristol, England, UK.
  • Heath A; University College London, London, England, UK; The Hospital for Sick Children, Toronto, ON, Canada; University of Toronto, Toronto, ON, Canada.
Value Health ; 23(6): 734-742, 2020 06.
Article em En | MEDLINE | ID: mdl-32540231
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.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Pesquisa / Projetos de Pesquisa / Técnicas de Apoio para a Decisão / Tomada de Decisões Tipo de estudo: Guideline / Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Pesquisa / Projetos de Pesquisa / Técnicas de Apoio para a Decisão / Tomada de Decisões Tipo de estudo: Guideline / Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article