Modeling good research practices-overview: A report of the ISPOR-SMDM modeling good research practices task force-1

J. Jaime Caro, Andrew H. Briggs, Uwe Siebert, Karen M. Kuntz

Research output: Contribution to journalArticlepeer-review

219 Scopus citations

Abstract

Models-mathematical frameworks that facilitate estimation of the consequences of health care decisions-have become essential tools for health technology assessment. Evolution of the methods since the first ISPOR modeling task force reported in 2003 has led to a new task force, jointly convened with the Society for Medical Decision Making, and this series of seven papers presents the updated recommendations for best practices in conceptualizing models; implementing state-transition approaches, discrete event simulations, or dynamic transmission models; dealing with uncertainty; and validating and reporting models transparently. This overview introduces the work of the task force, provides all the recommendations, and discusses some quandaries that require further elucidation. The audience for these papers includes those who build models, stakeholders who utilize their results, and, indeed, anyone concerned with the use of models to support decision making.

Original languageEnglish (US)
Pages (from-to)667-677
Number of pages11
JournalMedical Decision Making
Volume32
Issue number5
DOIs
StatePublished - Sep 2012

Bibliographical note

Funding Information:
Source of financial support: This Task Force was supported by ISPOR.

Keywords

  • good practice
  • guidelines
  • methods
  • modeling

Fingerprint Dive into the research topics of 'Modeling good research practices-overview: A report of the ISPOR-SMDM modeling good research practices task force-1'. Together they form a unique fingerprint.

Cite this