title: Recommendations for the Conduct and Reporting of Modeling and Simulation Studies in Health Technology Assessment.
abstract: Models and simulations are valuable tools for addressing the uncertainty, tradeoffs, and heterogeneous preferences that complicate research questions in health technology assessment. This article presents recommendations for the conduct and reporting of modeling and simulation studies based on a systematic review of published recommendation statements, a survey of Web sites of international health technology assessment organizations, and input from experts and other stakeholders. The recommendations apply to mathematical models that represent structural relationships among model components and integrate information from multiple sources; they address model identification, estimation, verification, and validation, as well as the conduct of sensitivity, stability, and uncertainty analyses. They are organized into model conceptualization and structure, data, model assessment and consistency, and interpreting and reporting results. They should contribute to increased use and better conduct and reporting of modeling and simulation studies in health technology assessment.
authors.affiliation: From Brown University, Providence, Rhode Island, and Tufts Medical Center, Boston, Massachusetts.
authors.forename: Issa J
authors.initials: IJ
authors.lastname: Dahabreh
authors.affiliation: From Brown University, Providence, Rhode Island, and Tufts Medical Center, Boston, Massachusetts.
authors.forename: Thomas A
authors.initials: TA
authors.lastname: Trikalinos
authors.affiliation: From Brown University, Providence, Rhode Island, and Tufts Medical Center, Boston, Massachusetts.
authors.forename: Ethan M
authors.initials: EM
authors.lastname: Balk
authors.affiliation: From Brown University, Providence, Rhode Island, and Tufts Medical Center, Boston, Massachusetts.
authors.forename: John B
authors.initials: JB
authors.lastname: Wong
mesh_terms: D003627:Data Interpretation, Statistical; D019317:Evidence-Based Medicine / Q000379:methods; D006801:Humans; D008962:Models, Theoretical; D015203:Reproducibility of Results; D013673:Technology Assessment, Biomedical / Q000379:methods*