Comparison of Decision Modeling Approaches for Health Technology and Policy Evaluation.
Ontology highlight
ABSTRACT: We discuss tradeoffs and errors associated with approaches to modeling health economic decisions. Through an application in pharmacogenomic (PGx) testing to guide drug selection for individuals with a genetic variant, we assessed model accuracy, optimal decisions, and computation time for an identical decision scenario modeled 4 ways: using 1) coupled-time differential equations (DEQ), 2) a cohort-based discrete-time state transition model (MARKOV), 3) an individual discrete-time state transition microsimulation model (MICROSIM), and 4) discrete event simulation (DES). Relative to DEQ, the net monetary benefit for PGx testing (v. a reference strategy of no testing) based on MARKOV with rate-to-probability conversions using commonly used formulas resulted in different optimal decisions. MAR
SUBMITTER: Graves J
PROVIDER: S-EPMC9181506 | biostudies-literature | 2021 May
REPOSITORIES: biostudies-literature
ACCESS DATA