Comparer des méthodes

	Modèle de chaîne de Markov en économie de la santé	Analyse Coûts-Bénéfices (ACB)
Domaine	Économie de la santé	Économie de la santé
Famille	Process / pipeline	Process / pipeline
Année d'origine	1983	1970s
Auteur d'origine	Beck & Pauker (medical decision analysis, Massachusetts General Hospital)	Boardman, Greenberg, and colleagues (welfare economics)
Type	Method	Method
Source fondatrice	Beck, J. R., & Pauker, S. G. (1983). The Markov Process in Medical Prognosis. Medical Decision Making, 3(4), 419-458.	Boardman, A. E., Greenberg, D. H., Vining, A. R., & Weimer, D. L. (2018). Cost-Benefit Analysis: Concepts and Practice (5th ed.). Cambridge: Cambridge University Press.
Alias	Markov model, state transition model, cohort simulation	CBA, economic appraisal, benefit-cost ratio
Apparentées	5	5
Résumé	A Markov model is a decision-analytic tool that simulates disease progression through defined health states over time, calculating cumulative costs and quality-adjusted life years (QALYs) to enable cost-effectiveness analysis. Developed by Beck and Pauker in 1983, Markov models are now the standard framework for projecting long-term outcomes of health interventions, especially chronic diseases where patients transition between clinical states (treatment response, disease progression, remission, death). Used by health technology assessment bodies and pharmaceutical companies to predict intervention value beyond trial duration.	Cost-benefit analysis compares the total monetary value of benefits produced by a program against its total monetary costs, reporting net present value (NPV) or benefit-cost ratio (BCR). Rooted in welfare economics and used extensively in public policy (transportation, environmental, education, health), CBA answers the question: 'Is this program worth doing from a societal perspective?' Unlike cost-effectiveness analysis, CBA monetizes both costs and benefits, enabling comparison across disparate program types.