手法を比較

	健康経済学におけるマルコフ連鎖モデル	費用対効果分析 (CEA)
分野	医療経済学	医療経済学
系統	Process / pipeline	Process / pipeline
提唱年	1983	1984
提唱者	Beck & Pauker (medical decision analysis, Massachusetts General Hospital)	Drummond & Stoddart (Health Economics Research Group, McMaster University)
種類	Method	Method
原典	Beck, J. R., & Pauker, S. G. (1983). The Markov Process in Medical Prognosis. Medical Decision Making, 3(4), 419-458.	Gold, M. R., Siegel, J. E., Russell, L. B., & Weinstein, M. C. (Eds.). (1996). Cost-Effectiveness in Health and Medicine. New York: Oxford University Press.
別名	Markov model, state transition model, cohort simulation	CEA, ICER, Incremental Cost-Effectiveness Ratio
関連	5	5
概要	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-effectiveness analysis compares the incremental cost per unit of health benefit gained by one intervention relative to a comparator (standard care or best alternative). Developed rigorously in the 1980s by Drummond, Stoddart, and colleagues, CEA is now the standard framework for technology appraisal globally. NICE, HAS, CADTH, and other health technology assessment bodies use CEA to decide which treatments warrant public funding and at what price.