방법 비교

	의료 경제학에서의 마르코프 연쇄 모형	Budget Impact Analysis (BIA)
분야	보건경제학	보건경제학
계열	Process / pipeline	Process / pipeline
기원 연도	1983	2005
창시자	Beck & Pauker (medical decision analysis, Massachusetts General Hospital)	Sullivan, Mauskopf, and colleagues (ISPOR task force)
유형	Method	Method
원전	Beck, J. R., & Pauker, S. G. (1983). The Markov Process in Medical Prognosis. Medical Decision Making, 3(4), 419-458.	Sullivan, S. D., Mauskopf, J. A., Augustovski, F., et al. (2014). Budget Impact Analysis—Principles of Good Practice: Report of the ISPOR 2012 Budget Impact Analysis Good Practice II Task Force. Value in Health, 17(1), 5-14.
별칭	Markov model, state transition model, cohort simulation	BIA, financial impact assessment, budget consequence analysis
관련	5	5
요약	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.	Budget impact analysis estimates the financial consequences (net costs or savings) of implementing a new health technology in a specific healthcare system or population over a short time horizon (typically 1–5 years). Distinct from cost-effectiveness analysis (which compares health outcomes per dollar), BIA answers a budgetary question: 'If we adopt this new drug/device, how much will it cost our health system next year?' Widely used by hospital procurement committees, insurance formularies, and government health budgets to assess financial feasibility and reimbursement decision.