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健康経済学における支払意思額(WTP)×健康経済学におけるマルコフ連鎖モデル×
分野医療経済学医療経済学
系統Process / pipelineProcess / pipeline
提唱年1980s1983
提唱者Carson & Louviere (stated preference/contingent valuation methods)Beck & Pauker (medical decision analysis, Massachusetts General Hospital)
種類MethodMethod
原典Carson, R. T., & Louviere, J. J. (2011). A Common Nomenclature for Stated Choice Studies. In S. Hess & A. Daly (Eds.), Choice Modelling: The State of the Art and the State of Practice. Cheltenham: Edward Elgar. link ↗Beck, J. R., & Pauker, S. G. (1983). The Markov Process in Medical Prognosis. Medical Decision Making, 3(4), 419-458. DOI ↗
別名WTP, contingent valuation, stated preference methodMarkov model, state transition model, cohort simulation
関連55
概要Willingness to pay (WTP) is an economic valuation method that elicits what individuals or society are willing to spend for a health benefit or to avoid a health risk. Rooted in contingent valuation (Carson & Louviere, 1980s), WTP is used to monetize health outcomes for cost-benefit analysis and to infer implicit cost-effectiveness thresholds from actual healthcare spending patterns. Unlike revealed preference (observing actual spending behavior), WTP uses stated preferences—surveys asking respondents: 'How much would you pay for this health improvement?'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.
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ScholarGate手法を比較: Willingness to Pay in Health · Markov Model in Health Economics. 2026-06-20に以下より取得 https://scholargate.app/ja/compare