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| 보건 경제학에서의 의사결정 분석 모델링× | 의료 경제학에서의 마르코프 연쇄 모형× | |
|---|---|---|
| 분야 | 보건경제학 | 보건경제학 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 1975 | 1983 |
| 창시자≠ | Pauker & Kassirer (medical decision analysis, Massachusetts General Hospital) | Beck & Pauker (medical decision analysis, Massachusetts General Hospital) |
| 유형 | Method | Method |
| 원전≠ | Pauker, S. G., & Kassirer, J. P. (1975). Therapeutic Decision Making: A Cost-Benefit Analysis. New England Journal of Medicine, 293(5), 229-234. DOI ↗ | Beck, J. R., & Pauker, S. G. (1983). The Markov Process in Medical Prognosis. Medical Decision Making, 3(4), 419-458. DOI ↗ |
| 별칭≠ | decision analysis, decision tree, decision model, health economic model | Markov model, state transition model, cohort simulation |
| 관련 | 5 | 5 |
| 요약≠ | Decision analytic modeling is a systematic framework for comparing health interventions by integrating evidence on probabilities, outcomes, costs, and patient preferences into a quantitative model. Developed by Pauker and Kassirer in 1975, decision analysis structures clinical uncertainty and economic trade-offs, enabling transparent comparison of treatment options and identification of optimal strategies. Used in health technology assessment, clinical practice guideline development, and resource allocation decisions. | 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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