Сравнение на методи
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| Анализ на разходите и ползите (CBA)× | Модел на Марковска верига в здравната икономика× | |
|---|---|---|
| Област | Икономика на здравеопазването | Икономика на здравеопазването |
| Семейство | Process / pipeline | Process / pipeline |
| Година на възникване≠ | 1970s | 1983 |
| Създател≠ | Boardman, Greenberg, and colleagues (welfare economics) | Beck & Pauker (medical decision analysis, Massachusetts General Hospital) |
| Тип | Method | Method |
| Основополагащ източник≠ | 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. link ↗ | Beck, J. R., & Pauker, S. G. (1983). The Markov Process in Medical Prognosis. Medical Decision Making, 3(4), 419-458. DOI ↗ |
| Други названия | CBA, economic appraisal, benefit-cost ratio | Markov model, state transition model, cohort simulation |
| Свързани | 5 | 5 |
| Резюме≠ | 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. | 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. |
| ScholarGateНабор от данни ↗ |
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