Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Modelado de análisis de decisiones en economía de la salud× | Modelo de Cadena de Markov en Economía de la Salud× | |
|---|---|---|
| Campo | Economía de la salud | Economía de la salud |
| Familia | Process / pipeline | Process / pipeline |
| Año de origen≠ | 1975 | 1983 |
| Autor original≠ | Pauker & Kassirer (medical decision analysis, Massachusetts General Hospital) | Beck & Pauker (medical decision analysis, Massachusetts General Hospital) |
| Tipo | Method | Method |
| Fuente seminal≠ | 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 ↗ |
| Alias≠ | decision analysis, decision tree, decision model, health economic model | Markov model, state transition model, cohort simulation |
| Relacionados | 5 | 5 |
| Resumen≠ | 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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