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| Budget Impact Analysis (BIA)× | Entscheidungsanalytische Modellierung in der Gesundheitsökonomie× | |
|---|---|---|
| Fachgebiet | Gesundheitsökonomie | Gesundheitsökonomie |
| Familie | Process / pipeline | Process / pipeline |
| Entstehungsjahr≠ | 2005 | 1975 |
| Urheber≠ | Sullivan, Mauskopf, and colleagues (ISPOR task force) | Pauker & Kassirer (medical decision analysis, Massachusetts General Hospital) |
| Typ | Method | Method |
| Wegweisende Quelle≠ | 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. DOI ↗ | Pauker, S. G., & Kassirer, J. P. (1975). Therapeutic Decision Making: A Cost-Benefit Analysis. New England Journal of Medicine, 293(5), 229-234. DOI ↗ |
| Aliasnamen≠ | BIA, financial impact assessment, budget consequence analysis | decision analysis, decision tree, decision model, health economic model |
| Verwandt | 5 | 5 |
| Zusammenfassung≠ | 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. | 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. |
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