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| Μέθοδος Εργαλειακών Μεταβλητών (IV) για Αιτιώδη Συμπερασματολογία× | Ανάλυση Κόστους-Αποτελεσματικότητας (CEA)× | |
|---|---|---|
| Πεδίο | Οικονομικά της Υγείας | Οικονομικά της Υγείας |
| Οικογένεια | Process / pipeline | Process / pipeline |
| Έτος προέλευσης≠ | 1990s (modern applications) | 1984 |
| Δημιουργός≠ | Angrist & Pischke (applied econometrics); rooted in econometric theory | Drummond & Stoddart (Health Economics Research Group, McMaster University) |
| Τύπος | Method | Method |
| Θεμελιώδης πηγή≠ | Angrist, J. D., & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton: Princeton University Press. link ↗ | Gold, M. R., Siegel, J. E., Russell, L. B., & Weinstein, M. C. (Eds.). (1996). Cost-Effectiveness in Health and Medicine. New York: Oxford University Press. link ↗ |
| Εναλλακτικές ονομασίες≠ | IV, two-stage least squares, TSLS, causal estimation | CEA, ICER, Incremental Cost-Effectiveness Ratio |
| Συναφείς≠ | 3 | 5 |
| Σύνοψη≠ | Instrumental variables (IV) is an econometric method to estimate causal effects when treatment or exposure is not randomly assigned and confounding is severe or unmeasured. IV relies on a third variable (instrument) that influences treatment but does not directly affect the outcome, allowing researchers to isolate the causal effect from the noise of confounding. Developed extensively in econometrics (Angrist & Pischke, 1990s–2000s), IV methods are increasingly used in health economics and health services research to leverage natural experiments and policy changes. | Cost-effectiveness analysis compares the incremental cost per unit of health benefit gained by one intervention relative to a comparator (standard care or best alternative). Developed rigorously in the 1980s by Drummond, Stoddart, and colleagues, CEA is now the standard framework for technology appraisal globally. NICE, HAS, CADTH, and other health technology assessment bodies use CEA to decide which treatments warrant public funding and at what price. |
| ScholarGateΣύνολο δεδομένων ↗ |
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