Revisiting the decision rule of cost-effectiveness analysis under certainty and uncertainty.
The classical decision rule of cost-effectiveness analysis uses a threshold cost-effectiveness ratio as a cut-off point for resources allocation. One assumption of this decision rule is complete divisibility of health care programs. In this article, we argue that health care programs cannot be compl...
| Publicado en: | Social Science & Medicine Vol. 57; no. 6; pp. 969 - 975 |
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| Autores principales: | , |
| Formato: | Artículo |
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Elsevier Science
September 2003
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=513149356&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 513149356 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 02779536 SMD jtl: Social Science & Medicine issn: 02779536 maglogo: N pubinfo: dt: September 2003 vid: 57 iid: 6 pid: 2410 pub: Elsevier Science artinfo: ui: 513149356 10.1016/S0277-9536(02)00477-X ppf: 969 ppct: 6 formats: tig: atl: Revisiting the decision rule of cost-effectiveness analysis under certainty and uncertainty. aug: au: Sendi, Pedram Al, Maiwenn J. su: Medical economics Medicine -- Decision making Cost effectiveness Medical care sug: subj: Medical economics Medicine -- Decision making Cost effectiveness Medical care ab: The classical decision rule of cost-effectiveness analysis uses a threshold cost-effectiveness ratio as a cut-off point for resources allocation. One assumption of this decision rule is complete divisibility of health care programs. In this article, we argue that health care programs cannot be completely divisible since individuals are not divisible. Consequently, instead of a linear programming approach, an integer programming approach to budget allocation is suggested. The integer programming framework can be extended to include uncertainty in the analysis. An objective function (expected aggregate effects) is maximised subject to the constraint that the probability of exceeding the budget is limited to an arbitrary level (e.g., 0.05). In case the budget is exceeded, the objective function is penalised in order to account for the opportunity costs of the additional resource requirements. Copyright (c) 2003 Elsevier Ltd pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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