CONFRONTING THE “GRAY ZONES” OF TECHNOLOGY ASSESSMENT: EVALUATING GENETIC TESTING SERVICES FOR PUBLIC INSURANCE COVERAGE IN CANADA
Identifieur interne : 003261 ( Istex/Curation ); précédent : 003260; suivant : 003262CONFRONTING THE “GRAY ZONES” OF TECHNOLOGY ASSESSMENT: EVALUATING GENETIC TESTING SERVICES FOR PUBLIC INSURANCE COVERAGE IN CANADA
Auteurs : Mita Giacomini [Canada] ; Fiona Miller [Canada] ; George BrowmanSource :
- International Journal of Technology Assessment in Health Care [ 0266-4623 ] ; 2003-04.
Abstract
We describe an evaluation model to guide public coverage of new predictive genetic tests in Ontario, Canada. The model confronts common “gray zones” in evaluation and coverage policy for challenging new technologies. Analysis addresses three domains of the evaluation picture. The first specifies evaluative criteria (purpose, effectiveness, additional effects, unit cost, demand, cost-effectiveness). The second induces or deduces acceptable cutoffs for each criterion. The third domain addresses the need to make decisions under uncertainty and to respond to “gray” evaluations with conditional-coverage decisions. The evaluation criteria should be applied within sound decision-making processes.
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DOI: 10.1017/S0266462303000278
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George Browman<affiliation><mods:affiliation>McMaster University, Hamilton Regional Cancer Centre</mods:affiliation>
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<front><div type="abstract">We describe an evaluation model to guide public coverage of new predictive genetic tests in Ontario, Canada. The model confronts common “gray zones” in evaluation and coverage policy for challenging new technologies. Analysis addresses three domains of the evaluation picture. The first specifies evaluative criteria (purpose, effectiveness, additional effects, unit cost, demand, cost-effectiveness). The second induces or deduces acceptable cutoffs for each criterion. The third domain addresses the need to make decisions under uncertainty and to respond to “gray” evaluations with conditional-coverage decisions. The evaluation criteria should be applied within sound decision-making processes.</div>
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