Determining Criteria and Weights for Prioritizing Health Technologies Based on the Preferences of the General Population: A New Zealand Pilot Study

Abstract Objectives The use of multicriteria decision analysis for health technology prioritization depends on decision-making criteria and weights according to their relative importance. We report on a methodology for determining criteria and weights that was developed and piloted in New Zealand an...

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Veröffentlicht in:Value in health 2017-04, Vol.20 (4), p.679-686
Hauptverfasser: Sullivan, Trudy, PhD, Hansen, Paul, PhD
Format: Artikel
Sprache:eng
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Zusammenfassung:Abstract Objectives The use of multicriteria decision analysis for health technology prioritization depends on decision-making criteria and weights according to their relative importance. We report on a methodology for determining criteria and weights that was developed and piloted in New Zealand and enables extensive participation by members of the general population. Methods Stimulated by a preliminary ranking exercise that involved prioritizing 14 diverse technologies, six focus groups discussed what matters to people when thinking about technologies that should be funded. These discussions informed the specification of criteria related to technologies’ benefits for use in a discrete choice survey designed to generate weights for each individual participant as well as mean weights. A random sample of 3218 adults was invited to participate. To check test-retest reliability, a subsample completed the survey twice. Cluster analysis was performed to identify participants with similar patterns of weights. Results Six benefits-related criteria were distilled from the focus group discussions and included in the discrete choice survey, which was completed by 322 adults (10% response rate). Most participants (85%) found the survey easy to understand, and the survey exhibited test-retest reliability. The cluster analysis revealed that participant weights are related more to idiosyncratic personal preferences than to demographic and background characteristics. Conclusions The methodology enables extensive participation by members of the general population, for whom it is both acceptable and reliable. Generating weights for each participant allows the heterogeneity of individual preferences, and the extent to which they are related to demographic and background characteristics, to be tested.
ISSN:1098-3015
1524-4733
DOI:10.1016/j.jval.2016.12.008