Using Multicriteria Decision Analysis to Support Research Priority Setting in Biomedical Translational Research Projects

Translational research is conducted to achieve a predefined set of economic or societal goals. As a result, investment decisions on where available resources have the highest potential in achieving these goals have to be made. In this paper, we first describe how multicriteria decision analysis can assist in defining the decision context and in ensuring that all relevant aspects of the decision problem are incorporated in the decision making process. We then present the results of a case study to support priority setting in a translational research consortium aimed at reducing the burden of di... Mehr ...

Verfasser: de Graaf, Gimon
Postmus, Douwe
Buskens, Erik
Dokumenttyp: Artikel
Erscheinungsdatum: 2015
Reihe/Periodikum: de Graaf , G , Postmus , D & Buskens , E 2015 , ' Using Multicriteria Decision Analysis to Support Research Priority Setting in Biomedical Translational Research Projects ' , Biomed Research International , vol. 2015 , 191809 . https://doi.org/10.1155/2015/191809
Schlagwörter: ACCEPTABILITY ANALYSIS / TECHNOLOGY-ASSESSMENT / NETHERLANDS / SELECTION / CRITERIA / SMAA
Sprache: Englisch
Permalink: https://search.fid-benelux.de/Record/base-29190509
Datenquelle: BASE; Originalkatalog
Powered By: BASE
Link(s) : https://hdl.handle.net/11370/27ef4e53-339e-41c8-9265-f8db42ecc2be

Translational research is conducted to achieve a predefined set of economic or societal goals. As a result, investment decisions on where available resources have the highest potential in achieving these goals have to be made. In this paper, we first describe how multicriteria decision analysis can assist in defining the decision context and in ensuring that all relevant aspects of the decision problem are incorporated in the decision making process. We then present the results of a case study to support priority setting in a translational research consortium aimed at reducing the burden of disease of type 2 diabetes. During problem structuring, we identified four research alternatives (primary, secondary, tertiary microvascular, and tertiary macrovascular prevention) and a set of six decision criteria. Scoring of these alternatives against the criteria was done using a combination of expert judgement and previously published data. Lastly, decision analysis was performed using stochastic multicriteria acceptability analysis, which allows for the combined use of numerical and ordinal data. We found that the development of novel techniques applied in secondary prevention would be a poor investment of research funds. The ranking of the remaining alternatives was however strongly dependent on the decision maker's preferences for certain criteria.