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...

Full description

Saved in:
Bibliographic Details
Published in:BioMed research international 2015-01, Vol.2015 (2015), p.1-9
Main Authors: de Graaf, Gimon, Buskens, Erik, Postmus, Douwe
Format: Article
Language:English
Subjects:
Algorithms
Biomedical research
Decision making
Decision Making, Organizational
Decision Support Techniques
Epidemiology
Industrial project management
Management
Mathematical functions
Medical research
Medicine, Experimental
Methods
Multiple criteria decision making
Needs Assessment - organization & administration
Netherlands
Product development
Project management
R&D
Research & development
Research - organization & administration
Translational Medical Research - organization & administration
Value chain
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:2314-6133
2314-6141
DOI:10.1155/2015/191809