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 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.

[1]  R. Baltussen,et al.  Priority setting of health interventions: the need for multi-criteria decision analysis , 2006, Cost effectiveness and resource allocation : C/E.

[2]  Theodor J. Stewart,et al.  Multiple criteria decision analysis - an integrated approach , 2001 .

[3]  W.A.H. Thissen,et al.  A modelling approach , 2010 .

[4]  P. Sawicki,et al.  Screening for diabetes: hope and despair , 2012, Diabetologia.

[5]  M Elisabeth Paté-Cornell,et al.  Early technology assessment of new medical devices , 2008, International Journal of Technology Assessment in Health Care.

[6]  Risto Lahdelma,et al.  SMAA - Stochastic multiobjective acceptability analysis , 1998, Eur. J. Oper. Res..

[7]  A. D. Henriksen,et al.  A practical R&D project-selection scoring tool , 1999 .

[8]  Tommi Tervonen,et al.  Hit-And-Run enables efficient weight generation for simulation-based multiple criteria decision analysis , 2013, Eur. J. Oper. Res..

[9]  Gimon de Graaf,et al.  A method for the early health technology assessment of novel biomarker measurement in primary prevention programs , 2012, Statistics in medicine.

[10]  H. Bilo,et al.  Diabetes nephropathy in the Netherlands: a cost effectiveness analysis of national clinical guidelines. , 2000, Health policy.

[11]  Henry Petroski,et al.  Crossing the Valley of Death , 2017 .

[12]  Richard J. Lilford,et al.  Investing in new medical technologies: A decision framework , 2007 .

[13]  M A Koopmanschap,et al.  Resource consumption and costs in Dutch patients with Type 2 diabetes mellitus. Results from 29 general practices , 2002, Diabetic medicine : a journal of the British Diabetic Association.

[14]  Douwe Postmus,et al.  Probability elicitation to inform early health economic evaluations of new medical technologies: a case study in heart failure disease management. , 2013, Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research.

[15]  P. Engelfriet,et al.  Opportunities for preventing diabetes and its cardiovascular complications , 2008 .

[16]  M. Fowler Microvascular and Macrovascular Complications of Diabetes , 2008, Clinical Diabetes.

[17]  Diederick E. Grobbee,et al.  The global burden of diabetes and its complications: an emerging pandemic , 2010, European journal of cardiovascular prevention and rehabilitation : official journal of the European Society of Cardiology, Working Groups on Epidemiology & Prevention and Cardiac Rehabilitation and Exercise Physiology.

[18]  G. Nijpels,et al.  Finse vragenlijst redelijk goede voorspeller van het optreden van diabetes in Nederland , 2008 .

[19]  D. Butler Translational research: Crossing the valley of death , 2008, Nature.

[20]  Jill U. Adams Building the bridge from bench to bedside , 2008, Nature Reviews Drug Discovery.

[21]  Pin-Yu Chu,et al.  A fuzzy AHP application in government-sponsored R&D project selection☆ , 2008 .

[22]  Risto Lahdelma,et al.  SMAA-2: Stochastic Multicriteria Acceptability Analysis for Group Decision Making , 2001, Oper. Res..

[23]  Kaisa Miettinen,et al.  Ordinal criteria in stochastic multicriteria acceptability analysis (SMAA) , 2003, Eur. J. Oper. Res..

[24]  Maarten J. IJzerman,et al.  Early assessment of medical technologies to inform product development and market access , 2011, Applied health economics and health policy.