title: A Novel Approach to Measuring Efficiency of Scientific Research Projects: Data Envelopment Analysis.
abstract: OBJECTIVE
  Measuring the efficiency of resource allocation for the conduct of scientific projects in medical research is difficult due to, among other factors, the heterogeneity of resources supplied (e.g., dollars or FTEs) and outcomes expected (e.g., grants, publications). While this is an issue in medical science, it has been approached successfully in other fields by using data envelopment analysis (DEA). DEA has a number of advantages over other techniques as it simultaneously uses multiple heterogeneous inputs and outputs to determine which projects are performing most efficiently, referred to as being at the efficiency frontier, when compared to others in the data set.
  
  
  METHODS
  This research uses DEA for the evaluation of supported translational science projects by the Oregon Clinical and Translational Research Institute (OCTRI), a NCATS Clinical & Translational Science Award (CTSA) recipient.
  
  
  RESULTS
  These results suggest that the primary determinate of overall project efficiency at OCTRI is the amount of funding, with smaller amounts of funding providing more efficiency than larger funding amounts.
  
  
  CONCLUSIONS
  These results, and the use of DEA, highlight both the success of using this technique in helping determine medical research efficiency and those factors to consider when distributing funds for new projects at CTSAs.
authors.affiliation: Oregon Health & Science University, Portland, Oregon, USA.
authors.forename: David M
authors.initials: DM
authors.lastname: Dilts
authors.affiliation: Oregon Clinical & Translational Research Institute, Oregon Health & Science University, Portland, Oregon, USA.
authors.forename: Adrienne
authors.initials: A
authors.lastname: Zell
authors.affiliation: Department of Medicine, Oregon Health & Science University, Portland, Oregon, USA.
authors.forename: Eric
authors.initials: E
authors.lastname: Orwoll
mesh_terms: D019985:Benchmarking; D003362:Cost-Benefit Analysis; D017598:Efficiency, Organizational; D017048:Health Care Costs; D006801:Humans; D017146:Models, Organizational; D015233:Models, Statistical; D011786:Quality Control; D019984:Quality Indicators, Health Care; D012109:Research Support as Topic / Q000191:economics / Q000458:organization & administration* / Q000592:standards; D057170:Translational Research, Biomedical / Q000191:economics / Q000458:organization & administration* / Q000592:standards
keywords: cost-benefit analysis; methodology; statistics