Measuring Efficiency of Knowledge Production in Health Research Centers Using Data Envelopment Analysis (DEA): A Case Study in Iran

Abstract

INTRODUCTION Efficiency analysis is necessary in order to avoid waste of materials, energy, effort, money, and time during scientific research. Therefore, analyzing efficiency of knowledge production in health areas is necessary, especially for developing and in-transition countries. As the first step in this field, the aim of this study was the analysis of selected health research center efficiency using data envelopment analysis (DEA). METHODS This retrospective and applied study was conducted in 2015 using input and output data of 16 health research centers affiliated with a health sciences university in Iran during 2010-2014. The technical efficiency of health research centers was evaluated based on three basic data envelopment analysis (DEA) models: input-oriented, output-oriented, and hyperbolic-oriented. The input and output data of each health research center for years 2010-2014 were collected from the Iran Ministry of Health and Medical Education (MOHE) profile and analyzed by R software. RESULTS The mean efficiency score in input-oriented, output-oriented, and hyperbolic-oriented models was 0.781, 0.671, and 0.798, respectively. Based on results of the study, half of the health research centers are operating below full efficiency, and about one-third of them are operating under the average efficiency level. There is also a large gap between health research center efficiency relative to each other. CONCLUSION It is necessary for health research centers to improve their efficiency in knowledge production through better management of available resources. The higher level of efficiency in a significant number of health research centers is achievable through more efficient management of human resources and capital. Further research is needed to measure and follow the efficiency of knowledge production by health research centers around the world and over a period of time.