Dynamic network data envelopment analysis for university hospitals evaluation

Abstract

OBJECTIVE: To develop an assessment tool to evaluate the efficiency of federal universitygeneral hospitals.METHODS: Data envelopment analysis, a linear programming technique, creates a bestpractice frontier by comparing observed production given the amount of resources used. Themodel is output-oriented and considers variable returns to scale. Network data envelopmentanalysis considers link variables belonging to more than one dimension (in the model, medicalresidents, adjusted admissions, and research projects). Dynamic network data envelopmentanalysis uses carry-over variables (in the model, financing budget) to analyze frontier shift insubsequent years. Data were gathered from the information system of the Brazilian Ministryof Education (MEC), 2010-2013.RESULTS: The mean scores for health care, teaching and research over the period were 58.0%,86.0%, and 61.0%, respectively. In 2012, the best performance year, for all units to reach thefrontier it would be necessary to have a mean increase of 65.0% in outpatient visits; 34.0% inadmissions; 12.0% in undergraduate students; 13.0% in multi-professional residents; 48.0% ingraduate students; 7.0% in research projects; besides a decrease of 9.0% in medical residents.In the same year, an increase of 0.9% in financing budget would be necessary to improve the careoutput frontier. In the dynamic evaluation, there was progress in teaching efficiency, oscillationin medical care and no variation in research.CONCLUSIONS: The proposed model generates public health planning and programmingparameters by estimating efficiency scores and making projections to reach the best practice frontier