A bootstrap DEA approach to estimate residency match rate efficiency: the case of allopathic medical schools in Texas

The match rate of medical schools in the U.S. has been extensively studied from the perspective of applicants and influential factors. A method to objectively estimate the efficiency of a medical school’s match rate has not been described in the literature. Such a method constitutes a significant improvement opportunity for medical schools via benchmarking best practices. This research fills the gap and proposes a bootstrap data envelopment analysis (DEA) framework to assess the residency match rate efficiency of medical schools. The efficacy of the proposed method is confirmed when benchmarking the Texas allopathic medical schools to representative samples of allopathic medical schools in the United States. The model allows to determine the statistical significance of differences in the residency match rate efficiency between groups of medical schools. The proposed bootstrap DEA approach is used to estimate the real efficiency's density function of 40 medical schools in the U.S. over the 2018–2020 period. The aggregate efficiency estimation showed that the medical schools are performing at a high competitive level; they have experienced a slight decline in scale efficiencies and have preserved high managerial performance. The study measured four groups: Texas medical schools, top ten ranked, middle ten ranked, and bottom ten ranked U.S. medical schools. The overall major improvement opportunity for medical schools is the scale of operations. Results confirm that medical schools are shown to be efficient in training future physicians.