Evaluating Post-Pandemic Efficiency in Mexico’s Public Healthcare System: A Two-Stage DEA Analysis

Abstract

The COVID-19 pandemic brought significant changes to global health care systems, including Mexico’s, where quality of services suffered, and hospitals faced capacity shortages. The Mexican public health system, however, remains under-researched, and its post-pandemic efficiency largely unexplored. This study aims to evaluate the efficiency of the Mexican Public Healthcare System from 2021 to 2022 by analyzing thirty-two states and six Nielsen zones using Data Envelopment Analysis (DEA). A two-stage BCC input-oriented efficiency model was developed. In the first stage, inputs like budget allocations, the growth rate of public healthcare spending, and current spending prices were analyzed. The second stage incorporated operational inputs such as the number of doctors, incubators, and pharmacies. Outputs included services coverage, service quality, and total consultations provided. The main findings reveal that budget size does not guarantee high quality, though quality correlates with the number of doctors and public spending prices. Mexico City, Jalisco, and Michoacán showed high efficiency levels across both stages, whereas Sinaloa, Nuevo León, and Baja California ranked as the least efficient states. Among Nielsen zones, the Pacific zone had the lowest efficiency. These findings suggest ways to improve resource allocation, prioritizing state needs to enhance healthcare coverage and quality. Additionally, this methodology can assess efficiency in services like mental healthcare, obesity, and cancer programs, providing a valuable approach to optimize healthcare resources in Mexico.