Efficiency and productivity of Mongolian public hospitals: a three-stage DEA and Malmquist productivity index approach
DOI:
https://doi.org/10.53468/mifyr.2026.6.3.58Keywords:
Three-stage DEA; Stochastic frontier analysis; Malmquist productivity index; Public hospital efficiency; Environmental adjustment; Financial resource allocationAbstract
This study evaluates the efficiency and productivity of 31 Mongolian public hospitals from 2017 to 2022 using a three-stage Data Envelopment Analysis (DEA), Stochastic Frontier Analysis (SFA), and Malmquist Productivity Index (MPI) framework. An input-oriented VRS/BCC model incorporated hospital beds, physicians, nurses, other staff, and expenditure as inputs, with total patients and revenue as outputs. SFA adjusted input slacks for socioeconomic, demographic, geographic, and COVID-19-related conditions before efficiency was re-estimated. Mean pure technical efficiency was higher after environmental adjustment in every year, with a statistically significant difference (z = −11.064, p < .001). The MPI results showed a slight productivity decline in 2017–2018 (MEPI = 0.9673), followed by improvements in subsequent periods, peaking in 2020–2021. Technological change contributed more to productivity growth than efficiency catch-up. These findings highlight the importance of environmental conditions in hospital performance evaluation and support equitable benchmarking and more efficient public healthcare resource allocation.
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Copyright (c) 2026 Bolorchimeg Uranchimeg, Young Kyun Kim
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