Journal: Modern Economics & Management Forum DOI: 10.32629/memf.v7i4.5517
Abstract
Community health service centers (CHSCs) anchor China's tiered healthcare system, yet efficiency in rural/peri-urban CHSCs facing depopulation and aging remains unclear once environment is accounted for. Using a ten-year panel of all 18 CHSCs in Chongming, Shanghai's largest, least dense, most aged district (2016-2025, 180 observations), we apply a three-stage DEA-Tobit framework: Stage 1 input-oriented BCC efficiency; Stage 2 stochastic frontier analysis (SFA) removing environmental effects and noise; Stage 3 re-estimation with adjusted inputs; then panel Tobit regression on determinants. Mean comprehensive technical efficiency was 0.874 (Stage 1) and 0.862 (Stage 3), but composition reversed: pure technical efficiency rose 0.917 to 0.939, scale efficiency fell 0.952 to 0.915, showing management is relatively strong and scale diseconomy binds. Bed redundancy was highest (15.8%). Bachelor's-degree staff share and operating years robustly raised efficiency; fiscal-subsidy dependence lowered it; family-doctor contract coverage showed no robust effect. Efficiency rose monotonically with township size (0.658, 0.897, 0.951 for remote, general, central townships). In environmentally homogeneous rural settings, efficiency gains hinge on management, human capital, and fiscal-incentive reform rather than capacity expansion.
Keywords
community health service center; three-stage DEA; Tobit regression; efficiency; aging; primary healthcare
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[2] Charnes A, Cooper W W, Rhodes E. Measuring the efficiency of decision making units[J]. European Journal of Operational Research, 1978, 2(6): 429-444.
[3] Farrell M J. The measurement of productive efficiency[J]. Journal of the Royal Statistical Society: Series A (General), 1957, 120(3): 253-290.
[4] Cooper W W, Seiford L M, Tone K. Data envelopment analysis: a comprehensive text with models, applications, references and DEA-solver software[M]. New York: Springer, 2007.
[4] Banker R D, Charnes A, Cooper W W. Some models for estimating technical and scale inefficiencies in data envelopment analysis[J]. Management Science, 1984, 30(9): 1078-1092.
[5] Fried H O, Lovell C A K, Schmidt S S, et al. Accounting for environmental effects and statistical noise in data envelopment analysis[J]. Journal of Productivity Analysis, 2002, 17(1-2): 157-174.
[6] Jondrow J, Lovell C A K, Materov I S, et al. On the estimation of technical inefficiency in the stochastic frontier production function model[J]. Journal of Econometrics, 1982, 19(2-3): 233-238.
[7] Tobin J. Estimation of relationships for limited dependent variables[J]. Econometrica, 1958, 26(1): 24-36.
[8] Greene W. Fixed effects and bias due to the incidental parameters problem in the Tobit model[J]. Econometric Reviews, 2004, 23(2): 125-147.
[9] Hood C. A public management for all seasons?[J]. Public Administration, 1991, 69(1): 3-19.
[10] Li Xuezhu, Kuang Li, Zhang Hui. Design of Quality and Results Framework in UK and its Enlightenment to China (2021-2022) [J]. China General Practice, 2022, 25(28): 3466-3474.
[11] Lu Yun, Jing Rize, Wang Demeng, et al. Analysis on the Incentive Mechanism of Family Doctor Contract Service--Based on the Model of "Three Division Management" in Xiamen City [J]. China General Practice, 2021, 24(16): 1995-2002.
[12] Zhou Yang, Lin Kunhe, Xiang Li. Analysis of the impact of total prepayment on medical service subsidence in Sanming City [J]. China Health Policy Research, 2024, 17(3): 24-30.
[13] Wu Nina, Gao Guangying, Li Lianhua, et al. Synergistic transformation and enlightenment of Japanese medical insurance system and health system under the background of aging [J]. China Health Policy Research, 2021, 14(11): 67-74.
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