Equity and efficiency of resource allocation for management and treatment of severe mental disorders in Shanghai in 2020
10.3969/j.issn.1006-2483.2023.01.005
- VernacularTitle:上海市严重精神障碍管理治疗资源配置的公平与效率分析
- Author:
Xin FAN
1
;
Wei-bo ZHANG
2
;
Yi ZHU
1
;
Yan-li SU
3
;
Bin XIE
1
;
Jun CAI
1
Author Information
1. Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030 , China
2. Center for Mental Health Management ,China Hospital Development Institute, Shanghai Jiao Tong University , Shanghai 200030 , China
3. Shanghai Xuhui Mental Health Center, Shanghai 200232 , China
- Publication Type:Journal Article
- Keywords:
Gini coefficient;
Data envelopment analysis;
Mental health;
Equity;
Efficiency
- From:
Journal of Public Health and Preventive Medicine
2023;34(1):20-24
- CountryChina
- Language:Chinese
-
Abstract:
Objective To analyze the equity and efficiency of resource allocation for management and treatment of severe mental disorders in Shanghai in 2020, and to provide a foundation for making relevant policies. Methods Data on resource allocation for the management and treatment of severe mental disorders in 17 district-level mental health institutions in 2020 were collected. The Gini coefficient was used to evaluate the equity of resource allocation by population and geographic area, and data envelopment analysis was carried out to analyze the equity of resource allocation. Results The Gini coefficients of special funds, psychiatric medical staff and actual open beds according to population were 0.24, 0.25 and 0.27, respectively. The Gini coefficients according to area were 0.54, 0.62 and 0.64, respectively. The average efficiency of resource allocation was 0.865. There were 5 institutions where DEA was effective, accounting for 29.41%. There were 12 institutions where DEA was non-effective, accounting for 70.59%. Conclusion The equity of resources allocation for the management and treatment of severe mental disorders according to population is good, but the equity of allocation based on geographic area is not high. The efficiency of resource allocation needs to be further improved. It is suggested that the resource allocation should be optimized to promote the fairness and efficiency of resource allocation for the management and treatment of severe mental disorders.
