Volume 7, Issue 3, May 2019, Page: 83-90
Evaluation of China's Health Resources Allocation Performance
Yunying Yan, School of Public Health and Management, Research Center for Medicine and Social Development, Collaborative Innovation Center of Social Risks Governance in Health, Chongqing Medical University, Chongqing, China
Xue Lei, School of Public Health and Management, Research Center for Medicine and Social Development, Collaborative Innovation Center of Social Risks Governance in Health, Chongqing Medical University, Chongqing, China
Huawei Tan, Research Center for Hospital Cost Management of Chongqing, The Ninth People’s Hospital of Chongqing, Chongqing, China
Ling Yu, College of Foreign Languages, Chongqing Medical University, Chongqing, China
Peilin Zhang, Research Center for Hospital Cost Management of Chongqing, The Ninth People’s Hospital of Chongqing, Chongqing, China
Fei Chen, School of Public Health and Management, Research Center for Medicine and Social Development, Collaborative Innovation Center of Social Risks Governance in Health, Chongqing Medical University, Chongqing, China
Received: May 6, 2019;       Accepted: Jun. 5, 2019;       Published: Jun. 24, 2019
DOI: 10.11648/j.sjph.20190703.13      View  116      Downloads  16
Abstract
Background As one of the limited public resources, health resources is the material basis for maintaining health, and its allocation has a direct impact on the demand and utilization of health services, thus affecting the health status of the population. How to improve the performance of health resources allocation, to obtain the best social and economic benefits within the least input has become the hot spot of social concern in China. Therefore, the study aimed to evaluate the performance of China's health resources allocation from 2004 to 2015 under the constraint of medical expenses. Methods An input-output performance evaluation index system was constructed under the background of constraint of medical expenses China. This study used the SBM-undesirable model to measure the performance of health resources allocation in 31 provinces of China from 2004 to 2015. Results The performance of health resources allocation measured by the SBM-undesirable model at the national and regional levels was significantly lower than that of the traditional CCR model. The undesirable output redundancy rate and desirable output shortage rate at the national and regional levels were far greater than the health resource input redundancy rate. The reasons for the loss of performance of allocation of health resources in different provinces were different. Conclusions Traditional DEA model overestimated the performance of China's health resource allocation and was less sensitive to its changing characteristics. Undesirable output redundancy and desirable output shortage were the main reasons for the performance loss.
Keywords
Health Resources, Allocation Performance, SBM-Undesirable Model, Health Equity, China
To cite this article
Yunying Yan, Xue Lei, Huawei Tan, Ling Yu, Peilin Zhang, Fei Chen, Evaluation of China's Health Resources Allocation Performance, Science Journal of Public Health. Vol. 7, No. 3, 2019, pp. 83-90. doi: 10.11648/j.sjph.20190703.13
Copyright
Copyright © 2019 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Reference
[1]
Charnes, A., Cooper, W. W., Rhodes, E.. Measuring the efficiency of decision making units. European Journal of Operational Research, 1978, 2 (6), 429- 444.
[2]
Cooper W W, Tone K, Seiford L M. Data Envelopment Analysis: A Comprehensive Text with Models, Applications References, and DEA-Solver Software with Cdrom. Kluwer Academic Publishers, 1999.
[3]
Hollingsworth B. Non-parametric and parametric applications measuring efficiency in healthcare. Health Care Management Science, 2003, 6: 203-218.
[4]
Worthington A C. Frontier efficiency measurement in health care: a review of empirical techniques and selected applications. Medical Care Research & Review, 2004, 61: 135-170.
[5]
Hussey P S, Han D V, Romley J, et al. A Systematic Review of Health Care Efficiency Measures. Health Services Research, 2010, 44: 784-805.
[6]
Campos M S, Fernández-Montes A, Gavilan J M, et al. Public resource usage in health systems: a data envelopment analysis of the efficiency of health systems of autonomous communities in Spain [J]. Public Health, 2016, 138: 33-40.
[7]
Pang, H. M., Wang, X. W., 2010. Study on the interphase efficiency of large comprehensive hospitals in China based on the Malmquist index of DEA. Chinese Hospital Management. 30, 35-37. (in Chinese).
[8]
Xie, J. L., Fang, P. Q., 2015. Research on the fairness and efficiency of the allocation of medical and health resources among provinces in China. Chinese Health Economics. 32, 60-62. (in Chinese).
[9]
Wang, X. W., Cui, Y. Y., Feng, R. H., 2015. Study on the efficiency characteristics and changes of county hospitals. Chinese Journal of Health Policy. 8, 13-20. (in Chinese).
[10]
Zhao, L., Zhang, H., Wang, Y. G., 2015. Evaluation of China's provincial health resources allocation efficiency based on Malmquist index of DEA. Chinese Journal of Health Statistics. 32, 984-987. (in Chinese).
[11]
Liu, X, Li, S. M., 2015. Empirical analysis of energy efficiency of provinces in China based on undesirable output SMB model. Mathematics in Practice and Theory. 45, 35-43. (in Chinese).
[12]
Hu, B., Wang, F., Li, J. Y., 2015. Empirical Study on efficiency evaluation of urban ecological civilization construction based on undesirable output SBM model. Journal of arid land resources and environment. 29, 13-18. (in Chinese).
[13]
Tone K. A slacks-based measure of efficiency in data envelopment analysis. European Journal of Operational Research, 2001, 130: 498-509.
[14]
Guo Y, Li N, Mu H, et al. Regional Total-Factor Coal Consumption Efficiency in China: A Meta-Frontier SBM-Undesirable Approach. Energy Procedia, 2017, 142: 2423-2428.
[15]
Cooper, W. W., Seiford, L. M., Tone, K., 2007. DATA ENVELOPMENT ANALYSIS A Comprehensive Text with Models, Applications, References Second Edition. Boston: Kluwer Academic Publishers.
[16]
Zhang, H., Zhao, L., Liu, Q., 2016. Research on the allocation efficiency of health resources in China based on the combination analysis of DEA and SFA. Chinese Journal of Public Health. 32, 1195-1197. (in Chinese).
[17]
Xu, M. M., Liu, J. T., 2016. Study on the Equity of Public Health Expenditure in Beijing, Henan and Shaanxi. Chinese Health Economics. 35, 45-48. (in Chinese).
[18]
Tan, H. W., Zhang, P. L., Liu, X., 2017. The mechanism and empirical analysis of the impact of central transfer payment on health expenditure of local governments. Chinese Health Economics. 36, 16-20. (in Chinese).
[19]
Tan, H. W., Zheng, W. H., Zhang, Y., 2016. Analysis of operational efficiency of three level public hospitals in Chongqing from the perspective of heterogeneity of production technology. Journal of Shanghai Jiaotong University (Medical Science)., 36, 1063-1069. (in Chinese).
[20]
Tan, H. W., Zheng, W. H., Zhang, Y., 2016. Study on the cost efficiency and its influencing factors of County-level public hospitals in chongqing. Journal of Shanghai Jiaotong University (Medical Science). 36, 730-736. (in Chinese).
[21]
Wang, X. T., 2014. Research on health input, technical efficiency and health performance, based on SFA method to measure health input efficiency. Chinese Health Economics. 33, 25-29. (in Chinese).
Browse journals by subject