Performance Evaluation of Public Non-Profit Hospitals Using a BP Artificial Neural Network: The Case of Hubei Province in China

International Journal of Environmental Research and Public Health

Chunhui Li¹ 

[1]School of Public Health, Wuhan University, 115 Donghu Road, Wuhan 430071, China

[2] E-Mail:

关键词: public non-profit hospitals;    health care reform;    indicator system;    performance evaluation;    BP neural network;    cross validation;   

DOI  :  10.3390/ijerph10083619

来源: mdpi

【 摘 要 】

To provide a reference for evaluating public non-profit hospitals in the new environment of medical reform, we established a performance evaluation system for public non-profit hospitals. The new “input-output” performance model for public non-profit hospitals is based on four primary indexes (input, process, output and effect) that include 11 sub-indexes and 41 items. The indicator weights were determined using the analytic hierarchy process (AHP) and entropy weight method. The BP neural network was applied to evaluate the performance of 14 level-3 public non-profit hospitals located in Hubei Province. The most stable BP neural network was produced by comparing different numbers of neurons in the hidden layer and using the “Leave-one-out” Cross Validation method. The performance evaluation system we established for public non-profit hospitals could reflect the basic goal of the new medical health system reform in China. Compared with PLSR, the result indicated that the BP neural network could be used effectively for evaluating the performance public non-profit hospitals.

【 授权许可】

CC BY   
© 2013 by the authors; licensee MDPI, Basel, Switzerland.