Abstract：Objective To investigate the comprehensive performance evaluation of the hospital with RSR statistics method based the diagnosis related group (DRGs). Methods The home page information of patients from a hospital in Beijing in the first half of 2015 was analyzed with the use of the Beijing edition of the diagnosis related group (BJ-DRGs), and then the DRGs related information of patients were obtained. The RSR statistics method was applied to the analysis of comprehensive performance evaluation on the medical services of the departments. Results The hospital treated disease categories (MDC) was 23 groups, DRGs group was 479, and case mix index (CMI) was 0.96, which was close to the average level of medical technology difficulty in Beijing; cost index and time consumption index were 1.06 and 1.07, which were higher than the average level of the service efficiency. The infectious disease department treated the most diseases, with 71 DRGs groups and the ICU department was with the most difficult treatment, with the case mix index 3.17. The time and pay consumption indexes in nephropathy department were the lowest, while those in obstetrics and gynecology department were 1.28 and 1.46, being the highest. The results of RSR showed the departments with best medical service performance were the department of Infectious diseases, department of Internal Nervous Medicine, department of urology, Chinese and western medicine department and ICU, while the departments with worst medical service performance were obstetrics and gynecology department and pediatrics department. Conclusion The RSR evaluation method based on the DRGs colligated the width, difficulty and efficiency index of the medical service, the evaluation result was objective, and it provided a feasible method for the hospital medical performance evaluation.
万钢，桑雁，郝一炜，李磊，于景祎，马静，王佳静，王中菲. 基于疾病诊断相关组的秩和比法对医院绩效评价[J]. 中国医院统计, 2016, 23(1): 19-21.
Wan Gang, Sang Yan, Hao Yiwei, Li Lei, Yu Jingyi, Ma Jing,Wang Jiajing, Wang Zhongfei. Comprehensive performance evaluation with RSR statistics method based on disease diagnosis related group. journal1, 2016, 23(1): 19-21.
