疾病诊断相关组数据分析在医院绩效评估中的应用

Application of DRGs based data analysis in hospital performance evaluation

  • 摘要:
      背景  疾病诊断相关组(diagnosis related groups,DRGs)作为一种新的医疗支付方式,不仅综合考虑了疾病复杂性及严重度,还考虑了医疗需要及资源使用强度。
      目的  探讨DRGs数据分析在医院绩效评估中的应用效果。
      方法  导入北京市某三甲综合医院(以下简称某院)2015年(模拟DRGs付费第1年)出院的医保病例,共计123 591例。以住院医疗服务能力和专科能力建设为测算核心,选取DRGs组数、病例组合指数、费用消耗指数、时间消耗指数、低风险和中低风险死亡率为测算指标。选取北京市同等级同类别的三甲医院为标杆医院,标杆医院2015年同时期出院的医保病例10 000例为标杆数据。通过对某院各专业与标杆医院相对应专业的比较,了解某院各专业医疗服务现状、资源使用和质量安全情况。
      结果  2015年某院医保患者出院病例123 591例,其中入组113 402例,未入组10 189例,入组率91.7%。某院涉及DRGs组数751组,标杆医院DRGs组数639组;某院病例组合指数(case mix index,CMI)为1.21,标杆医院1.34;某院费用消耗指数1.40,标杆医院1.20;某院时间消耗指数0.98,标杆医院0.84;某院低风险死亡率0.01%,标杆医院0;某院中低风险死亡率0.10%,标杆医院0.09%。与标杆医院比较,某院DRG组数较多,CMI较低,费用消耗和时间消耗指数较高,低风险和中低风险死亡率略高。
      结论  与标杆医院DRGs数据比较,某院疾病诊疗广度较高,医疗技术难度较低,绝大多数病组费用偏高,但平均住院日控制较好,医院可以在基本绩效政策不动摇的前提下,较好地运用 DRGs方法进行测算评估,为医院工作提供借鉴和思路。

     

    Abstract:
      Background  DRGs as the newest payment for medical care, not only considers the complexity and severity of different diseases, but also pays attention to the medical needs and resource intensity.
      Objective  To explore the application effect of DRGs based data analysis in hospital performance evaluation.
      Methods   A total of 123 591 medical insurance cases discharged from a tertiary general hospital (Hospital X) from January to October in 2015 were included in the study. The inpatient medical service ability and construction of specialty ability were the focus of calculation. The number of DRGs, case mix index, cost consumption index, time consumption index, low and medium risk mortality were selected as the measurement indexes. Another 10 000 medical insurance cases from a Tertiary General Hospital were selected for comparison, so as to foster learning about the current situation of our medical services, utilization of medical resources, and the quality of medical treatment.
      Results  Of the 123 591 cases in 2015, there were 113 402 cases enrolled, with an enrollment rate of 91.7%. The number of DRGs in Hospital X was 751, with CMI of 1.21, cost consumption index of 1.40, time consumption index of 0.98, low-risk mortality of 0.01%, and medium-risk group mortality of 0.10%, while the data in the Benchmarking Hospital were as follows: 639, 1.34, 1.20, 0.84, 0, 0.09%. Compared with the Benchmarking Hospital, Hospital X had more DRG groups, lower CMI, higher cost and time consumption index, and higher low-risk and medium-risk of mortality.
      Conclusion  By comparing with Benchmarking Hospital, we conclude that the breadth of disease diagnosis and treatment in Hospital X is high, the medical technical difficulty is low, despite the well-controlled of average length stayed in hospital, the cost is still high in most of disease groups. On the condition that the basic policies remain unchanged, the hospital should use DRGs method for evaluation, which can provide better methods and available thoughts for hospital operation.

     

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