——王兴强 周振宇 徐茂云
【摘要】为进一步激发疾病诊断相关分组(DRG)对医疗资源的管理效能和对诊疗行为的规范作用,提出了一种实时分组方案。根据医院已出院患者的临床诊断、治疗方案等诊疗数据,以大数据统计方式,构建DRG分组诊疗数据知识库,并提出患者诊疗分组、科室出院分组、病案编码分组和医保审核分组四级实时分组方法。实践后成效明显。DRG分组诊疗数据知识库契合医院实际,实时分组方案贯穿患者主要诊断的产生、修订全过程,可实现DRG事前、事中、事后管理,但医疗机构需注意甄别偏差数据,确保临床行为规范,提高DRG管理主动性。
【关键词】疾病诊断相关分组;分组诊疗知识库;实时分组;主要诊断
中图分类号:R197.323文献标识码:B
Real-Time Grouping Management Based on Hospital-Level DRG Grouped Medical Data Knowledge Base/WANG Xingqiang,ZHOU Zhenyu,XU Maoyun.//Chinese Health Quality Management,2023,30(5):51-54
Abstract A real-time grouping scheme was proposed in order to further stimulate the effectiveness of Diagnosis Related Groups (DRGs) in the management of medical resources and the standardization of diagnosis and treatment behavior. According to the clinical diagnosis, treatment plan and other diagnosis and treatment data of grouped discharged patients in the hospital, the knowledge base of DRG grouped diagnosis and treatment data was constructed by means of big data statistics, and the four-level real-time grouping method of patient diagnosis and treatment grouping, department discharge grouping, medical record coding grouping and medical insurance review grouping were proposed. The effect after practice was obvious. The knowledge base of DRG grouped diagnosis and treatment data conformed to the actual situation of the hospital. The real-time grouping scheme ran through the whole process of the generation and revision of the main diagnosis of patients, which can realize the management of DRG before, during and after the event. However, medical institutions should pay attention to the screening of deviation data, maintain the norms of clinical behavior, and improve the initiative of DRG management.
Key words Diagnosis Related Groups; Grouped Medical Knowledge Base; Real-Time Grouping; Primary Diagnosis
Firstauthor's address 960th Hospital of PLA, Jinan, Shandong,250031, China
1研究背景
2019年6月,国家医疗保障局发布《关于印发按疾病诊断相关分组付费国家试点城市名单的通知》(医保发〔2019〕34号),公示了疾病诊断相关分组(Diagnosis Related Groups, DRG)付费的30个试点城市,DRG试点正式在全国铺开。DRG付费作为一种医保支付方式,表像上是对医疗费用的管理,本质上还是对诊疗行为的规范,它将费用的杠杆作用传导到诊疗中,从而实现精细化管理[1-2]。医保办通常定期对出院患者的分组情况和实际发生费用等进行统计分析,将结果反馈给科室,临床医生由于是事后被动告知,难以事前、事中参与到DRG管理中[3-4]。
DRG本质上是一种管理工具,其基于地区内不同医疗机构出院患者的医保基金结算清单大数据,采用统计学方法,根据诊断、治疗方式及病例个体特征构建分组器进行分组,医保经办机构依据分组权重、费率等指标对定点医疗机构的住院医保费用进行结算。对于医疗机构而言,分组器就是一个“黑匣子”。部分DRG厂商开发了医院端分组器,应用于病案质控、DRG分组管理、DRG绩效评价、DRG病组分析及DRG成本核算等。DRG医院端分组器以出院患者的医疗保障基金结算清单为依据,是终末行为。由于患者在诊疗过程中,医生书写的临床诊断与疾病诊断存在差异,且病案编码员尚未介入,因此难以实现实时分组,或分组准确率较低。本研究基于某院已分组出院患者的临床诊断、治疗方案等诊疗数据,以大数据统计的方式建立DRG分组诊疗数据知识库,以在院患者的临床诊断和治疗计划为依据,引导实时分组,并提出了DRG四级实时分组方案,使临床医生能够参与到整个DRG管理过程中,防止药品、耗材等卫生资源的过度使用[5],促进DRG组内诊疗的同质化,规范诊疗行为。
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