基于DRGs的精神专科费用异常病例的原因分析

Analysis and Rectification Measures on Psychiatric Medical Records of Abnormal Ex⁃pense Cases Based on DRGs

目的:采集某三甲精神专科医院DRGs分组费用异常的住院病例,分析原因并提出相应改进措施,以降低费用异常病例的发生率。方法:对该院2018年5月-2021年4月三年的出院病例经CHS-DRG1.1分组器分组后反馈为费用极高和极低病例进行分析,组织病案专家通过标准化分类方法,研讨临床专家对问题病例统计分析分组结果与编码符合情况。结果:10009份病例中有343例费用异常病例,其中主要诊断不规范169例(49.27%)、并发症或合并症填写不规范64例(18.66%)、编码质量缺陷52例(15.16%)、编码映射问题22例(6.41%)、其他36例(10.50%)。结论:DRGs费用异常病例显示了精神专科病案首页数据的问题,与医师书写诊断的规范性、编码工作人员技能的专业性等密切相关。医院应规范诊疗过程,提升DRGs分组正确性,减少费用异常病例,合理控费以提高医保结算清单填写完整性,提升医院绩效管理水平。

Objective:To analyze in-depth hospital records of abnormal expense cases under the three-year DRGs grouping of a psychiatric hospital in a certain grade A tertiary psychiatric hospital,and propose measures to solve the problems,so as to reduce the incidence of abnormal expense cases.Methods:Analyze the medical records of abnormal expense results from the hospital’s dis-charged medical records from May,2018 to April,2021 through the CHS-DRG1.1 grouping device,organize medical record experts and clinical experts to discuss the problem medical records,and adopt a standardized classification method,And normative means,to count the grouping results and coding conformance.Results:A total of 10,009 medical records had 343 cases of abnormal expense,of which 169 cases(49.27%)were mainly diagnosed as irregular;64 cases(18.66%)were filled out of complications or comorbidities;52 cases(15.16%)were defective in coding quality.;22 cases of coding mapping problems(6.41%);the other 36 cases(10.50%).Conclu-sion:The abnormal expense cases of DRGs cost show the problems of the first page data of psychiatric medical records,which are closely related to the standardization of doctors’writing diagnosis and the professional skills of coding staff.Reducing abnormal ex-pense cases is an important part of reasonable cost control,which can improve the completeness of filling in the medical insurance set-tlement list,standardize the diagnosis and treatment process,and improve the correctness of DRGs grouping,which is very important for hospital performance management.