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基于天津市某三甲医院的病案首页数据质量与DRGs评测分析 被引量:2

Medical Case Home Page Data Quality and DRGs Evaluation Analysis Based on a Tertiary Hospital in Tianjin
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摘要 目的分析某院DRGs分组入组病案首页数据的质量缺陷,提出持续改进措施,进一步提高病案首页质量和DRGs入组率等。方法从某公立三甲医院2020年上报的病案首页数据共21 482份,通过平台数据分析和人工复核的方式进行回顾性分析,对缺陷问题归类统计和分析,提出持续改进措施。结果入组的21 270份数据中,DRGs组数405组,代表疾病治疗难度的CMI值为1.01,时间消耗指数为0.64,费用消耗指数为0.86,低风险死亡病例为2,覆盖临床科室共计22个,由病案首页编码问题导致DRGs异常费用病案达5648例。结论该院的住院病案首页质量有待提高,应积极采取持续改进措施,为进一步实施按诊断相关组预付费制提供准确的数据支持。 Objective To analyze the quality defects of DRGs grouped into case home data in a hospital,and propose continuous improvement measures to further improve the quality of case home and DRGs enrollment rate,etc.Methods A total of 21 482 case home page data reported from a public tertiary care hospital in 2020 were retrospectively analyzed by platform data analysis and manual review,and the defective issues were categorized and analyzed,and continuous improvement measures were proposed.Results Among the 21 270 data enrolled,the number of DRGs groups was 405,the CMI value representing the difficulty of disease treatment was 1.01,the time consumption index was 0.64,the cost consumption index was 0.86,and the number of low-risk death cases was 2.The total number of clinical departments covered was 22,and the number of DRGs abnormal cost cases caused by the coding problem of the first page of the case reached 5648 cases,which showed that the quality of the first page of the case data need to be further improved.Conclusion The quality of the hospital’s inpatient case home page needs to be improved,and continuous improvement measures should be actively taken to provide accurate data support for further implementation of the prepayment system by diagnosisrelated groups.
作者 窦一峰 崔金广 杨洁 蒙文涛 吴秀春 DOU Yi-feng;CUI Jin-guang;YANG Jie;MENG Wen-tao;WU Xiu-chun(Network Information Center,Tianjin Baodi People’s Hospital,Tianjin 301899,China)
出处 《医学信息》 2022年第4期24-29,共6页 Journal of Medical Information
基金 天津市卫生信息学会科研项目(编号:TJHIA-2020-001)。
关键词 DRGS 病案首页 数据质量 评价指标 DRGs Medical record home page Data quality Evaluation indicators
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