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病理诊断编码错漏填写的原因与措施分析 被引量:3

Analysis on causes and measures for incorrect and missed filling in of pathological diagnostic codes
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摘要 目的探究病理诊断编码错漏填写的原因与措施。方法2016年1月~2017年1月我院以《病案首页质量检测软件》筛查ICD-10为C00-D48的病例,后抽取纸质病例核对,确定诊断编码错漏填写例数。分析致上述现象出现的原因并制定相关措施,后以同样方式筛查、确定2017年1月~2018年1月病理诊断编码错漏填写例数。结果干预后病理诊断编码错漏填写例数明显低于干预前,差异有统计学意义(P<0.05)。且Logisitc相关性分析可知,疾病诊断编码错误、病理诊断多余编码、病理报告归档延迟、病理诊断编码混淆与病理诊断编码错漏填写呈正相关性,差异无统计学意义(P>0.05)。结论病理诊断编码错漏填写干预措施可有效降低病理诊断编码错漏填写率。 Objective To explore the causes and measures for incorrect and missed filling in of pathological diagnosis codes.Methods From January 2016 to January 2017,ICD-10 as C00-D48 cases were screened by the“Quality Detection Software on the Home Page of Medical Records”.Then paper cases were selected for verification to determine the number of cases with errors and omissions in diagnostic codes.The causes of the above phenomena were analyzed and the relevant measures were formulated.Then,the number of cases with errors and omissions in pathological diagnostic codes from January 2017 to January 2018 was screened and determined by the same way.Results After intervention,the number of cases with errors and omissions in pathological diagnosis codes was significantly lower than that before the intervention,and the difference was statistically significant(P<0.05).And Logisitc correlation analysis showed that there was a positive correlation between the wrong coding of disease diagnosis,redundant coding of pathological diagnosis,delayed filing of pathological reports,pathological diagnosis code confusion and incorrect and missed filling in of pathological diagnosis codes(P>0.05).Conclusion Intervention measures for incorrect and missed filling in of pathological diagnosis codes can effectively reduce the rate of incorrect and missed filling in of pathological diagnosis codes.
作者 梁喜 刘丹丹 LIANG Xi;LIU Dandan(Gaozhou People’s Hospital,Gaozhou 525200,China)
出处 《中国医药科学》 2019年第22期274-276,共3页 China Medicine And Pharmacy
关键词 病理诊断编码 错漏填写 原因 措施 Pathological diagnosis code Incorrect and missed filling in Causes Measures
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