摘要
目的利用区域卫生信息平台诊疗数据,探讨其在降低垃圾编码率上的应用价值,从源头提高死因数据质量。方法本研究基于2023年3月1日—2024年2月29日上海市普陀区8717例户籍人口死亡审核数据,采用GBD-2019中ICD-10垃圾编码表筛选根本死因为垃圾编码的数据,并分析其基线特征。利用区域卫生信息平台对垃圾编码数据进行病案诊疗信息补充,由2名死因编码员对根本死因进行重新修正或确认,以评估数据质量优化效果。结果数据分析显示,<60岁人群、居民死亡推断书及死亡地点为“来院已死”“家中”和“其他”的数据,其根本死因的垃圾编码率较高,分别达14.14%、12.74%、23.81%、13.43%和13.04%。基于区域卫生信息平台,垃圾编码诊疗数据匹配成功率为55.32%,根本死因修正率为50.00%。经修正后,总垃圾编码率从7.01%显著降低至5.28%(χ^(2)=22.683,P<0.001),其中≥60岁人群、居民死亡医学证明书、居民死亡推断书及死亡地点为“医院病房”、“家中”和“敬老院”的数据垃圾编码率均显著下降(均P<0.05)。在垃圾编码级别方面,修正前级别Ⅰ(严重影响)~Ⅳ(局限影响)的编码率依次为1.96%、2.90%、1.28%、0.86%(χ^(2)=336.015,P<0.001),以级别Ⅱ(重大影响)编码为主,占41.41%。修正后,级别Ⅰ~级别Ⅲ编码率均显著下降(均P<0.05),26.48%的级别Ⅱ编码和29.46%的级别Ⅲ编码修正为非垃圾编码。级别Ⅱ的高频编码高血压和高血压脑病、级别Ⅲ的肺的其他疾患和其他特指的呼吸性疾患编码率显著下降(χ^(2)=15.599,P<0.001;χ^(2)=4.838,P=0.028)。结论区域卫生信息平台在优化死因数据质量时,能够精准覆盖最主要的死亡报告来源,有效降低垃圾编码率,从而对整体数据质量的提升产生实质性影响。
Objective To explore the application value of regional health information platform data in reducing garbage code rates and improving data quality at the source.Methods We analyzed 8717 death records of registered residents in Putuo district,Shanghai from March 1,2023 to February 29,2024.Using the GBD-2019 ICD-10,we extracted cases with the underlying cause of death being classified as a garbage code and examined their baseline characteristics.Using the regional health information platform,we supplemented medical records for cases with garbagecoded underlying causes of death.Two trained mortality coders then revised the underlying causes to evaluate data quality improvement.Results The garbage code rates were higher for underlying causes of deaths among individuals<60 years(14.14%),cases documented in resident death inference certificates(12.74%),and deaths occurring at locations categorized as dead on arrival(23.81%),at home(13.43%),and others(13.04%).On the basis of the regional health information platform,the successful matching rate for medical records with garbage-coded underlying causes was 55.32%,and the effective correction rate for underlying causes reached 50.00%.After correction,the overall garbage code rate decreased from 7.01%to 5.28%(χ^(2)=22.683,P<0.001).Notably,significant reductions were observed in the garbage code rates for individuals≥60 years,cases recorded in both official death certificates and death inference certificates,and deaths occurring in hospital wards,at home,and in nursing homes(all P<0.05).Regarding garbage code classification,prior to correction,the coding rates for Level I(severe impact)to LevelⅣ(limited impact)were 1.96%,2.90%,1.28%,and 0.86%,respectively(χ^(2)=336.015,P<0.001),with LevelⅡ(major impact)codes predominating at 41.41%of cases.Post-correction,the coding rates for Level I to LevelⅢreduced(all P<0.05),with 26.48%of LevelⅡcodes and 29.46%of LevelⅢcodes reclassified as non-garbage codes.High-frequency LevelⅡcodes such as hypertension and hypertensive encephalopathy,as well as LevelⅢcodes including other diseases of the lung and other specified respiratory conditions exhibited decreases(χ^(2)=15.599,P<0.001;χ^(2)=4.838,P=0.028).Conclusions The regional health information platform effectively targets major mortality reporting sources and significantly reduces garbage code rates,thus substantially improving the overall data quality in mortality statistics.
作者
桑灏
宋允雪
陈蕾
沈莉
王婉
虞慧婷
徐征宇
刘星航
SANG Hao;SONG Yunxue;CHEN Lei;SHEN Li;WANG Wan;YU Huiting;XU Zhengyu;LIU Xinghang(Shanghai Putuo District Center for Disease Control and Prevention,Shanghai 200333,China;Shanghai Center for Disease Control and Prevention,Shanghai 201107,China;Shanghai Putuo District Health Affairs Management Center,Shanghai 200333,China)
出处
《中国公共卫生》
北大核心
2025年第10期1240-1245,共6页
Chinese Journal of Public Health
基金
上海市加强公共卫生体系建设三年行动计划学科人才建设项目(2023-2025)(GWVI-11.1-35、GWVI-11.1-31)
上海市加强公共卫生体系建设三年行动计划优秀青年人才项目(2023-2025)(GWVI-11.2-YQ07)
上海市“科技创新行动计划”技术标准项目(22DZ2206000)
上海市卫生健康委员会卫生行业临床研究专项(20224Y0328)
上海市普陀区卫生健康系统科技创新项目(ptkwws202322)。
关键词
死因监测
垃圾编码
质量控制
区域卫生信息平台
信息化
mortality surveillance
garbage codes
quality control
regional health information platform
informatization
