对致病原因的系统审查会影响数据质量问题
Sam Yan1, Jessica Dickson2, Brandon Cheong1
1Australian Catholic University, 115 Victoria Parade, Fitzroy, Victoria 3065, Australia.
International journal of medical informatics
|February 11, 2026
概括
医院发病率数据质量问题源于有缺陷的标准,影响疾病的准确分类. 改进数据收集需要解决编码标准中的模两可,并加强医疗保健专业人员的培训.
科学领域:
- 医疗信息学 医疗信息学
- 医疗编码系统 医学编码系统
- 数据质量管理数据质量管理
背景情况:
- 对于公共卫生至关重要的医院发病率数据的可靠性是不确定的.
- 需要进行系统审查,以确定危及疾病分类数据质量的因素.
研究的目的:
- 系统地识别和调查医院发病率数据中问题的根本原因.
- 专注于使用国际疾病分类第10版,澳大利亚修改 (ICD-10-AM) 和澳大利亚卫生干预分类 (ACHI) 收集的数据.
主要方法:
- 2017-2025年使用主要数据库 (Scopus,Embase,Medline) 的研究的系统审查.
- 使用SQUIRE和STROBE检查清单进行包含研究的质量评估.
- 叙事综合以确定数据质量问题的主题和子类别,遵循PRISMA 2020指南.
主要成果:
- 包括52项研究,主要来自澳大利亚.
- 出现了四个主要主题:标准的质量问题,技术,教育/培训和临床实践.
- 确定的问题包括模两可的标准,不够的细节性和碎片化的信息结构,导致不一致的编码.
结论:
- 致病率数据收集错误的主要根本原因与分类标准的质量有关.
- 建议进行进一步的研究,以改进数据采集系统和标准化分类写作.
- 解决标准质量对于准确的医院发病率数据至关重要.
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