在医院质量报告中对自我报告病例数量的内部验证:为医疗服务研究准备二次数据
Limei Ji1, Max Geraedts2, Werner de Cruppé2
1Institute for Health Services Research and Clinical Epidemiology, Philipps-Universität Marburg, Karl-von-Frisch-Strasse 4, Marburg, 35043, Germany. limei.ji@uni-marburg.de.
BMC medical research methodology
|December 30, 2024
概括
这项研究验证了德国医院质量报告 (GHQR) 关于最低案件负载要求 (MCR) 的数据,纠正了许多错误,并提高了医院研究的数据完整性. 验证过程提高了最低案件负载要求 (MCR) 研究的数据质量.
科学领域:
- 医疗保健服务研究 医疗服务研究
- 医疗信息学 医疗信息学
- 数据质量管理数据质量管理
背景情况:
- 二次数据对于医疗服务研究至关重要,但需要严格的质量检查.
- 处理不可思议数据的方法包括消除,统计估计或值替换.
- 这项研究的重点是验证德国医院质量报告 (GHQR) 数据集用于最低案件负载要求 (MCR) 研究.
研究的目的:
- 从2016-2021年开始,在GHQR内对MCR相关数据进行内部验证.
- 评估数据的可用性,一致性,并纠正不合理的MCR案件负载值.
- 识别错误来源并评估验证对数据完整性和医院报告的影响.
主要方法:
- 在GHQR (2016-2021) 中对MCR数据进行内部跨领域验证.
- 报告的MCR案例与其他GHQR变量进行有效性检查的比较.
- 在同一报告中使用最合理的数据纠正不可思议的值.
- 对错误来源的分析和诊断相关群体的使用 评估结果的统计数据.
主要成果:
- 11.8-27.7%的MCR案件负载值是模两可的; 7.9-23.7%需要纠正.
- 校正增加了MCR病例负载的0.7-3.7%,并确定了1.5-26.1%的MCR执行医院.
- 主要的错误来源是不报告MCR病例数量,特别是小规模医院的不报告.
- 由于自2018年以来实施的可信性控制,数据质量得到了改善.
结论:
- 对GHQR数据集成功应用了全面的内部验证方法.
- 选择的方法优先考虑了数据完整性,通过选择可信的值而不是数据消除.
- 建议包括实施GHQR数据的验证流程,并完善MCR文档的可信性控制.
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