识别初级保健电子医疗记录中的代码序列中的潜在偏差:对代码频率决定因素的回顾性队列研究
Thomas Beaney1,2, Jonathan Clarke2, David Salman3,4
1Department of Primary Care and Public Health, Imperial College London, London, UK thomas.beaney@imperial.ac.uk.
BMJ open
|September 27, 2023
概括
初级保健中长期疾病 (LTC) 的诊断编码受金融激励,患者人口统计和COVID-19大流行影响. 这些因素必须在健康记录分析中考虑.
科学领域:
- 医疗信息学 医疗信息学
- 初级保健研究研究初级保健研究
- 电子健康记录 (EHR) 是一种电子健康记录.
背景情况:
- 在初级保健电子健康记录 (EHR) 中准确编码长期疾病 (LTC) 对临床护理和研究至关重要.
- 了解影响诊断代码频率的因素对于可靠的数据分析和质量改进举措至关重要.
研究的目的:
- 调查LTC诊断代码在初级保健电子健康记录中的频率与疾病编码激励机制之间的关联.
- 检查通用医疗 (GP) 特性,患者社会人口统计因素和诊断年份对编码频率的影响.
- 评估质量和成果框架 (QOF) 对LTC诊断编码率的影响.
主要方法:
- 使用英国临床实践研究Datalink Aurum数据集 (2015-2022) 的回顾性队列研究.
- 包括2015年1月至2019年12月期间诊断出至少一次LTC事件的患者.
- 在诊断后的头两年中,对诊断代码频率的分析,按QOF纳入分层.
主要成果:
- 与非QOF条件相比,QOF中包含的条件的年度编码率显著更高 (1.03对比0.32个代码/年).
- 在全科医生之间观察到编码频率的显著变化,独立于患者的社会人口统计.
- 较高的编码率与QOF和非QOF条件的患者剥夺率增加有关;由于COVID-19大流行,编码频率在2020年下降.
结论:
- LTC诊断代码频率是多因素的,受到QOF激励,患者社会人口统计,GP实践变化以及COVID-19大流行等外部事件的影响.
- 未来使用自然语言处理或代码序列分析进行的分析应考虑这些已识别的影响因素,以减轻电子健康记录数据中的潜在偏差.
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