从自我报告与电子健康记录中获得的种族和种族数据之间的可靠性评估
Phillip C Sojka1, Micaela M Maron2, Shira I Dunsiger3
1Warren Alpert Medical School, Brown University, Providence, RI, USA. Psojka1@JH.edu.
Journal of racial and ethnic health disparities
|June 5, 2024
概括
电子健康记录数据可能不准确地反映患者的种族和种族,影响健康差异研究. 自我报告的数据对于了解患者人口统计学和促进公平护理更可靠.
科学领域:
- 医疗信息学 医疗信息学
- 健康差距 研究 研究 研究 研究
- 社会医学科学 社会医学科学
背景情况:
- 在各种医疗领域,医疗保健的差异仍然存在.
- 准确的人口统计数据收集对于解决这些差异至关重要.
- 电子健康记录 (EHR) 中数据的有效性需要进行彻底的评估.
研究的目的:
- 将自我报告的种族和种族数据的有效性与电子健康记录 (EHR) 中记录的数据进行比较.
- 评估人口统计数据收集方法中的潜在差异.
- 为收集患者人口统计信息提供最佳实践信息.
主要方法:
- 通过接受精神病室住院治疗的青少年 (2019年2月 - 2022年7月) 的问卷收集了自我报告的人口统计数据.
- 对同一个患者队伍的医院电子健康记录 (EHR) 的人口统计信息进行了自我报告数据比较.
- 利用统计措施,包括科恩的卡帕 (κ),来量化数据源之间的一致性.
主要成果:
- 在西班牙裔族群中观察到实质性的一致性 (κ = 0.64).
- 对于特定的种族群体的共识从微小到实质性 (κ = 0.10-0.63) 不同.
- 在多种族识别中发现了显著的差异:17.1%的人自我报告,而在EHR数据中为3.1%.
结论:
- 在使用EHR数据来得出健康差异结论时,建议谨慎使用.
- 数据收集方法显著影响患者报告的反应.
- 改进数据收集策略对于推进健康公平至关重要.
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