Division of Pediatrics Hospital Medicine, Stanford University School of Medicine, Palo Alto, California, USA.
Division of Neonatology, University of California San Diego, La Jolla, California, USA.
J Hosp Med. 2023 Jul;18(7):610-616. doi: 10.1002/jhm.13140. Epub 2023 May 25.
Electronic health records (EHRs) have become an important repository for patient race and ethnicity. Misclassification could negatively affect efforts to monitor and reduce health disparities and structural discrimination.
We assessed the concordance of parental reports of race/ethnicity for their hospitalized children with EHR-documented demographics. We also aimed to describe parents' preferences on how race/ethnicity should be captured in the hospital's EHR.
DESIGNS, SETTINGS, AND PARTICIPANTS: From December 2021 to May 2022, we conducted a single-center cross-sectional survey of parents of hospitalized children asking to describe their child's race/ethnicity and compared these responses to the race/ethnicity documented in the EHR.
Concordance was analyzed with a kappa statistic (κ). Additionally, we queried respondents about their awareness of and preferences for race/ethnicity documentation.
Of the 275 participants surveyed (79% response rate), there was 69% agreement (κ = 0.56) for race and 80% agreement (κ = 0.63) for ethnicity between parent report and EHR documentation. Sixty-eight parents (21%) felt that the designated categories poorly represent their child's race/ethnicity. Twenty-two (8%) were uncomfortable with their child's race/ethnicity being displayed on the hospital's EHR. Eighty-nine (32%) preferred a more comprehensive list of race/ethnicity categories.
Nonconcordance between EHR-recorded race/ethnicity and parental report exists in the EHR for our hospitalized patients, which has implications for describing patient populations and for understanding racial and ethnic disparities. Current EHR categories may be limited in their ability to capture the complexity of these constructs. Future efforts should focus on ensuring that demographic information in the EHR is accurately collected and appropriately reflects families' preferences.
电子健康记录 (EHR) 已成为患者种族和民族的重要存储库。分类错误可能会对监测和减少健康差距和结构性歧视的努力产生负面影响。
我们评估了父母报告的其住院子女的种族/民族与 EHR 记录的人口统计学数据的一致性。我们还旨在描述父母对医院 EHR 中应如何记录种族/民族的偏好。
设计、地点和参与者：从 2021 年 12 月至 2022 年 5 月，我们对住院儿童的父母进行了一项单中心横断面调查，要求他们描述孩子的种族/民族，并将这些回答与 EHR 记录中的种族/民族进行比较。
一致性采用 Kappa 统计量 (κ) 进行分析。此外，我们还询问了受访者对种族/民族记录的认识和偏好。
在接受调查的 275 名参与者中（响应率为 79%），父母报告与 EHR 记录之间在种族方面的一致性为 69%（κ=0.56），在民族方面的一致性为 80%（κ=0.63）。68 名父母（21%）认为指定类别不能很好地代表他们孩子的种族/民族。22 名父母（8%）对其孩子的种族/民族在医院 EHR 上显示感到不舒服。89 名父母（32%）更倾向于使用更全面的种族/民族类别列表。
我们住院患者的 EHR 中存在 EHR 记录的种族/民族与父母报告之间的不一致，这对描述患者人群和了解种族和民族差异具有影响。目前的 EHR 类别在捕捉这些结构的复杂性方面可能存在局限性。未来的努力应侧重于确保 EHR 中人口统计学信息准确收集并适当反映家庭的偏好。
