Hamilton Natia S, Edelman David, Weinberger Morris, Jackson George L
Center for Health Services Research in Primary Care, Durham Veterans Affairs Medical Center, USA.
N C Med J. 2009 Jul-Aug;70(4):296-300.
Using information from electronic health records (EHRs) to examine racial/ethnic health disparities is increasingly common. This study examines the degree of concordance between administratively recorded race/ethnicity and the criterion standard of self-reported race/ethnicity at a tertiary care Veterans Affairs Medical Center (VAMC) in North Carolina.
We compared self-reported race among 204 respondents to a cross-sectional mailed survey of patients with diabetes conducted in 2006-2007 to the race/ethnicity recorded in the EHR. Concordance was defined as the percent agreement between self-reported and administratively-reported race.
The overall response rate to the survey was 68.9% (204 of 296). Of the 204 respondents, 32 (15.7%) reported a different race/ethnicity from the race/ethnicity reported in the EHR. Misclassification resulted from either the patient reporting a race/ethnicity and having the information missing in the EHR (9.3% of respondents) or the EHR having a different race/ethnicity listed than reported by the patient (6.3% of respondents).
This study was conducted at one VAMC.
While we found misclassification of race/ethnicity in the EHR, the level of discordance is smaller than previously reported in the Veterans Health Administration. Despite this, efforts still need to be made to ensure correct information is included in the EHR.
利用电子健康记录(EHRs)中的信息来研究种族/民族健康差异的情况日益普遍。本研究在北卡罗来纳州一家三级医疗退伍军人事务医疗中心(VAMC),考察行政记录的种族/民族与自我报告的种族/民族这一标准之间的一致程度。
我们将2006 - 2007年对糖尿病患者进行的横断面邮寄调查中204名受访者自我报告的种族,与电子健康记录中记录的种族/民族进行了比较。一致性定义为自我报告和行政报告的种族之间的一致百分比。
调查的总体回复率为68.9%(296人中的204人)。在这204名受访者中,32人(15.7%)报告的种族/民族与电子健康记录中报告的不同。错误分类是由于患者报告了种族/民族但电子健康记录中信息缺失(占受访者的9.3%),或者电子健康记录中列出的种族/民族与患者报告的不同(占受访者的6.3%)。
本研究是在一家退伍军人事务医疗中心进行的。
虽然我们发现电子健康记录中存在种族/民族错误分类,但不一致程度比退伍军人健康管理局此前报告的要小。尽管如此,仍需努力确保电子健康记录中包含正确信息。