McAdam Jordan, Richard Stephanie A, Olsen Cara H, Byrne Celia, Clausen Shawn, Michel Amber, Agan Brian K, O'Connell Robert, Burgess Timothy H, Tribble David R, Pollett Simon, Mancuso James D, Rusiecki Jennifer A
Department of Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD, USA.
Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, Bethesda, MD, USA.
J Racial Ethn Health Disparities. 2025 Mar 21. doi: 10.1007/s40615-025-02351-7.
Unequal disease burdens such as SARS-CoV-2 infection rates and COVID-19 outcomes across race/ethnicity groups have been reported. Misclassification of and missing race and ethnicity (race/ethnicity) data hinder efforts to identify and address health disparities in the US Military Health System (MHS); therefore, we evaluated the statistical accuracy of administratively recorded race/ethnicity data in the MHS Data Repository (MDR) through comparison to self-reported race/ethnicity collected via questionnaire in the Epidemiology, Immunology, and Clinical Characteristics of Emerging Infectious Diseases with Pandemic Potential (EPICC) cohort study.
The study population included 6009 active duty/retired military (AD/R) and dependent beneficiaries (DB). Considering EPICC study responses the "gold standard," we calculated sensitivity and positive predictive value (PPV) by race/ethnicity category (non-Hispanic (NH) White, NH Black, Hispanic, NH Asian/Pacific Islander (A/PI), NH American Indian/Alaskan Native (AI/AN), NH Other, missing/unknown).
Among AD/R, the highest sensitivity and PPV values were for NH White (0.93, 0.96), NH Black (0.90, 0.92), Hispanic (0.80, 0.93), and NH A/PI (0.84, 0.95) and lowest for NH AI/AN (0.62, 0.57) and NH Other (0.09, 0.03). The MDR was missing race/ethnicity data for approximately 63% of DB and sensitivity values, though not PPV, were comparatively much lower: NH White (0.35, 0.88), NH Black (0.55, 0.89), Hispanic (0.13, 1.00), and NH A/PI (0.28, 0.84).
Our evaluation of MDR race/ethnicity data revealed misclassification, particularly among some minority groups, and substantial missingness among DB. The potential bias introduced impacts the ability to address health disparities and conduct health research in the MHS, including studies of COVID-19, and needs further examination.
据报道，不同种族/族裔群体之间存在不平等的疾病负担，如SARS-CoV-2感染率和COVID-19结局。种族和族裔数据的错误分类以及缺失阻碍了美国军事卫生系统（MHS）识别和解决健康差异的努力；因此，我们通过与在具有大流行潜力的新兴传染病的流行病学、免疫学和临床特征（EPICC）队列研究中通过问卷收集的自我报告种族/族裔进行比较，评估了MHS数据存储库（MDR）中行政记录的种族/族裔数据的统计准确性。
研究人群包括6009名现役/退休军人（AD/R）及其受抚养受益人（DB）。以EPICC研究的回答为“金标准”，我们按种族/族裔类别（非西班牙裔（NH）白人、NH黑人、西班牙裔、NH亚裔/太平洋岛民（A/PI）、NH美洲印第安人/阿拉斯加原住民（AI/AN）、NH其他、缺失/未知）计算敏感性和阳性预测值（PPV）。
在AD/R中，敏感性和PPV值最高的是NH白人（0.93，0.96）、NH黑人（0.90，0.92）、西班牙裔（0.80，0.93）和NH A/PI（0.84，0.95），最低的是NH AI/AN（0.62，0.57）和NH其他（0.09，0.03）。MDR中约63%的DB缺少种族/族裔数据，敏感性值虽然不是PPV，但相对低得多：NH白人（0.35，0.88）、NH黑人（0.55，0.89）、西班牙裔（0.13，1.00）和NH A/PI（0.28，0.84）。
我们对MDR种族/族裔数据的评估揭示了错误分类，特别是在一些少数群体中，以及DB中的大量数据缺失。由此引入的潜在偏差影响了MHS中解决健康差异和开展健康研究的能力，包括对COVID-19的研究，需要进一步审查。
