Leveraging Multiple Administrative Data Sources to Reduce Missing Race and Ethnicity Data: A Descriptive Epidemiology Cross-Sectional Study of COVID-19 Case Relative Rates.

IF 3.2 3区 医学 Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH Journal of Racial and Ethnic Health Disparities Pub Date : 2024-10-22 DOI:10.1007/s40615-024-02211-w
Vajeera Dorabawila, Rebecca Hoen, Dina Hoefer
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Abstract

Background: Understanding race and ethnicity (RE) differentials improves health outcomes. However, RE data are consistently missing from electronic laboratory reports, the primary source of COVID-19 case metrics. We addressed the missing RE differentials and compared vaccinated and unvaccinated cases from March 1, 2020, to May 30, 2023, in New York State (NYS), excluding New York City.

Methods: This descriptive epidemiology cross-sectional study linked the NYS Electronic Clinical Laboratory Reporting System (ECLRS) with NYS Immunization Information System (NYSIIS) to address the missing RE data in the ECLRS system. The primary metric was the COVID-19 case relative risk (RR) for each RE relative to white individuals.

Results: There were 4,212,741 COVID-19 cases with 39% (1,624,818) missing RE data in ECLRS; missing RE data declined to 17% (726,023) after matching with NYSIIS. For those aged 65 years or older (after matching), 42% were missing in 2020, which declined by 17% by 2023. In May 2021, COVID-19 RRs for vaccinated individuals were 1.09 (95% CI 0.90-1.32), 1.11 (95% CI 0.87-1.43), 1.13 (95% CI 0.93-1.39), and 1.89 (95% CI 1.01-3.52), and for unvaccinated individuals were 1.73 (95% CI 1.66-1.82), 0.84 (95% CI 0.78-0.92), 3.10 (95% CI 2.98-3.22), and 3.49 (95% CI 3.05-3.98) respectively for Hispanic, Asian/Pacific Islander, Black people, and American Indian/Alaska Native individuals.

Conclusion: Matching case data with vaccine registries reduce missing RE data for COVID-19 cases. Disparity was lower in vaccinated than in unvaccinated individuals indicating that vaccination mitigated RE disparities early in the pandemic. This underscores the value of interoperable systems with automated matching for disparity analyses.

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利用多种管理数据源减少缺失的种族和民族数据:COVID-19 病例相对比率的描述性流行病学横断面研究》(A Descriptive Epidemiology Cross-Sectional Study of COVID-19 Case Relative Rates)。
背景:了解种族和民族(RE)差异可改善健康结果。然而,作为 COVID-19 病例指标的主要来源,电子实验室报告中一直缺少 RE 数据。我们研究了缺失的 RE 差异,并比较了 2020 年 3 月 1 日至 2023 年 5 月 30 日期间纽约州(NYS)(不包括纽约市)接种疫苗和未接种疫苗的病例:这项描述性流行病学横断面研究将纽约州电子临床实验室报告系统(ECLRS)与纽约州免疫信息系统(NYSIIS)连接起来,以解决ECLRS系统中缺少RE数据的问题。主要指标是每种RE相对于白人的COVID-19病例相对风险(RR):ECLRS系统中有4,212,741例COVID-19病例,其中39%(1,624,818例)的RE数据缺失;与NYSIIS系统匹配后,缺失的RE数据降至17%(726,023例)。对于 65 岁或以上的人群(匹配后),2020 年有 42% 的数据缺失,到 2023 年下降了 17%。2021 年 5 月,接种疫苗者的 COVID-19 RRs 分别为 1.09(95% CI 0.90-1.32)、1.11(95% CI 0.87-1.43)、1.13(95% CI 0.93-1.39)和 1.89(95% CI 1.01-3.52),未接种疫苗者的 COVID-19 RRs 分别为 1.73(95% CI 1.在西班牙裔、亚太裔、黑人和美国印第安人/阿拉斯加原住民中,未接种者分别为1.73(95% CI 1.66-1.82)、0.84(95% CI 0.78-0.92)、3.10(95% CI 2.98-3.22)和3.49(95% CI 3.05-3.98):结论:将病例数据与疫苗登记进行匹配可减少 COVID-19 病例中 RE 数据的缺失。已接种疫苗者的差异低于未接种疫苗者,这表明在大流行早期接种疫苗可减轻RE差异。这凸显了具有自动匹配功能的互操作系统在差异分析中的价值。
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来源期刊
Journal of Racial and Ethnic Health Disparities
Journal of Racial and Ethnic Health Disparities PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH-
CiteScore
7.30
自引率
5.10%
发文量
263
期刊介绍: Journal of Racial and Ethnic Health Disparities reports on the scholarly progress of work to understand, address, and ultimately eliminate health disparities based on race and ethnicity. Efforts to explore underlying causes of health disparities and to describe interventions that have been undertaken to address racial and ethnic health disparities are featured. Promising studies that are ongoing or studies that have longer term data are welcome, as are studies that serve as lessons for best practices in eliminating health disparities. Original research, systematic reviews, and commentaries presenting the state-of-the-art thinking on problems centered on health disparities will be considered for publication. We particularly encourage review articles that generate innovative and testable ideas, and constructive discussions and/or critiques of health disparities.Because the Journal of Racial and Ethnic Health Disparities receives a large number of submissions, about 30% of submissions to the Journal are sent out for full peer review.
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