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苏格兰健康记录中种族数据的质量以及分类错误对 COVID-19 重症患者中种族不平等现象的影响:一项全国性关联数据研究。

Quality of ethnicity data within Scottish health records and implications of misclassification for ethnic inequalities in severe COVID-19: a national linked data study.

机构信息

MRC/CSO Social & Public Health Sciences Unit, University of Glasgow, Glasgow G12 8TB, UK.

Department of Sociology, School of Social Sciences, University of Manchester, Manchester M13 9PL, UK.

出版信息

J Public Health (Oxf). 2024 Feb 23;46(1):116-122. doi: 10.1093/pubmed/fdad196.

Abstract

BACKGROUND

We compared the quality of ethnicity coding within the Public Health Scotland Ethnicity Look-up (PHS-EL) dataset, and other National Health Service datasets, with the 2011 Scottish Census.

METHODS

Measures of quality included the level of missingness and misclassification. We examined the impact of misclassification using Cox proportional hazards to compare the risk of severe coronavirus disease (COVID-19) (hospitalization & death) by ethnic group.

RESULTS

Misclassification within PHS-EL was higher for all minority ethnic groups [12.5 to 69.1%] compared with the White Scottish majority [5.1%] and highest in the White Gypsy/Traveller group [69.1%]. Missingness in PHS-EL was highest among the White Other British group [39%] and lowest among the Pakistani group [17%]. PHS-EL data often underestimated severe COVID-19 risk compared with Census data. e.g. in the White Gypsy/Traveller group the Hazard Ratio (HR) was 1.68 [95% Confidence Intervals (CI): 1.03, 2.74] compared with the White Scottish majority using Census ethnicity data and 0.73 [95% CI: 0.10, 5.15] using PHS-EL data; and HR was 2.03 [95% CI: 1.20, 3.44] in the Census for the Bangladeshi group versus 1.45 [95% CI: 0.75, 2.78] in PHS-EL.

CONCLUSIONS

Poor quality ethnicity coding in health records can bias estimates, thereby threatening monitoring and understanding ethnic inequalities in health.

摘要

背景

我们比较了公共卫生苏格兰族裔查询(PHS-EL)数据集和其他国民保健服务数据集与 2011 年苏格兰人口普查的族裔编码质量。

方法

质量衡量标准包括缺失程度和分类错误程度。我们使用 Cox 比例风险模型检查了分类错误的影响,以比较按族裔划分的严重冠状病毒病(COVID-19)(住院和死亡)的风险。

结果

与白人苏格兰多数族裔(5.1%)相比,PHS-EL 中所有少数族裔群体的分类错误率更高(12.5%至 69.1%),而白种吉普赛/游民族裔的分类错误率最高(69.1%)。PHS-EL 中的缺失率在白种其他英国人组中最高(39%),在巴基斯坦组中最低(17%)。PHS-EL 数据通常低估了 COVID-19 严重程度的风险,与人口普查数据相比。例如,在白种吉普赛/游民群体中,使用人口普查族裔数据时,风险比(HR)为 1.68(95%置信区间[CI]:1.03,2.74),而使用 PHS-EL 数据时为 0.73(95%CI:0.10,5.15);在人口普查中,孟加拉裔的 HR 为 2.03(95%CI:1.20,3.44),而 PHS-EL 中的 HR 为 1.45(95%CI:0.75,2.78)。

结论

健康记录中族裔编码质量差可能会导致估计值出现偏差,从而威胁到对健康领域族裔不平等的监测和理解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c589/10901260/de039dc231c7/fdad196f1.jpg

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