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BackgroundWe 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.MethodsMeasures 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.ResultsMisclassification 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.ConclusionsPoor quality ethnicity coding in health records can bias estimates, thereby threatening monitoring and understanding ethnic inequalities in health.

Original publication

DOI

10.1093/pubmed/fdad196

Type

Journal article

Journal

Journal of public health (Oxford, England)

Publication Date

02/2024

Volume

46

Pages

116 - 122

Addresses

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

Keywords

Humans, State Medicine, Scotland, Semantic Web, COVID-19, Ethnicity