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

Amele, S. et al. (2024) Quality of ethnicity data within Scottish health records and implications of misclassification for ethnic inequalities in severe COVID-19: a national linked data study.Journal of Public Health, 46(1), pp. 116-122. (doi: 10.1093/pubmed/fdad196) (PMID:37861114) (PMCID:PMC10901260)

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.

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Funder and Project Information

1

Inequalities in health

Alastair Leyland

MC_UU_00022/2

HW - MRC/CSO Social and Public Health Sciences Unit

1

Inequalities in health

Alastair Leyland

SPHSU17

HW - MRC/CSO Social and Public Health Sciences Unit

Understanding the impacts of welfare policy on health: A novel data linkage study

Srinivasa Katikireddi

SCAF/15/02

SHW - Public Health

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