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

Authors: Amele, Sarah;

McCabe, Ronan;

Kibuchi, Eliud ;

Pearce, Anna;

Hainey, Kirsten J.;

Demou, Evangelia ;

Irizar, Patricia ;

Kapadia, Dharmi;

Taylor, Harry;

Nazroo, James;

Bécares, Laia ;

Buchanan, Duncan;

Henery, Paul M.;

Jayacodi, Sandra;

Woolford, Lana;

Simpson, Colin R. ;

Sheikh, Aziz ;

Jeffrey, Karen;

Shi, Ting ;

Daines, Luke ;

Tibble, Holly ;

Almaghrabi, Fatima;

Fagbamigbe, Adeniyi F. ;

Kurdi, Amanj ;

Robertson, Chris;

Pattaro, Serena;

Katikireddi, Srinivasa Vittal

Source: Journal of Public Health

Full text

: https://doi.org/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.

Rights

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

Cite as

Amele, S., McCabe, R., Kibuchi, E., Pearce, A., Hainey, K., Demou, E., Irizar, P., Kapadia, D., Taylor, H., Nazroo, J., Bécares, L., Buchanan, D., Henery, P., Jayacodi, S., Woolford, L., Simpson, C., Sheikh, A., Jeffrey, K., Shi, T., Daines, L., Tibble, H., Almaghrabi, F., Fagbamigbe, A., Kurdi, A., Robertson, C., Pattaro, S. & Katikireddi, S. 2023, '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, article no: fdad196. https://doi.org/10.1093/pubmed/fdad196

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Identifiers

DOI: https://doi.org/10.1093/pubmed/fdad196

Repository URI: https://eprints.gla.ac.uk/306684/