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

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Amele, Sarah and McCabe, Ronan and Kibuchi, Eliud and Pearce, Anna and Hainey, Kirsten and Demou, Evangelia and Irizar, Patricia and Kapadia, Dharmi and Taylor, Harry and Nazroo, James and Bécares, Laia and Buchanan, Duncan and Henery, Paul and Jayacodi, Sandra and Woolford, Lana and Simpson, Colin R. and Sheikh, Aziz and Jeffrey, Karen and Shi, Ting and Daines, Luke and Tibble, Holly and Almaghrabi, Fatima and Fagbamigbe, Adeniyi Francis and Kurdi, Amanj and Robertson, Chris and Pattaro, Serena and Katikireddi, Srinivasa Vittal (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, 46 (1). pp. 116-122. fdad196. ISSN 1741-3842 (https://doi.org/10.1093/pubmed/fdad196)

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Abstract

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

ORCID iDs

Amele, Sarah, McCabe, Ronan, Kibuchi, Eliud, Pearce, Anna, Hainey, Kirsten, Demou, Evangelia, Irizar, Patricia, Kapadia, Dharmi, Taylor, Harry, Nazroo, James, Bécares, Laia, Buchanan, Duncan, Henery, Paul, Jayacodi, Sandra, Woolford, Lana, Simpson, Colin R., Sheikh, Aziz, Jeffrey, Karen, Shi, Ting, Daines, Luke, Tibble, Holly, Almaghrabi, Fatima, Fagbamigbe, Adeniyi Francis, Kurdi, Amanj ORCID logoORCID: https://orcid.org/0000-0001-5036-1988, Robertson, Chris, Pattaro, Serena and Katikireddi, Srinivasa Vittal;
CORE (COnnecting REpositories)