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, CR, Sheikh, A, Jeffrey, K, Shi, T, Daines, L et al, Tibble, H, Almaghrabi, F, Fagbamigbe, AF, Kurdi, A, Robertson, C, Pattaro, S and Katikireddi, SV (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. ISSN 1741-3842

Preview

Text fdad196.pdf - Published Version Available under License Creative Commons Attribution. Download (457kB) | Preview

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.

Item Type:	Article
Uncontrolled Keywords:	Humans; State Medicine; Scotland; Semantic Web; COVID-19; Ethnicity; COVID-19; ethnicity; quality; Humans; Ethnicity; State Medicine; Semantic Web; COVID-19; Scotland; 4202 Epidemiology; 4206 Public Health; 42 Health Sciences; Coronaviruses; Clinical Research; Emerging Infectious Diseases; Infectious Diseases; 10 Reduced Inequalities; Humans; Ethnicity; State Medicine; Semantic Web; COVID-19; Scotland; 1117 Public Health and Health Services; Public Health; 4202 Epidemiology; 4203 Health services and systems; 4206 Public health
Subjects:	B Philosophy. Psychology. Religion > BF Psychology
Divisions:	Psychology (from Sep 2019)
Publisher:	Oxford University Press (OUP)
SWORD Depositor:	A Symplectic
Date Deposited:	18 Feb 2025 16:04
Last Modified:	18 Feb 2025 16:15
DOI or ID number:	10.1093/pubmed/fdad196
URI:	https://researchonline.ljmu.ac.uk/id/eprint/25659

View Item