Dataset Information

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

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.

SUBMITTER: Amele S

PROVIDER: S-EPMC10901260 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature

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Publications

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

Amele Sarah S McCabe Ronan R Kibuchi Eliud E Pearce Anna A Hainey Kirsten K Demou Evangelia E Irizar Patricia P Kapadia Dharmi D Taylor Harry H Nazroo James J Bécares Laia L Buchanan Duncan D Henery Paul P Jayacodi Sandra S Woolford Lana L Simpson Colin R CR Sheikh Aziz A Jeffrey Karen K Shi Ting T Daines Luke L Tibble Holly H Almaghrabi Fatima F Fagbamigbe Adeniyi Francis AF Kurdi Amanj A Robertson Chris C Pattaro Serena S Katikireddi Srinivasa Vittal SV

Journal of public health (Oxford, England) 20240201 1

<h4>Background</h4>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.<h4>Methods</h4>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.<h4>Results</h4>Miscla ...[more]

PMID: 37861114

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Dataset Information

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

Background

Methods

Results

Conclusions

Publications

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

Similar Datasets

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