Literature DB >> 31884514

The challenge of using routinely collected data to compare hospital admission rates by ethnic group: a demonstration project in Scotland.

S Knox1, R S Bhopal2, C S Thomson1, A Millard3, A Fraser4, L Gruer2, D Buchanan1.   

Abstract

BACKGROUND: Recording patients' ethnic group supports efforts to achieve equity in health care provision. Before the Equality Act (2010), recording ethnic group at hospital admission was poor in Scotland but has improved subsequently. We describe the first analysis of the utility of such data nationally for monitoring ethnic variation.
METHODS: We analysed all in-patient or day case hospital admissions in 2013. We imputed missing data using the most recent ethnic group recorded for a patient from 2009 to 2015. For episodes lacking an ethnic code, we attributed known ethnic codes proportionately. Using the 2011 Census population, we calculated rates and rate ratios for all-cause admissions and ischaemic heart diseases (IHDs) directly standardized for age.
RESULTS: Imputation reduced missing ethnic group codes from 24 to 15% and proportionate redistribution to zero. While some rates for both all-cause and IHD admissions appeared plausible, unexpectedly low or high rates were observed for several ethnic groups particularly amongst White groups and newly coded groups.
CONCLUSIONS: Completeness of ethnicity recoding on hospital admission records has improved markedly since 2010. However the validity of admission rates based on these data is variable across ethnic groups and further improvements are required to support monitoring of inequality.
© The Author(s) 2019. Published by Oxford University Press on behalf of Faculty of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  data quality; ethnic group coding; ethnicity; hospital admission

Mesh:

Year:  2020        PMID: 31884514     DOI: 10.1093/pubmed/fdz175

Source DB:  PubMed          Journal:  J Public Health (Oxf)        ISSN: 1741-3842            Impact factor:   2.341


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