Ethnicity recording in primary care: multiple imputation of missing data in ethnicity recording using The Health Improvement Network (THIN) database

Tra My Pham, Tim P. Morris () and Irene Petersen ()
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Tim P. Morris: MRC Clinical Trials Unit, University College London, UK
Irene Petersen: Department of Primary Care and Population Health, University College London, UK

United Kingdom Stata Users' Group Meetings 2015 from Stata Users Group

Abstract: Ethnicity is an important factor to be considered in many epidemiological studies because of its association with inequality in disease prevalence and the utilisation of healthcare. Ethnicity recording has been incorporated in primary care electronic health records, and therefore is available in a number of large UK primary care databases such as The Health Improvement Network (THIN). However, since primary care data are routinely collected to serve clinical purposes, a large amount of data that are relevant for research purposes including ethnicity is often missing. A popular approach is to use multiple imputation, but the standard multiple imputation does not give plausible estimates of the ethnicity distribution in THIN compared to the general UK population. However, census data can be utilised to form weights to use in multiple imputation such that the correct ethnicity distribution is recovered. I will describe how the method of weighted multiple imputation of missing data is implemented using the Stata’s mi impute suite, note some issues, and introduce a new procedure to implement the method for multiple incomplete variables which require different imputation weights. Finally, I will give an example showing how the method works when ethnicity is used as an explanatory variable in a cohort study.

Date: 2015-09-16
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Persistent link: https://EconPapers.repec.org/RePEc:boc:usug15:07

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