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Approaches to handling missing ethnicity data in primary care data research in England and Wales: a systematic review
Anna Meffen1, Joanne Miksza2, Safoora Gharibzadeh2
1Leicester Real World Evidence Unit, University of Leicester, Leicester, UK am1313@le.ac.uk.
Background:
Ethnicity data are essential for understanding health inequalities yet incomplete data can bias analyses and undermine representation. Reporting guidelines recommend that studies report how missing data are handled as methodology varies. However, little is known about trends in ethnicity missingness method use. Patient and Public Involvement (PPI) can shape equitable practices although its role in decisions about handling missing ethnicity remains unclear. This review aimed to describe trends in handling missing ethnicity data, reporting guideline adherence and the role of PPI.
Methods:
A systematic review identified approaches to handling missing ethnicity data in studies using national primary care databases in England and Wales. Medline, Cochrane Library, CINAHL, Scopus, Web of Science and database bibliographies were searched. Approaches to handling missing ethnicity were extracted and grouped (eg, 'missing/unknown' categorisation exclusion imputation). Time trends, reporting guidelines and PPI use were summarised.
Results:
313 studies were included. Over half used Clinical Practice Research Datalink. Nearly half linked to secondary care data; only one in four supplemented ethnicity using secondary sources. The most frequent methods were 'missing/unknown' categorisation (85, 27.2%) and exclusion (83, 26.5%); 71 studies (22.7%) used imputation. Nearly one-third of studies (99) provided no or unclear details; 100 (31.9%) cited reporting guidelines. 38 studies (12.1%) mentioned PPI; none detailed PPI involvement in missing data choices.
Conclusion:
Handling of missing ethnicity data in primary care research in England and Wales is inconsistent and poorly reported. Greater transparency is needed to improve interpretability, comparability and inclusivity of research using routine health data.
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