Is it possible to identify populations experiencing material disadvantage in primary care? A feasibility study using the Clinical Practice Research Database

BackgroundMaterial disadvantage is associated with poor health, but commonly available area-based metrics provide a poor proxy for it. We investigate if a measure of material disadvantage could be constructed from UK primary care electronic health records.MethodsUsing data from Clinical Practice Res...

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Bibliographic Details
Published in:Journal of epidemiology and community health (1979) 2024-09, Vol.78 (12), p.806-808
Main Authors: Davies, Laurie E, Sinclair, David R, Kingston, Andrew, Spiers, Gemma Frances, Hanratty, Barbara
Format: Article
Language:English
Subjects:
Adolescent
Adult
Aged
Clinical medicine
Codes
Databases, Factual
Electronic Health Records
Electronic medical records
Ethics
Feasibility Studies
Female
GENERAL PRACTICE
Health disparities
Health inequalities
Health Status Disparities
Humans
Male
Middle Aged
Patients
Population studies
POVERTY
Practice research
Primary care
PRIMARY HEALTH CARE
PUBLIC HEALTH
Short Report
Socioeconomic Factors
United Kingdom
Vulnerable Populations
Young Adult
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Summary:BackgroundMaterial disadvantage is associated with poor health, but commonly available area-based metrics provide a poor proxy for it. We investigate if a measure of material disadvantage could be constructed from UK primary care electronic health records.MethodsUsing data from Clinical Practice Research Datalink Aurum (May 2022) linked to the 2019 English Index of Multiple Deprivation (IMD), we sought to (1) identify codes that signified material disadvantage, (2) aggregate these codes into a binary measure of material disadvantage and (3) compare the proportion of people with this binary measure against IMD quintiles for validation purposes.ResultsWe identified 491 codes related to benefits, employment, housing, income, environment, neglect, support services and transport. Participants with one or more of these codes were defined as being materially disadvantaged. Among 30,897,729 research-acceptable patients aged ≥18 with complete data, only 6.1% (n=1,894,225) were classified as disadvantaged using our binary measure, whereas 42.2% (n=13,038,085) belonged to the two most deprived IMD quintiles.ConclusionData in a major primary care research database do not currently contain a useful measure of individual-level material disadvantage. This represents an omission of one of the most important health determinants. Consideration should be given to creating codes for use by primary care practitioners.
ISSN:0143-005X
1470-2738
1470-2738
DOI:10.1136/jech-2024-222396