Observational studyBMJ open2024
Identifying markers of health-seeking behaviour and healthcare access in UK electronic health records.
Observational study in BMJ open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Sex-specific associations between homelessness and cerebrovascular disease among aging US veterans in the Veterans Affairs healthcare system.GeroScience · 2025Article
- The impact of COVID vaccination on incidence of long COVID and healthcare resource utilisation in a primary care cohort in England, 2021-2022.BMC infectious diseases · 2025Article
- Assessment of common mental disorders in the Avon Longitudinal Study of Parents and Children (ALSPAC) birth cohort at age 24 years using the Clinical Interview Schedule-Revised (CIS-R).Wellcome open research · 2025Article
- Quantifying and Adjusting for Confounding From Health-Seeking Behavior and Health Care Access in Observational Research.Open forum infectious diseases · 2024Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo assess the feasibility of identifying markers of health-seeking behaviour and healthcare access in UK electronic health records (EHR), for identifying populations at risk of poor health outcomes and adjusting for confounding in epidemiological studies.
designCross-sectional observational study using the Clinical Practice Research Datalink Aurum prelinked to Hospital Episode Statistics.
settingIndividual-level routine clinical data from 13 million patients across general practices (GPs) and secondary data in England.
participantsIndividuals aged ≥66 years on 1 September 2019.
main outcome measuresWe used the Theory of Planned Behaviour (TPB) model and the literature to iteratively develop criteria for markers selection. Based on this we selected 15 markers: those that represented uptake of public health interventions, markers of active healthcare access/use and markers of lack of access/underuse. We calculated the prevalence of each marker using relevant lookback periods prior to the index date (1 September 2019) and compared with national estimates. We assessed the correlation coefficients (phi) between markers with inferred hierarchical clustering.
resultsWe included 1 991 284 individuals (mean age: 75.9 and 54.0% women). The prevalence of markers ranged from <0.1% (low-value prescriptions) to 92.6% (GP visits), and most were in line with national estimates; for example, 73.3% for influenza vaccination in the 2018/2019 season, compared with 72.4% in national estimates. Screening markers, for example, abdominal aortic aneurysm screening were under-recorded even in age-eligible groups (54.3% in 65-69 years old vs 76.1% in national estimates in men). Overall, marker correlations were low (<0.5) and clustered into groups according to underlying determinants from the TPB model.
conclusionOverall, markers of health-seeking behaviour and healthcare access can be identified in UK EHRs. The generally low correlations between different markers of health-seeking behaviour and healthcare access suggest a range of variables are needed to capture different determinants of healthcare use.
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