OBJECTIVE: To 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. DESIGN: Cross-sectional observational study using the Clinical Practice Research Datalink Aurum prelinked to Hospital Episode Statistics. SETTING: Individual-level routine clinical data from 13 million patients across general practices (GPs) and secondary data in England. PARTICIPANTS: Individuals aged ≥66 years on 1 September 2019. MAIN OUTCOME MEASURES: We 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. RESULTS: We 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. CONCLUSION: Overall, 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.