The relationship between general practice characteristics, case-mix, and secondary care attendances/admissions before...

Healthcare services in England experience increased pressure during winter months due to seasonal infectious diseases, increased multimorbidity, and fluctuating demand. Understanding how characteristics of general practices, and their registered patient case-mix contribute to secondary care use-particularly for Ambulatory Care Sensitive Conditions (ACSCs)-is essential for planning and resource allocation. Primary and secondary care activity also significantly changed during the COVID-19 pandemic, and not all activity-types have returned to pre-pandemic levels in the years since, making it critical to examine trends across both pre-and post-pandemic periods.

OpenSAFELY-TPP was used to access linked electronic health record data, covering approximately 2,600 general practices (about 40% of all practices in England) and 26 million registered patients in England using TPP SystmOne software (2018-2025). Our analysis focused on weekly and aggregated rates of A&E attendances and hospital admissions during the flu and winter months (October to February), comparing patterns before and after the COVID-19 pandemic. Practice-level exposures included consultation rate per capita, practice size, region, and patient case-mix variables (e.g. age, sex, ethnicity, deprivation, multimorbidity). Outcomes included weekly rates of A&E attendances, total hospital admissions, and admissions for ACSCs.

We will summarise variation in practice characteristics, registered patient sociodemographics, case-mix, and service use across time periods. Associations between exposures and outcomes will be examined using generalised linear models, with additional subgroup analyses by age distribution. Sensitivity analyses will assess alternative flu season definitions and account for holiday and extreme weather.

This high-level descriptive study will provide valuable insights into variation in secondary care use across general practices and identify practice-level and case-mix factors that may contribute to winter pressures. The inclusion of both pre- and post-pandemic data will provide essential benchmarking data for future health system planning and further understanding of how the general practice context and patient case-mix affects hospital demand.