Combinations of multiple long-term conditions and risk of hospitalisation and death during the winter season: population-based study of 48 million people in England

Background The annual winter season poses substantial challenges to the National Health Service (NHS) in England. Hospitalisation and mortality increase during winter, especially in people with multiple long-term conditions (MLTC or multimorbidity). We aimed to describe which combinations of long-term conditions (LTC) are associated with a higher risk of hospitalisation and death during winter amongst adults in England. Methods In this population-based study, we used linked primary and secondary care data from the General Practice Extraction Service Data for Pandemic Planning (GDPPR) database, Hospital Episode Statistics, and Office for National Statistics death registry. We included individuals aged ≥18 years and alive on 1st December 2021 and used overdispersed Poisson models to estimate the incidence rate ratios of all-cause hospitalisations and deaths associated with the combinations of MLTCs – compared to those with no LTC – during the winter season (1 December 2021 to 31 March 2022). Findings Complete data were available for 48,253,125 adults, of which 15 million (31.2%) had MLTC. Hospitalisation per 1000 person-years was higher in individuals with MLTCs, and varied by combination, e.g.: 96, 1643, and 1552 in individuals with no LTC, cancer+chronic kidney disease (CKD)+cardiovascular disease (CVD)+type 2 diabetes mellitus, and cancer+CKD+CVD+osteoarthritis, respectively. Incidence of death (per 1000 person-years) was 345 in individuals with cancer+CKD+CVD+dementia and 1 with no LTC. CVD+dementia appeared in all the top five MLTC combinations by death and was associated with a substantially higher rate of death than many 3-, 4- and 5-disease combinations. Interpretation Risks of hospitalisation and death vary by combinations of MLTCs and are substantially higher in those with vs. without any LTCs. We have highlighted high-risk combinations for prioritisation and preventive action by policymakers to help manage the challenges imposed by winter pressures on the NHS. Funding National Institute for Health and Care Research (NIHR) through Health Data Research UK rapid funding call for the research activity “Data Science to inform NHS compound winter pressure policy response” (grant number: HDRUK2022.0313) Evidence before this study We searched PubMed, from inception to April 2023, for published population-based studies examining MLTC combinations in cohorts of adults aged 18 years and over. The search terms were “multimorbidity” or ‘’multiple-long-term conditions’’ alongside “groups” or “combinations”. We found no previous studies examining MLTC in relation to death or hospitalisation during the winter season. Added value of this study We have identified distinct combinations of LTCs and estimated the associated risk of hospitalisation and deaths during the winter season using the whole-population primary and secondary care data in England. Implications of all the available evidence Understanding which combinations of MLTCs are associated with the highest risk of hospitalisation and death allows clinicians and policymakers to prioritise resources for preventative measures, such as vaccination to those that will benefit most during winter seasons. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This work is supported by the National Institute for Health and Care Research (NIHR) through Health Data Research UK rapid funding call for the research activity - Data Science to inform NHS compound winter pressure policy response (grant number: HDRUK2022.0313). Health Data Research UK is funded by the British Heart Foundation, Chief Scientists Office of the Scottish Government, Health and Care Research Wales, Health & Social Care Research and Development N. Ireland, Engineering and Physical Sciences Research, Economic and Social Research Council, Medical Research Council, National Institute for Health Research, Cancer Research UK. The funder had no role in study design, data collection, analysis or interpretation, or manuscript writing. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: This project used anonymised electronic health records and administrative data which were collected and curated by NHS Digital in a Trusted Research Environment. Data access is available for research conditional on the approval of a research proposal and protocol, data access agreements with NHS Digital, and other information governance requirements. This project falls within the remit of the CVD-COVID-UK/COVID-IMPACT research programme, supported by the British Heart Foundation (BHF) Data Science Centre and the Health Data Research UK (HDR UK), which obtained overall ethics from the Northeast-Newcastle and North Tyneside 2 research ethics committee (REC No 20/NE/0161). Additional details of the linkage, approval, and scope of the consortium approved to use this data have been described here: Wood A, Denholm R, Hollings S, Cooper J, Ip S, Walker V, et al. Linked electronic health records for research on a nationwide cohort of more than 54 million people in England: data resource. BMJ [Internet]. 2021 Apr 7 [cited 2023 May 26];373. Available from: https://www.bmj.com/content/373/bmj.n826 I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes The analytical codes and phenotypes used within the NHS Digital Trusted Research Environment are available in the following repository (GitHub link https://github.com/BHFDSC/CCU059_01). This project used anonymised electronic health records and administrative data which were collected and curated by NHS Digital in a Trusted Research Environment. Due to policies on information governance restrictions, the authors are unable to share individual patient data directly, but data access is available for research conditional on the approval of a research proposal and protocol, data access agreements with NHS Digital, and other information governance requirements. The authors and colleagues across the CVD-COVID-UK/COVID-IMPACT consortium have invested considerable time and energy in developing this data resource and would like to ensure that it is used widely to maximise its value. For inquiries about data access, please see https://web.www.healthdatagateway.org/dataset/7e5f0247-f033-4f98-aed3-3d7422b9dc6d. Data access approval was granted to the CVD-COVID-UK consortium (under project proposal CCU059) through the NHS Digital online Data Access Request Service (DARS-NIC-391419-J3W9T). NHS Digital data have been made available for research under the Control of Patient Information notice, which mandated the sharing of national electronic health records for COVID-19 research (https://digital.nhs.uk/coronavirus/coronavirus-covid-19-response-information-governance-hub/control-of-patient-informationcopi-notice) * BHF : British Heart Foundation CKD : Chronic Kidney Disease CVD : Cardiovascular Diseases DHSC : Department of Health and Social Care GDPPR : General Practice Extraction Service Data for pandemic planning GPES : General Practice Extraction Service HDRUK : Health Data Research United Kingdom HES APC : Hospital Episode Statistics Admitted Patient Care IMD : Index of Multiple Deprivation LTC : Long term conditions NHS : National Health Service NIHR : National Institute for Health and Care Research OA : Osteoarthritis ONS : Office for National Statistics PPIE : Public and Patient Involvement and Engagement T2DM : Type 2 Diabetes Mellitus TRE : Trusted Research Environment