High Risk and Preventable Harm Groups Identified in Clustering of Older Patients on Features Associated with Adverse Drug Reactions

Title:High Risk and Preventable Harm Groups Identified in Clustering of Older Patients on Features Associated with Adverse Drug Reactions

Authors:Volodymyr Chapman, Asra Aslam, Andrew Clegg, Mark Gabbay, Roy Ruddle, Maurice O'Connell, Matthew Sperrin, Eduard Shantsila, Tjeerd Van Staa, Frances Mair, Alan Woodall, Gary Leeming, Danushka Bollegala, Olusegun Popoola, Simon Maskell, Alan Griffiths, Iain Buchan, Lauren Walker and Samuel Relton

Conference:IEEE CBMS 2026

Tags:Adverse drug reactions, Clustering, Cox Regression and Time-to-event analysis

Abstract:

Background Adverse drug reactions (ADR) leading to hospitalization cause considerable physical and emotional harm to patients and have been estimated to cost the UK NHS £2.21Bn per year. Structured Medication Reviews (SMRs) aim to prevent such harm through comprehensive review and revision of medications. Challenges remain in objective selection of patients for SMR, considering both risk of harm and potential for medicine optimization. We present subgroups of older patients with distinct characteristics and use of medications previously reported to associate with preventable ADRs. Methods Published ADR event codes were used to classify ADR hospitalizations in 634k electronic healthcare records from the CPRD AURUM dataset, filtered for patients defined as older (65+ years) on 01/04/2019. Time for ADR hospitalization was monitored from this date to 31/03/2020. Patients were split into training (90%) and testing (10%) partitions, stratified for equal proportions of ADR hospitalization. LASSO Cox regression extracted features associated with ADR hospitalization risk from 1,014 features describing medication, patient demographics and clinical characteristics. Finally, semi-supervised clustering was performed on extracted features to group patients on ADR risk. Results LASSO Cox regression extracted 74 features associated with ADR hospitalization, including scaled age (hazard ratio / HR: 2.48), alcohol liver disease (HR: 1.75) and unrecorded ethnicity (HR: 1.44). Patients clustered into two high ADR hospitalization older groups, two disease-specific groups and a healthy ageing group. Conclusion This work identified 5 patient subgroups with characteristic features and ADR risk. Future work will investigate scope for medicines optimization within groups, for prevention of ADR harm.