An optimisation framework for resource allocation in palliative and end-of-life care.

End-of-life care for frail and elderly patients is frequently characterised by high healthcare utilisation, fragmented service delivery, and limited coordination, resulting in variable quality and excess cost. This study presents a proof-of-concept framework, tested using synthetic data to illustrate potential applications in strategic planning. Few planning approaches integrate patient-level pathways into operational models that balance efficiency with patient-centred outcomes. Optimisation models were developed to support strategic resource planning for frail, elderly, and palliative patients in the final year of life. Two formulations were explored: one minimising overall cost and another aligning demand with available capacity. Patients were stratified into ten representative categories and assigned to structured pathways with varying resource intensities across hospital beds, palliative beds, community nursing, and virtual wards. A synthetic dataset representing plausible twelve-month service trajectories was used to assess model performance. Both models produced feasible allocations that satisfied expected demand within capacity limits. Most patient groups were consistently assigned to dominant pathways, while some shifted depending on the optimisation objective, illustrating trade-offs between cost efficiency and balanced utilisation. Demand intensified in the final months of life but remained manageable under planning assumptions. The modelling framework demonstrates the feasibility of applying optimisation to anticipatory planning, enabling comparison of service configurations and supporting more coordinated, efficient, and patient-centred end-of-life care.