Asset Details
MbrlCatalogueTitleDetail
Do you wish to reserve the book?
An optimisation framework for resource allocation in palliative and end-of-life care
by
Gartner, Daniel
, Kumar, Maneesh
, Brice, Syaribah
, Williams, Elizabeth
, Harper, Paul
, Byrne, Anthony
in
639/705
/ 692/308
/ 692/700
/ Aged
/ Data-driven modelling
/ Decision making
/ Efficiency
/ Expenditures
/ Frailty
/ Health services utilization
/ Healthcare optimisation
/ Humanities and Social Sciences
/ Humans
/ Integer programming
/ Integrated approach
/ multidisciplinary
/ Palliation
/ Palliative care
/ Palliative Care - economics
/ Patients
/ Resource Allocation
/ Resource planning
/ Science
/ Science (multidisciplinary)
/ Strategic planning
/ Terminal Care - economics
2026
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
You are currently in the queue to collect this book. You will be notified once it is your turn to collect the book.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
An optimisation framework for resource allocation in palliative and end-of-life care
by
Gartner, Daniel
, Kumar, Maneesh
, Brice, Syaribah
, Williams, Elizabeth
, Harper, Paul
, Byrne, Anthony
in
639/705
/ 692/308
/ 692/700
/ Aged
/ Data-driven modelling
/ Decision making
/ Efficiency
/ Expenditures
/ Frailty
/ Health services utilization
/ Healthcare optimisation
/ Humanities and Social Sciences
/ Humans
/ Integer programming
/ Integrated approach
/ multidisciplinary
/ Palliation
/ Palliative care
/ Palliative Care - economics
/ Patients
/ Resource Allocation
/ Resource planning
/ Science
/ Science (multidisciplinary)
/ Strategic planning
/ Terminal Care - economics
2026
Oops! Something went wrong.
While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
An optimisation framework for resource allocation in palliative and end-of-life care
by
Gartner, Daniel
, Kumar, Maneesh
, Brice, Syaribah
, Williams, Elizabeth
, Harper, Paul
, Byrne, Anthony
in
639/705
/ 692/308
/ 692/700
/ Aged
/ Data-driven modelling
/ Decision making
/ Efficiency
/ Expenditures
/ Frailty
/ Health services utilization
/ Healthcare optimisation
/ Humanities and Social Sciences
/ Humans
/ Integer programming
/ Integrated approach
/ multidisciplinary
/ Palliation
/ Palliative care
/ Palliative Care - economics
/ Patients
/ Resource Allocation
/ Resource planning
/ Science
/ Science (multidisciplinary)
/ Strategic planning
/ Terminal Care - economics
2026
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
An optimisation framework for resource allocation in palliative and end-of-life care
Journal Article
An optimisation framework for resource allocation in palliative and end-of-life care
2026
Request Book From Autostore
and Choose the Collection Method
Overview
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.
This website uses cookies to ensure you get the best experience on our website.