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1746. Supporting long-term decision making at regional level through modelling long-term changes in population health state and associated healthcare resource usage
Invited abstract in session MA-17: Decision support in healthcare, stream OR in Health Services (ORAHS).
Monday, 8:30-10:00Room: 40 (building: 116)
Authors (first author is the speaker)
| 1. | Christos Vasilakis
|
| School of Management, University of Bath | |
| 2. | Zehra Önen-Dumlu
|
| School of Management, University of Bath | |
| 3. | Luke Shaw
|
| NHS BNSSG ICB | |
| 4. | Richard Wood
|
| BNSSG Clinical Commissioning Group |
Abstract
Decisions around medium and long-term allocation of healthcare resources are fraught with challenges arising from the inherent uncertainties in population growth as well as developments in the economy, society and technology. Against this background, health and care planners are constantly facing challenges on how to allocate healthcare resources with limited budget. The aim of this paper is to describe the development and early use of an innovative mathematical model and accompanying tool that captures the likely impact of long-term changes in a regional population and associated healthcare resource requirements. The modelling tool works in two stages: first, it derives 20-year population projections based on a Markov chain; second, it calculates healthcare activity and related costs for same time horizon. Population projections are based on segmentation of the population with respect to the Cambridge Multimorbidity Score derived from a state-of-the-art system wide dataset that provides patient-level linkable data for the entire population of a region in England of about 1 million people. Our innovative model and tool, which is already informing decisions in the collaborating health care system, offers planning support by generating long-term population projections as well as provides capacity for running scenarios that flex the 'do nothing' (baseline) scenario by considering various mitigations.
Keywords
- Health Care
Status: accepted
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