Abstract
Decisions around the provision and allocation of care services within a regional health economy are multifaceted and often require a delicate balancing act across a number of trade-offs. Operational research is thus very suitable in providing insights and quantitative support to those tasked with making such decisions. The support can take different shapes, from providing a practical quantitative analysis of the problem, to deciding on the metrics the decisions should be based upon, to the development and use of more advanced techniques such as optimisation.
In this case study, we were commissioned to look into the provision and allocation of maternity services within a region in the UK. Having recently acquired a number of relevant facilities, the collaborating organisation asked us to evaluate the model of service provision currently in use and to support, through quantitative and geographic analysis, decisions around the strategic reconfiguration of the service.
The objectives, parameters and scenarios of the location analysis were discussed between the modelling team and the commissioners of the study. As part of this discussion, we articulated 12 scenarios to form the basis of the location analysis. We used a specialised software tool developed by researchers in the University of Bath to help with identifying the optimal locations of maternity service facilities. We did so by calculating the minimum distances travelled between a geographic central point of aggregate demand, as defined by the Middle Layer Super Output Area (MSOA), to the closest maternity facility (for the quickest route). Aggregate demand, used as input in the tool, was estimated based on historical data of demand adjusted for the index of deprivation associated with the relevant MSOA. The experimental results, which we will present during the talk, have been fed back to planners and are currently used to inform the reconfiguration process.
In this case study, we were commissioned to look into the provision and allocation of maternity services within a region in the UK. Having recently acquired a number of relevant facilities, the collaborating organisation asked us to evaluate the model of service provision currently in use and to support, through quantitative and geographic analysis, decisions around the strategic reconfiguration of the service.
The objectives, parameters and scenarios of the location analysis were discussed between the modelling team and the commissioners of the study. As part of this discussion, we articulated 12 scenarios to form the basis of the location analysis. We used a specialised software tool developed by researchers in the University of Bath to help with identifying the optimal locations of maternity service facilities. We did so by calculating the minimum distances travelled between a geographic central point of aggregate demand, as defined by the Middle Layer Super Output Area (MSOA), to the closest maternity facility (for the quickest route). Aggregate demand, used as input in the tool, was estimated based on historical data of demand adjusted for the index of deprivation associated with the relevant MSOA. The experimental results, which we will present during the talk, have been fed back to planners and are currently used to inform the reconfiguration process.
| Original language | English |
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| Publication status | Published - 2018 |
| Event | 44th meeting of the EURO Working Group on Operational Research Applied to Health Services - Oslo, Norway Duration: 29 Jul 2018 → 3 Aug 2018 http://www.ccnorway.no/orahs2018/ |
Conference
| Conference | 44th meeting of the EURO Working Group on Operational Research Applied to Health Services |
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| Abbreviated title | (ORAHS2018) |
| Country/Territory | Norway |
| City | Oslo |
| Period | 29/07/18 → 3/08/18 |
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