Optimal administrative geographies: an algorithmic approach
Optimal administrative geographies: an algorithmic approach
Centrally planned Beveridge healthcare systems typically rely heavily on local or regional “health authorities” as responsible organisations for the care of geographically defined populations. The frequency of reorganisations in the English NHS suggests that there is no compelling unitary definition of what constitutes a good healthcare geography. In this paper we propose a set of desirable objectives for an administrative healthcare geography, specifically: geographical compactness, co-extensiveness with current local authorities and size and population homogeneity, and we show how these might be operationally measured. Based on these objectives, we represent the problem of how to partition a territory into health authorities as a multi-objective optimisation problem. We use a state-of-the-art multi-objective genetic algorithm customised for the needs of our study to partition the territory of the East England into 14 Primary Care Trusts and 50 GP consortia and study the tradeoffs between objectives which this reveals.
primary care trusts, multi-objective optimisation, genetic algorithm, healthcare geography, GP consortium
247-257
Datta, D.
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Figueira, J.R.
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Gourtani, A.M.
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Morton, A.
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September 2013
Datta, D.
b261c3e5-ff64-476f-a836-72ba049a459c
Figueira, J.R.
7990a800-9bb8-40ca-9428-3484dfcbb212
Gourtani, A.M.
e52b011f-3885-4fcb-8c58-02149c223585
Morton, A.
5633d9e0-db77-4c03-ae3d-9f879a123e4c
Datta, D., Figueira, J.R., Gourtani, A.M. and Morton, A.
(2013)
Optimal administrative geographies: an algorithmic approach.
Socio-Economic Planning Sciences, 47 (3), .
(doi:10.1016/j.seps.2013.03.002).
Abstract
Centrally planned Beveridge healthcare systems typically rely heavily on local or regional “health authorities” as responsible organisations for the care of geographically defined populations. The frequency of reorganisations in the English NHS suggests that there is no compelling unitary definition of what constitutes a good healthcare geography. In this paper we propose a set of desirable objectives for an administrative healthcare geography, specifically: geographical compactness, co-extensiveness with current local authorities and size and population homogeneity, and we show how these might be operationally measured. Based on these objectives, we represent the problem of how to partition a territory into health authorities as a multi-objective optimisation problem. We use a state-of-the-art multi-objective genetic algorithm customised for the needs of our study to partition the territory of the East England into 14 Primary Care Trusts and 50 GP consortia and study the tradeoffs between objectives which this reveals.
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Published date: September 2013
Keywords:
primary care trusts, multi-objective optimisation, genetic algorithm, healthcare geography, GP consortium
Organisations:
Faculty of Social, Human and Mathematical Sciences
Identifiers
Local EPrints ID: 369307
URI: http://eprints.soton.ac.uk/id/eprint/369307
ISSN: 0038-0121
PURE UUID: f375e0f3-c317-48db-bfab-889d878c4b2f
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Date deposited: 23 Sep 2014 13:14
Last modified: 14 Mar 2024 18:00
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Author:
D. Datta
Author:
J.R. Figueira
Author:
A.M. Gourtani
Author:
A. Morton
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