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Optimal administrative geographies: an algorithmic approach

Datta, D., Figueira, J. R., Gourtani, A. M. and Morton, A. (2013) Optimal administrative geographies: an algorithmic approach. Socio-Economic Planning Sciences, 47 (3). pp. 247-257. ISSN 0038-0121

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Identification Number: 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.

Item Type: Article
Official URL: http://www.journals.elsevier.com/socio-economic-pl...
Additional Information: © 2013 Elsevier Ltd
Divisions: Management
LSE Health
Subjects: H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
R Medicine > RA Public aspects of medicine
Sets: Departments > Management
Research centres and groups > LSE Health
Research centres and groups > Management Science Group
Date Deposited: 16 May 2013 14:27
Last Modified: 20 Feb 2019 10:33
Projects: SFRH/BPD/34482/2006
Funders: Economic and Social Research Council, Joint Information Systems Committee
URI: http://eprints.lse.ac.uk/id/eprint/50286

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