Evidence map›Paper›PMID 20050933›Full record

ArticleHealth services research2010

Identification of hospital catchment areas using clustering: an example from the NHS.

Stuart John Gilmour

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Article in Health services research, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
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16citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

1 author.

Stuart John GilmourThe King's Fund, 11-13 Cavendish Square, London W1G 0AN, United Kingdom. s.gilmour@kingsfund.org.uk

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo develop a method of hospital market area identification using multivariate data, and compare it with existing standard methods. DATA SOURCES: Hospital Episode Statistics, a secondary dataset of admissions data from all hospitals in England, between April 2005 and March 2006. STUDY

designSeven criteria for catchment area definition were proposed. K-means clustering was used on several variables describing the relationship between hospitals and local authority districts (LADs) to enable the placement of every LAD into or out of the catchment area for every hospital. Principal component analysis confirmed the statistical robustness of the method, and the method was compared against existing methods using the seven criteria. PRINCIPAL

findingsExisting methods for identifying catchment areas do not capture desirable properties of a hospital market area. Catchment areas identified using K-means clustering are superior to those identified using existing Marginal methods against these criteria and are also statistically robust.

conclusionsK-means clustering uses multivariate data on the relationship between hospitals and geographical units to define catchment areas that are both statistically robust and more informative than those obtained from existing methods.

Indexed as

Catchment Area, HealthHospitals, PublicCluster AnalysisEnglandHumansState MedicineUnited Kingdom

Identifiers

PMID20050933
PMCPMC2838157

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.