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Optimising spatial accessibility to inform rationalisation of specialist health services

Overview of attention for article published in International Journal of Health Geographics, April 2017
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Title
Optimising spatial accessibility to inform rationalisation of specialist health services
Published in
International Journal of Health Geographics, April 2017
DOI 10.1186/s12942-017-0088-6
Pubmed ID
Authors

Catherine M. Smith, Hannah Fry, Charlotte Anderson, Helen Maguire, Andrew C. Hayward

Abstract

In an era of budget constraints for healthcare services, strategies for provision of services that improve quality whilst saving costs are highly valued. A proposed means to achieve this is consolidation of services into fewer specialist centres, but this may lead to reduced spatial accessibility. We describe a methodology which includes implementing a combinatorial optimisation algorithm to derive combinations of services which optimise spatial accessibility in the context of service rationalisation, and demonstrate its use through the exemplar of tuberculosis clinics in London. Our methodology involves (1) identifying the spatial distribution of the patient population using the service; (2) calculating patient travel times to each service location, and (3) using a combinatorial optimisation algorithm to identify subsets of locations that minimise overall travel time. We estimated travel times for tuberculosis patients notified in London between 2010 and 2013 to each of 29 clinics in the city. Travel time estimates were derived from the Transport for London Journey Planner service. We identified the subset of clinics that would provide the shortest overall travel time for each possible number of clinic subsets (1-28). Based on the 29 existing clinic locations, mean estimated travel time to clinics used by 12,061 tuberculosis patients in London was 33 min; and mean time to their nearest clinics was 28 min. Using optimum combinations of clinic locations, and assuming that patients attended their nearest clinics, a mean travel time of less than 45 min could be achieved with three clinics; of 34 min with ten clinics, and of less than 30 min with 18 clinics. We have developed a methodological approach to optimise spatial accessibility which can be used to inform rationalisation of health services. In urban conurbations, this may enable service reorganisation which increases quality and efficiency without substantially affecting spatial accessibility. This approach could be used to inform planning of service reorganisations, but may not be generalisable to rural areas or smaller urban centres.

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The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 41 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 7 17%
Researcher 7 17%
Student > Postgraduate 4 10%
Student > Ph. D. Student 4 10%
Student > Doctoral Student 3 7%
Other 6 15%
Unknown 10 24%
Readers by discipline Count As %
Medicine and Dentistry 8 20%
Social Sciences 5 12%
Nursing and Health Professions 5 12%
Engineering 2 5%
Environmental Science 2 5%
Other 7 17%
Unknown 12 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 May 2017.
All research outputs
#15,454,502
of 22,965,074 outputs
Outputs from International Journal of Health Geographics
#445
of 629 outputs
Outputs of similar age
#193,898
of 309,877 outputs
Outputs of similar age from International Journal of Health Geographics
#6
of 11 outputs
Altmetric has tracked 22,965,074 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 629 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.4. This one is in the 22nd percentile – i.e., 22% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 309,877 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.