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An optimization framework for measuring spatial access over healthcare networks

Overview of attention for article published in BMC Health Services Research, July 2015
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1 tweeter

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53 Mendeley
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Title
An optimization framework for measuring spatial access over healthcare networks
Published in
BMC Health Services Research, July 2015
DOI 10.1186/s12913-015-0919-8
Pubmed ID
Authors

Zihao Li, Nicoleta Serban, Julie L. Swann

Abstract

Measurement of healthcare spatial access over a network involves accounting for demand, supply, and network structure. Popular approaches are based on floating catchment areas; however the methods can overestimate demand over the network and fail to capture cascading effects across the system. Optimization is presented as a framework to measure spatial access. Questions related to when and why optimization should be used are addressed. The accuracy of the optimization models compared to the two-step floating catchment area method and its variations is analytically demonstrated, and a case study of specialty care for Cystic Fibrosis over the continental United States is used to compare these approaches. The optimization models capture a patient's experience rather than their opportunities and avoid overestimating patient demand. They can also capture system effects due to change based on congestion. Furthermore, the optimization models provide more elements of access than traditional catchment methods. Optimization models can incorporate user choice and other variations, and they can be useful towards targeting interventions to improve access. They can be easily adapted to measure access for different types of patients, over different provider types, or with capacity constraints in the network. Moreover, optimization models allow differences in access in rural and urban areas.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Kenya 1 2%
Unknown 52 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 25%
Student > Master 11 21%
Researcher 10 19%
Student > Doctoral Student 3 6%
Professor 3 6%
Other 5 9%
Unknown 8 15%
Readers by discipline Count As %
Social Sciences 12 23%
Medicine and Dentistry 6 11%
Engineering 6 11%
Computer Science 4 8%
Nursing and Health Professions 3 6%
Other 13 25%
Unknown 9 17%

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 12 February 2016.
All research outputs
#11,480,543
of 14,481,748 outputs
Outputs from BMC Health Services Research
#4,126
of 4,921 outputs
Outputs of similar age
#232,975
of 341,147 outputs
Outputs of similar age from BMC Health Services Research
#1
of 1 outputs
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