Abstract：
BACKGROUND: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. METHODS: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. RESULTS: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. CONCLUSIONS: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.
journal_name
BMC Health Serv Resjournal_title
BMC health services researchauthors
Li Z,Serban N,Swann JLdoi
10.1186/s12913-015-0919-8subject
Has Abstractpub_date
2015-07-17 00:00:00pages
273issn
1472-6963pii
10.1186/s12913-015-0919-8journal_volume
15pub_type
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