Volume 53 | Number 1 | February 2018

Abstract List

Yujie Hu Ph.D., Fahui Wang Ph.D., Imam M. Xierali Ph.D.


Objective

To develop an automated, data‐driven, and scale‐flexible method to delineate hospital service areas (s) and hospital referral regions (s) that are up‐to‐date, representative of all patients, and have the optimal localization of hospital visits.


Data Sources

The 2011 state inpatient database in Florida from the Healthcare Cost and Utilization Project.


Study Design

A network optimization method was used to redefine s and s by maximizing patient‐to‐hospital flows within each / while minimizing flows between them. We first constructed as many s/s as existing Dartmouth units in Florida, and then compared the two by various metrics. Next, we sought to derive the optimal numbers and configurations of s/s that best reflect the modularity of hospitalization patterns in Florida.


Principal Findings

The s/s by our method are favored over the Dartmouth units in balance of region size and market structure, shape, and most important, local hospitalization.


Conclusions

The new method is automated, scale‐flexible, and effective in capturing the natural structure of the health care system. It has great potential for applications in delineating other health care service areas or in larger geographic regions.