TY - JOUR
T1 - Automated Delineation of Hospital Service Areas and Hospital Referral Regions by Modularity Optimization
AU - Hu, Yujie
AU - Wang, Fahui
AU - Xierali, Imam M.
N1 - Funding Information:
Joint Acknowledgment/Disclosure Statement: The financial support from the Graduate School of Louisiana State University to Yujie Hu under the Economic Development Assistantship (EDA) is gratefully acknowledged. We appreciate very detailed and constructive comments by three reviewers and the editors who helped improve the revision. The authors declare no conflicts of interests. Disclosures: None. Disclaimers: None.
Publisher Copyright:
© Health Research and Educational Trust
PY - 2018/2
Y1 - 2018/2
N2 - Objective: To develop an automated, data-driven, and scale-flexible method to delineate hospital service areas (HSAs) and hospital referral regions (HRRs) 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 HSAs and HRRs by maximizing patient-to-hospital flows within each HSA/HRR while minimizing flows between them. We first constructed as many HSAs/HRRs 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 HSAs/HRRs that best reflect the modularity of hospitalization patterns in Florida. Principal Findings: The HSAs/HRRs 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.
AB - Objective: To develop an automated, data-driven, and scale-flexible method to delineate hospital service areas (HSAs) and hospital referral regions (HRRs) 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 HSAs and HRRs by maximizing patient-to-hospital flows within each HSA/HRR while minimizing flows between them. We first constructed as many HSAs/HRRs 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 HSAs/HRRs that best reflect the modularity of hospitalization patterns in Florida. Principal Findings: The HSAs/HRRs 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.
KW - Dartmouth method
KW - HCUP
KW - Hospital service area
KW - community detection method
KW - hospital referral region
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U2 - 10.1111/1475-6773.12616
DO - 10.1111/1475-6773.12616
M3 - Article
C2 - 27861822
AN - SCOPUS:85003032081
SN - 0017-9124
VL - 53
SP - 236
EP - 255
JO - Health Services Research
JF - Health Services Research
IS - 1
ER -