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Health Serv Res. 2018 Aug;53 Suppl 1:3148-3169. doi: 10.1111/1475-6773.12777. Epub 2017 Sep 22.

Using Weighted Hospital Service Area Networks to Explore Variation in Preventable Hospitalization.

Author information

1
Centre for Big Data Research in Health, UNSW Sydney, Sydney, NSW, Australia.
2
MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK.

Abstract

OBJECTIVE:

To demonstrate the use of multiple-membership multilevel models, which analytically structure patients in a weighted network of hospitals, for exploring between-hospital variation in preventable hospitalizations.

DATA SOURCES:

Cohort of 267,014 people aged over 45 in NSW, Australia.

STUDY DESIGN:

Patterns of patient flow were used to create weighted hospital service area networks (weighted-HSANs) to 79 large public hospitals of admission. Multiple-membership multilevel models on rates of preventable hospitalization, modeling participants structured within weighted-HSANs, were contrasted with models clustering on 72 hospital service areas (HSAs) that assigned participants to a discrete geographic region.

DATA COLLECTION/EXTRACTION METHODS:

Linked survey and hospital admission data.

PRINCIPAL FINDINGS:

Between-hospital variation in rates of preventable hospitalization was more than two times greater when modeled using weighted-HSANs rather than HSAs. Use of weighted-HSANs permitted identification of small hospitals with particularly high rates of admission and influenced performance ranking of hospitals, particularly those with a broadly distributed patient base. There was no significant association with hospital bed occupancy.

CONCLUSION:

Multiple-membership multilevel models can analytically capture information lost on patient attribution when creating discrete health care catchments. Weighted-HSANs have broad potential application in health services research and can be used across methods for creating patient catchments.

KEYWORDS:

Patient catchments; hospital service areas; multilevel modeling; preventable hospitalizations

PMID:
28940236
PMCID:
PMC6056604
DOI:
10.1111/1475-6773.12777
[Indexed for MEDLINE]

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