Objectives: Sepsis is a severe condition associated with high mortality, and hospital performance is variable. The objective of this study was to develop geospatial sepsis clusters, identify sources of variation between clusters, and test the hypothesis that redistributing sepsis patients from low-performing hospitals to higher-performing hospitals within a cluster will improve sepsis outcomes.
Design, setting, and patients: We conducted a cohort study of age-qualifying Medicare beneficiaries using administrative claims data from 2013 to 2015. We calculated risk-standardized mortality for hospitals then used a clustering algorithm to define geospatial cluster boundaries based on care-seeking and interhospital transfer patterns. Finally, we used simulation to model the effect of reallocating sepsis patients to higher-performing hospitals within the same cluster.
Interventions: None.
Measurements and main results: We included 1,125,308 patients, and they were grouped into 222 regional clusters. High-performing clusters were located largely in the Midwest, and they tended to be in less urban regions with smaller hospitals. In our simulation, the most impactful strategy was reassigning cases from the lowest-performing hospital in a cluster to the highest-performing hospital in the cluster, which was predicted to prevent 1705 deaths per year in the United States. This aggregate benefit was lower than the 5702 deaths predicted from reducing mortality by 1% absolute in hospitals in the lower half of the performance distribution.
Conclusions: Geospatial clusters provide insight into regional approaches to system-based acute care. In a simulation study, targeted sepsis regionalization appears less effective than local performance improvement in reducing preventable sepsis deaths.
Keywords: computer simulation; quality of healthcare; regional medical programs; sepsis.
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