Hot spotting preventable hospitalizations to inform clinical practice and improve patient outcomes
Methods: Using 2012-13 inpatient data from a major Bronx medical center’s electronic health records, adult hospitalization rates for two ACS conditions, (1) diabetes long-term complications (n=2,722) and (2) COPD/asthma (n=4,177), are calculated at the US Census block group level and small area “hot spots” are mapped for both unique admission rates and super-user counts (patients with ≥2 readmissions). Spatial regression models are specified to assess the relationship between preventable hospitalization rates and neighborhood composition.
Results: Spatial analysis reveals significant spatial autocorrelation in both diagnoses; clusters of unique admissions and super-utilizers overlap in several areas, particularly in the northeast Bronx. Higher rates for diabetes and COPD/asthma are significantly associated (p<.05) with older neighborhood age composition, yet only diabetes is related to greater proportions of Hispanic and black residents.
Conclusions: The observed clustering of admission rates and super-utilizer counts for diabetes and COPD/asthma suggests a unique opportunity to target vulnerable communities to reduce unnecessary hospitalization. Future efforts focused on investigating contextual neighborhood factors that drive these localized hot spots will help clinicians and administrators develop community interventions to improve patient outcomes.
Learning Areas:Chronic disease management and prevention
Public health or related research
Discuss the clinical importance of hot spotting preventable hospitalizations. Identify clusters of preventable hospitalizations for diabetes and COPD/asthma among adults in the Bronx, NY. Identify next steps in developing community interventions aimed at reducing unnecessary hospitalizations.
Keyword(s): Chronic Disease Prevention, Geographic Information Systems (GIS)
Qualified on the content I am responsible for because: I've been a public health spatial epidemiologist for 9 years. I work at Montefiore as senior data analyst and have been working on ACS conditions for over 2 years.
Any relevant financial relationships? No
I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.