16 - Association between PICU/PCICU Utilization by Neighborhood and Socioeconomic Status in Monroe County, NY

Poster Number: 16
Publication Number: 16.201

Andrea Gero, Golisano Children's Hospital at The University of Rochester Medical Center, Rochester, NY, United States; Erin Gosekamp, University of Utah, Salt Lake Coty, UT, United States; Adam Dziorny, University of Rochester School of Medicine, Rochester, NY, United States; Kathryn Palumbo, University of Rochester School of Medicine and Dentistry, Rochester, NY, United States; Elizabeth A. Nocera, Golisano Children's Hospital at The University of Rochester Medical Center, Rochester, NY, United States

Background: The place-based environment, defined as the ecological and sociodemographic makeup of a specific geographic location, is an emerging marker of healthcare disparity. While previous studies have demonstrated the effects of place-based environment on factors such as ED utilization, hospitalizations for asthma and diabetes, and hospital mortality, there remains a relative lack of data describing how place-based environment is associated with pediatric critical care service utilization.

Objective: We hypothesized that there is a difference in Pediatric ICU (PICU) and Pediatric Cardiac ICU (PCICU) utilization among children living in neighborhoods with contrasting rates of poverty.

Design/Methods: Retrospective observational study of patients admitted to an academic PICU & PCICU over a 6-year period. We classified all census tracts in Monroe County, NY, into childhood population quintiles by level of poverty based on American Community Survey (ACS) data “Percentage of families and people whose income in the past 12 months is below the poverty level: Under 18 years”. We then geocoded all encounters whose primary address was in Monroe County to the census tract level. We compared admission counts, normalized admission rates (by number of children per quintile), age at admission, hospital length of stay, and mortality among quintiles using the Kruskal-Wallis Test. We identified hospital encounter billing diagnoses (ICD-9/10) and converted them to more clinically meaningful diagnostic categories using Clinical Classification Software Refined (AHRQ). We identified diagnoses which were statistically different across quintiles (chi square test).

Results: There were 7,881 ICU encounters over the study period, of which 3,441 met inclusion criteria (Table 1). Both counts of admissions and admission age were significantly different across quintiles (Table 2, p < 0.01), with quintiles representing greater poverty having higher admission counts and lower median ages. Hospital length of stay (LOS) and mortality did not differ by quintile. Several diagnoses were disproportionately represented across quintiles, with diagnoses such as asthma and obesity observed at higher frequency among quintiles with higher rates of poverty (Table 3).Conclusion(s): Children residing in neighborhoods stratified by one marker of poverty status, “Percent Individuals and Families Living Below Poverty Line”, exhibited different patterns of critical care service utilization. Further study and community collaboration will be needed to elucidate the root causes of this observed pattern.
Gero, Andrea CVGero_CV.pdf
Quintile DescriptionTable 2: Description of each quintile, showing total number of children contained in each quintile, the percent of children living in poverty in each quintile (both from ACS), the number (and percentage) of hospital encounters of children residing in each quintile and the median age at admission for patients admitted from each quintile.