Geomedicine: area-based socioeconomic measures for assessing risk of hospital reutilization among children admitted for asthma.
OBJECTIVE
We assessed whether geographic information available at the time of asthma admission predicts time to reutilization (readmission or emergency department revisit).


METHODS
For a prospective cohort of children hospitalized with asthma in 2008 and 2009 in Cincinnati, Ohio, we constructed a geographic social risk index from geocoded home addresses linked to census tract extreme poverty and high school graduation rates and median home values. We examined geographic risk associations with reutilization and caregiver report of hardship.


RESULTS
Thirty-nine percent of patients reutilized within 12 months. Compared with those in the lowest geographic risk stratum, those at medium and high risk had 1.3 (95% confidence interval [CI] = 0.9, 1.9) and 1.8 (95% CI = 1.4, 2.4) the risk of reutilization, respectively. Caregivers of children at highest geographic risk were 5 times as likely to report more than 2 financial hardships (P < .001) and 3 times as likely to report psychological distress (P = .001).


CONCLUSIONS
A geographic social risk index may help identify asthmatic children likely to return to the hospital. Targeting social risk assessments and interventions through geographic information may help to improve outcomes and reduce disparities.
Division of General and Community Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA. Andrew.Beck1@cchmc.org
Andrew F
AF
Beck
Jeffrey M
JM
Simmons
Bin
B
Huang
Robert S
RS
Kahn
D001247:Asthenia / Q000453:epidemiology*; D002675:Child, Preschool; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data*; D005260:Female; D006776:Hospitals, Pediatric / Q000706:statistics & numerical data; D006801:Humans; D007182:Income / Q000706:statistics & numerical data; D008297:Male; D009820:Ohio / Q000453:epidemiology; D010359:Patient Readmission / Q000706:statistics & numerical data*; D011203:Poverty / Q000706:statistics & numerical data; D016016:Proportional Hazards Models; D011446:Prospective Studies; D018570:Risk Assessment; D012307:Risk Factors; D012959:Socioeconomic Factors