title: Differences in quality of care among non-safety-net, safety-net, and children's hospitals.
abstract: OBJECTIVE
  To understand factors associated with pediatric inpatient safety events, we test 2 hypotheses: (1) scarce resources (as measured by Medicaid burden) in safety-net hospitals relative to non-safety-net hospitals result in higher rates of safety events; and (2) higher levels of severity and more chronic conditions in patient populations lead to higher rates of safety events within hospital category and in children's hospitals in comparison with non-children's hospitals.
  
  
  METHODS
  All nonnewborn pediatric hospital discharge records, which met criteria for potentially experiencing at least 1 pediatric quality indicator (PDI) event (using Agency for Healthcare Research and Quality's 2009 Nationwide Inpatient Sample and PDI) and weighted to represent national level estimates, were analyzed for patterns of PDI events within and across hospital categories by using bivariate comparisons and multivariable logit models with robust SEs. The outcome measure "ANY PDI" captures the number of pediatric discharges at the hospital level with 1 or more PDI event.
  
  
  RESULTS
  High Medicaid burden does not seem to be a factor in the likelihood of ANY PDI. Severity of illness (adjusted odds ratio high relative to low, 15.12) and presence of chronic conditions (adjusted odds ratio 1 relative to 0, 1.78; relative to 2 or more, 3.38) are the strongest predictors of ANY PDI events.
  
  
  CONCLUSIONS
  Our findings suggest that the patient population served, rather than hospital category, best predicts measured quality, underscoring the need for robust risk adjustment when incentivizing quality or comparing hospitals. Thus, problems of quality may not be systemic across hospital categories.
authors.affiliation: 330 BAC, Haile/US Bank College of Business, Northern Kentucky University, Highland Heights, KY 41099, USA. dynanl@nku.edu
authors.forename: Linda
authors.initials: L
authors.lastname: Dynan
authors.forename: Anthony
authors.initials: A
authors.lastname: Goudie
authors.forename: Richard B
authors.initials: RB
authors.lastname: Smith
authors.forename: Gerry
authors.initials: G
authors.lastname: Fairbrother
authors.forename: Lisa A
authors.initials: LA
authors.lastname: Simpson
mesh_terms: D000293:Adolescent; D002648:Child; D002675:Child, Preschool; D002908:Chronic Disease / Q000453:epidemiology*; D016638:Critical Illness / Q000453:epidemiology*; D005260:Female; D006295:Health Resources / Q000706:statistics & numerical data; D006302:Health Services Research / Q000706:statistics & numerical data; D006776:Hospitals, Pediatric / Q000706:statistics & numerical data*; D006801:Humans; D007049:Iatrogenic Disease / Q000453:epidemiology; D007223:Infant; D016013:Likelihood Functions; D008297:Male; D008484:Medicaid / Q000706:statistics & numerical data*; D019300:Medical Errors / Q000706:statistics & numerical data*; D010351:Patient Discharge / Q000706:statistics & numerical data; D061214:Patient Safety / Q000706:statistics & numerical data*; D019984:Quality Indicators, Health Care / Q000706:statistics & numerical data*; D020379:Risk Adjustment / Q000706:statistics & numerical data; D012307:Risk Factors; D017664:Uncompensated Care / Q000706:statistics & numerical data*; D014481:United States; D016270:United States Agency for Healthcare Research and Quality; D014947:Wounds and Injuries / Q000453:epidemiology*