title: Factors Associated With Potentially Preventable Pediatric Admissions Vary by Diagnosis: Findings From a Large State.
abstract: The objective of this study was to determine characteristics associated with potentially preventable pediatric admissions as defined by the Agency for Healthcare Research and Quality.
  
  
  
  The Texas Inpatient Public Use Data File, an administrative database of hospital admissions, identified 747 040 pediatric admissions ages 0 to 17 years to acute care facilities between 2005 and 2008. Potentially preventable admissions included 5 diagnoses: asthma, perforated appendicitis, diabetes, gastroenteritis, and urinary tract infection. A hierarchical multivariable logistic regression model clustered by admitting hospital and adjusted for admission date estimated the patient and hospital factors associated with potentially preventable admission.
  
  
  
  An average of 71 444 hospital days per year and 14.1% (N = 105 055) of all admissions were potentially preventable, generating $304 million in hospital charges per year in 1 state. Younger age (odds ratio [OR]: 2.88 [95% confidence interval (CI): 2.80-2.96]), black race (OR: 1.48 [95% CI: 1.45-1.52]) or Hispanic ethnicity (OR: 1.06 [95% CI: 1.04-1.08]), lower income (OR: 1.11 [95% CI: 1.02-1.20]), comorbid substance abuse disorder (OR: 2.03 [95% CI: 1.75-2.34]), and admission on a weekend (OR: 1.05 [95% CI: 1.03-1.06]) or to a critical access hospital (OR: 1.61 [95% CI: 1.20-2.14]) were high-risk factors for potentially preventable admission, whereas Native American race (OR: 0.91 [95% CI: 0.85-0.98]), government insurance (OR: 0.83 [95% CI: 0.89-0.96]) or no insurance (OR: 0.93 [95% CI: 0.89-0.96]), and living in a rural county (OR: 0.70 [95% CI: 0.68-0.73]) were associated factors. However, most factors varied from high to low odds depending on which of the 5 potentially preventable diagnoses was examined.
  
  
  
  Potentially preventable admissions represent a high burden of time and costs for the pediatric population, but strategies to reduce them should be tailored to each diagnosis because the associated factors are not uniform across all potentially preventable admissions.
authors.affiliation: Department of Emergency Medicine, medford.davis@gmail.com.
authors.forename: Laura N
authors.initials: LN
authors.lastname: Medford-Davis
authors.affiliation: Baylor College of Medicine, Houston, Texas; and.
authors.forename: Rohan
authors.initials: R
authors.lastname: Shah
authors.affiliation: University of Pennsylvania, Philadelphia, Pennsylvania.
authors.forename: Danielle
authors.initials: D
authors.lastname: Kennedy
authors.affiliation: Texas Health and Human Services Commission, Texas Medicaid and CHIP Program, Austin, Texas.
authors.forename: Emilie
authors.initials: E
authors.lastname: Becker
mesh_terms: D000293:Adolescent; D001064:Appendicitis / Q000453:epidemiology / Q000628:therapy; D001249:Asthma / Q000453:epidemiology / Q000628:therapy; D002675:Child, Preschool; D003920:Diabetes Mellitus / Q000453:epidemiology / Q000628:therapy; D003953:Diagnosis-Related Groups / Q000191:economics / Q000706:statistics & numerical data; D005260:Female; D005759:Gastroenteritis / Q000453:epidemiology / Q000628:therapy; D006801:Humans; D007231:Infant, Newborn; D008297:Male; D000069342:Medical Overuse / Q000517:prevention & control / Q000706:statistics & numerical data; D016017:Odds Ratio; D010359:Patient Readmission / Q000191:economics / Q000706:statistics & numerical data; D018570:Risk Assessment; D012307:Risk Factors; D013781:Texas / Q000453:epidemiology; D014552:Urinary Tract Infections / Q000453:epidemiology / Q000628:therapy