title: Provider density and health system facility factors and their relationship to rates of pediatric perforated appendicitis in US counties.
abstract: OBJECTIVE
  To examine whether density of providers or health care facility factors have a significant effect on the rates of perforated appendicitis in the pediatric population.
  
  
  METHODS
  A retrospective database analysis. Data were linked to the Area Resource File to determine if there was an association between perforated appendicitis and density of provider and facility factors.
  
  
  METHODS
  The National Inpatient Sample database and the Kids' Inpatient Database from 1988 to 2005.
  
  
  METHODS
  All patients included had an age at admission of younger than 18 years and were selected by International Classification of Diseases, Ninth Revision code as having perforated appendicitis (540.0 or 540.1) or acute appendicitis (540.9). Main Outcome Measure Odds ratio of perforated appendicitis to acute appendicitis by county-level density of provider and health care facility factors.
  
  
  RESULTS
  The odds ratio of perforated appendicitis to acute appendicitis when stratified by quartiles of increasing density of providers and facility-level factors was statistically significant only for the highest-density quartile of pediatricians (odds ratio = 0.88; 95% confidence interval = 0.78-0.99).
  
  
  CONCLUSIONS
  Increasing geographic density of pediatricians was associated with a decreasing trend in the odds ratio of perforated appendicitis, with a statistically significant protective effect observed in the highest-density quartile of pediatricians. The density of all other provider and health care facility factors analyzed did not demonstrate a significant association with the rates of perforated appendicitis.
authors.affiliation: Center for Pediatric Surgical Clinical Trials and Outcomes Research, The Johns Hopkins University School of Medicine, Baltimore, Maryland 21287-0005, USA.
authors.forename: Melissa
authors.initials: M
authors.lastname: Camp
authors.forename: David C
authors.initials: DC
authors.lastname: Chang
authors.forename: Yiyi
authors.initials: Y
authors.lastname: Zhang
authors.forename: Meghan
authors.initials: M
authors.lastname: Arnold
authors.forename: Leilani
authors.initials: L
authors.lastname: Sharpe
authors.forename: Alodia
authors.initials: A
authors.lastname: Gabre-Kidan
authors.forename: Melinda A
authors.initials: MA
authors.lastname: Bathurst
authors.forename: Fizan
authors.initials: F
authors.lastname: Abdullah
mesh_terms: D000293:Adolescent; D017677:Age Distribution; D001062:Appendectomy / Q000379:methods / Q000706:statistics & numerical data; D001064:Appendicitis / Q000175:diagnosis / Q000453:epidemiology* / Q000601:surgery; D002648:Child; D002675:Child, Preschool; D002983:Clinical Competence; D016208:Databases, Factual; D042241:Early Diagnosis; D005260:Female; D006268:Health Facilities / Q000600:supply & distribution*; D006282:Health Personnel / Q000706:statistics & numerical data; D006297:Health Services Accessibility / Q000706:statistics & numerical data*; D006801:Humans; D015994:Incidence; D016015:Logistic Models; D008297:Male; D016017:Odds Ratio; D010372:Pediatrics; D010808:Physical Examination / Q000379:methods; D010818:Practice Patterns, Physicians'; D012189:Retrospective Studies; D018570:Risk Assessment; D017678:Sex Distribution; D014481:United States / Q000453:epidemiology; D000078329:Workforce