title: The july effect: an analysis of never events in the nationwide inpatient sample.
abstract: BACKGROUND
  Prior studies examining the impact of the "July effect" on in-hospital mortality rates have generated variable results. In 2008, the Centers for Medicare & Medicaid Services published a series of high-cost, high-volume, nonreimbursable hospital-acquired complications (HACs). These events were believed to be preventable and indicate deficiencies in healthcare delivery.
  
  
  OBJECTIVE
  The present study aims to investigate the impact of July admissions on patient safety in a national sample using the HACs as a metric.
  
  
  METHODS
  Discharge data were collected from all admissions recorded in the Nationwide Inpatient Sample database from 2008 to 2011. HAC incidence was evaluated as a function of admission month, adjusting for demographic and hospital factors in multivariable analysis.
  
  
  METHODS
  The outcome measures were HAC occurrence, prolonged length of stay (LOS), and higher inpatient costs.
  
  
  RESULTS
  A total of 143,019,381 inpatient admissions were recorded, with an overall HAC occurrence of 4.7%. July admissions accounted for 7.6% of the total number of inpatient admissions. July admissions experienced a 6% increase in likelihood of HAC occurrence (odds ratio = 1.06, 95% confidence interval: 1.06-1.07, P < 0.001) when compared to those admitted during all other months. Patients with HAC occurrence had almost 2 times increased likelihood of prolonged LOS (P < 0.001) and higher inpatient costs (P < 0.001).
  
  
  CONCLUSIONS
  July admissions are associated with increased likelihood of HAC occurrence. This trend may represent breakdowns in organization structure distinct from traditional quality measures, requiring novel transition protocols dedicated to improving HACs.
authors.affiliation: Keck School of Medicine, University of Southern California, Los Angeles, California.
authors.forename: Timothy
authors.initials: T
authors.lastname: Wen
authors.affiliation: Department of Neurosurgery, Keck School of Medicine, University of Southern California, Los Angeles, California.
authors.forename: Frank J
authors.initials: FJ
authors.lastname: Attenello
authors.affiliation: Department of Integrative Biology of Disease, Keck School of Medicine, University of Southern California, Los Angeles.
authors.forename: Brian
authors.initials: B
authors.lastname: Wu
authors.affiliation: Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California.
authors.forename: Alvin
authors.initials: A
authors.lastname: Ng
authors.affiliation: Department of Neurosurgery, Keck School of Medicine, University of Southern California, Los Angeles, California.|Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California.|Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, California.|Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, California.
authors.forename: Steven Y
authors.initials: SY
authors.lastname: Cen
authors.affiliation: Department of Neurosurgery, Keck School of Medicine, University of Southern California, Los Angeles, California.
authors.forename: William J
authors.initials: WJ
authors.lastname: Mack
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D017721:Hospital Costs; D017052:Hospital Mortality / Q000639:trends; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D007297:Inpatients; D007902:Length of Stay / Q000706:statistics & numerical data; D008297:Male; D008875:Middle Aged; D010343:Patient Admission / Q000706:statistics & numerical data; D012189:Retrospective Studies; D012307:Risk Factors; D012621:Seasons; D013997:Time Factors; D014481:United States / Q000453:epidemiology; D055815:Young Adult