title: The effect of laboratory testing on emergency department length of stay: a multihospital longitudinal study applying a cross-classified random-effect modeling approach.
abstract: OBJECTIVE
  The objective was to examine the relationship between laboratory testing (including test volume and turnaround time [TAT]) and emergency department (ED) length of stay (LOS), using linked patient-level data from four hospitals across 4 years.
  
  
  METHODS
  This was a retrospective, multisite cohort study of patients presenting to any one of four EDs in New South Wales, Australia, during a 2-month period (August and September) in 2008, 2009, 2010, and 2011. Data from ED information systems were linked to laboratory test data. A cross-classified random-effect modeling approach was applied to identify factors affecting ED LOS, taking into account the correlation between patients' presentations at the same hospital and/or in the same calendar year. Number of test order episodes (tests ordered at one point in time during the ED stay) and TAT (time from laboratory order receipt to result available) were examined.
  
  
  RESULTS
  As the number of test order episodes increased, so did the duration of patient ED LOS (p < 0.0001). For every five additional tests ordered per test order episode, the median ED LOS increased by 10 minutes (2.9%, p < 0.0001); each 30-minute increase in TAT was, on average, associated with a 5.1% (17 minutes; p < 0.0001) increase in ED LOS, after adjustment for other factors. Patients presenting to the ED at night (7 p.m. to 7 a.m.) had longer stays than those presenting during the daytime, although the median TATs at nights were shorter than those during the daytime.
  
  
  CONCLUSIONS
  Laboratory testing has a direct effect on patients' LOS in ED. Laboratory TAT, number of testing episodes, and test volume influence ED LOS. Targeted increases of ED resources and staffing after-hours may also contribute to reductions in ED LOS.
authors.affiliation: The Centre for Health Systems and Safety Research, Australian Institute of Health Innovation, UNSW Medicine, University of New South Wales, Sydney, NSW.
authors.forename: Ling
authors.initials: L
authors.lastname: Li
authors.forename: Andrew
authors.initials: A
authors.lastname: Georgiou
authors.forename: Elia
authors.initials: E
authors.lastname: Vecellio
authors.forename: Alex
authors.initials: A
authors.lastname: Eigenstetter
authors.forename: George
authors.initials: G
authors.lastname: Toouli
authors.forename: Roger
authors.initials: R
authors.lastname: Wilson
authors.forename: Johanna I
authors.initials: JI
authors.lastname: Westbrook
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D019937:Diagnostic Techniques and Procedures / Q000706:statistics & numerical data*; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D007755:Laboratories, Hospital / Q000706:statistics & numerical data*; D007902:Length of Stay / Q000706:statistics & numerical data*; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D009517:New South Wales; D012189:Retrospective Studies; D012737:Sex Factors; D013997:Time Factors; D014218:Triage / Q000706:statistics & numerical data