title: Estimating the degree of emergency department overcrowding in academic medical centers: results of the National ED Overcrowding Study (NEDOCS).
abstract: OBJECTIVE
  No single universal definition of emergency department (ED) overcrowding exists. The authors hypothesize that a previously developed site-sampling form for academic ED overcrowding is a valid model to quantify overcrowding in academic institutions and can be used to develop a validated short form that correlates with overcrowding.
  
  
  METHODS
  A 23-question site-sampling form was designed based on input from academic physicians at eight medical schools representative of academic EDs nationwide. A total of 336 site-samplings at eight academic medical centers were conducted at 42 computer-generated random times over a three-week period by independent observers at each site. These sampling times ranged from very slow to severely overcrowded. The outcome variable was the degree of overcrowding as assessed by the charge nurse and ED physicians. The full model consisted of objective data that were obtained by counting the number of patients, determining patients' waiting times, and obtaining information from registration, triage, and ancillary services. Specific objective data were indexed to site-specific demographics. The outcome and objective data were compared using a multiple linear regression to determine predictive validity of the full model. A five-question reduced model was calculated using a backward stepdown procedure. Predictive validity and relationships between the outcome and objective data were assessed using a mixed-effects linear regression model, treating center as random effect.
  
  
  RESULTS
  Overcrowding occurred 12% to 73% of the time (mean, 35%), with two hospitals being overcrowded more than 50% of the time. Comparison of objective and outcome data resulted in an R(2) of 0.49 (p < 0.001), indicating a good degree of predictive validity. A reduced five-question model predicted the full model with 88% accuracy.
  
  
  CONCLUSIONS
  Overcrowding varied widely between academic centers during the study period. Results of a five-question reduced model are valid and accurate in predicting the degree of overcrowding in academic centers.
authors.affiliation: University of California Davis Medical Center, Sacramento, CA, USA. sweiss52@aol.com
authors.forename: Steven J
authors.initials: SJ
authors.lastname: Weiss
authors.forename: Robert
authors.initials: R
authors.lastname: Derlet
authors.forename: Jeanine
authors.initials: J
authors.lastname: Arndahl
authors.forename: Amy A
authors.initials: AA
authors.lastname: Ernst
authors.forename: John
authors.initials: J
authors.lastname: Richards
authors.forename: Madonna
authors.initials: M
authors.lastname: Fernández-Frackelton
authors.forename: Robert
authors.initials: R
authors.lastname: Schwab
authors.forename: Thomas O
authors.initials: TO
authors.lastname: Stair
authors.forename: Peter
authors.initials: P
authors.lastname: Vicellio
authors.forename: David
authors.initials: D
authors.lastname: Levy
authors.forename: Mark
authors.initials: M
authors.lastname: Brautigan
authors.forename: Ashira
authors.initials: A
authors.lastname: Johnson
authors.forename: Todd G
authors.initials: TG
authors.lastname: Nick
authors.forename: Madonna
authors.initials: M
authors.lastname: Fernández-Frankelton
mesh_terms: D000046:Academic Medical Centers / Q000458:organization & administration / Q000706:statistics & numerical data*; D003441:Crowding; D004635:Emergency Medicine / Q000458:organization & administration*; D004636:Emergency Service, Hospital / Q000458:organization & administration / Q000706:statistics & numerical data*; D019538:Health Care Surveys; D006801:Humans; D016014:Linear Models; D010561:Personnel Staffing and Scheduling; D010564:Personnel, Hospital; D010865:Pilot Projects; D011795:Surveys and Questionnaires; D013997:Time Factors; D014481:United States / Q000453:epidemiology; D014600:Utilization Review