title: The Impact of Emergency Department Census on the Decision to Admit.
abstract: We evaluated the effect of emergency department (ED) census on disposition decisions made by ED physicians.
  
  
  
  We performed a retrospective analysis using 18 months of all adult patient encounters seen in the main ED at an academic tertiary care center. Patient census information was calculated at the time of physician assignment for each individual patient and included the number of patients in the waiting room (waiting room census) and number of patients being managed by the patient's attending (physician load census). A multiple logistic regression model was created to assess the association between these census variables and the disposition decision, controlling for potential confounders including Emergency Severity Index acuity, patient demographics, arrival hour, arrival mode, and chief complaint.
  
  
  
  A total of 49,487 patient visits were included in this analysis, of whom 37% were admitted to the hospital. Both census measures were significantly associated with increased chance of admission; the odds ratio (OR) per patient increase for waiting room census was 1.011 (95% confidence interval [CI] = 1.001 to 1.020), and the OR for physician load census was 1.010 (95% CI = 1.002 to 1.019). To put this in practical terms, this translated to a modeled rise from 35.3% to 40.1% when shifting from an empty waiting room and zero patient load to a 12-patient wait and 16-patient load for a given physician.
  
  
  
  Waiting room census and physician load census at time of physician assignment were positively associated with the likelihood that a patient would be admitted, controlling for potential confounders. Our data suggest that disposition decisions in the ED are influenced not only by objective measures of a patient's disease state, but also by workflow-related concerns.
authors.affiliation: BerbeeWalsh Department of Emergency Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI.
authors.forename: Jillian K
authors.initials: JK
authors.lastname: Gorski
authors.affiliation: Wisconsin School of Business, University of Wisconsin-Madison, Madison, WI.
authors.forename: Robert J
authors.initials: RJ
authors.lastname: Batt
authors.affiliation: BerbeeWalsh Department of Emergency Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI.
authors.forename: Erkin
authors.initials: E
authors.lastname: Otles
authors.affiliation: BerbeeWalsh Department of Emergency Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI.
authors.forename: Manish N
authors.initials: MN
authors.lastname: Shah
authors.affiliation: BerbeeWalsh Department of Emergency Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI.
authors.forename: Azita G
authors.initials: AG
authors.lastname: Hamedani
authors.affiliation: BerbeeWalsh Department of Emergency Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI.
authors.forename: Brian W
authors.initials: BW
authors.lastname: Patterson
mesh_terms: D000046:Academic Medical Centers; D000328:Adult; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D007902:Length of Stay; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D010343:Patient Admission / Q000706:statistics & numerical data*; D012189:Retrospective Studies; D012720:Severity of Illness Index; D013997:Time Factors; D014850:Waiting Lists; D016526:Workload / Q000706:statistics & numerical data*