title: Does hospital occupancy impact discharge rates?
abstract: OBJECTIVE
  To understand what impact hospital inpatient occupancy levels have on patient throughput by analysing one hospital's occupancy levels and the rate of patient discharge.
  
  
  METHODS
  A four-stage model was fit to hospital admission and separation data and used to analyse the per-capita separation rate according to the patient load and the impact of hospital over-census actions.
  
  
  RESULTS
  Per-capita separation rates are significantly higher on days when the hospital declares an over-census due to emergency department crowding. Per-capita separation rates are also higher or lower on days with 8-10% higher or lower patient loads, respectively, but the response is not nearly as strong as the response to an over-census declaration, and is limited to patients with an elapsed stay of 10 days or more. Within the medical division there is an increase in per-capita separation rates on over-census days, but no significant difference in per-capita release rates for different patient loads. Within the surgical division there is no significant difference in per-capita separation rates on over-census days compared with other days, but the patient load does make a significant difference.
  
  
  CONCLUSIONS
  Staff do discharge a greater proportion of long-stay patients when the hospital is experiencing high demand and a lower proportion when occupancy is low, but the reasons driving those changes remains unclear.
authors.affiliation: College of Charleston, Charleston, SC 29424, USA. Email:
authors.forename: Gary
authors.initials: G
authors.lastname: Harrison
authors.forename: Kathryn
authors.initials: K
authors.lastname: Zeitz
authors.forename: Robert
authors.initials: R
authors.lastname: Adams
authors.forename: Mark
authors.initials: M
authors.lastname: Mackay
mesh_terms: D001509:Bed Occupancy / Q000706:statistics & numerical data*; D003441:Crowding; D016208:Databases, Factual; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data; D006784:Hospitals, Teaching; D006801:Humans; D015233:Models, Statistical; D010351:Patient Discharge / Q000706:statistics & numerical data* / Q000639:trends; D011793:Queensland