title: The relationship between inpatient discharge timing and emergency department boarding.
abstract: BACKGROUND
  Patient crowding and boarding in Emergency Departments (EDs) impair the quality of care as well as patient safety and satisfaction. Improved timing of inpatient discharges could positively affect ED boarding, and this hypothesis can be tested with computer modeling.
  
  
  OBJECTIVE
  Modeling enables analysis of the impact of inpatient discharge timing on ED boarding. Three policies were tested: a sensitivity analysis on shifting the timing of current discharge practices earlier; discharging 75% of inpatients by 12:00 noon; and discharging all inpatients between 8:00 a.m. and 4:00 p.m.
  
  
  METHODS
  A cross-sectional computer modeling analysis was conducted of inpatient admissions and discharges on weekdays in September 2007. A model of patient flow streams into and out of inpatient beds with an output of ED admitted patient boarding hours was created to analyze the three policies.
  
  
  RESULTS
  A mean of 38.8 ED patients, 22.7 surgical patients, and 19.5 intensive care unit transfers were admitted to inpatient beds, and 81.1 inpatients were discharged daily on September 2007 weekdays: 70.5%, 85.6%, 82.8%, and 88.0%, respectively, occurred between noon and midnight. In the model base case, total daily admitted patient boarding hours were 77.0 per day; the sensitivity analysis showed that shifting the peak inpatient discharge time 4h earlier eliminated ED boarding, and discharging 75% of inpatients by noon and discharging all inpatients between 8:00 a.m. and 4:00 p.m. both decreased boarding hours to 3.0.
  
  
  CONCLUSIONS
  Timing of inpatient discharges had an impact on the need to board admitted patients. This model demonstrates the potential to reduce or eliminate ED boarding by improving inpatient discharge timing in anticipation of the daily surge in ED demand for inpatient beds.
authors.affiliation: Department of Emergency Medicine, Northwestern University, Feinberg School of Medicine, Chicago, Illinois, USA.
authors.forename: Emilie S
authors.initials: ES
authors.lastname: Powell
authors.forename: Rahul K
authors.initials: RK
authors.lastname: Khare
authors.forename: Arjun K
authors.initials: AK
authors.lastname: Venkatesh
authors.forename: Ben D
authors.initials: BD
authors.lastname: Van Roo
authors.forename: James G
authors.initials: JG
authors.lastname: Adams
authors.forename: Gilles
authors.initials: G
authors.lastname: Reinhardt
mesh_terms: D003198:Computer Simulation; D003430:Cross-Sectional Studies; D003441:Crowding; D004636:Emergency Service, Hospital / Q000458:organization & administration*; D006301:Health Services Needs and Demand; D006786:Hospitals, Urban; D006801:Humans; D017146:Models, Organizational; D010343:Patient Admission; D010351:Patient Discharge; D013997:Time Factors