title: Unravelling relationships: Hospital occupancy levels, discharge timing and emergency department access block.
abstract: OBJECTIVE
  To investigate the effect of hospital occupancy levels on inpatient and ED patient flow parameters, and to simulate the impact of shifting discharge timing on occupancy levels.
  
  
  METHODS
  Retrospective analysis of hospital inpatient data and ED data from 23 reporting public hospitals in Queensland, Australia, across 30 months. Relationships between outcome measures were explored through the aggregation of the historic data into 21 912 hourly intervals. Main outcome measures included admission and discharge rates, occupancy levels, length of stay for admitted and emergency patients, and the occurrence of access block. The impact of shifting discharge timing on occupancy levels was quantified using observed and simulated data.
  
  
  RESULTS
  The study identified three stages of system performance decline, or choke points, as hospital occupancy increased. These choke points were found to be dependent on hospital size, and reflect a system change from 'business-as-usual' to 'crisis'. Effecting early discharge of patients was also found to significantly (P < 0.001) impact overcrowding levels and improve patient flow.
  
  
  CONCLUSIONS
  Modern hospital systems have the ability to operate efficiently above an often-prescribed 85% occupancy level, with optimal levels varying across hospitals of different size. Operating over these optimal levels leads to performance deterioration defined around occupancy choke points. Understanding these choke points and designing strategies around alleviating these flow bottlenecks would improve capacity management, reduce access block and improve patient outcomes. Effecting early discharge also helps alleviate overcrowding and related stress on the system.
authors.affiliation: CSIRO Australian e-Health Research Centre, Brisbane, Australia. sankalp.khanna@csiro.au
authors.forename: Sankalp
authors.initials: S
authors.lastname: Khanna
authors.forename: Justin
authors.initials: J
authors.lastname: Boyle
authors.forename: Norm
authors.initials: N
authors.lastname: Good
authors.forename: James
authors.initials: J
authors.lastname: Lind
mesh_terms: D016009:Chi-Square Distribution; D017598:Efficiency, Organizational; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data*; D006742:Hospital Bed Capacity / Q000706:statistics & numerical data*; D006761:Hospitals / Q000706:statistics & numerical data*; D006779:Hospitals, Public / Q000706:statistics & numerical data; D006801:Humans; D007902:Length of Stay / Q000706:statistics & numerical data*; D010351:Patient Discharge / Q000706:statistics & numerical data*; D011793:Queensland; D012189:Retrospective Studies; D013997:Time Factors