title: Impact of co-located general practitioner (GP) clinics and patient choice on duration of wait in the emergency department.
abstract: OBJECTIVE
  To empirically model the determinants of duration of wait of emergency (triage category 2) patients in an emergency department (ED) focusing on two questions: (i) What is the effect of enhancing the degree of choice for non-urgent (triage category 5) patients on duration of wait for emergency (category 2) patients in EDs; and (ii) What is the effect of co-located GP clinics on duration of wait for emergency patients in EDs? The answers to these questions will help in understanding the effectiveness of demand management strategies, which are identified as one of the solutions to ED crowding.
  
  
  METHODS
  The duration of wait for each patient (difference between arrival time and time first seen by treating doctor) was modelled as a function of input factors (degree of choice, patient characteristics, weekend admission, metro/regional hospital, concentration of emergency (category 2) patients in hospital service area), throughput factors (availability of doctors and nurses) and output factor (hospital bed capacity). The unit of analysis was a patient episode and the model was estimated using a survival regression technique.
  
  
  RESULTS
  The degree of choice for non-urgent (category 5) patients has a non-linear effect: more choice for non-urgent patients is associated with longer waits for emergency patients at lower values and shorter waits at higher values of degree of choice. Thus more choice of EDs for non-urgent patients is related to a longer wait for emergency (category 2) patients in EDs. The waiting time for emergency patients in hospital campuses with co-located GP clinics was 19% lower (1.5 min less) on average than for those waiting in campuses without co-located GP clinics.
  
  
  CONCLUSIONS
  These findings suggest that diverting non-urgent (category 5) patients to an alternative model of care (co-located GP clinics) is a more effective demand management strategy and will reduce ED crowding.
authors.affiliation: Centre for Health Economics, Monash University, Melbourne VIC 3800, Australia. anurag.sharma@buseco.monash.edu.au
authors.forename: Anurag
authors.initials: A
authors.lastname: Sharma
authors.forename: Brett
authors.initials: B
authors.lastname: Inder
mesh_terms: D001071:Appointments and Schedules; D003441:Crowding; D004636:Emergency Service, Hospital / Q000458:organization & administration* / Q000706:statistics & numerical data; D005194:Family Practice; D006801:Humans; D008505:Medical Staff, Hospital / Q000600:supply & distribution; D015233:Models, Statistical; D009741:Nursing Staff, Hospital / Q000600:supply & distribution; D011365:Professional Practice Location; D013997:Time Factors; D014218:Triage / Q000458:organization & administration*