title: Using demand analysis and system status management for predicting ED attendances and rostering.
abstract: BACKGROUND
  It has been observed that emergency department (ED) attendances are not random events but rather have definite time patterns and trends that can be observed historically.
  
  
  OBJECTIVE
  To describe the time demand patterns at the ED and apply systems status management to tailor ED manpower demand.
  
  
  METHODS
  Observational study of all patients presenting to the ED at the Singapore General Hospital during a 3-year period was conducted. We also conducted a time series analysis to determine time norms regarding physician activity for various severities of patients.
  
  
  RESULTS
  The yearly ED attendances increased from 113387 (2004) to 120764 (2005) and to 125773 (2006). There was a progressive increase in severity of cases, with priority 1 (most severe) increasing from 6.7% (2004) to 9.1% (2006) and priority 2 from 33.7% (2004) to 35.1% (2006). We noticed a definite time demand pattern, with seasonal peaks in June, weekly peaks on Mondays, and daily peaks at 11 to 12 am. These patterns were consistent during the period of the study. We designed a demand-based rostering tool that matched doctor-unit-hours to patient arrivals and severity. We also noted seasonal peaks corresponding to public holidays.
  
  
  CONCLUSIONS
  We found definite and consistent patterns of patient demand and designed a rostering tool to match ED manpower demand.
authors.affiliation: Department of Emergency Medicine, Singapore General Hospital, 169608 Singapore. Electronic address: marcus.ong.e.h@sgh.com.sg.
authors.forename: Marcus Eng Hock
authors.initials: MEH
authors.lastname: Ong
authors.affiliation: Department of Emergency Medicine, Singapore General Hospital, 169608 Singapore.
authors.forename: Khoy Kheng
authors.initials: KK
authors.lastname: Ho
authors.affiliation: Department of Emergency Medicine, Singapore General Hospital, 169608 Singapore.
authors.forename: Tiong Peng
authors.initials: TP
authors.lastname: Tan
authors.affiliation: Department of Emergency Medicine, Singapore General Hospital, 169608 Singapore.
authors.forename: Seoh Kwee
authors.initials: SK
authors.lastname: Koh
authors.affiliation: Service Operations Department, Singapore General Hospital, Singapore.
authors.forename: Zain
authors.initials: Z
authors.lastname: Almuthar
authors.affiliation: Richmond Ambulance Authority, Virginia, USA.
authors.forename: Jerry
authors.initials: J
authors.lastname: Overton
authors.affiliation: Department of Emergency Medicine, Singapore General Hospital, 169608 Singapore.
authors.forename: Swee Han
authors.initials: SH
authors.lastname: Lim
mesh_terms: D003441:Crowding; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data* / Q000639:trends; D005544:Forecasting; D006301:Health Services Needs and Demand / Q000706:statistics & numerical data* / Q000639:trends; D006801:Humans; D010561:Personnel Staffing and Scheduling / Q000706:statistics & numerical data; D012621:Seasons; D012846:Singapore; D013997:Time Factors; D014218:Triage / Q000706:statistics & numerical data; D000078329:Workforce