title: Projected acute inpatient activity in New South Wales - aIM2005.
abstract: OBJECTIVE
  To describe the statewide projections of acute inpatient activity in New South Wales.
  
  
  METHODS
  Data on acute inpatient activity in NSW for the period 1998-1999 to 2003-04 were derived from the Admitted Patient Data Collection. Regression analysis was used to project trends in utilisation and length of stay by age group, clinical specialty groups and stay type (day-only and overnight). The projected separation rates and length of stay were subject to clinical review. Projected separation rates (by age group, clinical speciality and stay type) were applied to NSW population projections to derive the projected number of separations. Bed-days were calculated by applying projected overnight average length of stay.
  
  
  RESULTS
  Total acute inpatient activity in NSW public hospitals is projected to increase from around 1.05 million separations in 2004 to around 1.3 million separations by 2017 (24%). Same-day separations are projected to increase from around 368 000 to around 514 000 (40%). Overnight separations are projected to rise from around 690 000 in 2003-04 to around 798 000 in 2016-17 (18%). Overnight bed-days are projected to increase from around 3.7 million in 2003-04 to around 4.1 million bed-days in 2017 (12%). Differences across age groups and clinical specialties are also evident from the modelling.
authors.affiliation: Statewide Services Development Branch, NSW Department of Health, Locked Mail Bag 961, North Sydney, Sydney, NSW 2060, Australia. neill.jones@doh.health.nsw.gov.au.
authors.forename: Neill
authors.initials: N
authors.lastname: Jones
authors.forename: Greg
authors.initials: G
authors.lastname: Hardes
authors.forename: Stephen
authors.initials: S
authors.lastname: Ryan
authors.forename: Jennifer
authors.initials: J
authors.lastname: Sheehan
authors.forename: Cathryn
authors.initials: C
authors.lastname: Cox
authors.forename: Kathy
authors.initials: K
authors.lastname: Meleady
authors.forename: Hirani
authors.initials: H
authors.lastname: Jayasinha
mesh_terms: D000293:Adolescent; D000328:Adult; D017677:Age Distribution; D000368:Aged; D000369:Aged, 80 and over; D002391:Catchment Area, Health; D002648:Child; D002675:Child, Preschool; D005260:Female; D005843:Geography; D006301:Health Services Needs and Demand / Q000706:statistics & numerical data / Q000639:trends*; D006302:Health Services Research; D006760:Hospitalization / Q000706:statistics & numerical data / Q000639:trends*; D006779:Hospitals, Public / Q000706:statistics & numerical data*; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D008297:Male; D008511:Medicine / Q000145:classification; D008875:Middle Aged; D009517:New South Wales / Q000453:epidemiology; D012044:Regression Analysis; D013038:Specialization; D014600:Utilization Review