title: The challenges of population ageing: accelerating demand for emergency ambulance services by older patients, 1995-2015.
abstract: OBJECTIVE
  To measure the growth in emergency ambulance use across metropolitan Melbourne since 1995, to measure the impact of population growth and ageing on these services, and to forecast demand for these services in 2015.
  
  
  METHODS
  A population-based retrospective analysis of Ambulance Victoria's metropolitan emergency ambulance transportation data for the period from financial year 1994-95 to 2007-08, and modelling of demand in the financial year 2014-15.
  
  
  METHODS
  Numbers and rates of emergency ambulance transportations.
  
  
  RESULTS
  The crude annual rate of emergency transportations across all age groups increased from 32 per 1000 people in 1994-95 to 58 per 1000 people in 2007-08. The rate of transportation for all ages increased by 75% (95% CI, 62%-89%) over the 14-year study period, representing an average annual growth rate of 4.8% (95% CI, 4.3%-5.3%) beyond that explained by demographic changes. Patients aged ≥ 85 years were eight times (incident rate ratio, 7.9 [95% CI, 7.6-8.3]) as likely to be transported than those aged 45-69 years over this period. Forecast models suggest that the number of transportations will increase by 46%-69% between 2007-08 and 2014-15, disproportionately driven by increasing usage by patients aged ≥ 85 years.
  
  
  CONCLUSIONS
  These findings confirm a dramatic rise in emergency transportations over the study period, beyond that expected from demographic changes. Rates increased across all age groups, but more so in older patients. In the future, such acceleration is likely to have major effects on ambulance services and acute hospital capacity. This calls for further investigation of underlying causes and alternative models of care.
authors.affiliation: School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC. Judy.LowthianATmonash.edu
authors.forename: Judy A
authors.initials: JA
authors.lastname: Lowthian
authors.forename: Damien J
authors.initials: DJ
authors.lastname: Jolley
authors.forename: Andrea J
authors.initials: AJ
authors.lastname: Curtis
authors.forename: Alexander
authors.initials: A
authors.lastname: Currell
authors.forename: Peter A
authors.initials: PA
authors.lastname: Cameron
authors.forename: Johannes U
authors.initials: JU
authors.lastname: Stoelwinder
authors.forename: John J
authors.initials: JJ
authors.lastname: McNeil
mesh_terms: D000293:Adolescent; D000328:Adult; D017677:Age Distribution; D000368:Aged; D000369:Aged, 80 and over; D000552:Ambulances / Q000706:statistics & numerical data*; D001315:Australia / Q000453:epidemiology; D002648:Child; D002675:Child, Preschool; D004632:Emergency Medical Services / Q000706:statistics & numerical data; D005260:Female; D005544:Forecasting; D006301:Health Services Needs and Demand / Q000706:statistics & numerical data / Q000639:trends*; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D011157:Population Dynamics; D012189:Retrospective Studies; D017678:Sex Distribution; D055815:Young Adult