title: Population ageing and healthcare expenditure projections: new evidence from a time to death approach.
abstract: BACKGROUND
  Health care expenditure (HCE) is not distributed evenly over a person's life course. How much is spent on the elderly is important as they are a population group that is increasing in size. However other factors, such as death-related costs that are known to be high, need be considered as well in any expenditure projections and budget planning decisions.
  
  
  OBJECTIVE
  This article analyses, for the first time in Scotland, how expenditure projections for acute inpatient care are influenced when applying two different analytical approaches: (1) accounting for healthcare (HC) spending at the end of life and (2) accounting for demographic changes only. The association between socioeconomic status and HC utilisation and costs at the end of life is also estimated.
  
  
  METHODS
  A representative, longitudinal data set is used. Survival analysis is employed to allow inclusion of surviving sample members. Cost estimates are derived from a two-part regression model. Future population estimates were obtained for both methods and multiplied separately by cost estimates.
  
  
  RESULTS
  Time to death (TTD), age at death and the interaction between these two have a significant effect on HC costs. As individuals approach death, those living in more deprived areas are less likely to be hospitalised than those individuals living in the more affluent areas, although this does not translate into incurring statistically significant higher costs. Projected HCE for acute inpatient care for the year 2028 was approximately 7% higher under the demographic approach as compared to a TTD approach.
  
  
  CONCLUSIONS
  The analysis showed that if death is postponed into older ages, HCE (and HC budgets) would not increase to the same extent if these factors were ignored. Such factors would be ignored if the population that is in their last year(s) of life were not taken into consideration when obtaining cost estimates.
authors.affiliation: Health Economics and Health Technology Assessment, Institute of Health and Wellbeing, University of Glasgow, 1 Lilybank Gardens, Glasgow, G12 8RZ, UK, Claudia.Geue@glasgow.ac.uk.
authors.forename: Claudia
authors.initials: C
authors.lastname: Geue
authors.forename: Andrew
authors.initials: A
authors.lastname: Briggs
authors.forename: James
authors.initials: J
authors.lastname: Lewsey
authors.forename: Paula
authors.initials: P
authors.lastname: Lorgelly
mesh_terms: D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D003695:Delivery of Health Care / Q000191:economics / Q000706:statistics & numerical data; D005260:Female; D005544:Forecasting; D005102:Health Expenditures / Q000706:statistics & numerical data* / Q000639:trends; D006801:Humans; D008297:Male; D008875:Middle Aged; D017059:Models, Econometric; D009026:Mortality / Q000639:trends; D012606:Scotland / Q000453:epidemiology; D016019:Survival Analysis; D013997:Time Factors