Population ageing and healthcare expenditure projections: new evidence from a time to death approach
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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.
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.
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.
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.
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.
KeywordsHealthcare expenditure projection Population ageing Time to death Acute inpatient care costs
The authors would like to thank Fiona Cox, Lee Williamson, Claire Boag and Joan Nolan of the Longitudinal Studies Centre-Scotland (LSCS) for their help provided. The LSCS is supported by the ESRC/JISC, the Scottish Funding Council, the Chief Scientist’s Office and the Scottish Executive. The authors alone are responsible for the interpretation of the data. Census output is Crown copyright and is reproduced with the permission of the Controller of HMSO and the Queen’s Printer for Scotland. This work was supported by a Medical Research Council (MRC) PhD studentship.
Conflict of interest
Permission was given by the Privacy Advisory Committee of ISD to use linked SMR data.
- 6.Breyer, F., Lorenz, N., Niebel, T.: Health care expenditures and longevity: is there a Eubie Blake effect? Discussion Paper 1226, DIW Berlin (2012)Google Scholar
- 12.WHO World Health Organisation: Health inequality, inequity and social determinants of health. http://www.who.int/social_determinants/resources/interim_statement/csdh_interim_statement_inequity_07.pdf (2007). Accessed Sept 2011
- 13.Graham, B., Normand, C.: Proximity to death and acute health care utilisation in Scotland. Final Report, Chief Scientist Office (2001)Google Scholar
- 14.Hattersley, L., Boyle, P: The Scottish longitudinal study. An introduction. LSCS working paper 1.0. Edinburgh/St Andrews, Longitudinal Studies Centre Scotland (2007)Google Scholar
- 15.Hattersley, L., Raab, G., Boyle, P.: The Scottish longitudinal study. Tracing rates and sample quality for the 1991 census SLS sample. LSCS Working Paper 2.0. Edinburgh/St Andrews: Longitudinal Studies Centre Scotland (2007)Google Scholar
- 16.Hattersley, L., Boyle, P.: The Scottish longitudinal study, a technical guide to the creation, quality and linkage of the 2001 census SLS sample. LSCS working paper 3.0. Edinburgh/St Andrews, Longitudinal Studies Centre Scotland (2009)Google Scholar
- 17.Hattersley, L., Boyle, P.: The Scottish longitudinal study, The 1991–2001 Scottish longitudinal study census link. LSCS Working paper 4.0. Edinburgh/St Andrews, Longitudinal Studies Centre Scotland (2009)Google Scholar
- 19.Cleves, M., Gould, W., Gutierrez, R., Marchenko, Y.: An introduction to survival analysis using STATA, 2nd edn. STATA Press, College Station (2008)Google Scholar
- 20.Glick, H.A.: ‘glmdiagnostic.do’. http://www.uphs.upenn.edu/dgimhsr/eeinct_multiv.htm (2008). Accessed Sept 2010