Simulation of health care and related costs in people with dementia in Australia
Lachlan Standfield A B D , Tracy Comans A B C and Paul A. Scuffham AA Centre for Applied Health Economics, Menzies Health Institute Queensland, Griffith University, Nathan, Qld 4111, Australia. Email: t.comans@uq.edu.au; p.scuffham@griffith.edu.au
B NHMRC Cognitive Decline Partnership Centre, University of Sydney, Sydney, NSW 2006, Australia.
C Metro North Hospital and Health Service, Herston, Brisbane, Qld 4029, Australia.
D Corresponding author. Email: lachlan.standfield@griffithuni.edu.au
Australian Health Review 43(5) 531-539 https://doi.org/10.1071/AH18022
Submitted: 30 January 2018 Accepted: 24 July 2018 Published: 24 September 2018
Journal Compilation © AHHA 2019 Open Access CC BY-NC-ND
Abstract
Objectives The aim of this study was to develop a validated model to predict current and future Australian costs for people with dementia to help guide decision makers allocate scarce resources in the presence of capacity constraints.
Methods A hybrid discrete event simulation was developed to predict costs borne in Australia for people with dementia from 2015 to 2050. The costs captured included community-based care, permanent and respite residential aged care, hospitalisation, transitional care, pharmaceuticals, aged care assessments, out of hospital medical services and other programs.
Results The costs borne for people with dementia in Australia are predicted to increase from A$11.8 billion in 2015 to A$33.6 billion in 2050 at 2013–14 prices, ceteris paribus. If real per capita health and social expenditure increased by 1.0% annually, these costs are predicted to increase by around A$14.2 billion to a total of around A$47.8 billion by 2050.
Conclusions This simulation provides useful estimates of the potential future costs that will be borne for people with dementia and allows the exploration of the effects of capacity constraints on these costs. The model demonstrates that the level of real annual per capita growth in health and social expenditure has significant implications for the future sustainability of dementia care in Australia.
What is known about the topic? With the aging of the Australian population, the number of people living with dementia is predicted to rise markedly in the next four decades. As the number of people living with dementia increases, so too will the financial burden these debilitating and degenerative diseases place on private and public resources. These increases are likely to challenge the efficiency and sustainability of many health systems in the developed world.
What does this paper add? This research provides a validated model to predict current and future Australian costs for people with dementia to help guide decision makers allocate scarce resources in the presence of capacity constraints (i.e. where the supply of resources does not meet demand). The model predicts an increase in costs for people with dementia from A$11.8 billion in 2015 to A$33.6 billion in 2050 at 2013–14 prices. If real per capita health and social expenditure increased by 1.0% annually, these costs are predicted to increase by around A$14.2 billion to a total of around A$47.8 billion by 2050.
What are the implications for practitioners? This simulation provides useful estimates of the potential future costs that will be borne for people with dementia and allows the exploration of the effects of capacity constraints on these costs. The model demonstrates that the level of real annual per capita growth in health and social expenditure has significant implications for the future sustainability of dementia care in Australia.
Additional keywords: aged care, aging, health economics, health funding and financing, health system.
References
[1] Australian Institute of Health and Welfare (AIHW). Dementia in Australia. Catalogue no. Age 70. Canberra: AIHW; 2012.[2] Standfield LB, Comans TA, Scuffham PA. An empirical comparison of Markov cohort modeling and discrete event simulation in a capacity-constrained health care setting. Eur J Health Econ 2017; 18 33–47.
| An empirical comparison of Markov cohort modeling and discrete event simulation in a capacity-constrained health care setting.Crossref | GoogleScholarGoogle Scholar |
[3] Deloitte Access Economics. Keeping dementia front of mind: incidence and prevalence 2009–2050. Canberra: Alzheimer’s Australia; 2009.
[4] Brown L, Hansnata E, La HA. Economic cost of dementia in Australia 2016–2056. 2017. Available at: https://reports.dementia.org.au/costofdementia [verified 14 August 2018].
[5] Standfield LB, Comans T, Scuffham P. A simulation of dementia epidemiology and resource use in Australia. Aust N Z J Public Health 2018; 42 291–5.
| A simulation of dementia epidemiology and resource use in Australia.Crossref | GoogleScholarGoogle Scholar |
[6] Australian Institute of Health and Welfare (AIHW). Dementia and the take-up of residential respite care: an analysis using the PIAC cohort. Catalogue no. CSI 9. Canberra: AIHW; 2010.
[7] Australian Institute of Health and Welfare (AIHW). Dementia care in hospitals costs and strategies. Catalogue no. Age 72. Canberra: AIHW; 2013.
[8] Australian Institute of Health and Welfare (AIHW). Movement between hospital and residential aged care 2008–09. Data linkage series no. 16. Catalogue no. CSI 16. Canberra: AIHW; 2013.
[9] Deloitte Access Economics. Dementia across Australia: 2011–2050. Canberra: Alzheimer’s Australia; 2011.
[10] Anstey KJ, Burns RA, Birrell CL, Steel D, Kiely KM, Luszcz MA. Estimates of probable dementia prevalence from population-based surveys compared with dementia prevalence estimates based on meta-analyses. BMC Neurol 2010; 10 62
| Estimates of probable dementia prevalence from population-based surveys compared with dementia prevalence estimates based on meta-analyses.Crossref | GoogleScholarGoogle Scholar |
[11] Eddy DM, Hollingworth W, Caro JJ, Tsevat J, McDonald KM, Wong JB. Model transparency and validation: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force-7. Med Decis Making 2012; 32 733–43.
| Model transparency and validation: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force-7.Crossref | GoogleScholarGoogle Scholar |
[12] Deloitte Access Economics. The viability of residential aged care providers. Canberra: Deloitte Access Economics; 2011.
[13] Sharpe WF. Capital asset prices: a theory of market equilibrium under conditions of risk. J Finance 1964; 19 425–42.
[14] Lintner J. The valuation of risk assets and the selection of risky investments in stock portfolios and capital budgets. Rev Econ Stat 1965; 47 13–37.
| The valuation of risk assets and the selection of risky investments in stock portfolios and capital budgets.Crossref | GoogleScholarGoogle Scholar |
[15] Matthews FE, Stephan BC, Robinson L, Jagger C, Barnes LE, Arthur A, Brayne C, Cognitive Function and Ageing Studies Collaboration A two decade dementia incidence comparison from the Cognitive Function and Ageing Studies I and II. Nat Commun 2016; 7 11398
| A two decade dementia incidence comparison from the Cognitive Function and Ageing Studies I and II.Crossref | GoogleScholarGoogle Scholar |
[16] Fratiglioni L, Launer LJ, Andersen K, Breteler MM, Copeland JR, Dartigues JF, Lobo A, Martinez-Lage J, Soininen H, Hofman A. Incidence of dementia and major subtypes in Europe: a collaborative study of population-based cohorts. Neurologic Diseases in the Elderly Research Group. Neurology 2000; 54 S10–5.
[17] Australian Institute of Health and Welfare (AIHW). Health expenditure Australia 2013–14. Canberra: AIHW; 2015.
[18] Åkerborg O, Lang A, Wimo A, Skoldunger A, Fratiglioni L, Gaudig M, Rosenlund M. Cost of dementia and its correlation with dependence. J Aging Health 2016; 28 1448–64.
| Cost of dementia and its correlation with dependence.Crossref | GoogleScholarGoogle Scholar |
[19] Nepal B, Brown L, Anstey K.. Rising midlife obesity will worsen future prevalence of dementia. PLoS One 2014; 9 e99305
| Rising midlife obesity will worsen future prevalence of dementia.Crossref | GoogleScholarGoogle Scholar |
[20] Aged Care Financing Authority (ACFA). Report on the funding and financing of the aged care industry. Canberra: ACFA; 2014.
[21] Commonwealth of Australia. Intergenerational report: Australia in 2055. Canberra: The Commonwealth of Australia, The Treasury; 2015. Available at: https://treasury.gov.au/publication/2015-intergenerational-report/ [verified 14 August 2018].
[22] Department of Human Services. Pharmaceutical Benefits Schedule item reports. 2016. Available at: http://medicarestatistics.humanservices.gov.au/statistics/pbs_item.jsp [verified 8 August 2016].
[23] Department of Social Services. Home care packages programme guidelines. Canberra: Australian Government; 2014.
[24] Australian Institute of Health and Welfare (AIHW). Aged care packages in the community 2010–11: a statistical overview. Canberra: AIHW; 2012.
[25] Australian Institute of Health and Welfare (AIHW). Dementia among aged care residents: first information from the Aged Care Funding Instrument. Aged care statistics series no. 32. Catalogue no. Age 63. Canberra: AIHW; 2011.
[26] Reserve Bank of Australia (RBA). Yields on Commonwealth government bonds, 10 years maturity; Monthly; Series ID: FCMYGBAG10. Available at: http://www.rba.gov.au/statistics/tables/ [verified 12 August 2016]. 2016.
[27] Reserve Bank of Australia (RBA). Non-financial corporate BBB-rated bonds – spread to AGS – 10 year target tenor; Monthly; Series ID FNFCBBB10M; 2016. Available at: http://www.rba.gov.au/statistics/tables/ [verified 12 August 2016].
[28] Australian Institute of Health and Welfare (AIHW). Residential aged care in Australia 2010–11: a statistical overview. Aged care statistics series no. 36. Catalogue no. Age 68. Canberra: AIHW; 2012.
[29] Gray LC, Peel NM, Crotty M, Kurrle SE, Giles LC, Cameron ID. How effective are programs at managing transition from hospital to home? A case study of the Australian Transition Care Program. BMC Geriatr 2012; 12 6
| How effective are programs at managing transition from hospital to home? A case study of the Australian Transition Care Program.Crossref | GoogleScholarGoogle Scholar |