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Abstract Background The few studies that have attempted to estimate the future cost of caring for people with dementia in Australia are typically based on total prevalence and the cost per patient over the average duration of illness. However, costs associated with dementia care also vary according to the length of the disease, severity of symptoms and type of care provided. This study aimed to determine more accurately the future costs of dementia management by taking these factors into consideration. Methods The current study estimated the prevalence of dementia in Australia (2010-2040). Data from a variety of sources was recalculated to distribute this prevalence according to the location (home/institution), care requirements (informal/formal), and dementia severity. The cost of care was attributed to redistributed prevalences and used in prediction of future costs of dementia. Results Our computer modeling indicates that the ratio between the prevalence of people with mild/moderate/severe dementia will change over the three decades from 2010 to 2040 from 50/30/20 to 44/32/24. Taking into account the severity of symptoms, location of care and cost of care per hour, the current study estimates that the informal cost of care in 2010 is AU$3.2 billion and formal care at AU$5.0 billion per annum. By 2040 informal care is estimated to cost AU$11.6 billion and formal care $AU16.7 billion per annum. Interventions to slow disease progression will result in relative savings of 5% (AU$1.5 billion) per annum and interventions to delay disease onset will result in relative savings of 14% (AU$4 billion) of the cost per annum. With no intervention, the projected combined annual cost of formal and informal care for a person with dementia in 2040 will be around AU$38,000 (in 2010 dollars). An intervention to delay progression by 2 years will see this reduced to AU$35,000. Conclusions These findings highlight the need to account for more than total prevalence when estimating the costs of dementia care. While the absolute values of cost of care estimates are subject to the validity and reliability of currently available data, dynamic systems modeling allows for future trends to be estimated.

Abstract Background In an attempt to devise a simpler computable tool to assist workforce planners in determining what might be an appropriate mix of health service skills, our discussion led us to consider the implications of skill mixing and workforce composition beyond the 'stock and flow' approach of much workforce planning activity. Methods Taking a dynamic systems approach, we were able to address the interactions, delays and feedbacks that influence the balance between the major components of health and health care. Results We linked clinical workforce requirements to clinical workforce workload, taking into account the requisite facilities, technologies, other material resources and their funding to support clinical care microsystems; gave recognition to productivity and quality issues; took cognisance of policies, governance and power concerns in the establishment and operation of the health care system; and, going back to the individual, gave due attention to personal behaviour and biology within the socio-political family environment. Conclusion We have produced the broad endogenous systems model of health and health care which will enable human resource planners to operate within real world variables. We are now considering the development of simple, computable national versions of this model.