firstname.lastname@example.orgPeter Tanuseputro, MHSc, MD, CCFP, FRCPCPeter Tanuseputro
completed training as a Public Health and Preventive Medicine physician, and as a Family Physician at the University of Toronto. Peter is currently an Investigator at the Bruyere Research Institute, the Institute for Clinical Evaluative Sciences, and the Ottawa Hospital Research Institute, under the supervision of Dr. Doug Manuel. He also practices Family Medicine in the community. His research experience includes the development and application of tools to measure the health of populations and the burden of behavioural risk factors. His current research includes using linked health administrative databases to develop population perspectives on health care use and cost associated with aging and end of life in Ontario.Project description:
Health care utilization increases significantly at the end of life. Few studies have examined factors such as age and functional decline on health care utilization and cost at the end of life, in the Canadian context; none have examined a broad range of health system factors and compared their relative effects. There is a great need to better understand how to best meet the needs of individuals at the end of life. Implementing these in practice also requires targeting using predictive models that can provide for example probabilities of health care need and use within varying time periods. Such a product would not only allow better estimation of future health care costs, but presents opportunities to optimize health care use and cost associated with aging and end-of-life.
The central hypothesis of this project is that population level health care utilization and direct health care costs at the end of life can be accurately described and predicted using routinely collected data, and that doing so will identify opportunities to optimize care and increase value for money for the health care system. There are four main objectives of this project:
- To describe health care utilization and costs associated with end-of-life in Ontario using health administrative databases.
- To determine what factors are associated with utilization and cost at
the end-of-life, including: demographic factors (e.g. age, sex), disease
factors (e.g. presence of chronic diseases at time of death),
disability factors (e.g. activities of daily living), health services
factors (e.g. provision of palliative care, who is providing care, place
of care), socioeconomic factors (e.g. income), and community factors
- To generate algorithms to predict health care utilization and cost at
the end-of-life. These algorithms will be based on multivariable
modeling that includes factors found to be significant in objective 2,
and will predict health care use and cost at the individual and health
- To develop population level performance indicators in each health care
sector that report on the quality and cost-effectiveness of care at the
end of life. These indicators will be created and applied to different
planning regions across Ontario to measure performance.