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Advancing technology to improve health care decision-making
Osteoarthritis-6-1
Scientific Study Title:
Microsimulation Modeling of the Impact of Health Interventions and Policies: Simulation Technology for Applied Research (STAR).
Start Date:
  • 2008
End Date:
  • 2013
Research Category
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Why did we do this research?

The goal of the Simulation Technology for Applied Research (STAR) project was to show that computer-based models of chronic diseases are beneficial in predicting the effects of public health policies. Computer simulation modeling is a process that allows us to see how these policies will affect the population before they are implemented. Scientists will be able to use these models to learn how risk factors affect the future well-being of the population. Increased use of computer models of health and disease will improve decision-making at the local, provincial, and national levels and will help reduce the burden of disease in Canada.

What did we do?

We used a computer program called POHEM (Population Health Model) to predict which public health interventions and policies should be used to reduce the burden of major chronic conditions, such as heart disease, diabetes, and arthritis. It was developed at Statistics Canada. The key to the STAR team’s success was its strong group efforts and the diverse talents within the team. This group is experienced in Health Services Research, Epidemiology, Statistics, Medicine, Computer Science, Simulation Modelling, Health Economics and many other fields. The STAR team also worked closely with Government Officials to improve policy-related research. The modeling technique we used is called microsimulation. It simulated individual “people” to track the effect on the population. It then computed the risk of different diseases and predicted their effects on health.

What did we find?

Our research showed that the results from simulation models are trustworthy and can help both scientists and decision-makers. We have published an outline for the validation of these models. The POHEM model has been extensively confirmed. Except for obesity and diabetes, we have found that all other risk factors for heart disease were expected to decrease. Obesity was projected to surpass smoking as the most prevalent risk factor. The total cost of osteoarthritis (OA) was predicted to increase from $2.9 billion to $7.6 billion between 2010 and 2031, a 2.6-fold increase. OA prevalence was projected to grow from 13.9 to 18.4% between 2010 and 2030.

The Research Team

Principal Investigator

  • Jacek Kopec, PhD, Research Scientist Emeritus, Arthritis Research Canada (University of British Columbia)

Co-Investigators

  • Michal Abrahamowicz, PhD, Research Scientist, Arthritis Research Canada (McGill University)
  • David Buckeridge – MD, PhD (McGill University)
  • Philippe Fines – PhD (Statistics Canada)
  • William Flanagan (Statistics Canada)
  • Sam Harper MSPH – PhD (McGill University)
  • John Lynch – PhD, MPH (University of South Australia)
  • Douglas Manuel – MD, FRCPC (University of Ottawa)
  • Jillian Orderkirk (Organisation for Economic Co-operation and Development)
  • Michael Wolfson – PhD (University of Ottawa)

Who Funded This Research?

This study was funded by the Canadian Institutes of Health Research (CIHR).

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