In our economically rational world, the decision of whether or not to implement an intervention aimed at preventing a health problem must take into consideration the program's cost-effectiveness.
In disease prevention, this exercise is particularly difficult to carry out, in part because the expected effects only occur after many years. This latency poses major methodological challenges for researchers who need to estimate the cost-effectiveness of the intervention. It poses a problem for public health decision-makers who need this information quickly in order to determine whether the intervention should receive financing. Simulations can help to alleviate this problem by providing a means of modelling life events under different conditions, such as the presence or absence of a prevention program, using information that is already available.
Thanks to this research, a tool for estimating the cost-benefit of prevention programs is now available in Quebec.
The goal of this research was to develop a flexible, generic simulation tool, and to test it with a real-life problem: the cost-effectiveness of interventions for the prevention of osteoporosis. The simulation generated a virtual population of women with the same age distribution as that of women in Quebec in 2007, and compared the various options in the context of this population. These options corresponded to the present situation (absence of a specific prevention program), measures for disease prevention, and screening women for osteoporosis.
The results show that, when scientific data is available for the problem, the simulator can be used to determine the cost-effectiveness of each option (cost divided by a measure of health, such as individual lifespan), as well as its cost-utility (cost divided by lifespan weighted for quality). Thanks to this research, a tool for estimating the cost-benefit of prevention programs is now available in Quebec.
Daniel Reinharz, Université Laval
Call for proposals
Deposit of the research report: July 2010