Grant: Travel Awards - Institute Community Support

Dementia, including Alzheimer's disease, is a devastating and complex disease with a high burden for patients, families and the health care system, in particular in terms of high emergency department and hospital use, and requires well-coordinated, whole-person care. Family doctors who work in a team setting with other health care professionals, like nurses and social workers, are considered the best way to caring for this vulnerable population. Ontario's introduction of Family Health Teams offers one of the largest examples of this model of care. However, up until now, there has been little evaluation of these models within the general or older population, and none within the dementia population, who may particularly benefit from this model of care. Moreover, these evaluations did not fully account for the methodological complexities linked with trying to disentangle the 'real' effect of belonging to a Family Health Team from the differences between patients who go to Family Health Teams versus other types of clinics. This project aims to answer these questions by examining how new statistical models aimed at estimating cause and effect, called causal inference methods, can be applied to get a valid estimate of the effect of Family Health Teams in reducing emergency department and hospital use in the dementia population. Overall, this research will provide one of the most accurate assessments of a Canadian primary care policy reform to date. It will show how causal inference methods can be added to the toolbox of researchers to improve policy evaluations and inform decision makers on the effectiveness of Family Health Teams in caring for the growing dementia population in Ontario.