Personalized medicine, the tailoring of care based on individual characteristics, has grown rapidly in recent years, particularly for cancer treatment. How to evaluate the effectiveness and cost-effectiveness of personalized therapies poses a challenge for health care systems, as current methods have a limited ability to account for variability between patients. In the case of personalized medicines, understanding this variability is essential to understanding the effectiveness and cost-effectiveness of drugs.
Data access has been approved for a project which will use analytic methods to compare the benefits and costs of personalized medicine, using data on advanced colorectal cancer treatment as an example. The project is part of University of British Columbia student, Reka Pataky’s doctoral thesis, supervised by Dr. Dean Regier, a Scientist at BC Cancer.
“Current economic evaluation methods often do not explicitly consider heterogeneity in patient outcomes. With the growing use of personalized medicine, where choice of treatment is informed by the molecular characteristics of the patient or disease, we expect to see greater heterogeneity in effectiveness and costs of interventions,” says Ms Pataky. “Adding to the problem is that personalized medicine interventions are costly. Health economists and decision-makers need to be able to evaluate them appropriately to inform efficient resource allocation in health care.”
It is hoped that the methods developed in this study can be used to generate better evidence for policy decisions around personalized medicine, ultimately improving health at the individual and population levels, while using scarce healthcare resources more efficiently.
PopData will link data from the BC Ministry of Health and BC Vital Statistics Agency with data from BC Cancer, and the BC Cancer Genetics Lab.
The project is funded by the Canadian Institutes of Health Research (CIHI).
