Medication adherence in multiple sclerosis: a model for other chronic diseases?
Increasing medication adherence may have a greater impact on the health of a population than any improvements in specific medical treatments. However, little progress has been made in this area, in part due to a lack of understanding of predictors associated with non- adherence.
The economic burden of non-adherence in Canada is estimated at $7-9 billion annually, with 5-7% of all hospitalizations due to non-adherence. Reasons for non-adherence are complex and few well-identified predictors of non-adherence exist. Studies of sociodemographic factors including, age, sex, race, and socioeconomic status, have not been consistently associated with levels of adherence across diseases.
A team, led by Dr Charity Evans, Associate Professor of Pharmacy at the University of Saskatchewan, aims to improve this situation by exploring whether the treatment of multiple sclerosis (MS) can provide a model for optimal adherence to medication for other diseases. The study will use administrative data from British Columbia, Saskatchewan, and Manitoba.
“We recently conducted a large population-based study and found that 1 in 4 people have sub-optimal adherence to the disease-modifying therapies (DMTs) for MS.” says Dr. Helen Tremlett, Professor of Neurology, at the University of British Columbia and the British Columbia lead. “However, that also means that 75% of patients had optimal adherence to the MS DMTs” says Dr Evans, “This is considerably higher than the 50% estimated by the World Health Organization for other chronic diseases. We hypothesize that this higher adherence is due to the relatively unique management and support persons with MS receive when prescribed a DMT. Our ultimate goal is to explore if MS can be a model for optimal adherence to DMTs for other chronic diseases.”
The study, funded by the Canadian Institutes of Health Research, aims to fill this gap in current health-related knowledge by providing population-level information on adherence for four chronic diseases: MS, rheumatoid arthritis, epilepsy, and Parkinson’s disease. Each of these diseases has a significant impact on the Canadian health care system as well as on patient-related outcomes, including quality of life.
The identification of an existing, practical, and translatable model of disease management that improves adherence will have a substantial impact on patient outcomes and health care cost-savings across many different diseases.
PopData will link data from the BC Ministry of Health and BC Vital Statistics Agency for the project.