Metric Development to Interpret Measures of Medication Compliance

Medication non-compliance is associated with poor outcomes in patients. Although different methods are currently used to measure compliance, the ability to translate this measure into a meaningful metric, which is interpretable for both methodologists and clinicians, has not yet been realized. Medication compliance has become an increasingly important area of research as policy makers perceive the extent and effect of the problem that non-compliance poses. The intern, in partnership with the London Health Sciences Centre, Division of Critical Care, proposed to develop a new metric to interpret measures of medication compliance which would provide better insight into disease patterns, which would involve clearly defining the statistical properties of the new measure. In addition, the intern estimated the distributions of both the current and new compliance measures to quantify the uncertainty of compliance measures.

Faculty Supervisor:

Drs. Ying Zhang & Paul Cabilio

Student:

Maja Grubisic

Partner:

Centre for Critical Illness Research at the Lawson Research Institute

Discipline:

Mathematics

Sector:

Pharmaceuticals

University:

Acadia University