Predicting 30-Day Risk of Hospitalization, Emergency Department Visit and Death Among Albertans Receiving Opioid Prescriptions Using Machine Learning Algorithms: A Prognostic Study

Prescribers rely on guidelines for appropriate use and prescribing of opioids. Currently, there are no risk prediction calculators available to quantify the risk of prescribing an opioid that uses a patient’s history and drug utilization pattern. Machine learning algorithms offer an opportunity to perhaps develop such a risk calculator as a result of the large amount of heath data being collected in Alberta. OKAKI, a clinical analytics company, may benefit from this project as it may be able to offer a risk calculator to prescribers as a clinical decision aid tool. This may ultimately enhance patient safety.

Faculty Supervisor:

Dean Eurich

Student:

Partner:

OKAKI

Discipline:

Life Sciences

Sector:

Health and Related Sciences & Technology; Information and cultural industries; Professional, scientific and technical services

University:

University of Alberta

Program: