Speaker:
Dr. Christopher McCudden. University of Ottawa, Eastern Ontario Regional Laboratory Association, The Ottawa Hospital.
Dr. McCudden is a Clinical Biochemist at the Ottawa Hospital. He is a Professor and Vice Chair of the Department of Pathology & Laboratory Medicine at the University of Ottawa. He serves as the Deputy Chief Medical Scientific Officer and Medical Director of Informatics and Information Technology for the Eastern Ontario Regional Laboratory Association. His interests include automated chemistry, laboratory informatics & machine learning, quality improvement, plasma cell dyscrasias, and audit and feedback for laboratory stewardship.
Overview:
Development of a short timeframe (6-12 months) kidney failure risk prediction model may serve to improve transitions from advanced CKD to kidney failure and reduce rates of unplanned dialysis. This presentation will describe development of prediction models for urgent dialysis. In addition, it will describe the formation of the multi-disciplinary team who developed and validated the models as well as practical aspects of data acquisition, model development, and future implementation hurdles.
Objectives:
At the conclusion of this session, participants will be able to:
- Define urgent dialysis and describe its impact on patients
- Describe problems where machine learning algorithms may be useful
- List enablers and barriers to implementing machine learning in the real world