In Complexity of Clinical Care, the implications and practical application of the outputs of AI and Machine learning are discussed in class, and in select assigned readings. This class provides an overview of how clinicians can use the outputs of these methods to benefit clinical care. Students complete an assignment where they shadow a clinician and learn about some of the clinical challenges and questions experienced by the clinician. In a final assignment, students propose solutions to these observed challenges and questions. These solutions may require AI and/or machine learning methods.

Learner objectives: 1) Enhance understanding of the structure and function of the Canadian health care system and roles of various health professionals. 2) Improve awareness and understanding of the complexity of clinical data collection, processing, management, and use, throughout the patient/consumer-health professional encounter. 3) Understand the culture of health care, and how culture may influence care delivery and information processing by health professionals across settings. 4) Increase awareness of health professionals' experience with information systems and barriers to successful adoption. 5) Appreciate the interaction among organizational processes, information sharing and impact on care delivery and health professionals experience in various clinical care settings. 6) Enhance understanding of the powerful role that informatics plays in clinical health care.