Saturday, October 15, 2022 from 9:45 AM to 11:15 AM PDT at Continental Ballrooms 1-3
Available for 1.50 hours of CPE credit
Activity Number: 0217-0000-22-147-L04-P
Activity Type: An Application-Based Activity
This session looks to highlight artificial intelligence applications and approaches to implement these techniques in pharmacy practice. This session will have 3 presentations. The first presentation will lay the ground work of artificial intelligence for audience members unfamiliar with this technology and how it is embedded into clinical decision support tools. The session will review types of artificial intelligence applications and potential benefits of incorporation of artificial intelligence in practice. The second presentation will over view the currently available wearable technology with data supporting use to manage various comorbidities. This presentation looks to familiarize clinicians with these technologies and apply data obtained from wearable devices to optimize drug therapy outcomes. The third presentation will review steps to incorporating artificial intelligence into a current practice setting using a practical approach. Also, key consideration when vetting the accuracy and reliability of these clinical decision support tools. The talk will highlight strategies for incorporating artificial intelligence and practice areas that are prime for incorporation.
 | Moderator: Lawrence J. Cohen, Pharm.D., FCCP
Professor of Pharmacotherapy; Coordinator of Interprofessional Education and Continuing Professional Education, University of North Texas, Fort Worth, Texas
View Biography |
Learning Objectives
1. Review the historical applications of artificial intelligence in health care.
2. Categorize key concepts of artificial intelligence embedded into clinical decision support tools (i.e. drug interaction programs) that pertain to pharmacy practice.
3. Analyze the role artificial intelligence has in optimizing current practice.
4. Define a step wise approach to implement artificial intelligence in practice.
5. Assess data output from artificial intelligence for clinical practice optimization.
6. Apply artificial intelligence applications in various pharmacy practice.
7. Describe the currently available wearable devices used in healthcare.
8. Appraise the current literature surrounding the use of wearable technology and how artificial intelligence is used to process data.
9. Apply the use of wearable technology to optimize patient outcomes and population health.