The power and utility of Artificial intelligence and Augmented Intelligence continue to expand as new platforms and technologies emerge in our professional and personal lives. These tools have opened doors to new ways to capture patient specific data for monitoring treatment efficacy and outcomes. High level monitoring of large datasets in real time may provide insights into clinical decision making. The goal for this program will be to inform ACCP members on the newer methods and evolving practices for clinical analysis and guideline development. The goal of this session is to critically assess traditional monitoring of therapeutics, distill the complexities of AI into usable data for clinicians, and review the untapped potential of large data sets to project the population impact of new treatments as they become available. Limitations exist with the historical practices used to develop evidence-based guidelines. This session will review how big data, utilization of a rapid practice guideline approach, and use of natural language processing can help overcome the current confines of contemporary practice guideline development.

Faculty

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