AI Models to Optimize Opioid Prescribing

Description

Fadia T. Shaya, PhD, MPH, DESS, a professor in the University of Maryland Baltimore School of Pharmacy; Apoorva Pradhan, MD, MPH, a postdoctoral fellow in the Department of Pharmaceutical Health Services Research at the University of Maryland Baltimore School of Pharmacy; and James Tim Oates, PhD, a professor of computer science and electrical engineering at the University of Maryland Baltimore County will give a talk entitled "AI Models to Optimize Opioid Prescribing" as the March Informatics Grand Rounds. The speakers will discuss the issues with the current methods in opioid prescribing and how AI-based models have been developed to optimize opioid prescription.

CME credits are available. The activity code to join for CME is 31018.

Objectives:

1. Articulate the issues with opioid prescribing.
2. Describe methods currently used and articulate the need to translate data into action.
3. Describe the multiple AI-based methods developed to predict opioid related adverse events, and optimize opioid prescription.
4. Articulate the validity of the methods, based on the models structure, training data, validation data, and in-situ performance.