Alerts, Warnings, and AI

Learning Objectives
1. Describe clinical decision support and identify the role of warnings and recommendations in the EHR
2. Recognize how warnings are generated (human-determined parameters i.e. rule based vs learning AI systems)
3. Identify situations that may warrant overriding a warning and those that do not
4. Indicate key questions to ask yourself before ignoring or over-riding a warning
5. Define alert fatigue and how to avoid it

0.25 Credit

AMA EHR Workflow Learning Series

Activity Information and Disclosures

Interactive Course

Julian Genkins, MD^a;

Nadia Ismail, MD, MPH, MEd^b

Author Affiliations

^aFellow, Clinical Informatics, Hospitalist, Department of Internal Medicine, Stanford Health Care
^bVice Dean, School of Medicine; Associate Professor, Department of Medicine and Department of Education, Innovation and Technology, Baylor College of Medicine Houston Texas

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Within the EHR Workflow Learning Series medical students will learn systematic and efficient ways to transform an electronic health record (EHR) into their ally. In this micro learning course about alerts, warnings, and augmented intelligence (AI) you will learn how to describe clinical decision support, identify the role of warnings and recommendations in the EHR, and recognize how warnings are generated. You will also learn how to identify situations that may warrant overriding a warning and those that do not, indicate key questions to ask yourself before ignoring or over-riding a warning, and define alert fatigue and how to avoid it.

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Alerts, Warnings, and AI

Electronic Health Record (EHR) CME

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