How integrating AI and clinical decision support systems can help in the ER

Deployment of artificial intelligence for point-of-care clinical decision support is in its nascency. Despite the media attention and proliferation of AI studies, translation to clinical practice is rare. Little evidence exists on best practices for deployment, particularly in emergency medicine.

Emergency medicine serves as the frontline of healthcare and the integration of AI and clinical decision support at this critical care point has the potential to revolutionize the way care is delivered, affecting numerous downstream processes, said Andrew Taylor, associate professor of emergency medicine, director of emergency department clinical informatics and associate director of info.

Taylor will be speaking on this subject at the HIMSS24 Global Conference & Exhibition in an educational session titled "Deploying Artificial Intelligence for Clinical Decision Support in Emergency Medicine."

"In the ED, where quick and accurate decision-making is critical, AI-CDS tools can significantly streamline processes, improve patient outcomes and optimize the use of resources," he explained. "However, this is a complex environment with many variables – from patient demographics to symptom presentation. Therefore, the deployment of AI tools must be carried out with meticulous planning and sensitivity to the unique stressors and workflow of the ED.

"Throughout this session at HIMSS24, we will explore various applications of AI-CDS in the ED including triage, patient disposition, diagnosis and risk assessment," he continued. "We will also maintain a focus on a guiding philosophy: AI in medicine must grow as an organic extension of human empathy and care, not as a detached technological force."