WEBINAR | Saving Lives and Reducing Stress in the ICU at Houston Methodist: Predicting the future can help!

Faisal Masud, MD, FCCP, FCCM, Houston Methodist Chair in Anesthesiology & Critical Care and Medical Director, Center for Critical Care, Houston Methodist Hospital presents the Cardiac Arrest Prediction Model (CAP-M), an Augmented Intelligence (AI) tool.

An in-hospital cardiac arrest (IHCA) code blue affects nearly 290,000 hospitalized patients each year in the United States and is associated with poor survival and a high risk of neurological disability among survivors. Survival rates for IHCA have plateaued in recent years, with a mean survival rate of approximately 25%. That means 3 out of 4 will not make it.

What if we could predict In-Hospital Cardiac Arrest (IHCA) in an ICU patient? That is the question the Houston Methodist team asked themselves when they started their journey in developing the Cardiac Arrest Prediction Model (CAP-M). Critical Care patients are the most monitored patients in hospitals so this represents an opportunity to utilize the information to save lives, improve outcomes and even reduce stress in the ICUs.

Dr. Masud discusses their goals, methodologies, and the progress made in developing a model that promises to be a key Augmented Intelligence (AI) tool that will play an important role in keeping the promise of delivering world class critical care at Houston Methodist through innovative thinking.