Virtual Symposium: Using AI in the Emergency Department for Accurate Patient Status Prediction

Healthcare providers managing front line emergencies face the decision on a daily, if not hourly basis, of whether to place a patient under observation or whether to admit them as an inpatient. Accuracy in making this determination is vital to patient care as well as the time spent on utilization reviews, denials of claims, and reimbursement rates. In this session, we will explore how organizations are using data analytics and machine learning to aid staff in determining the right course of action.

By viewing this on-demand session, you should be able to:

• Assess the organization’s current emergency room procedures and how they compare to leading practices aided by data analytics
• Identify integration points of machine learning into key decision-making areas to drive higher success rates for patients and the organization
• Outline key staffing skills needed to develop and implement computer-aided decision making designed to achieve more accurate patient status predictions

Quickly assessing and determining a patient’s status in the emergency room is vital to the success of the patient and the organization. Find out how data-driven decision making is enabling faster and more accurate predictions

Presented by:
Colleen Hall, Crowe