Real-Time Analytics Monitoring Platform: Usable AI in Action
Tuesday, March 4, 2025 12:45 PM to 1:45 PM · 1 hr. (US/Pacific)
Venetian | Level 5 | Palazzo J
General Education
Data and Information
Information
Use of AI tools in healthcare has been accelerating, with growing trust in results produced and delivered by such tools. RAMP, one such tool already in action, focuses on delivering actionable, verifiable and explainable machine learning, integrating it as a decision support tool into clinical workflow to improve insights into patient health trends and facilitate faster delivery of necessary care, improving patient outcomes. AI-driven predictive analytics models utilize complex real-time and historical patient data to provide healthcare professionals with actionable insights, and to alert care teams if the patient is in need of immediate attention.
Sub-Topic Category
Data Science
Target Audience
Chief Data OfficerClinical InformaticistData Scientist
Level
Intermediate
CEU Type
ACHECAHIMSCMECNECPDHTSCPHIMSPMI/PDU
Contact Hours
1.00
Format
60-Minute Case Study
Learning Objective #1
Develop a technology stack and clinical workflow to integrate machine learning models into patient care to improve outcomes
Learning Objective #2
Identify key factors in establishing clinician trust in AI/machine learning models
Learning Objective #3
Design strategies to monitor machine learning model performance and downstream outcomes
Learning Objective #4
Create clinical guidelines in collaboration with clinicians to govern the interpretation and use of predictive models
Session #
32
