At Loma Linda University Children's Hospital, we have identified a large number of historical congenital heart defect patients whom have not been consistently tracked and may require monitoring, cardiological intervention or surgical repair. Our challenge is to correctly classify all of these patients, identify their providers, determine their followup needs and contact them. In this paper, we will present a solution which combines data mining and analytics with a new EMR workflow and supervised learning to create a system for managing these patients.

Learning Objective 1: After participating in this session, the learner should be better able to:

● Understand the current challenges with monitoring and following up on congenital heart defect patient
● Learn how to use analytics to identify and classify a complex patient cohort
● Understand how a good workflow can be used to monitor and track an at-risk patient population


James McGlothlin (Presenter)
Fusion Consulting Inc

Evan Crawford, Fusion Consulting Inc
ilija Stojic, Fusion Consulting Inc
Timothy Martens, Loma Linda University Health System

Presentation Materials: