Jaclyn manages the Innovations Team at Texas Children’s Hospital. Under her leadership, the team develops and deploys predictive analytics solutions and does custom application development. With experience spanning the vendor, consultant, and enterprise IT spaces, Jaclyn considers herself to be an “IT generalist” whose emphasis on People, Process, Technology, and Culture enables digital transformation across contexts. She has been with Texas Children’s for seven years; prior to her current role with Innovations, she worked on various strategic initiatives across the Business Intelligence, Epic, and Clinical Applications spaces. Jaclyn’s hobbies include backcountry camping, scuba diving, rock climbing, and experimenting in the kitchen.
A good predictive model alone won’t yield real-world outcomes. To achieve results, organizations must pair predictive models with effective interventions and delivery tools. In this session, representatives from Texas Children’s Hospital, the largest pediatric hospital in the U.S., will describe a framework for effective predictive model implementation in clinical practice, featuring the organization’s custom Pediatric Readmissions model. By accurately flagging 20 percent of patients as potential readmissions, Texas Children’s was able to apply early interventions and reduce potential readmissions by 5 percent.
Participants will learn:
- The value predictive models add to clinical decision making.
- The tools and interventions needed to maximize predictive models.
- How to effectively implement predictive models in clinical practice.