Spaeder, Michael C.
Primary Appointment
Professor of Pediatrics, Pediatrics
Education
- MS, Statistics, George Washington University
- MD, Medicine, George Washington University School of Medicine
Contact Information
Email: ms7uw@Virginia.EDU
Research Interests
Predictive Analytics in the Pediatric Intensive Care Unit
Research Description
Children and infants in the Pediatric Intensive Care Unit (PICU) often deteriorate suddenly due to sub-acute potentially catastrophic illness. Standard around-the-clock bedside monitoring of physiologic parameters, which might give clues about incipient deterioration, often flies by unnoticed. To solve this problem of undetected changes, predictive analytics integrates these data to give clinicians early warning of events, allowing earlier, more effective intervention. The Center for Advanced Medical Analytics at UVA is a national leader is the creation and implementation of predictive modeling algorithms of clinical deterioration in critically ill patients. These algorithms often work through the analysis of the behavior of certain physiologic parameters (e.g. heart rate variability). Often coupled with data extracted from the electronic health record, individualized patient stability indices can be calculated, allowing for early identification of at-risk patients. Dr. Spaeder has developed predictive algorithms for sepsis and respiratory failure for infants and children in the PICU. These algorithms are now incorporated into the Continuous Monitoring of Event Trajectories (CoMET) predictive analytics software, which has been implemented in the UVA Health Children’s PICU since 2022. Dr. Spaeder continues to work on developing additional predictive algorithms for clinical deterioration as well as investigating the impact of CoMET on clinical outcomes in the PICU.