This project creates the foundations for a patient safety learning laboratory focused on improving maternal health. Drawing on the team’s expertise in clinical informatics, human factors, systems engineering, simulation and healthcare, the team will create methods that address problem analysis, design, development, implementation, and evaluation for high impact projects focused on safety and quality. The proposed prototype project addresses postpartum hemorrhage, a complex healthcare prediction-alarm-response-intervention challenge. Postpartum hemorrhage risk prediction draws from data sources in the outpatient, admission intake, and inpatient settings. These data combined with machine learning methods are predictive of postpartum hemorrhage, but the challenges of combining data sources, deploying alarms, optimizing alarm timing and utility, and triggering deployment of effective care team interventions remain. This work will define optimal alarm methods, utility, timing, and presentation capped by simulation testing of alarm integration. The long-term goal is to reduce maternal morbidity and mortality from postpartum hemorrhage. The project lays the foundation of improved methods for alarm response processes that extend into all fields of healthcare and capitalize on ever improving predictive intelligence.
Funding: Jump ARCHES endowment through the Health Care Engineering Systems Center
This work is complemented by Dr. Wooldridge’s Faculty Fellowship position at OSF HealthCare, which is examining the usage of a digital health technology to support pregnant women.