Bennett Lab for Clinical Decision Making
We focus on clinical decision-making, particularly in high-risk environments such as intensive care units, and on the development and implementation of informatics and data science methods and tools to improve outcomes.
Collaborations and Tools
- Design and develop novel computational models, tools, and interfaces
- Build tools into real-time clinical decision support systems
- Partner with health systems to deploy tools and rigorously evaluate their impact
Work We Do
Current projects include:
- Development and validation of novel data-driven pediatric sepsis criteria applicable globally, including both low- and high-resource environments.
- Tracking and testing trajectories of pediatric COVID-19 hospitalization rates and severity distribution as SARS-CoV-2 variants emerge.
- Development and validation of multiple tools to support clinical decisions for children and adults with traumatic brain injury (TBI). These include tools to predict the need for intracranial pressure monitoring, tools based on dynamical systems modeling to noninvasively estimate ICP, and tools to estimate features of cerebral autoregulation.
- Development and validation of long COVID phenotypes and implementation of tools to predict long COVID using EHR data.
- Prospective validation of tools to predict serious bacterial infection at the time of pediatric ICU admission.
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