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Updated: Oct 21, 2025

A Data-Driven Approach to Quantifying Immune States in Sepsis
Published on: February 7, 2025
Confidence-weighted Testing as an Impactful Education Intervention within a Pediatric Sepsis Quality Improvement
Emma D Nathaniel1, Halden F Scott2, Beth Wathen3
1Section of Hospital Medicine, Department of Pediatrics, University of Colorado School of Medicine, Aurora, Colo.
Introduction:
Confidence-weighted testing assesses learners' beliefs about their knowledge and skills. As part of a hospital-wide quality improvement initiative to enhance care for pediatric patients with suspected sepsis, we developed a novel intervention using confidence-weighted testing to identify institutional areas of misinformation and knowledge gaps while also providing real-time feedback to individual learners.
Methods:
We developed pediatric sepsis eLearning modules incorporating confidence-weighted testing. We distributed them to nurses, advanced practitioners, and physicians in emergency departments and acute care/non-intensive care unit inpatient settings in our hospital system. We analyzed completion and response data over 2 years following module distribution. Our outcomes included completion, confidently held misinformation (CHM; when a learner answers a question confidently but incorrectly), struggle (when a learner repeatedly answers a question incorrectly or with low confidence), and mastery (when a learner initially answers a question correctly and confidently).
Results:
Eighty-three percent of assigned learners completed the modules (1,463/1,754). Although nurses had significantly more misinformation and struggled more than physicians and advanced practitioners, learners of all roles achieved 100% mastery as part of module completion. The greatest CHM and struggle were found in serum lactate interpretation's nuances and the hemodynamic shock states commonly seen in sepsis.
Conclusions:
Our novel application of confidence-weighted testing enhanced learning by correcting learners' misinformation. It also identified systems issues and institutional knowledge gaps as targets for future improvement.
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