NIH Reporter #5F31HD114398-03

PreoP-SSI: Prediction and prevention of pediatric surgical site infections

The award funds a project to develop machine learning-based prediction models and a clinical decision support tool to prevent pediatric surgical site infections, improving patient care and reducing infection risks through evidence-based, individualized recommendations.

Description

This project aims to apply machine learning to generate prediction models using electronic health data to inform the design of a clinical decision support tool prototype that provides clinicians with precision pediatric infection risk estimations and prevention recommendations. The study leverages a large national pediatric surgical dataset to train, validate, and test algorithms, and applies human-centered design to create and test an EHR-embedded clinical decision support tool prototype for real-time, evidence-based SSI risk estimations and prevention guidance.

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