This federal Project Grant award, provided by the National Institute of Child Health and Human Development (NICHD) under the Child Health and Human Development Extramural Research program (CFDA 93.865), aims to validate approaches for detecting and predicting pediatric prescribing errors. The award, valued at $642,859.00 and effective from July 1, 2025 to April 30, 2030, will support research at The Leland Stanford Junior University (Stanford University) to: Validate an algorithmic approach to detecting pediatric prescribing errors by comparing algorithmic detection to expert prescription review. Validate the use of electronic health record (EHR) metadata to measure team composition and interactions related to prescribing errors through comparative ethnographic research. Evaluate individual, team, and system context factors associated with prescribing errors at three children's hospitals, and develop a machine learning model to predict prescribing errors using EHR metadata. The overarching goal is to develop a transformational clinical decision support approach that incorporates relevant contextual factors to provide real-time feedback on high-risk prescriptions, thereby improving patient safety for vulnerable pediatric populations.
Mod # | Description | Reason For Modification | Federal Obligation (Click to sort descending) | Date (Click to sort ascending) |
|---|---|---|---|---|
| Not listed | $642.9k | 6/17/25 |