Trends and inEquities Through Real-time Injury Surveillance (TETRIS)

We will use a hybrid implementation-effectiveness design to establish a novel multi-center ED data network for near real-time injury surveillance to identify injury patterns. We will employ an innovative application of AI data mining technology (NLP) in the narrative elements across multiple existing PECARN data sources: the PECARN data registry and PECARN site-level EHR data. PECARN’s geographic distribution and robust data and research infrastructure of the PECARN Data Coordinating Center (DCC) are essential for the successful creation of this surveillance system. Our long-term goal is to track and prevent injuries more efficiently. Our overall objectives in this application, which are the next steps towards our long-term goal, are to establish and test the performance of a novel injury surveillance data network.