Using Kafka-Powered AI Models to Predict and Prevent Sepsis at City of Hope

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This post details City of Hope's implementation of a Kafka-powered AI system for sepsis prediction and prevention. It highlights the use of real-time data streams from Epic EHR, processed through Kafka topics (vitals, lab results, ADT, etc.) and microservices, to feed AI models. The system ensures timely predictions by bypassing traditional batch processing, with predictions fed back into Epic to trigger clinical workflows. Confluent Cloud on Azure is utilized for its scalability, reliability, and observability, enabling quick identification and resolution of data anomalies. The immutable log feature of Kafka is leveraged for uninterrupted processing during model crashes.