Implementing a Real-time Complex Event Stream Processing System to Help Identify Potential Participants in Clinical and Translational Research Studies
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Updated: Jun 4, 2026

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020
Susan Weber1, Henry J Lowe, Sanjay Malunjkar
1Center for Clinical Informatics.
Abstract:
Event Stream Processing is a computational approach to the problem of how to infer the occurrence of an event from a data stream in real time without reference to a database. This paper describes how we implemented this technology on the STRIDE platform to address the challenge of real time notification of patients presenting in the Emergency Department (ED) who potentially meet eligibility criteria for a clinical study. The system was evaluated against a standalone legacy alerting system and found to perform adequately. While our initial use of this technology was focused on relatively simple alerts, the system is extensible and has the potential to provide enterprise-level research alerting services supporting more complex scenarios.
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