Enabling the integration of clinical event and physiological data for real-time and retrospective analysis

Abstract

There is a growing trend of developing advanced clinical decision support systems that analyze physiological data streams for early detection of a variety of clinical diagnoses. This paper presents prototype architecture for both a real-time mobile clinical event data capture application and an Artemis-based replay system for retrospective analysis and validation of physiological data analytics. These two components provide important information for improving the ability of clinical decision support systems and patient monitoring algorithms to detect and adjust for artifacts caused by clinical events. A description of the prototypes, as well as results from initial prototype testing is provided. Although the sample size is small for the initial testing, significant information with respect to design principles and infrastructure needs were uncovered. Future research directions are identified to improve the mobile application through increased security, robustness, further integration into data mining analysis, and future clinical decision support algorithms.