Skip to main content
SHARE
Publication

Advanced Health Information Technology Analytic Framework and Application to Hazard Detection

Publication Type
Conference Paper
Book Title
2020 IEEE International Conference on Big Data (Big Data)
Publication Date
Page Numbers
1 to 4
Issue
2020 IEEE
Conference Name
Big Data Tools, Methods, and Use Cases for Innovative Scientific Discovery (BTSD) 2020
Conference Location
Atlanta, Georgia, United States of America
Conference Sponsor
IEEE
Conference Date
-

Health Information Technology (HIT) aims to improve healthcare outcomes by organizing and analyzing various health-related data. With data accumulating at a staggering rate, the importance of real-time analytics has been increasing dramatically, shifting the focus of informatics from batch processing to streaming analytics. HIT is also facing unprecedented challenges in adapting to this new requirement and leveraging advanced IT technologies. This paper introduces a HIT data and compute platform that supports multi-granularity real-time analytics from heterogeneous data sources. The paper first identifies functional requirements and proposes a framework that satisfies the requirements using state-of-the-art big data technologies including Apache Kafka, Spark Structured Streaming Engine, and Delta Lake. To demonstrate its capability to support data analytics in multiple time granularities analytics, a statistical process control-based hazard detection algorithm has been implemented on top of the framework to detect unexpected hazards from order cancellation data of the Department of US Veterans Affairs (VA) in near real-time.