In this article we adopt the Complex Event Processing (CEP) approach for the management of information related to patients status in the context of RFID-enabled hospitals. Our main objective is to support clinical risk management by combining data from different RFID-based appliances used to monitor patient identification, patient tracking and drugs administration control. We propose a distributed system that directly embodies essential CEP principles such as event abstraction, event aggregation and event transformation to offer a hierarchical and distributed architecture where CEP capabilities are supplied by processing nodes. Events flowing through the system levels are progressively aggregated and refined in order to produce a global scoped information. In addition, we introduce specific events patterns aimed at identifying possible dangerous patient conditions.
Zappia, I., Ciofi, L., Paganelli, F., Iadanza, E., Gherardelli, M., Giuli, D. (2014). A distributed approach to Complex Event Processing in RFID-enabled hospitals. In 2014 Euro Med Telco Conference (EMTC) (pp.1-6). New York : Institute of Electrical and Electronics Engineers Inc. [10.1109/EMTC.2014.6996628].
A distributed approach to Complex Event Processing in RFID-enabled hospitals
IADANZA, ERNESTO;
2014-01-01
Abstract
In this article we adopt the Complex Event Processing (CEP) approach for the management of information related to patients status in the context of RFID-enabled hospitals. Our main objective is to support clinical risk management by combining data from different RFID-based appliances used to monitor patient identification, patient tracking and drugs administration control. We propose a distributed system that directly embodies essential CEP principles such as event abstraction, event aggregation and event transformation to offer a hierarchical and distributed architecture where CEP capabilities are supplied by processing nodes. Events flowing through the system levels are progressively aggregated and refined in order to produce a global scoped information. In addition, we introduce specific events patterns aimed at identifying possible dangerous patient conditions.
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https://hdl.handle.net/11365/1215420