Research Article
Enhancing the Early Warning Score System Using Data Confidence
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@INPROCEEDINGS{10.1007/978-3-319-58877-3_12, author={Maximilian G\o{}tzinger and Nima Taherinejad and Amir Rahmani and Pasi Liljeberg and Axel Jantsch and Hannu Tenhunen}, title={Enhancing the Early Warning Score System Using Data Confidence}, proceedings={Wireless Mobile Communication and Healthcare. 6th International Conference, MobiHealth 2016, Milan, Italy, November 14-16, 2016, Proceedings}, proceedings_a={MOBIHEALTH}, year={2017}, month={6}, keywords={Early Warning Score Self-awareness Data confidence Consistency Plausibility Hierarchical agent-based system}, doi={10.1007/978-3-319-58877-3_12} }- Maximilian Götzinger
Nima Taherinejad
Amir Rahmani
Pasi Liljeberg
Axel Jantsch
Hannu Tenhunen
Year: 2017
Enhancing the Early Warning Score System Using Data Confidence
MOBIHEALTH
Springer
DOI: 10.1007/978-3-319-58877-3_12
Abstract
Early Warning Score (EWS) systems are utilized in hospitals by health-care professionals to interpret vital signals of patients. These scores are used to measure and predict amelioration or deterioration of patients’ health status to intervene in an appropriate manner when needed. Based on an earlier work presenting an automated Internet-of-Things based EWS system, we propose an architecture to analyze and enhance data reliability and consistency. In particular, we present a hierarchical agent-based data confidence evaluation system to detect erroneous or irrelevant vital signal measurements. In our extensive experiments, we demonstrate how our system offers a more robust EWS monitoring system.
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