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Published in: Journal of Medical Systems 1/2017

01-01-2017 | Systems-Level Quality Improvement

Preventable Medical Errors Driven Modeling of Medical Best Practice Guidance Systems

Authors: Andrew Y.-Z. Ou, Yu Jiang, Po-Liang Wu, Lui Sha, Richard B. Berlin Jr

Published in: Journal of Medical Systems | Issue 1/2017

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Abstract

In a medical environment such as Intensive Care Unit, there are many possible reasons to cause errors, and one important reason is the effect of human intellectual tasks. When designing an interactive healthcare system such as medical Cyber-Physical-Human Systems (CPHSystems), it is important to consider whether the system design can mitigate the errors caused by these tasks or not. In this paper, we first introduce five categories of generic intellectual tasks of humans, where tasks among each category may lead to potential medical errors. Then, we present an integrated modeling framework to model a medical CPHSystem and use UPPAAL as the foundation to integrate and verify the whole medical CPHSystem design models. With a verified and comprehensive model capturing the human intellectual tasks effects, we can design a more accurate and acceptable system. We use a cardiac arrest resuscitation guidance and navigation system (CAR-GNSystem) for such medical CPHSystem modeling. Experimental results show that the CPHSystem models help determine system design flaws and can mitigate the potential medical errors caused by the human intellectual tasks.
Footnotes
1
This paper is an extension of our previously published 6 pages conference paper on the 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2016).
 
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Metadata
Title
Preventable Medical Errors Driven Modeling of Medical Best Practice Guidance Systems
Authors
Andrew Y.-Z. Ou
Yu Jiang
Po-Liang Wu
Lui Sha
Richard B. Berlin Jr
Publication date
01-01-2017
Publisher
Springer US
Published in
Journal of Medical Systems / Issue 1/2017
Print ISSN: 0148-5598
Electronic ISSN: 1573-689X
DOI
https://doi.org/10.1007/s10916-016-0614-2

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