Near-Miss Detection in Nursing: Rules and Semantics

  • Mikhail Simonov
  • Flavia Mazzitelli
Part of the Annals of Information Systems book series (AOIS, volume 11)


Nursing science deals with human-to-human interaction delivering care service, showing several peculiarities compared with other life science domains. Semantic technologies can be applied to clinical nursing, where the risk management forms a particular application class. Bone marrow transplantation is a specific sub-domain in which nursing process lacks the quality of service’s predictability at run time, requiring error detection before their happening and semantic technologies complementing best nursing strategies. The intelligent mix of technologies delivering proactive feedback to human actors in a natural way is a challenge. We investigate on possible risk control measures in the above-said nursing, suggesting a combination of ICT and knowledge technologies.


Fuzzy Rule Tacit Knowledge Knowledge Technology Patient Room Event Chain 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



Some of the achievements described in the chapter are inherited from Eureka co-funded projects HPPC/SEA, IKF, and FP7 project DOC@HAND. The work described in this chapter draws upon the contributions of many people, to whom the authors are indebted. Of course authors are solely responsible for any possible mistakes.


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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.ISMBTurinItaly
  2. 2.Facoltà di Medicina e chirurgiaUniversità di TorinoTurinItaly

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