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Avoiding Hazards - What Can Health Care Learn from Aviation?

Olli Sjöblom, Juho Heimonen, Lotta Kauhanen, Veronika Laippala, Heljä Lundgrén-Laine, Laura-Maria Murtola, Tapio Salakoski, Sanna Salanterä, Avoiding Hazards - What Can Health Care Learn from Aviation?. In: Kristina Eriksson-Backa, Annika Luoma, Erica Krook (Eds.), Exploring the Abyss of Inequalities - Proceedings of the 4th International Conference on Well-Being in the Information Society, Communications in Computer and Information Science 313, 119–127, Springer, 2012.

Abstract:

Effective methods are needed to identify and analyze risks to improve patient safety. Analysing patient records and learning from “touch and go”- situations is one possible way to prevent hazardous conditions. The eventuality for the incident or accident occurring may be markedly reduced in case the risks can be efficiently diagnosed. Through this outlook, flight safety has been successfully improved during decades. Aviation and health care share many important points and similarities, thus the methods for improving safety could be transferred between the domains. In this paper, text mining and especially clustering is applied to identify lethal trend in both patient records and aviation for comparing and evaluating these trends in the two fields.

BibTeX entry:

@INPROCEEDINGS{inpSjHeKaLaLuMuSaSa12a,
  title = {Avoiding Hazards - What Can Health Care Learn from Aviation?},
  booktitle = {Exploring the Abyss of Inequalities - Proceedings of the 4th International Conference on Well-Being in the Information Society},
  author = {Sjöblom, Olli and Heimonen, Juho and Kauhanen, Lotta and Laippala, Veronika and Lundgrén-Laine, Heljä and Murtola, Laura-Maria and Salakoski, Tapio and Salanterä, Sanna},
  volume = {313},
  series = {Communications in Computer and Information Science},
  editor = {Eriksson-Backa, Kristina and Luoma, Annika and Krook, Erica},
  publisher = {Springer},
  pages = {119–127},
  year = {2012},
  keywords = {health care, aviation safety, text mining, clustering},
}

Belongs to TUCS Research Unit(s): Turku BioNLP Group, UTU Information Systems Science (ISS)

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