Using cluster analysis to identify weak signals of lethal trends in aviation and healthcare documentation. (1st January 2013)

• Record Type: Journal Article
• Authors: Sjöblom, Olli; Murtola, Laura-Maria; Heimonen, Juho; Kauhanen, Lotta; Laippala, Veronika; Lundgren-Laine, Heljä; Salakoski, Tapio; Salanterä, Sanna
• Is Part Of: International journal of networking and virtual organisations. Volume 13:Number 1(2013)
• Page Start: 66
• Page End: 80
• Publication Date: 2013-01-01
• Subjects: aviation safety -- patient safety -- lethal trend -- hazardous event -- healthcare -- aviation -- risk management -- text mining -- clustering -- weak signal; Computer networks -- Periodicals; Information networks -- Periodicals; Virtual corporations -- Periodicals; Electronic commerce -- Periodicals; Management information systems -- Periodicals; Management -- Data processing -- Periodicals; 004.65
• Languages: English
• ISSNs: 1470-9503

Abstract

Effective methods are needed to identify and manage risks in both aviation and healthcare to improve safety. Analysing safety related records and learning from 'touch and go' situations is one possible way of preventing hazardous conditions from occurring in both aviation and healthcare. The eventuality of an incident or an accident may markedly be reduced if the risks connected to it are efficiently diagnosed. With the aid of this outlook, flight safety has witnessed decades of successful improvement. Since aviation and healthcare share similarities, the methods for improving safety could be transferable between the domains. This paper explores how a data mining technique used in aviation to identify the weak signals of lethal trends can be applied to healthcare documentation.