A fuzzy taxonomy for e-Health projects
D'Urso, Pierpaolo and De Giovanni, Livia and Spagnoletti, Paolo (2012) A fuzzy taxonomy for e-Health projects. International Journal of Machine Learning and Cybernetics p. 1-18. ISSN 1868-8071. (In Press)
Evaluating the impact of Information Technology (IT) projects represents a problematic task for policy and decision makers aiming to define roadmaps based on previous experiences. Especially in the healthcare sector IT can support a wide range of processes and it is difficult to analyze in a comparative way the benefits and results of e-Health practices in order to define strategies and to assign priorities to potential investments. A first step towards the definition of an evaluation framework to compare e-Health initiatives consists in the definition of clusters of homogeneous projects that can be further analyzed through multiple case studies. However imprecision and subjectivity affect the classification of e-Health projects that are focused on multiple aspects of the complex healthcare system scenario. In this paper we apply a method, based on advanced cluster techniques and fuzzy theories, for validating a project taxonomy in the e-Health sector. An empirical test of the method has been performed over a set of European good practices in order to define a taxonomy for classifying e-Health projects.
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|Research documents and activity classification:||Journal Articles > Articles > Articles published in or submitted to a Journal without IF refereed / of international relevance|
|Divisions:||Department of Political Science
Department of Business and Management > CeRSI (Information Systems Research Centre)
|Uncontrolled Keywords:||e-health, healthcare, fuzzy clustering, imprecise evaluation scales, soft taxonomy|
|MIUR Scientific Area:||Area 13 - Economics and Statistics > SECS-P/10 Business Organisation
Area 13 - Economics and Statistics > SECS-S/01 Statistics
|Deposited by:||Paolo Spagnoletti|
|Date Deposited:||02 Oct 2012 12:51|
|Last Modified:||22 Apr 2015 00:14|
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