IRIS - Institutional Research Information System
IRIS è il sistema di gestione integrata dei dati della ricerca adottato dalla Luiss Guido Carli. Il Catalogo dei prodotti della ricerca della Luiss raccoglie e rende disponibile, dove possibile nel rispetto del diritto d'autore, la produzione scientifica dei docenti e ricercatori dell'Ateneo. Il Catalogo alimenta inoltre i siti docenti del MIUR.
EnglishEvaluating 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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| Titolo: | A fuzzy taxonomy for e-Health projects | |
| Autori: | ||
| Data di pubblicazione: | 2012 | |
| Rivista: | ||
| Abstract: | 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. | |
| Handle: | http://hdl.handle.net/11385/38855 | |
| Appare nelle tipologie: | 01.1 - Articolo su rivista (Article) |
File in questo prodotto:
| File | Descrizione | Tipologia | Licenza | |
|---|---|---|---|---|
| JMLC2012author_copy.pdf | Documento in Pre-print | DRM non definito | Administrator | |
| abstract.pdf | Abstract | DRM non definito | Administrator |
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