A fuzzy ELECTRE structure methodology to assess big data maturity in healthcare SMEs

Alejandro Peña, Isis Bonet, Christian Lochmuller, Marta S. Tabares, Carlos C. Piedrahita, Carmen C. Sánchez, Lillyana María Giraldo Marín, Mario Góngora, Francisco Chiclana

Resultado de la investigación: Contribución a una revistaArtículoInvestigaciónrevisión exhaustiva

Resumen

Advances in technology and an increase in the amount and complexity of data that are generated in healthcare have led to an indispensable revolution in this sector related to big data. Analytics of information based on multimodal clinical data sources requires big data projects. When starting big data projects in the healthcare sector, it is often necessary to assess the maturity of an organization with respect to big data, i.e., its capacity in managing big data. The assessment of the maturity of an organization requires multicriteria decision making as there is no single criterion or dimension that defines the maturity level regarding big data but an entire set of them. Based on the ISO 15504, this article proposes a fuzzy ELECTRE structure methodology to assess the maturity level of small- and medium-sized enterprises in the healthcare sector. The obtained experimental results provide evidence that this methodology helps to determine and compare maturity levels in big data management of organizations or the evolution of maturity over time. This is also useful in terms of diagnosing the readiness of an organization before starting to implement big data initiatives or technologies.

Idioma originalInglés
PublicaciónSoft Computing
DOI
EstadoAceptada/en prensa - 1 ene 2018

Huella dactilar

Small and Medium-sized Enterprises
Healthcare
Methodology
Sector
Big data
Multicriteria Decision-making
Information management
Data Management
Decision making
Entire
Necessary

Palabras clave

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    Peña, Alejandro ; Bonet, Isis ; Lochmuller, Christian ; Tabares, Marta S. ; Piedrahita, Carlos C. ; Sánchez, Carmen C. ; Giraldo Marín, Lillyana María ; Góngora, Mario ; Chiclana, Francisco. / A fuzzy ELECTRE structure methodology to assess big data maturity in healthcare SMEs. En: Soft Computing. 2018.
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    abstract = "Advances in technology and an increase in the amount and complexity of data that are generated in healthcare have led to an indispensable revolution in this sector related to big data. Analytics of information based on multimodal clinical data sources requires big data projects. When starting big data projects in the healthcare sector, it is often necessary to assess the maturity of an organization with respect to big data, i.e., its capacity in managing big data. The assessment of the maturity of an organization requires multicriteria decision making as there is no single criterion or dimension that defines the maturity level regarding big data but an entire set of them. Based on the ISO 15504, this article proposes a fuzzy ELECTRE structure methodology to assess the maturity level of small- and medium-sized enterprises in the healthcare sector. The obtained experimental results provide evidence that this methodology helps to determine and compare maturity levels in big data management of organizations or the evolution of maturity over time. This is also useful in terms of diagnosing the readiness of an organization before starting to implement big data initiatives or technologies.",
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    A fuzzy ELECTRE structure methodology to assess big data maturity in healthcare SMEs. / Peña, Alejandro; Bonet, Isis; Lochmuller, Christian; Tabares, Marta S.; Piedrahita, Carlos C.; Sánchez, Carmen C.; Giraldo Marín, Lillyana María; Góngora, Mario; Chiclana, Francisco.

    En: Soft Computing, 01.01.2018.

    Resultado de la investigación: Contribución a una revistaArtículoInvestigaciónrevisión exhaustiva

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    AU - Bonet, Isis

    AU - Lochmuller, Christian

    AU - Tabares, Marta S.

    AU - Piedrahita, Carlos C.

    AU - Sánchez, Carmen C.

    AU - Giraldo Marín, Lillyana María

    AU - Góngora, Mario

    AU - Chiclana, Francisco

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    N2 - Advances in technology and an increase in the amount and complexity of data that are generated in healthcare have led to an indispensable revolution in this sector related to big data. Analytics of information based on multimodal clinical data sources requires big data projects. When starting big data projects in the healthcare sector, it is often necessary to assess the maturity of an organization with respect to big data, i.e., its capacity in managing big data. The assessment of the maturity of an organization requires multicriteria decision making as there is no single criterion or dimension that defines the maturity level regarding big data but an entire set of them. Based on the ISO 15504, this article proposes a fuzzy ELECTRE structure methodology to assess the maturity level of small- and medium-sized enterprises in the healthcare sector. The obtained experimental results provide evidence that this methodology helps to determine and compare maturity levels in big data management of organizations or the evolution of maturity over time. This is also useful in terms of diagnosing the readiness of an organization before starting to implement big data initiatives or technologies.

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