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ReportFlow: an application for EEG visualization and reporting using cloud platform

BACKGROUND: The cloud is a promising resource for data sharing and computing. It can optimize several legacy processes involving different units of a company or more companies. Recently, cloud technology applications are spreading out in the healthcare setting as well, allowing to cut down costs for...

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Detalles Bibliográficos
Autores principales: Bertuccio, S., Tardiolo, G., Giambò, F. M., Giuffrè, G., Muratore, R., Settimo, C., Raffa, A., Rigano, S., Bramanti, A., Muscarà, N., De Cola, M. C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7789295/
https://www.ncbi.nlm.nih.gov/pubmed/33407445
http://dx.doi.org/10.1186/s12911-020-01369-7
Descripción
Sumario:BACKGROUND: The cloud is a promising resource for data sharing and computing. It can optimize several legacy processes involving different units of a company or more companies. Recently, cloud technology applications are spreading out in the healthcare setting as well, allowing to cut down costs for physical infrastructures and staff movements. In a public environment the main challenge is to guarantee the patients’ data protection. We describe a cloud-based system, named ReportFlow, developed with the aim to improve the process of reporting and delivering electroencephalograms. METHODS: We illustrate the functioning of this application through a use-case scenario occurring in an Italian hospital, and describe the corresponding key encryption and key management used for data security guarantee. We used the X(2) test or the unpaired Student t test to perform pre-post comparisons of some indexes, in order to evaluate significant changes after the application of ReportFlow. RESULTS: The results obtained through the use of ReportFlow show a reduction of the time for exam reporting (t = 19.94; p < 0.001) and for its delivering (t = 14.95; p < 0.001), as well as an increase of the number of neurophysiologic examinations performed (about 20%), guaranteeing data integrity and security. Moreover, 68% of exam reports were delivered completely digitally. CONCLUSIONS: The application resulted to be an optimal solution to optimize the legacy process adopted in this scenario. The comparative pre-post analysis showed promising preliminary results of performance. Future directions will be the creation and release of certificates automatically.