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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...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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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 |
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author | 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. |
author_facet | 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. |
author_sort | Bertuccio, S. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7789295 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-77892952021-01-07 ReportFlow: an application for EEG visualization and reporting using cloud platform 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. BMC Med Inform Decis Mak Technical Advance 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. BioMed Central 2021-01-06 /pmc/articles/PMC7789295/ /pubmed/33407445 http://dx.doi.org/10.1186/s12911-020-01369-7 Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Technical Advance 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. ReportFlow: an application for EEG visualization and reporting using cloud platform |
title | ReportFlow: an application for EEG visualization and reporting using cloud platform |
title_full | ReportFlow: an application for EEG visualization and reporting using cloud platform |
title_fullStr | ReportFlow: an application for EEG visualization and reporting using cloud platform |
title_full_unstemmed | ReportFlow: an application for EEG visualization and reporting using cloud platform |
title_short | ReportFlow: an application for EEG visualization and reporting using cloud platform |
title_sort | reportflow: an application for eeg visualization and reporting using cloud platform |
topic | Technical Advance |
url | 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 |
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