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ReportFlow: an application for EEG visualization and reporting using cloud platform.
- Source :
-
BMC medical informatics and decision making [BMC Med Inform Decis Mak] 2021 Jan 06; Vol. 21 (1), pp. 7. Date of Electronic Publication: 2021 Jan 06. - Publication Year :
- 2021
-
Abstract
- 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.<br />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 <superscript>2</superscript> 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.<br />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.<br />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.
Details
- Language :
- English
- ISSN :
- 1472-6947
- Volume :
- 21
- Issue :
- 1
- Database :
- MEDLINE
- Journal :
- BMC medical informatics and decision making
- Publication Type :
- Academic Journal
- Accession number :
- 33407445
- Full Text :
- https://doi.org/10.1186/s12911-020-01369-7