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GEN-RWD Sandbox: bridging the gap between hospital data privacy and external research insights with distributed analytics.
Gottardelli, Benedetta; Gatta, Roberto; Nucciarelli, Leonardo; Tudor, Andrada Mihaela; Tavazzi, Erica; Vallati, Mauro; Orini, Stefania; Di Giorgi, Nicoletta; Damiani, Andrea.
Afiliación
  • Gottardelli B; Department of Diagnostic Imaging, Oncological Radiotherapy and Hematology, Università Cattolica del Sacro Cuore, Rome, Italy.
  • Gatta R; Department of Clinical and Experimental Sciences, Università degli Studi di Brescia, Brescia, Italy.
  • Nucciarelli L; Department of Diagnostic Imaging, Oncological Radiotherapy and Hematology, Università Cattolica del Sacro Cuore, Rome, Italy. leo.nucciarelli@gmail.com.
  • Tudor AM; Department of Diagnostic Imaging, Oncological Radiotherapy and Hematology, Università Cattolica del Sacro Cuore, Rome, Italy.
  • Tavazzi E; Department of Information Engineering, University of Padova, Padova, Italy.
  • Vallati M; School of Computing and Engineering, University of Huddersfield, Huddersfield, UK.
  • Orini S; Department of Clinical and Experimental Sciences, Università degli Studi di Brescia, Brescia, Italy.
  • Di Giorgi N; Alzheimer Operative Unit, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.
  • Damiani A; Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy.
BMC Med Inform Decis Mak ; 24(1): 170, 2024 Jun 17.
Article en En | MEDLINE | ID: mdl-38886772
ABSTRACT

BACKGROUND:

Artificial intelligence (AI) has become a pivotal tool in advancing contemporary personalised medicine, with the goal of tailoring treatments to individual patient conditions. This has heightened the demand for access to diverse data from clinical practice and daily life for research, posing challenges due to the sensitive nature of medical information, including genetics and health conditions. Regulations like the Health Insurance Portability and Accountability Act (HIPAA) in the U.S. and the General Data Protection Regulation (GDPR) in Europe aim to strike a balance between data security, privacy, and the imperative for access.

RESULTS:

We present the Gemelli Generator - Real World Data (GEN-RWD) Sandbox, a modular multi-agent platform designed for distributed analytics in healthcare. Its primary objective is to empower external researchers to leverage hospital data while upholding privacy and ownership, obviating the need for direct data sharing. Docker compatibility adds an extra layer of flexibility, and scalability is assured through modular design, facilitating combinations of Proxy and Processor modules with various graphical interfaces. Security and reliability are reinforced through components like Identity and Access Management (IAM) agent, and a Blockchain-based notarisation module. Certification processes verify the identities of information senders and receivers.

CONCLUSIONS:

The GEN-RWD Sandbox architecture achieves a good level of usability while ensuring a blend of flexibility, scalability, and security. Featuring a user-friendly graphical interface catering to diverse technical expertise, its external accessibility enables personnel outside the hospital to use the platform. Overall, the GEN-RWD Sandbox emerges as a comprehensive solution for healthcare distributed analytics, maintaining a delicate equilibrium between accessibility, scalability, and security.
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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Seguridad Computacional / Confidencialidad Límite: Humans Idioma: En Revista: BMC Med Inform Decis Mak Asunto de la revista: INFORMATICA MEDICA Año: 2024 Tipo del documento: Article País de afiliación: Italia

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Seguridad Computacional / Confidencialidad Límite: Humans Idioma: En Revista: BMC Med Inform Decis Mak Asunto de la revista: INFORMATICA MEDICA Año: 2024 Tipo del documento: Article País de afiliación: Italia