TY - JOUR
T1 - Next-generation capabilities in trusted research environments
T2 - interview study
AU - Kavianpour, Sanaz
AU - Sutherland, James
AU - Mansouri-Benssassi, Esma
AU - Coull, Natalie
AU - Jefferson, Emily
N1 - Publisher Copyright:
©Sanaz Kavianpour, James Sutherland, Esma Mansouri-Benssassi, Natalie Coull, Emily Jefferson
This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.
Data availability statement:
Not present.
PY - 2022/9/20
Y1 - 2022/9/20
N2 - BACKGROUND: A Trusted Research Environment (TRE; also known as a Safe Haven) is an environment supported by trained staff and agreed processes (principles and standards), providing access to data for research while protecting patient confidentiality. Accessing sensitive data without compromising the privacy and security of the data is a complex process.OBJECTIVE: This paper presents the security measures, administrative procedures, and technical approaches adopted by TREs.METHODS: We contacted 73 TRE operators, 22 (30%) of whom, in the United Kingdom and internationally, agreed to be interviewed remotely under a nondisclosure agreement and to complete a questionnaire about their TRE.RESULTS: We observed many similar processes and standards that TREs follow to adhere to the Seven Safes principles. The security processes and TRE capabilities for supporting observational studies using classical statistical methods were mature, and the requirements were well understood. However, we identified limitations in the security measures and capabilities of TREs to support "next-generation" requirements such as wide ranges of data types, ability to develop artificial intelligence algorithms and software within the environment, handling of big data, and timely import and export of data.CONCLUSIONS: We found a lack of software or other automation tools to support the community and limited knowledge of how to meet the next-generation requirements from the research community. Disclosure control for exporting artificial intelligence algorithms and software was found to be particularly challenging, and there is a clear need for additional controls to support this capability within TREs.
AB - BACKGROUND: A Trusted Research Environment (TRE; also known as a Safe Haven) is an environment supported by trained staff and agreed processes (principles and standards), providing access to data for research while protecting patient confidentiality. Accessing sensitive data without compromising the privacy and security of the data is a complex process.OBJECTIVE: This paper presents the security measures, administrative procedures, and technical approaches adopted by TREs.METHODS: We contacted 73 TRE operators, 22 (30%) of whom, in the United Kingdom and internationally, agreed to be interviewed remotely under a nondisclosure agreement and to complete a questionnaire about their TRE.RESULTS: We observed many similar processes and standards that TREs follow to adhere to the Seven Safes principles. The security processes and TRE capabilities for supporting observational studies using classical statistical methods were mature, and the requirements were well understood. However, we identified limitations in the security measures and capabilities of TREs to support "next-generation" requirements such as wide ranges of data types, ability to develop artificial intelligence algorithms and software within the environment, handling of big data, and timely import and export of data.CONCLUSIONS: We found a lack of software or other automation tools to support the community and limited knowledge of how to meet the next-generation requirements from the research community. Disclosure control for exporting artificial intelligence algorithms and software was found to be particularly challenging, and there is a clear need for additional controls to support this capability within TREs.
U2 - 10.2196/33720
DO - 10.2196/33720
M3 - Article
C2 - 36125859
SN - 1439-4456
VL - 24
JO - Journal of Medical Internet Research
JF - Journal of Medical Internet Research
IS - 9
M1 - e33720
ER -