TY - UNPB
T1 - A review of Trusted Research Environments to support next generation capabilities based on interview analysis
AU - Kavianpour, Sanaz
AU - Sutherland, James
AU - Mansouri-Benssassi, Esma
AU - Coull, Natalie
AU - Jefferson, Emily
N1 - This project was supported by MRC and EPSRC [grant number MR/S010351/1] programme grant: InterdisciPlInary Collaboration for efficienT and effective Use of clinical images in big data health care RESearch: PICTURES [grant number MR/S010351/1]. This work was also supported by Health Data Research UK (HDR UK: 636000/ RA4624) which receives its funding from HDR UK Ltd (HDR-5012) funded by the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (Northern Ireland), British Heart Foundation (BHF) and the Wellcome Trust.
PY - 2021/9/20
Y1 - 2021/9/20
N2 - Background:A Trusted Research Environment (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 whilst protecting patient confidentially. 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 TRE operators, 20 of whom, in the UK and internationally, agreed to be interviewed remotely under a non-disclosure agreement and to complete a questionnaire about their TRE.Results:We observed many similar processes and standards which 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 well understood. However, we identified limitations in the security measures and capabilities of TREs to support “next-generation” requirements such as wider ranges of data types, the ability to develop artificial intelligence algorithms and software within the environment, the handling of big data, and timely import and export of data.Conclusions:We found a lack of software/automation tools to support the community and limited knowledge of how to meet next-generation requirements from the research community. Disclosure control for exporting artificial intelligence (AI) algorithms and software was found to be particularly challenging where there is a clear need for additional controls to support this capability within TREs.
AB - Background:A Trusted Research Environment (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 whilst protecting patient confidentially. 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 TRE operators, 20 of whom, in the UK and internationally, agreed to be interviewed remotely under a non-disclosure agreement and to complete a questionnaire about their TRE.Results:We observed many similar processes and standards which 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 well understood. However, we identified limitations in the security measures and capabilities of TREs to support “next-generation” requirements such as wider ranges of data types, the ability to develop artificial intelligence algorithms and software within the environment, the handling of big data, and timely import and export of data.Conclusions:We found a lack of software/automation tools to support the community and limited knowledge of how to meet next-generation requirements from the research community. Disclosure control for exporting artificial intelligence (AI) algorithms and software was found to be particularly challenging where there is a clear need for additional controls to support this capability within TREs.
M3 - Preprint
T3 - Journal of Medical Internet Research
BT - A review of Trusted Research Environments to support next generation capabilities based on interview analysis
ER -