TY - JOUR
T1 - Management of Medico-Legal Risks in Digital Health Era: A Scoping Review
AU - Oliva, Antonio
AU - Grassi, S.
AU - Vetrugno, Giuseppe
AU - Rossi, Riccardo
AU - Della Morte, Gabriele
AU - Pinchi, V.
AU - Caputo, Matteo
PY - 2022
Y1 - 2022
N2 - Artificial intelligence needs big data to develop reliable predictions. Therefore, storing and processing health data is essential for the new diagnostic and decisional technologies but, at the same time, represents a risk for privacy protection. This scoping review is aimed at underlying the medico-legal and ethical implications of the main artificial intelligence applications to healthcare, also focusing on the issues of the COVID-19 era. Starting from a summary of the United States (US) and European Union (EU) regulatory frameworks, the current medico-legal and ethical challenges are discussed in general terms before focusing on the specific issues regarding informed consent, medical malpractice/cognitive biases, automation and interconnectedness of medical devices, diagnostic algorithms and telemedicine. We aim at underlying that education of physicians on the management of this (new) kind of clinical risks can enhance compliance with regulations and avoid legal risks for the healthcare professionals and institutions.
AB - Artificial intelligence needs big data to develop reliable predictions. Therefore, storing and processing health data is essential for the new diagnostic and decisional technologies but, at the same time, represents a risk for privacy protection. This scoping review is aimed at underlying the medico-legal and ethical implications of the main artificial intelligence applications to healthcare, also focusing on the issues of the COVID-19 era. Starting from a summary of the United States (US) and European Union (EU) regulatory frameworks, the current medico-legal and ethical challenges are discussed in general terms before focusing on the specific issues regarding informed consent, medical malpractice/cognitive biases, automation and interconnectedness of medical devices, diagnostic algorithms and telemedicine. We aim at underlying that education of physicians on the management of this (new) kind of clinical risks can enhance compliance with regulations and avoid legal risks for the healthcare professionals and institutions.
KW - COVID-19
KW - artificial intelligence
KW - big data
KW - privacy
KW - risk management
KW - COVID-19
KW - artificial intelligence
KW - big data
KW - privacy
KW - risk management
UR - https://publicatt.unicatt.it/handle/10807/201663
UR - https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85123422013&origin=inward
UR - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85123422013&origin=inward
U2 - 10.3389/fmed.2021.821756
DO - 10.3389/fmed.2021.821756
M3 - Article
SN - 2296-858X
VL - 2022
SP - 1
EP - 7
JO - Frontiers in Medicine
JF - Frontiers in Medicine
IS - 11
ER -