Advertisement

Rethinking Patient Consent in the Era of Artificial Intelligence and Big Data

      Electronic data allow health care workers and industry to analyze large data sets for population health and to develop artificial intelligence (AI) tools. Researchers may find patterns in the data to prevent disease, understand disease risk and cause, improve diagnosis, develop new treatments, improve patient safety, and evaluate health care policy. These new uses of massive amounts of patient data often result in retrospective data mining for purposes not anticipated when patients consented to allow their data to be used [
      • Balthazar P.
      • Harri P.
      • Prater A.
      • Safdar N.M.
      Protecting your patients’ interests in the era of big data, artificial intelligence, and predictive analytics.
      ].
      To read this article in full you will need to make a payment
      ACR Member Login
      ACR Members, access to JACR is a member benefit. Use your ACR credentials to access all JACR articles and features.
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect

      References

        • Balthazar P.
        • Harri P.
        • Prater A.
        • Safdar N.M.
        Protecting your patients’ interests in the era of big data, artificial intelligence, and predictive analytics.
        J Am Coll Radiol. 2018; 15: 580-586
        • Padmanabhan P.
        The new innovation model: monetizing healthcare data. CIO. August 20, 2019.
        (Available at:)
        • Coombes A.
        • Lehmann O.
        Reply to procedure for consent still leaves much to be desired.
        BMJ. 2000; 321: 111
        • Ozhan M.O.
        • Suzer M.A.
        • Comak I.
        • et al.
        Do the patients read the informed consent?.
        Balkan Med J. 2014; 31: 132-136
        • Manta C.J.
        • Ortiz J.
        • Moulton B.W.
        • Sonnad S.S.
        From the patient perspective, consent forms fall short of providing information to guide decision making.
        J Patient Saf. 2016; (Available at:): 10
        • Geis J.R.
        • Brady A.P.
        • Wu C.C.
        • et al.
        Ethics of artificial intelligence in radiology: summary of the Joint European and North American Multisociety Statement.
        J Am Coll Radiol. 2019; 16: 1516-1521
        • Moore S.M.
        • Maffitt D.R.
        • Smith K.E.
        • et al.
        De-identification of medical images with retention of scientific research value.
        Radiographics. 2015; 35: 727-735
        • Chen J.J.
        • Juluru K.
        • Morgan T.
        • Moffitt R.
        • Siddiqui K.M.
        • Siegel E.L.
        Implications of surface-rendered facial CT images in patient privacy.
        AJR Am J Roentgenol. 2014; 202: 1267-1271
        • Prior F.W.
        • Brunsden B.
        • Hildebolt C.
        • et al.
        Facial recognition from volume-rendered magnetic resonance imaging data.
        IEEE Trans Inf Technol Biomed. 2009; 13: 5-9
        • Schwartz C.G.
        • Kremers W.K.
        • Therneaus T.M.
        • et al.
        Identification of anonymous MRI research participants with face-recognition software.
        N Engl J Med. 2019; 381: 1684-1686
        • Neavyn M.
        • Murphy C.
        Coming to a consensus on informed consent for case reports.
        J Med Toxicol. 2014; 10: 337-339
        • Retraction Watch
        Authors couldn’t find a patient to give consent for case report. Then the patient found the report.
        (Available at:)
        • Jaremko J.L.
        • Azar M.
        • Bromwich R.
        • et al.
        Canadian Association of Radiologists white paper on ethical and legal issues related to artificial intelligence in radiology.
        Can Assoc Radiol J. 2019; : 107-118
        • Wakabayashi D.
        Google and the University of Chicago are sued over data sharing.
        The New York Times. June 26, 2019; (Available at:)
        • Stoller D.R.
        Google, University of Chicago face revamped health privacy suit.
        Bloomberg Law. October 3, 2019; (Available at:)
        • Barry M.J.
        • Edgman-Levitan S.
        Shared decision making—the pinnacle of patient-centered care.
        N Engl J Med. 2012; 366: 780-781
        • Ploug T.
        • Holm S.
        Meta consent—a flexible solution to the problem of secondary use of health data.
        Bioethics. 2016; 30: 721-732
        • Budin-Ljosne I.
        • Teare H.J.A.
        • Beck S.
        • et al.
        Dynamic consent: a potential solution to some of the challenges of modern biomedical research.
        BMC Med Ethics. 2017; 18: 4
        • Smith A.
        U.S. smartphone use in 2015.
        (Available at:)
        • US Department of Health and Human Services
        Office of Disease Prevention and Health Promotion. Health literacy online: a guide for simplifying the user experience.
        (Available at:)
        https://health.gov/healthliteracyonline/
        Date accessed: August 18, 2020