Artificial Intelligence and Healthcare Regulatory and Legal Concerns
DOI:
https://doi.org/10.30953/tmt.v6.252Keywords:
algorithm, artificial intelligence, Digital Information Security in Healthcare Act, regulatory requirements, softwareAbstract
We are in a stage of transition as artificial intelligence (AI) is increasingly being used in healthcare across the world. Transitions offer opportunities compounded with difficulties. It is universally accepted that regulations and the law can never keep up with the exponential growth of technology. This paper discusses liability issues when AI is deployed in healthcare. Ever-changing, futuristic, user friendly, uncomplicated regulatory requirements promoting compliance and adherence are needed. Regulators have to understand that software itself could be a software as a medical device (SaMD). Benefits of AI could be delayed if slow, expensive clinical trials are mandated. Regulations should distinguish between diagnostic errors, malfunction of technology, or errors due to initial use of inaccurate/inappropriate data as training data sets. The sharing of responsibility and accountability when implementation of an AI-based recommendation causes clinical problems is not clear. Legislation is necessary to allow apportionment of damages consequent to malfunction of an AI-enabled system. Product liability is ascribed to defective equipment and medical devices. However, Watson, the AI-enabled supercomputer, is treated as a consulting physician and not categorised as a product. In India, algorithms cannot be patented. There are no specific laws enacted to deal with AI in healthcare. DISHA or the Digital Information Security in Healthcare Act when implemented in India would hopefully cover some issues. Ultimately, the law is interpreted contextually and perceptions could be different among patients, clinicians and the legal system. This communication is to create the necessary awareness among all stakeholders.
Downloads
References
Chouffani RC. AI in healthcare: Beyond IBM Watson. TechTarget. 2017 Available from: http://media.techtarget.com/digitalguide/images/Misc/EA-Marketing/Eguides/AI-in-Healthcare.pdf [cited 18 January 2021].
Fomenko A, Lozano A. Artificial intelligence in neurosurgery. UTMJ 2019; 96: 19–21.
Amisha, Malik P, Pathania M, Rathaur VK. Overview of artificial intelligence in medicine. J Fam Med Prim Care 2019; 8: 2328–31. doi: 10.4103/jfmpc.jfmpc_440_19
Hedges L. The future of AI in healthcare. Software advice. 2020 Available from: https://www.softwareadvice.com/resources/future-of-ai-in-healthcare/ [cited 18 January 2021].
Buch VH, Ahmed I, Maruthappu M. Artificial intelligence in medicine: current trends and future possibilities. Br J Gen Pract 2018; 68: 143–4. doi: 10.3399/bjgp18X695213
Kelly CJ, Karthikesalingam A, Suleyman M, Corrado G, King D. Key challenges for delivering clinical impact with artificial intelligence. BMC Med 2019; 17: 1–9. doi: 10.1186/s12916-019-1426-2
AI Report. Artificial intelligence for authentic engagement. Syneos Health Communication. 2018 Available from: http://syneoshealthcommunications.com/perspectives/artificial-intelligence [cited 18 January 2021].
Topol EJ. Welcoming new guidelines for AI clinical research. Nat Med 2020; 26: 1318–20. doi: 10.1038/s41591-020-1042-x
Google’s medical AI was super accurate in a lab. Real life was a different story. MIT Technological Review. Available from: https://www.technologyreview.com/2020/04/27/1000658/google-medical-ai-accurate-lab-real-life-clinic-covid-diabetes-retina-disease/ [cited 18 January 2021].
Oakden-Rayner L, Dunnmon J, Carniero G, Re C. Hidden Stratification causes clinically meaningful failures in machine learning for medical imaging. arXiv 2019. Available from: http://arxiv.org/abs/1909.12475 [cited 18 January 2021].
AI can outperform doctors. So why don’t patients trust it? Harvard Business Review. Available from: https://hbr.org/2019/10/ai-can-outperform-doctors-so-why-dont-patients-trust-it [cited 18 January 2021].
LaRosa E, Danks D. Impacts on trust of healthcare AI. Proceedings of the 2018 AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society, New Orleans, LA, 2–3 February 2018. Available from: https://dl.acm.org/doi/10.1145/3278721.3278771 [cited 18 January 2021].
Rigby MJ. Ethical dimensions of using artificial intelligence in health care. AMA J Ethics 2019; 21: 121–4. doi: 10.1001/amajethics.2019.121
AI Report. Artificial intelligence in healthcare. Academy of Medical Royal Colleges. 2019 Available from: https://www.aomrc.org.uk/wp-content/uploads/2019/01/Artificial_intelligence_in_healthcare_0119.pdf [cited 18 January 2021].
Davenport T, Kalakota R. The potential for artificial intelligence in healthcare. Future Healthc J 2019; 6: 94–8. doi: 10.7861/futurehosp.6-2-94
Asan O, Bayrak AE, Choudhury A. Artificial intelligence and human trust in healthcare: focus on clinicians. J Med Internet Res 2020; 22: e15154. doi: 10.2196/15154
Department of Food and Drug Administration, USA. Proposed regulatory framework for modifications to artificial intelligence/machine learning (AI/ML)-based software as a medical device (SaMD) – discussion paper and request for feedback. Regulations.gov. 2019 Available from: https://www.regulations.gov/document?D=FDA-2019-N-1185-0001 [cited 18 January 2021].
Price WN II. Artificial intelligence in health care: applications and legal implications. University of Michigan Law School. The SciTech Lawyer 14. 2017 Available from: https://repository.law.umich.edu/articles/1932/ [cited 18 January 2021].
Narsana B, Lokhandwala M. Artificial intelligence in healthcare: applications and legal implications. ET Healthworld.com. 2018 Available from: https://health.economictimes.indiatimes.com/news/industry/artificial-intelligence-in-healthcare-applications-and-legal-implications/66690368 [cited 18 January 2021].
Muoio D. Clinical AI’s limitations: some are short-term, others are unavoidable. Mobihealth News. 2020 Available from: https://www.mobihealthnews.com/news/clinical-ais-limitations-some-are-short-term-others-are-unavoidable [cited 18 January 2021].
Case study supplied by Philips Healthcare. Discover the benefits of AI in healthcare. Imaging Technology News. 2018 Available from: https://www.itnonline.com/content/discover-benefits-ai-healthcare [cited 18 January 2021].
Froomkin A, Kerr I, Pineau J. When AIs outperform doctors: confronting the challenges of a tort-induced over-reliance on machine learning. Ariz L Rev 2019; 61: 33. doi: 10.2139/ssrn.3114347
Gerke S, Minssen T, Cohen G. Ethical and legal challenges of artificial intelligence-driven healthcare. Artif Intell Healthc 2020: 295–336. doi: https://doi.org/10.1016/B978-0-12-818438-7.00012-5
Hoffman S. Artificial intelligence in medicine raises legal and ethical concerns. The Conversation. 2019 Available from: https://theconversation.com/artificial-intelligence-in-medicine-raises-legal-and-ethical-concerns-122504 [cited 18 January 2021].
Lupton M. Some ethical and legal consequences of the application of artificial intelligence in the field of medicine. Trends Med 2018; 18: 3–7. doi: 10.15761/TiM.1000147
Singh S. The medico-legal discussion of the digital and AI revolution in the Indian healthcare industry. New Age Healthcare. 2020 Available from: https://newagehealthcare.in/2020/01/06/the-medico-legal-discussion-of-the-digital-and-ai-revolution-in-the-indian-healthcare-industry/ [cited 18 January 2021].
Tabriz A. Medico-legal perils of artificial intelligence and deep learning. Data Driven Investor. 2019 Available from: https://www.datadriveninvestor.com/2019/10/24/medico-legal-perils-of-artificial-intelligence-and-deep-learning/# [cited 18 January 2021].
Williams D. An ode to Osler: a physician profile. Resident Student Organization. 2017 Available from: https://www.acoep-rso.org/the-fast-track/an-ode-to-osler-a-physician-profile/ [cited 18 January 2021].
Published
How to Cite
Issue
Section
License
Copyright (c) 2021 Krishnan Ganapathy, M.Ch (NEURO) FACS FICS FAMS Ph.D.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Authors retain copyright of their work, with first publication rights granted to Telehealth and Medicine Today (THMT).
THMT is published under a Creative Commons Attribution-NonCommercial 4.0 International License.