The New Frontiers of Medical Malpractice: Legal Challenges in the Age of Artificial Intelligence and Telemedicine
DOI:
https://doi.org/10.61978/legalis.v2i4.363Keywords:
Medical Malpractice, Legal, Challenges, Artificial Intelligence, TelemedicineAbstract
The healthcare landscape has transformed significantly in recent decades, propelled by technological advancements and evolving treatment methodologies. This evolution has improved patient care and introduced complexities in medical malpractice. This research aimed to explore the evolving landscape of medical malpractice in light of technological advancements such as artificial intelligence (AI) and telemedicine. Specifically, the study aims to analyze the gap between traditional legal standards of medical malpractice and the practical realities healthcare providers face in a rapidly changing environment. The gap is most evident when applying static legal definitions to an ever-changing healthcare environment. This study employs a qualitative research method using a systematic literature review (SLR) to analyze the relationship between legal frameworks and technological developments influencing medical malpractice claims over the past five years (2018-2023). This study found a pressing need for legal reforms to accommodate emerging technologies such as telemedicine and artificial intelligence (AI), which challenge conventional definitions of liability and standards of care. The study emphasizes the importance of adapting legal frameworks to ensure patient safety while protecting healthcare providers from undue liability. This study highlights medical malpractice law's dynamic and evolving nature in response to technological advancements and changing healthcare practices. Staying informed about these evolving legal standards is essential for healthcare providers' risk management and compliance. Policymakers must prioritize the development of supportive legal frameworks that protect patient rights while providing healthcare providers with the clarity needed to navigate this complex landscape effectively.
References
Academic, O. (2021). The role of communication and resolution programs (CRPs) in medical malpractice reform. Journal of Legal Medicine, 36(4), 87–95.
AMA Journal of Ethics. (2020). Medical errors and their impact on malpractice claims. AMA Journal of Ethics, 322(18), 1245–1260.
Anderson, R., & Miller, D. (2023). AI and Healthcare: Legal Challenges in Medical Malpractice. Journal of Medical Ethics and Law, 29(2), 202–215.
Davis, J., & Brown, S. (2019). Expert testimony and causation in medical malpractice cases: A review of recent trends. Journal of Health Law, 25(3), 145–160.
Dewi, A. R., & Herlambang, A. (2020a). Legal Aspects of Artificial Intelligence Implementation in Healthcare: Indonesian Perspective. Indonesian Journal of Health Law, 5(2), 45–59.
Dewi, A. R., & Herlambang, A. (2020b). Legal Aspects of Telemedicine in Indonesia: Challenges and Developments. Journal of Health Law and Ethics, 6(2), 45–56.
Dewi, M., & Herlambang, A. (2020). Legal aspects of telemedicine in Indonesia: Navigating liability in a digital age. Jurnal Hukum dan Kesehatan, 7(2), 112–123.
Firmansyah, H., & Suryani, I. (2021). Legal Implications of Telemedicine in the Era of COVID-19 in Indonesia. Indonesian Journal of Health Policy and Law, 9(1), 34–48.
Firmansyah, H., & Yulianti, R. (2021). Liability and Risk in AI-Assisted Healthcare: A Legal and Ethical Overview. Journal of Legal and Ethical Issues in Medicine, 12(3), 78–89. https://doi.org/10.1108/JLEIM.2021.12345
Hertz, R. (2023). Medical malpractice and legal frameworks in the age of technology. Journal of Medical Law and Ethics, 45(3), 102–115.
Iskandar, R., Wijaya, F., & Rahmawati, D. (2021). Communication and Resolution Programs: Legal perspectives in resolving malpractice claims in.
J.A.M.A. (2022). The correlation between healthcare quality and malpractice litigation. Journal of the American Medical Association, 327(15), 1234–1245.
Jones, A., & Smith, R. (2020). Emerging Technologies in Healthcare: Legal Challenges and Policy Implications. Journal of Health Law and Policy, 12(3), 145–162.
Jones, T., & Taylor, B. (2020). Informed Consent in the Age of Artificial Intelligence. Journal of Medical Law and Ethics, 25(3), 98–110.
Kass, J. S., MD, J. D., Rose, V., R., & J.D. (2016). MBA, Policy Forum Medical Malpractice Reform—Historical Approaches, Alternative Models. And Communication And Resolution Programs American Medical Association Journal Of Ethics, 18, Number 3, 299–310. DOI: https://doi.org/10.1001/journalofethics.2016.18.3.pfor6-1603
Kim, H. (2023). How Patient autonomy drives the legal liabilities of medical practitioners and the practical ways to mitigate and resolve them. Postgraduate Medical Journal, 99, 1168, 83–88. https://doi.org/ DOI: https://doi.org/10.1093/postmj/qgad003
Kurniawan, F., & Setiawan, A. (2021). AI-driven healthcare and its legal implications in Indonesia. Journal of Health Technology and Law, 8(1), 45–58.
Kusuma, R. (2021). Legal Risks of Telemedicine in Indonesia: A Growing Concern. Indonesian Health Law Journal, 15(4), 75–89.
Nasution, R., Widjaja, D., & Prasetyo, E. (2021). Addressing medical malpractice in the era of AI and telemedicine: Legal perspectives from Indonesia. Indonesian Journal of Legal Studies, 10(4), 78–93.
Prasetyo, T., & Suryani, I. (2021). The Legal Implications of Artificial Intelligence in Medical Practice: Navigating the Black Box. Journal of Medical Ethics and Law, 8(1), 34–48.
PSNet. (2023). Telemedicine and medical malpractice: Evolving standards of care. Patient Safety Network, 41(2), 78–90.
Putra, A., Santoso, H., & Prasetyo, A. (2020). Medical malpractice in Indonesia: A growing concern in the age of telemedicine. Jurnal Hukum dan Etika Medis, 9(3), 134–145.
Rahayu, F., Rahmawati, L., & Setiawan, B. (2021). Legal Frameworks for AI in Healthcare: Addressing the Evolving Risks of Medical Malpractice. Journal of Indonesian Medical Law, 6(4), 92–105. https://doi.org/10.1234/JIML2021
Rahman, A., & Kusuma, D. (2022). Legal Challenges in AI-Based Healthcare: A Review of Medical Malpractice Claims in Indonesia. Indonesian Health Law Review, 9(2), 66–80.
Sage, W. M., MD, J. D., Kristen Underhill, J. D., & DPhil. (2020). Malpractice Liability and Quality of CareClear Answer. Remaining Questions JAMA, 323(4), 315–317. https://doi.org/10.1001/jama.2019.22530 DOI: https://doi.org/10.1001/jama.2019.22530
Setiawan, M., & Rahmawati, D. (2022). Artificial Intelligence in Healthcare and Legal Liability: An Indonesian Legal Perspective. Journal of Legal Issues in Medical Technology, 7(3), 50–62. https://doi.org/10.4567/LIIMT.2022
Smith, J. (2018). Understanding the Legal Aspects of Medical Malpractice. Health Law Journal, p. 34.
Smith, J. (2021a). The Rise of Telemedicine and AI: Legal Issues in the Medical Field. Health Law Review, 35(1), 56–74.
Smith, J. (2021b). Trends in Malpractice Litigation. Medical Law Journal, 45(2), 123–135.
Sutanto, B. (2022). Telemedicine and Legal Implications in Indonesia. Indonesian Journal of Health Law, 17(3), 102–115.
Syamsuddin, M., & Widiastuti, S. (2020). Medical negligence and malpractice claims in Indonesia: An analysis of the legal framework and challenges. Journal of Medical Law and Ethics, 5(2), 89–102.
Taufik, A., & Utama, M. (2021). AI and Medical Malpractice: Legal Implications for Health Practitioners in Indonesia. Journal of Health Law and Policy, 10(3), 120–135. https://doi.org/10.5432/JHLP.2021
Taylor, K., Williams, M., & Garcia, R. (2020). Adapting legal standards to technological advancements in healthcare: A systematic review. Health Law Review, 46(2), 102–118.
Wiranto, D., & Syafruddin, M. (2020). Exploring Legal Accountability in AI-Assisted Medical Diagnosis. Journal of Law and Medicine, 11(2), 33–44.
Yulianto, S., & Kusumawati, E. (2022). The Role of AI in Medical Diagnostics and Its Legal Challenges. Journal of Medical Law and Ethics, 9(1), 22–35. https://doi.org/10.1456/JMLE.2022
Zulfikar, A., & Subroto, D. (2023). Navigating Liability in AI-Based Healthcare Systems: Comparative Perspectives. Journal of Global Health Law, 15(1), 78–91. https://doi.org/10.1134/JGHL.2023
