Balancing Innovation and Compassion: The Role of Artificial Intelligence in Modern Healthcare

Babayode Bakare, MS 3
Morehouse School of Medicine
EMRA MSC Southern Coordinator

Edited By:
Olivia Voltaggio, OMS-IV
RVUCOM-SU,
EMRA MSC Editor

              Artificial Intelligence (AI) is a new technological advancement that is reshaping healthcare. This tool provides students and physicians with a means to streamline patient care and improve learning. Despite the benefits AI offers for the future of healthcare, it raises concerns about the art of medicine and whether it is being lost, a predominance of a protocol-based medical approach, and a potential rise in health disparities for low socioeconomic status communities.

              The phrase “art of medicine” describes the fluidity within medicine and the diverse approaches clinicians take in treating patients. This flexibility is essential for treating each patient on a case-by-case basis. Medical education is centered around competency-based medical education (CBME), which can be defined as "an existing framework that addresses similar complexities in training human clinicians who are also dynamic general-purpose problem-solvers with opaque cognitive processes" (Vokinger et al., 2023). This description highlights the human component in clinical processing and analysis of medical issues. CBME is further elaborated with five core components: defining competencies, sequenced progression, tailored learning experiences, competency-focused instruction, and programmatic assessment (Vokinger et al., 2023). While these competencies may be replicated by technology, they do not reflect the core aspect of what it means to be a clinician.

              Critical thinking is the backbone of medical education, enabling clinicians to navigate the diverse nature of medicine based on scientific knowledge. However, the necessity of critical thinking is being reduced as AI assists in the development of protocol-based medicine. "Critics, on the contrary, argue that protocols will lead to cookbook medicine, to de-skilling, and to a reduced quality of care. In the continuing reiteration of these claims, they have more and more become removed from the actual practices of medical work and of the creation and use of protocols" (Berg, 1997). Protocol utilization in medicine has long been in development, and while AI is not intended to replace human judgment, it capitalizes on premade protocols and may reduce the necessity of human input in clinical cases. As a result, it can perpetuate a “one size fits all” approach to medicine, lacking the nuanced differentiation human clinicians provide. Without the ability to accurately capture the subtleties within medicine, AI constrains both patients and clinicians.

              The development of AI is heavily influenced by a country’s wealth and socioeconomic status. Countries unable to invest in their own technological advancements become reliant on others, such as the USA and Europe, for AI development and implementation. This reliance perpetuates financial discrepancies in low-SES countries and strips them of their ability to invest in their own healthcare advancements. Furthermore, it perpetuates medical biases from high-income countries, which can be transferred to other regions, thereby compromising appropriate medical decision-making. "Algorithms trained on health-care datasets that reflect bias in health-care spending, for example, worsened racial disparities in access to care in the USA. Most health data come from high-income countries, which could bias models, exacerbating historical injustice and discrimination when used elsewhere. These issues all risk eroding patient trust" (The Lancet, 2023). This indicates that the use of biased algorithms within AI not only increases the risk of patient information breaches but also exacerbates bias in healthcare.

              AI is an innovative field that provides numerous benefits, while also raising concerns for the future of healthcare. As time progresses, the art of medicine may continue to erode while protocol-based medicine surges, driven by AI. The integration of human judgment and reasoning may recede as medical education transforms and aspects of CBME diminish. The integration of AI can perpetuate bias and discrepancies within healthcare due to overreliance on these protocols. Despite these concerns, AI remains a powerful tool, particularly in specialties such as Emergency Medicine, where it has significantly aided in patient care. "Most Emergency Department and Emergency Medical Dispatch AI applications are based on Natural Language Processing and Automatic Speech Recognition because of the privileged documentation medium of free or semi-structured text or the practitioner-patient interaction" (Chenais et al., 2024). This demonstrates how AI improves note-taking for clinicians in emergency departments and increases efficiency by reducing documentation time. It is imperative that as AI continues to develop, the medical field remains vigilant and proactive in addressing variables that could compromise the structure of healthcare to ensure the human aspect of medicine is preserved.

References

• Berg, M. (1997). Problems and promises of the protocol. Social Science & Medicine, 44(8), 1081-1088. https://pubmed.ncbi.nlm.nih.gov/9131732/
• Chenais, N., et al. (2024). Natural Language Processing in emergency medicine: Improving documentation and patient care. PMC, 10632920. https://pmc.ncbi.nlm.nih.gov/articles/PMC10632920/
• The Lancet. (2023). Bias in AI algorithms and health equity. The Lancet, 402(10395), 1060-1061. https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(23)01668-9/fulltext
• Vokinger, K. N., & Gasser, U. (2023). Artificial intelligence and the future of medicine. New England Journal of Medicine AI, 1(1), Article e2401059. https://doi.org/10.1056/AIp2401059

Time. (2023). AI in medicine: How artificial intelligence is reshaping the doctor-patient relationship. TIME Magazine. https://time.com/6306922/artificial-intelligence-medicine-doctors/