The Transformative Role of AI in Healthcare: An Interview with Dr. Rahul Goyal

In a fascinating discussion with Dr. Rahul Goyal, the Clinical Executive for the EMEALAAP region at Elsevier, we delve into how artificial intelligence (AI) is reshaping clinical decision-making, patient care, and healthcare workflows. With a background in both ophthalmology and family medicine, Dr. Goyal brings a wealth of experience that enriches our understanding of AI’s role in modern medicine.

Dr. Goyal’s Journey in Medicine

Dr. Goyal’s career trajectory began with training as an eye physician, where he quickly recognized the value of technology in clinical settings. His transition to a general physician revealed a stark contrast in technology support, prompting him to advocate for AI tools in clinical workflows. He emphasizes the critical gap between clinical judgment and digital augmentation, positioning AI as a tool to bridge that divide.

Evolution of Technology in Medicine

Reflecting on his early days in practice, Dr. Goyal explains that technology was minimal, with personal digital assistants being one of the few resources available. He noted that the evolution has been marked by significant advancements, moving from limited support to an integral component of clinical decision-making. Despite the historical lag in healthcare innovation due to safety, privacy, and regulatory concerns, recent developments have begun to dismantle these barriers, signaling a new revolution in clinical workflows.

Dr. Goyal stresses that not every new technology is beneficial, advocating for tools that enhance clinician experience—specifically, technologies that save time, reduce cognitive burden, and ultimately improve patient outcomes. He believes that the most successful implementations occur when clinicians play an active role in co-designing AI tools.

Practice-Changing Moments with AI

Dr. Goyal shares poignant examples of how AI has directly improved patient care. In one case, he treated an elderly lady with a leg infection. The complexity of her medical history, including renal impairment and a long list of medications, could have made manual evaluation time-consuming. However, using ClinicalKey AI, he quickly received an evidence-based treatment plan that saved time and minimized risks associated with medication interactions.

Another compelling instance involved a 7-year-old boy with a recurrent limp, which conventional tests failed to explain. Feeding his unique background—recent travel to India and familial exposure to tuberculosis—into ClinicalKey AI led to a timely diagnosis of tuberculosis, illustrating how AI can prompt critical insights that human operators may overlook.

Enhancing Patient Interactions

The integration of AI has undeniably altered the quality of time Dr. Goyal can spend with patients. By automating note-taking and data aggregation, he has reclaimed precious minutes in each consultation. This newfound efficiency allows him to focus on building rapport and providing valuable resources for his patients. Recognizing that patients often forget a majority of what’s discussed during their visits, this additional time is pivotal in ensuring that patients leave with credible information that enhances compliance and trust.

Addressing Colleagues’ Concerns About AI

Dr. Goyal notes the initial skepticism and fear of ‘black box’ AI among his colleagues, particularly concerns about AI potentially replacing clinicians. He underscores the importance of transparency in AI development, advocating for what he refers to as “glass box” tools that allow clinicians to understand the logic and limitations behind AI suggestions. This kind of transparency fosters a collaborative environment where clinicians can actively engage with AI rather than view it as a threat.

Building trust with patients regarding AI-supported decisions involves treating the AI as another reference tool. Dr. Goyal shares real-time interactions with patients to showcase how AI can inform clinical decisions while emphasizing the clinician’s role in interpretation and application.

AI’s Impact on Multidisciplinary Teams

AI’s role extends beyond individual clinician-patient interactions; it is also reshaping teamwork within multidisciplinary care teams. With diverse specialties involved in patient care, AI can facilitate communication by summarizing relevant evidence across disciplines. Dr. Goyal describes a trial in the Middle East where AI provided referenced reasoning in ICU cases, dramatically speeding up decision-making and improving inter-specialty collaboration.

Accelerating AI Rollout Across Healthcare Systems

Dr. Goyal addresses the structural changes needed to promote a safe and effective AI rollout, particularly within the NHS. He emphasizes the importance of establishing standardized protocols for AI tools and fostering collaborative ecosystems that include all stakeholders—clinicians, patients, and commissioners. Such a unified approach could potentially set a global standard for AI in healthcare.

Common Misconceptions About AI in Healthcare

Throughout his interactions, Dr. Goyal encounters various misconceptions about AI, notably the belief that all AI solutions are interchangeable. He clarifies that AI solutions can vary widely in terms of their design and applicability to clinical workflows. Over-promising can lead to disappointment, particularly in tools that do not seamlessly integrate with existing workflows.

He also addresses the fear that AI will replace healthcare professionals, reiterating that AI should be seen as an assistive tool—one that requires human oversight and intervention to deliver optimal results.

Encouragement for NHS Hospitals

For NHS hospitals just embarking on their AI journey, Dr. Goyal advises starting small by identifying specific workflow pain points. Focusing on high-impact tasks like documentation can yield significant benefits. He emphasizes the importance of involving staff at all levels to ensure that the technology aligns with actual clinical needs.

This approach not only enhances efficiency but also empowers healthcare professionals by involving them in the technology’s development and implementation process.

Further Learning and Resources

For those interested in exploring AI in healthcare further:

• Discover ClinicalKey AI here.
• Explore practical applications of ClinicalKey AI across various clinical scenarios here.
• Enroll in Elsevier’s Gen AI Academy for Health, a CME-accredited course available here.

About Dr. Rahul Goyal

Dr. Rahul Goyal is a clinical leader with nearly 20 years of experience in various health technology roles. Before joining Elsevier, he served as the Chief Medical Information Officer at Mediclinic, leading initiatives in electronic health record adoption and clinical decision support tools. Alongside his leadership responsibilities, Dr. Goyal continues to practice as a Family Physician in the UK, showcasing a blend of clinical and technological expertise that informs his vision for the future of healthcare.