India’s medical education system, tasked with shaping the healers of a billion-plus population, faces a daunting challenge. By the end of 2025, over 700 medical colleges will produce more than 118,000 MBBS graduates annually, a significant jump from 70,000 seats in 2019. Yet, this expansion strains educators, who must train vast cohorts with limited clinical exposure, all while grappling with a doctor-to-patient ratio of 1:1,457, far below the World Health Organization’s ideal. The system’s outdated pedagogy struggles to meet modern healthcare demands, leaving doctors stretched thin. However, technologies like augmented reality (AR), virtual reality (VR), Artificial Intelligence (AI), machine learning (ML), and generative AI (GenAI) offer a lifeline to ease this burden and transform training into a more effective, equitable process.
The current pedagogical framework, rooted in lecture-heavy, rote-based learning, places immense pressure on faculty. Educators juggle large classes, often exceeding a 1:10 faculty-student ratio while managing administrative loads, leaving little room for innovative teaching. Students memorise volumes of theory with delayed hands-on practice, a structure misaligned with the critical thinking and adaptability modern medicine demands. The National Education Policy 2020 advocated for competency-based medical education (CBME), but its rollout remains uneven, hindered by inadequate faculty training and resources. The Covid-19 crisis exposed these gaps, as virtual classes failed to replicate bedside experience, leaving graduates underprepared for real-world complexities. For doctors tasked with mentoring, this creates a cycle of frustration, as they strive to impart skills amidst constrained clinical opportunities.
Financial and structural inequities add to the strain. Private institutions, accounting for 60% of seats, charge fees upwards of 20,00,000, while public colleges, stretched by subsidies, lack funds for modern tools. Rural colleges, with minimal infrastructure, exacerbate disparities, mirroring India’s urban-rural health care divide. CBME, introduced in 2019, struggles against these barriers, with curricula not fully addressing emerging challenges like antimicrobial resistance or lifestyle diseases. Educators face the herculean task of preparing students for diverse scenarios with limited access to real patients, compounded by intense competition that fuels trainee burnout and mental health struggles.
Technology offers a compassionate solution to lighten this load. AR and VR can transform clinical training by simulating patient interactions and procedures. Virtual dissections and surgical rehearsals, such as practising laparoscopic procedures with haptic feedback reduce errors by up to 40% in studies, easing the pressure on faculty to secure cadavers or clinical slots. Institutions like AIIMS have adopted AR to visualise anatomy in resource-scarce settings, enhancing understanding without overwhelming mentors. Though costs (£5,000-£10,000 per system) and training needs pose challenges, partnerships with Indian tech firms could establish shared VR labs, making these tools accessible across urban and rural colleges. The NEP’s SWAYAM platform, equipping 300+ colleges with digital anatomy, shows this can scale.
AI and ML can personalise learning, reducing the mentoring burden. By analysing student performance, these systems tailor content, suggesting deeper study in areas like diagnostics while identifying those needing extra support. Programmes like IIIT Hyderabad’s 2024 ‘AI for Medical Professionals’ course teach ML for imaging analysis, embedding practical skills into rotations. In India’s overstretched TB screening system, AI tools like Qure.ai’s accelerate X-ray evaluations, allowing educators to focus on teaching rather than repetitive tasks. Expanding such initiatives through CBME, with reskilling at IITs and AIIMS reaching state levels, could ensure equitable access and lighten faculty workloads.
Generative AI brings further relief by crafting virtual patients for scenario-based training. These tools simulate diverse cases, from rural epidemics to urban chronic conditions in languages like Hindi, fostering empathy and decision-making without straining clinical resources. A 2024 EY report suggests GenAI could cut training time by 30%, offering tailored ethics and treatment simulations. To ensure fairness, the National Medical Commission should integrate GenAI ethics training, addressing data biases to support inclusive education. This allows educators to focus on nuanced guidance rather than repetitive case creation.
Revamping medical education requires supportive reforms: Outcome-focused accreditation, public-private partnerships for tech infrastructure, and incentives to bolster faculty morale. By 2030, a blended curriculum, where AR & VR reveals anatomy, AI personalises learning, and GenAI simulates real-world challenges could produce skilled, empathetic doctors ready for India’s diverse needs. This technological embrace doesn’t just ease the strain on educators; it empowers them to shape a healthcare workforce that thrives under pressure, delivering care where it’s needed most.
This article is authored by Dr. Chandrakant S Pandav, former professor and head, Centre for Community Medicine, AIIMS and Dr. Adith Chinnaswami, COO, MediSim VR.
