Healing Through Innovation: Role of Digitalisation and Artificial Intelligence in Preventing Violence in Indian Healthcare

Abstract

Editor, The recent article by Saleem et al.[1] sheds light on the critical measures to combat violence against healthcare workers (HCWs). Violence against doctors in India, ranging from physical assaults to verbal abuse and property damage, has become alarmingly frequent. This issue arises from overburdened healthcare systems, emotional distress among patients and families, and inadequate communication about treatment processes. Root causes include, unmet expectations, limited understanding of disease progression and treatment outcomes, and misinformation from unreliable online sources. Such misinformation often contradicts doctors’ advice, fostering mistrust. The English literacy rate in India is merely 10.6% and patients often find it difficult if the doctor does not speak local dialect or uses medical jargon. Additionally, overburdened doctors in India struggle to spend sufficient time with patients due to the high workloads, further straining doctor-patient relationships.[2] Inadequate security staffing in hospitals amplifies these risks, underscoring that legislation alone cannot resolve the problem. Moreover, India lacks strong and specific legal protection for HCWs, leaving them highly vulnerable to workplace violence. The tragic case of Dr. Abhaya, a young doctor who was raped and murdered, while on duty, serves as a grim reminder of the severe risks HCWs face in the absence of robust protective frameworks.[3] Systemic changes, including leveraging digitalization and artificial intelligence (AI), are vital to bridge communication gaps, foster mutual understanding, and ensure a safer environment for HCWs and patients. Role of Digitalization And AI Enhancing personalized patient education: AI-powered chatbots, like PROSCA for prostate cancer, enhance patient education and understanding, bridging language barriers, and adapting materials to various reading levels.[4,5] Chatbots assist patients by offering information on conditions, treatments, and side effects, answering FAQs, and providing updates to alleviate patient frustration and support doctors’ efficiency. Administrative applications: A U.S. survey found physicians spend 16.6% of their working hours on administrative tasks. Digitalization and AI can streamline tasks like clinical documentation, record management, and claims processing, saving time and allowing doctors more face-to-face interaction with patients, enhancing rapport. Patient engagement: Proactive patient involvement improves compliance, outcomes, and satisfaction. Yet, surveys reveal low engagement, with less than half of patients being highly engaged. AI can improve this by sending reminders for medications, tests, and appointments, as well as enabling virtual consultations and telemedicine, making care more accessible.[4] Assistance in diagnostics and treatment: AI with Machine Learning can help generate diagnostic tools with high precision and can assist doctors in clinical decision making.[5] This can, in turn reduce human errors in medicine and thereby, violence against HCWs. Management of patient complaints: AI automates complaint management, streamlining registration, categorization, and resolution. It analyses patient feedback, identifies trends, and highlights improvement areas, enabling hospitals to address concerns efficiently and make informed decisions. Limitations Safety and Accuracy: AI relies on high-quality data, but healthcare data can often be biased or incomplete. Techniques like Retrieval-Augmented Generation are crucial to ensure reliability. Ethics and Privacy: AI raises issues like patient consent, privacy, and diminished empathy. Liability: Determining responsibility for AI-induced errors is challenging. Training: Both HCWs and patients require training, particularly in India, where the patient population is largely uneducated and lack digital literacy. System Integration: Incorporating AI into existing healthcare systems is complex and time consuming. Cost: The cost of AI implementation can divert resources away from essential healthcare infrastructure improvements. Financial support and sponsorship Nil. Conflicts of interest There are no conflicts of interest.

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