Artificial Intelligence (AI) tools are transforming industries, such as finance and banking, retail, and telecommunications, by boosting efficiency and quality. The potential of AI lies in its adaptability and customisation, which have vast benefits for health care management and clinical practice.
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While AI technologies in imaging, radiology, and precision medicine hold significant promise for transforming health care, their integration into the Indian health care system remains limited due to low levels of hospital digitalisation and a lack of widespread AI literacy. However, with the undeniable benefits offered by AI tools for patients and clinicians alike, adoption is gradually gaining momentum in the Indian health care landscape. The 2023 guidelines on ethical and responsible use of AI by Indian Council of Medical Research (ICMR) were a welcome step to pave the way for safe, human-centric AI integration.
Generative AI demonstrates significant potential in health care by optimising medical workflows, supporting evidence-based clinical decision-making, and improving patient outcomes. The deployment of specialised, use-case-specific AI tools enables health care systems to enhance operational efficiency while advancing the quality of care.
Hospitals are intricate ecosystems that demand seamless coordination among administrative staff, clinicians, surgeons, radiologists, nurses, and support services.
Medical management teams are tasked with ensuring quality and safety, overseeing the synergy between different departments, and facilitating optimal resource utilisation.
Adoption of electronic health records (EHR) and AI-optimized hospital information management systems can enable GenAI tools to create impact through strategic support. For instance, adoption of GAI-powered conversational chatbots is suitable and effective in various clinical settings. These chatbots can conduct pre-consultation interviews with patients, which saves time for both clinicians and patients. By capturing medical histories and relevant details in advance, they enable physicians to focus more on meaningful patient interaction during consultations. GAI-based clinical assistants also contribute significantly to tasks such as medicine reconciliation and auto-reporting for investigations, which can be vetted and approved by the treating physician. By automating tasks like test ordering, communication between departments becomes faster and less burdensome for doctors.
Beyond administration, GenAI supports evidence-based medicine, transforming clinical decision support by enabling more dynamic, context-aware, and patient-centred care. GAI-powered Clinical Decision Support Systems (CDSS) works as a highly specialised search engine that draws on a database of only peer-reviewed, verified, and high-quality sources, conforming to strict medical guidelines and standards. This prioritises the Human-in-the-Loop (HITL) approach, where human expertise and knowledge to make critical decisions are supported by GAI capabilities..
Traditionally, clinicians relied on extensive textbooks or unverified online sources for medical research. Today, GAI-powered Clinical Decision Support Systems (CDSS) offer instant access to the latest, evidence-based clinical data, enabling personalised treatment planning with precision. While CDSS does not replace medical expertise, it enhances it--empowering doctors and nurses to make faster, better-informed decisions backed by verified sources and transparent citations, ultimately improving patient care.
There’s much that CDSS and GenAI can do, but their limits are clearly defined. The role of AI in health care will always be to support and enhance. Values like accountability, empathy, sensitivity, and compassion are the domain of human beings. AI tools for health care must be ethically designed and sensitively implemented with a non-negotiable focus on safety and quality, allowing health care professionals to do the best possible work they can.
As GAI uptake increases and becomes more accessible, such tools have the potential to greatly benefit medical students, doctors in remote and underserved areas, ASHA workers, and community physicians – making health care more accessible, accurate, and patient-centric across India.
This article is authored by Nimisha Goswami, director, content strategy, Elsevier.
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