India's vast healthcare system is undergoing a transformation fueled by artificial intelligence (AI). From early disease detection to personalised treatment plans, AI promises to revolutionise diagnostics, drug discovery, and overall patient care. However, this exciting journey necessitates a delicate balancing act – harnessing AI's immense potential while safeguarding the privacy and security of sensitive patient data.
In 2023, the Indian Council of Medical Research (ICMR) took a proactive step by establishing a set of ethical guidelines for AI in healthcare and biomedical research. The document highlights ten key patient-centric ethical principles for AI applications. These principles include accountability and liability, autonomy, data privacy, collaboration, risk minimisation and safety, accessibility and equity, data quality optimisation, non-discrimination and fairness, validity, and trustworthiness. The autonomy principle stresses the need to attain the patient's consent, who must also be informed of the physical, psychological and social risks involved. In contrast, the safety and risk minimisation principle prevents "unintended or deliberate misuse", ensuring anonymised data is delinked from global technology to avoid cyber-attacks.
The body responsible for assessing the scientific rigour and ethical aspects of all health research will ensure that the proposal is scientifically sound and weigh all potential risks and benefits for the population where the research is being carried out. Informed consent and governance of AI tools in the health sector are other critical areas highlighted in the guidelines, which are still in the preliminary stages, even in developed countries.
These guidelines emphasise a patient-centric approach, prioritising informed consent, data privacy, and human oversight in clinical decision-making. The "Human in The Loop" model ensures that AI recommendations are carefully reviewed and ultimately endorsed by qualified medical professionals.
Data security is another paramount concern in the age of AI. Here is where Attribute-Based Data Management (ABDM) architecture emerges as a promising solution. By assigning attributes (e.g., disease category, age group) to data, ABDM restricts access, allowing users to see only the information relevant to their specific needs. This minimises unauthorised exposure and potential breaches. Once the adoption of ABDM is smooth and widespread, the kind of comprehensive, standardized data that will be gathered can be utilized to transform the Indian healthcare system. This wealth of information could power population health studies, enable more accurate disease prediction models, and inform evidence-based policy decisions. The importance of data-driven policy cannot be overstated in this context. With access to real-time, nationwide health data, policymakers can make more informed decisions about resource allocation, healthcare infrastructure development, and public health initiatives. This data-centric approach can lead to more targeted and effective interventions, potentially reducing healthcare disparities across different regions and socioeconomic groups. Furthermore, this data can significantly enhance Clinical Decision Support Systems (CDSS). These AI-powered tools can analyse patient data in real-time, providing healthcare professionals with evidence-based recommendations for diagnosis and treatment. By integrating with ABDM, CDSS can offer more personalized and contextually relevant suggestions, improving patient outcomes while respecting data privacy protocols. Additionally, the forthcoming Personal Data Protection Act (DPDP Act) will further strengthen data security in healthcare. The act mandates clear patient consent for data collection and usage, data minimization (collecting only necessary data), and the right for patients to access and rectify their information. These regulations, coupled with the ICMR guidelines, form a robust framework for secure AI development in the Indian healthcare landscape.
The potential of AI and big data in Indian healthcare is transformative. Innovative startups like ClinAlly are developing AI-powered platforms that revolutionize patient care and health management. Their solutions assist doctors in managing chronic conditions and help individuals track personal health data. These AI-driven tools enable more precise and personalized health management, potentially transforming patient care and accelerating drug discovery processes.
AI can analyse complex biological data to accelerate the process and reduce costs, leading to faster availability of life-saving medications. Personalised medicine, a long-sought-after goal, becomes more achievable with AI's ability to analyse individual patient data and tailor treatment plans for optimal outcomes.
AI can also significantly improve diagnostics. By analysing medical images like X-rays and CT scans with exceptional speed and accuracy, AI can assist doctors in making faster and more precise diagnoses. Qure.ai, another innovative Indian company, specialises in just that – AI-powered medical image analysis. Furthermore, AI-powered chatbots and virtual assistants can streamline the healthcare experience by answering patient queries, scheduling appointments, and providing basic health information. Practo, a prominent Indian healthcare app, is exploring the potential of AI for automating some aspects of doctor-patient interactions.
The future of Indian healthcare is undeniably bright with the integration of AI. However, responsible development remains paramount. A collaborative approach involving doctors, technologists, policymakers, and legal experts is crucial to ensure AI benefits patients while safeguarding their privacy and well-being. By prioritising ethical considerations, data security, and a human-centric approach, India can harness the power of AI to create a future where advanced healthcare is accessible and affordable for all.
Authored by Dr Sabine Kapasi, Co-Founder and MD at Enira Consulting Pvt Ltd, and Co-authored by Dr Hardik Sankhla, Partner, Enira Consulting Pvt Ltd