The Hindu Editorial Analysis- 13th September 2024 | Current Affairs & Hindu Analysis: Daily, Weekly & Monthly - UPSC PDF Download

Health care using AI is bold, but much caution first

Why in News?

The news about the idea of a “free A1 primary care physician for every Indian, available 24/7” in the next five years is very ambitious. This raises important questions about feasibility, sustainability, and whether India is ready to handle such a big task.

• Primary health care (PHC) is essential as it helps people achieve the best possible health by providing integrated services close to where they live.
• PHC addresses health needs and looks at broader factors that affect health through multisectoral action.
• It also empowers individuals to take charge of their own health.
• However, if we depend too much on Artificial Intelligence (AI), we might weaken this key aspect of PHC.
• AI can be impersonal, which may turn people into passive recipients of care instead of active participants in their health journeys.

Developments in the sphere of AI Health Care In India 

• iOncology.ai: This platform is created for the early identification of breast and ovarian cancer.
• It was launched by the All India Institute of Medical Sciences (AIIMS) in Delhi, in partnership with the Centre for Development of Advanced Computing (C-DAC) in Pune.
• AI-based Health Care Start-ups: For example, Wadhwani AI is a non-profit organization that is working on various solutions related to tuberculosis (TB) care. They aim to assist India’s National TB Elimination Programme (NTEP) to adopt AI technology.
• The government of Maharashtra has signed a memorandum of understanding (MoU) with NITI Aayog to establish the International Centre for Transformational Artificial Intelligence (ICTAI), which will focus on improving healthcare in rural areas.
• NITI Aayog is collaborating closely with Microsoft and the medical start-up Forus Health to create automated tools for the early detection of diabetic retinopathy, a condition affecting the retina.
• The Indian Council of Medical Research has published Ethical Guidelines for using Artificial Intelligence in biomedical research and healthcare.

Potential of AI in Health Care 

• Diagnosis and Treatment Planning: AI can analyze medical images, like X-rays, to help doctors find diseases and create better treatment plans.
• Example: Apollo Hospitals introduced the Apollo Clinical Intelligence Engine, which supports clinical decisions.
• Predictive Analytics: AI can sift through electronic health records and patient information to foresee which patients might develop specific health issues.
• Clinical Research and Discovery: AI helps examine data related to drug interactions and side effects, and it can also predict which medicines will work best for certain conditions.
• Example: The ProteinSGM model from the University of Toronto is used for designing proteins.
• Robotic Surgery: AI-assisted robotic surgeries can help lower the risk of complications and support doctors in performing precise tasks.
• Workforce Optimization: AI can automate workflows, making the best use of limited staff, reducing fatigue and burnout, and improving efficiency and cost-effectiveness.
• Administrative Task Automation: Routine tasks like scheduling appointments and processing insurance claims can be automated with AI, such as through Virtual Assistants and Chatbots.
• Healthcare Supply Chain Resilience: Predictive models using data can give ongoing insights into supply levels, offering real-time information about shortages and excesses.

Initiatives facilitating Integration of AI in Current Healthcare Ecosystem 

• Ayushman Bharat Digital Mission (ABDM): This initiative aims to provide a unique digital health ID for every citizen.
• Healthlocker/Personal Health Records (PHR): This is a digital national health database that uses a cloud-based storage system. It acts as a single source of health information for the entire country.
• National Health Stack (NHS): This includes the National Health Analytics Platform and other related components.

Concerns Associated with AI in Health Care 

• Data Privacy and Security: Using AI in healthcare involves handling a lot of patient information, which can lead to worries about how this data is kept safe and private.
• Bias: If AI healthcare models are trained on data that does not represent a broad range of society, they can produce biased results. This may result in incorrect or unfair outcomes, especially affecting marginalized communities.
• Lack of Transparency: Users often do not understand how AI models operate. This makes AI systems feel like "black boxes", which can reduce trust in their reliability.
• Regulation and Governance: There is a shortage of clear rules and guidelines for using AI in healthcare. This raises concerns about who is accountable if an AI system makes a mistake, such as an error from an AI-assisted surgical robot.

Other: Equitable use (in the initial phase will be unaffordable for a lot of people), fear of job loss, etc. 

Conclusion 

AI has immense potential but it needs to be accompanied with adequate regulation and governance mechanism. In this regard, World Health Organisation has released guidance on the ethics and governance of AI for health.