ARTIFICIAL INTELLIGENCE IN HEALTH SECTOR OF INDIA

ARTIFICIAL INTELLIGENCE IN HEALTH SECTOR OF INDIA

IN NEWS –

The ambitious goal of providing a free AI-powered primary care physician available 24/7 to every Indian within five years has raised critical questions about feasibility, sustainability, and India’s preparedness to manage such a large-scale initiative.

What is meant by Primary Health Care (PHC) ?

1. It is a model of health care that aims to provide accessible, continuous, and coordinated care to people.
2. It is based on the idea that everyone has the right to the highest attainable level of health.
3. It has three components:
   • Integrated health services: Provide health services to meet people's needs throughout their lives
   • Addressing health determinants: Use multi sectoral policy and action to address the broader determinants of health
   • Empowering communities: Empower individuals, families, and communities to take charge of their own health

MERIT OF AI IN HEALTH

1. Reduce errors and increase efficiency - AI can increase efficiency and reduce errors in health care.
2. Reduce errors and increase efficiency - AI can be useful in specific, well-defined tasks such as predicting hospital supply needs, managing biomedical waste, or optimising drug procurement.
3. Support medical education - These models enhance personalised learning experiences for medical professionals.
4. Predicting hospital supply needs
5. Screening medical images
6. Research writing through LLMs - AI can assist in screening histopathology slides and medical images or support medical education and research writing through Large Language Models (LLMs) and Large Multimodal Models (LMMs).

CHALLENGES ASSOCIATED WITH AI IN HEALTH SECTOR

1. It lacks human characteristics like understanding the physical world, reasoning, and moral decision-making, all of which are essential in health care.
2. Establishing infrastructure to capture, collect, and train data for AI is expensive.
   • Additionally, health data constantly evolves, requiring ongoing updates and fine-tuning of models, leading to recurring costs.
3. AI’s decision-making is often opaque.
   • In health care, this lack of transparency undermines trust, as medical professionals and patients are unable to understand how diagnoses or treatment recommendations are made.
4. Health care decisions require accountability and understanding, which AI lacks.
   • Example: Mistakes in health care can be life-threatening and requires accountability.
5. India’s diverse population complicates data standardisation, as health-related data is complex, personal, and requires contextualization.
6. India lacks comprehensive AI regulation, unlike the European Union's Artificial Intelligence Act.
   • Recent concerns, such as the exploitation of underpaid workers in AI training, as highlighted in Kenya's Parliament, underscore the ethical complexities of AI.
   • Safeguarding patients' privacy and data rights is crucial, especially given India's lack of regulations.

WAY FORWARD

• While AI holds promise for improving health care efficiency in India, significant concerns remain about its readiness to tackle complex health care needs, the cost of developing and maintaining AI infrastructure, and ethical concerns surrounding patient data privacy.
• A more measured approach is required, with a focus on establishing robust governance, ensuring data quality, and addressing ethical considerations.