AI in healthcare

AI in healthcare

Context:

The article- “Health care using AI is bold, but much caution first”, discusses the idea of providing every Indian with a “free AI-powered primary-care physician” available 24/7 within the next five years.

• The topic is a question about its practicality, challenges, and potential risks.

Relevance:
GS-02 (Health, Science and technology)

Dimensions of the Article

• What is a “Free AI-Powered Primary-Care Physician”?
• Advantages of AI in Healthcare
• Disadvantages and Challenges of AI in Healthcare

What is a “Free AI-Powered Primary-Care Physician”?

• It refers to an intelligence system that provides basic healthcare services to individuals at no cost which could operate round the clock.
• It will be offering initial consultations, shall diagnose common health issues including suggesting treatments through digital platforms.
• It aims to make healthcare more accessible, especially for underserved and remote populations, by reducing the need for physical visits to healthcare facilities.

Advantages of AI in Healthcare

1. Increased Accessibility and Convenience: Regardless of the patients location and time, the AI enabled system can be used to diagnose the illness during emergencies. It will play an important role in rural and remote areas where access to doctors and medical facilities is limited.
2. Efficiency in Handling Routine Tasks: However, it can used to perform repetitive tasks such as managing medical records, scheduling appointments, providing reminders for medication, and also analyzing symptoms to suggest initial treatments.
3. Data Analysis and Predictive Health: AI systems can analyze vast amounts of health data to identify patterns and predict potential health risks. For example, AI could predict the likelihood of developing certain diseases using patient’s history, helping in early diagnosis and intervention.
4. Support for Medical Professionals: The enabling of AI, if not for patients, shall definitely assist doctors or nurses in offering treatment based on the available datasets. Large Language Models (LLMs) and Large Multimodal Models (LMMs) can also help in medical education by simulating patient interactions and providing targeted learning resources

Disadvantages and Challenges of AI in Healthcare

• Lack of Human Touch: Healthcare is not just about diagnosing and treating the diseases. AI will lack the human touch and will fall short in understanding patients’ emotional and psychological needs.
• Data Privacy and Security Concerns: AI integration will accompany, collecting and processing large amounts of personal data which could pose a serious threat to individual privacy and data leaks.
• The “Black Box” Problem: AI algorithms mostly work as a “black box,” – i.e., decision-making processes are not transparent or easily understood. In the healthcare sector, understanding the rationale behind a diagnosis or treatment plan is very critical, this problem of AI shall leave healthcare practitioners in the dark about how certain conclusions are reached by AI. Which leads to mistrust and cause potential harm if the AI makes an incorrect decision. And unlike other sectors, errors in healthcare can have life-threatening consequences.
• Dependence on High-Quality Data: India being a diverse country with minimal to average healthcare quality to the maximum number of people, the health data is often scattered, incomplete, and inconsistent. And AI to perform accurately, needs accurate information on the healthcare data. This could be a complication. The example of Naegele’s rule in obstetrics illustrates how outdated or limited data can lead to inaccurate predictions and recommendations.
• Ethical and Governance Issues: India’s regulatory environment for AI is not as developed as that of other European Unions and in order to use AI in the healthcare sector, a strong ethical framework should be developed as it involves the personal data of vulnerable populations, and chances of exploitation is more as seen in other countries., raising questions about patient rights and data ownership.

Way Forward

• India should implement comprehensive regulations for AI in healthcare that prioritize patient safety, privacy, and ethical use.
• Although AI can be very useful in diagnosing and suggesting treatments, it also comes with errors. Hence, it should be allowed with caution where AI is only used for preliminary assessments, while a human doctor makes the final diagnoses and prescription.
• Rather than planning to replace human doctors entirely, it can be used for managing hospital logistics, predicting medical supply needs, screening medical images, or assisting in administrative tasks
• In order to fully utilize AI’s potential, India must also invest in improving its health data infrastructure, ensuring data is accurate, comprehensive, and regularly updated.