Context:  

• Artificial Intelligence has potential to revolutionise India’s healthcare model, making it a global leader in AI-driven healthcare solutions and healthcare more accessible and affordable.

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• India is now the world’s diabetes capital with over 100 million diabetics individuals and millions having hypertension, and youth are succumbing to heart attacks, cancer, respiratory issues, depression and more.
• The Indian healthcare AI industry is anticipated to expand at a compound annual growth rate (CAGR) of 40 per cent from 2019 to 2025, according to a NASSCOM analysis.
• While India is already one of the leading destinations for patients seeking care abroad, there is adequate headroom for growth.

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About Artificial Intelligence:

• According to NITI Aayog, “AI refers to the ability of machines to perform cognitive tasks like thinking, perceiving, learning, problem solving and decision making.”
• AI uses various technologies such as computer vision, audio processing, cognitive robotics, speech analytics, language processing and machine learning techniques to derive AI-based solutions.
• AI has the capability to help human beings contribute more effectively to society and also helps bring in more timely, accurate and fast solutions. 
• It has an immense potential to transform the healthcare landscape of India. 

Healthcare Sector in India:

• Indian healthcare is known as one of the largest sectors, both in terms of employment and revenue generation opportunities.
• As per the NASSCOM report, the market size of healthcare industry in India was valued at $372 billion in 2022 and is expected to grow at a compound annual growth rate (CAGR) of nearly 20% from 2023 to 2030.
• AI expenditure in India is expected to reach $11.78 billion by 2025 and add $1 trillion to India’s economy by 2035, as per a World Economic Forum report. The AI in Healthcare Market is projected to grow from $14.6 Billion in 2023 to $102.7 Billion by 2028.
• The pandemic not only pushed rapid advancements in technology but also propelled the AI related investment in the Indian medical and healthcare start-ups.
• Union Budget 2023-24: The healthcare sector has been allocated INR 89,155 crore to undertake all the new-age research and innovation-based healthcare initiatives on a massive scale. 
  • The government has also encouraged several industry players to invest in research and development in the priority areas including innovative technologies in healthcare.

Potential of AI in Healthcare:

• Medical imaging: AI in MRI and CT imaging is the new boon in the radiology segment which allows deep learning of every organ of the body under scan.
  • For instance, the AIIMS (All India Institute of Medical Sciences) in Delhi has created a technology that uses artificial intelligence to detect oral cancer in its early stage.
• Analysis of Electronic Health Records (EHRs): Using this technology, it is possible to identify patients who are at a high risk of developing chronic diseases. 
  • For instance, Apollo Hospitals teamed up with Microsoft to create an AI-powered cardiovascular disease risk score.
• Addressing the Healthcare Crisis: A report on the National Strategy for Artificial Intelligence by the NITI Aayog showed that shortage of qualified healthcare professionals and non-uniform accessibility to healthcare across the country prevails. 
• • For example, India has only 64 doctors available per 1,00,000 people compared to the global average of 150. 
• Reduce Out of Pocket Expenditure: According to the Economic Survey 2022-23, almost half of all health spending in India is still paid by patients themselves directly at the point of treatment. 
  • According to Harvard, using AI to make diagnoses may reduce treatment costs by up to 50% and improve health outcomes by 40%
  • According to research by Accenture, AI might save the Indian healthcare sector $4.4 billion by 2025.

Significance of Integrating AI in Healthcare:

• Accuracy in Patient Treatment: AI-powered Robotic Process Automation (RPA) solutions can minimise human error, streamline workflows, and ensure more accurate patient treatment.
• Early Diagnosis of Diseases: AI algorithms can be utilised in wearable devices, such as smartwatches or fitness trackers, to continuously monitor vital signs, collect health data, and identify patterns or anomalies.
  • By analysing this data in real time, AI-powered smart devices can alert users and healthcare providers about potential health risks or early signs of diseases.
• Promoting Medical Value Travel (MVT): India has emerged as a global MVT hub, particularly in the fields of oncology, orthopaedics, and robotic surgery.
  • MVT is gaining strategic importance given its ability to create employment as well as earn foreign exchange.
• Precision Medicines: By using AI algorithms and patient data, tailor made treatment plans or personalised treatments for individuals can improve efficiency and efficacy.
• Quick Disease Prediction: Additionally, AI can help predict disease outbreaks, analyse health-care data, and optimise treatment plans, expediting health-care procedures, and revolutionising drug discovery ultimately making health care more personalised and effective.
• Healthcare Management: AI optimises hospital and healthcare facility operations by predicting patient admissions, managing bed allocations, and streamlining supply chain logistics.
  • Chatbots and virtual assistants enhance patient engagement and streamline administrative tasks. 

Challenges of Integrating AI in Healthcare:

• Blind spots in data collection: Lack of access to reliable data is one of the main problems. To be trained efficiently, AI systems require a lot of high-quality data. 

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• • In India, there are not many EHRs that are standardised, and the data is frequently jumbled and unfinished.
• Biases: There are AI models that use audio data to diagnose diseases such as Alzheimer’s. If these models are not trained with a wide range of accents, their outputs can be biased.
  •  For example, an AI algorithm created in Canada used speech samples from only Canadian English speakers, putting English speakers of other accents in the country at a disadvantage. 
• Privacy: Sensitive healthcare data may be jeopardised since AI systems must be educated on enormous volumes of data. Therefore, protecting healthcare data and guaranteeing that it is only used for specific purposes is a challenging task.
• Misuse: The linking of health data with other systems will create new avenues for discrimination. 
  • For example, health insurance data can be leveraged by banks to evaluate eligibility for loans which could lead to discrimination in patient treatment.
• Ethical Issues- Accountability and Transparency: Determining liability in cases of AI-driven medical errors can be challenging. Is it the responsibility of the healthcare provider, the AI software developer, or a combination of both? A Comprehensive Legal framework must define liability and accountability.
• Cultural Acceptance: While AI offers remarkable capabilities, the expertise, intuition, and compassion of healthcare professionals which make a critical difference remain indispensable. 
  • For example,an AI system may be able to allocate a patient to a particular care centre based on a specific diagnosis. However, it may not account for patient economic restrictions or other personalised preferences.

Government Steps for Integrating AI in Healthcare: 

The government of India has also created a national digital health infrastructure to implement the digital health systems across the country, which includes:

• Healthlocker: Digital national health database backed with cloud-based storage system which serves as a single source of health data for the nation.
• Personal Health Records (PHR): Allow data to be available for citizens and for medical research purposes.
• Digi Doctors: A digital directory of doctors along with their name, specialisation, qualifications, number of years of experience.   
• Coverage and claims digital platform.
• National health analytics platform.
• Unique digital health ID for each citizen.

Way Forward: 

• Boosting investments: AI integration into healthcare requires critical investments in the workforce, infrastructure, regulatory mechanisms, stakeholders, and business models.
• Promoting Telemedicine: Incorporating AI with telemedicine platforms can extend quality healthcare access to rural and underserved areas.
• Research & Development: Government must also invest in public and private organisations like NITI Aayog, Tata Institute of Healthcare, Apollo Hospitals, etc. to facilitate the research being done to integrate AI-based solutions into healthcare.
• Ensuring Data Security: Digital transformation success is not possible without security thus safeguarding of patient data against breaches or data loss and ensuring robust data security is the need of the hour. 
• Data Standardisation: Promoting the standardisation of healthcare data formats by encouraging EHRs and interoperability between different healthcare systems and providers. 

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Conclusion: 

India stands at a pivotal moment in its health-care journey. By reimagining its health-care model, the country can position itself as the global destination for medical value travel, a powerhouse in AI-driven health-care solutions. To achieve this vision, India must prioritise community health, foster public-private partnerships, and invest in innovation and research. 

News Source: The Hindu