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Empowering Indian Healthcare with AI: What More Should be Done?

3 Mins read

The integration of AI into healthcare has the potential to revolutionize the way medical services are delivered, especially in a country as vast and diverse as India. AI-driven solutions can address long-standing challenges of healthcare accessibility, affordability and quality. Yet, while India has made significant strides in leveraging AI for healthcare, it is clear that the journey is far from over. The Indian government has laid a strong foundation by offering various forms of support to integrate AI into the healthcare ecosystem, but several roadblocks still prevent widespread adoption.

 

 

Government Support for AI in Indian Healthcare
The Indian government has been proactive in recognizing the potential of AI to transform healthcare, particularly under its broader agenda to digitize healthcare services. One of the key initiatives is the IndiaAI Mission, which emphasizes the application of AI across various sectors, including healthcare. Under this mission, the Ministry of Electronics and Information Technology (MeitY) has launched initiatives to incentivize AI-driven solutions. The IndiaAI Application Development Initiative (IADI), one of the mission’s pillars, focuses specifically on healthcare, agriculture, and climate change.

Another critical aspect of the government’s support is seen in the Ayushman Bharat Digital Mission (ABDM), which is laying the groundwork for building a digital health ecosystem. Under ABDM, millions of Ayushman Bharat Health Accounts (ABHA) have been created to ensure that patient records are readily accessible, which is crucial for AI integration. By ensuring digitization and accessibility of patient data, the government is paving the way for AI-driven personalized care, prediction models, and public health interventions.

The Global Initiative on Digital Health (GIDH), launched during India’s G20 presidency, is also a significant step towards fostering international cooperation in digital health, with AI playing a central role in shaping healthcare solutions. The government’s focus on building digital health registries and its push for private-sector innovation to scale AI solutions underline India’s commitment to harnessing AI in healthcare.

 

 

The Roadblocks to AI Adoption in Indian Healthcare
Despite the government’s active participation, several critical challenges are stifling the full-scale adoption of AI in Indian healthcare. These obstacles range from infrastructure limitations to regulatory ambiguities, and they threaten to derail the potential gains that AI promises.

One of the most significant barriers is data accessibility. Although the government has made efforts through the ABDM to create a unified health data infrastructure, there remains a significant gap in the adoption of Electronic Health Records (EHRs). The lack of standardized, digitized, and interoperable patient data across healthcare providers means that AI tools struggle to access the datasets they require for training and refinement. Without proper datasets, AI systems cannot achieve the accuracy needed to be trusted in clinical settings, limiting their utility.

Another pressing issue is the skills gap in AI technology within the healthcare workforce. The workforce, both in healthcare and AI development, lacks the necessary upskilling to fully leverage the power of AI. While India has a large pool of IT professionals, there is a shortage of specialized talent that understands both healthcare and AI, limiting the development of India-centric AI solutions.

The high cost of infrastructure also poses a challenge, particularly in rural areas where the healthcare system is already underfunded. AI-driven systems, while cost-effective in the long run, require substantial initial investment in hardware, software, and digital infrastructure. This poses a significant challenge in a country where many healthcare facilities are still functioning with outdated equipment.

There are also regulatory concerns surrounding the use of AI in healthcare. Data privacy, patient consent, and accountability in cases of AI-related errors are some of the areas that lack clear regulatory frameworks. As AI systems become more integrated into decision-making processes, questions around who is responsible when an AI makes a wrong diagnosis or treatment suggestion will need to be addressed urgently. The absence of robust ethical guidelines and accountability mechanisms hampers the confidence of healthcare providers in adopting AI solutions.

 

 

What More Needs to be Done?
To accelerate the adoption of AI in Indian healthcare, both the government and private sector need to take several strategic steps. Since strategically focusing on all issues can be challenging, the latest nasscom-Kantar report, titled Advancing Healthcare in India: Navigating the Transformative Impact of AI, presents a very detailed playbook to aid ecosystem stakeholders in focusing on all key action pillars in a very effective manner. Following is a broad outline of the playbook. The detailed playbook, which is freely accessible in the complete report, double clicks on each of the individual requirements across all pillars to help stakeholders in effectively navigating them.

Source: nasscom-Kantar report “Advancing Healthcare in India: Navigating the Transformative Impact of AI

With coordinated efforts from all ecosystem stakeholders, AI-driven healthcare can significantly improve health outcomes for millions of Indians, bringing the country closer to a future where quality healthcare is accessible to all.