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The Indian healthcare industry is working to balance accuracy and privacy as adoption of artificial intelligence (AI) is raising confidentiality concerns. India's data protection landscape is evolving. The Personal Data Protection Bill, 2019 is still under review, even though it intends to address these concerns with guidelines for the collection, storage, and processing of personal data.
Therefore, the gap between technological advancement and regulatory frameworks remains a challenge when healthcare sector requires robust safeguards to ensure patient privacy while leveraging AI's potential, said Dr Shivani Sharma, lab director & vice-president, CORE Diagnostics.
The country’s move towards integrating AI into diagnostics is a double-edged sword. While the technology offers diagnostic accuracy, it also poses significant privacy challenges. As AI continues to evolve, balancing these aspects will be critical in shaping the future of healthcare, Dr Shivani told Pharmabiz in an email.
Despite these benefits, AI in diagnostics brings in substantial privacy concerns. AI systems rely on vast amounts of data to function effectively, often involving sensitive patient information. The recent data breach of a leading Indian diagnostic chain highlighted the risks associated with storing and processing personal health data. This incident underscores the urgent need for stringent data protection measures, she said.
AI has become a game-changer, especially in diagnostics, assuring exceptional accuracy in disease identification and health outcome prediction. However, the integration of AI into diagnostics raises significant ethical concerns, particularly regarding privacy and data security. It is crucial for India to explore the balance between accuracy and privacy, she noted.
Quoting a recent report by the Indian Council of Medical Research (ICMR), she said, “AI models can now diagnose diabetic retinopathy with 90% accuracy, a significant improvement from the 70% accuracy seen with traditional methods. This improved accuracy not only enhances early detection but also reduces the burden on healthcare professionals.”
In data analysis, AI algorithms can process vast amounts of electronic health records (EHRs) quickly, identifying patterns and predicting patient outcomes missed by human analysts. Digital pathology has benefited from AI to detect abnormalities in tissue samples with high precision, providing pathologists with valuable second opinions and minimizing the risk of diagnostic errors.
Moreover, AI has made significant strides in point-of-care testing (POCT), enabling rapid diagnostic testing at or near the site of patient care. Furthermore, AI tools are proving valuable in disease prediction. These advancements promise to revolutionize diagnostics, particularly in areas with restricted access to specialist care, ultimately improving patient outcomes and enhancing the overall efficiency of healthcare delivery.
According to Dr Shivani, to strike the right balance between accuracy and privacy, data anonymization can help remove identifiable information with without compromising individual privacy. There is need for regulatory compliance where AI systems comply with legal standards and implement best practices for data security. AI systems should be transparent, and there should be mechanisms to make AI developers accountable for any data misuse. Further, integrating ethical considerations into AI development can prevent potential abuses.
NASSCOM reports India’s AI market is expected to reach $7.8 billion by 2025. Ensuring that this growth does not come at the cost of patient privacy is essential. By adopting robust privacy practices and complying with evolving regulations, India can lead the way in ethical AI integration in healthcare, paving for a future where accuracy and privacy coexist harmoniously, said Dr Shivani.
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