It wasn’t long ago that blockchain was the hottest topic in the tech world. Originally developed for secure and transparent financial transactions (which prompted the meteoric rise of cryptocurrencies), blockchain technology promised to revolutionize processes and enhance data integrity across industries, with healthcare poised to benefit tremendously. So what happened?
AI Has Taken the Spotlight
In the early days of blockchain, the promise of technological innovation in healthcare was massive. It had the potential to address challenges like supply chain, transparency, data, security, interoperability, and patient privacy.
But while there have been some noted successes within the financial and supply chain industries, blockchain’s adoption within the healthcare field has been slow. Not many people are even talking about it anymore; in fact, at this year’s HIMSS conference, we don’t recall it even being mentioned.
The spotlight, unsurprisingly, has shifted to Artificial Intelligence (AI), which offers more practical applications, more mature technology, and easier scalability. Within healthcare, we’re seeing AI systems capable of enhanced clinical decision support; medical imaging analysis; fraud, waste, and abuse detection; and clinical participation and support.
However, despite its potential advantages in the healthcare industry, AI doesn’t come without its own drawbacks and hurdles for widespread adoption. Outside of the obvious lack of human touch and emotional intelligence, there is concern around trust, data, transparency, and security.
Why Blockchain and AI are Better Together
While blockchain has seemingly lost its momentum and AI has captured the world’s attention, the real potential is in the combination of both AI and blockchain. In fact, within healthcare, blockchain’s greatest use case may be to bring trust, verification, and security for AI into the industry.
Stronger Security and Privacy
Blockchain’s decentralized and immutable nature provides a secure storage system for sensitive healthcare data, including Personally Identifiable Information (PII) and Protected Health Information (PHI). AI relies on large datasets for developing and training models. By integrating blockchain with AI, healthcare organizations can ensure privacy, integrity, and traceability of patient data throughout its lifecycle – from validating the authenticity of data sources, to secure storage, through identity and access management.
Greater Transparency and Auditability
AI models frequently function within a black box, giving transparency only to results, not necessarily the logic and decision making behind it. This lack of transparency creates risk within the high-stakes healthcare setting. Leveraging and integrating blockchain technology can create a transparent and auditable ecosystem; every step of data manipulation can be recorded on its ledger, creating traceability and accountability.
Improved Collaboration and Data Sharing
Collaboration and data sharing across healthcare organizations are foundational to interoperability, improved health outcomes, and a leaner system. By leveraging blockchain to securely share patient, outcome, and administrative data, organizations can train AI models on larger and more diverse datasets without compromising privacy and security. This collaboration will lead to better trained models resulting in greater insights, better outcomes, and a more efficient industry.
A More Trustworthy System
While blockchain may have lost some of its ongoing momentum, the union of AI and blockchain technology creates a fuller and more trustworthy system. By leveraging blockchain’s security, transparency, and collaborative natures, we can enhance AI offerings to address critical challenges and transform healthcare delivery.