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Written by David Houlding December 18, Today most healthcare data exists in silos. There is only limited sharing of healthcare data. There is massive, largely untapped potential for securely sharing healthcare data to improve the quality of patient care and reduce the cost of care. Healthcare is under increasing pressure to reduce the cost of care.
Exacerbating this are the trends of aging populations and rampant chronic diseases. Several key new technologies are poised to disrupt healthcare, alleviate these problems, and pave the way for both improved quality of patient care, and reduced cost of care. In this article, I take a brief look at how these technologies can help, how they relate to each other, and how they enable and build upon each other. Today, healthcare data is mostly in silos within enterprises across providers, payers, pharmaceuticals, life sciences, and increasingly also with patients and consumer health organizations.
There is massive untapped potential to both improve the quality of patient care and reduce the cost of care with targeted safe sharing of this healthcare data.
In the near term, blockchain, or decentralized ledger technology, can be used across a broad variety of existing B2B networks of health and life sciences organizations to enable secure discovery, location, and sharing of healthcare data.
Examples of such networks include clearinghouses, health information exchanges, provider credentialing networks, drug supply chain networks, medical device networks, and many more. In these networks, it is not that blockchain will replace enterprise systems used today, or that blockchains will store all the patient information, but rather blockchains will augment such enterprise systems in the role of enterprise B2B network middleware, and enable the secure exchange of minimal but sufficient data to enable specific healthcare use cases.
Longer term, blockchains will enable entirely new use cases around which fundamentally new types of healthcare organizations and new B2B networks coalesce, and the impacts of these could be revolutionary, but this will take more time. In the near term on the evolutionary adoption curve, blockchain will likely need to first prove itself out in existing B2B healthcare networks.
Breaches and ransomware in healthcare have reached alarming levels of impact and frequency of occurrence. To enable blockchain to reach its full potential and minimize associated breaches and ransomware, which could quickly tarnish and stunt the use of blockchains, it is essential that we not take the security of blockchains for granted, but rather address the security, privacy, and compliance aspects up front as we design and implement blockchains.
Interoperability continues to be a challenge, and interoperability must be maximized for blockchain to realize its full potential. This impacts both information stored on the blockchain as well as information stored off the blockchain that is pointed to by blockchain metadata. Blockchain metadata can, of course, include information such as format and version information that can be used to help enable interoperability. A critical mass of healthcare B2B networks using blockchains, and a critical mass of healthcare data on these blockchains, will lead to the ability to improve the efficiency and speed of transactions by automating the processing of such transactions right on the blockchain using code stored on the blockchain.
These nuggets of code on the blockchain are called smart contracts. They can trigger when certain transactions are appended to the blockchain. When triggered, smart contracts execute the results of their execution and can, in turn, produce new output transactions that are then appended to the same blockchain. Note that smart contracts are not an all-or-nothing thing. Smart contracts can be introduced first for basic transactions that require only simple code.
This could include, for example, simple pre-authorizations that are traditionally sent from providers to payers for processing. Through the use of blockchain and smart contracts in a clearinghouse type blockchain B2B network consisting of healthcare provider and payer organizations, these simple pre-authorizations could be handled directly on the blockchain by smart contracts rather than in the payer's enterprise systems.
This both enables speed and efficiencies to providers, and also offloads authorization transaction loads from payer systems to the blockchain network, helping to improve efficiency and drive down the cost of patient care. Over time more and more smart contracts can automate more and more types of transactions on blockchains delivering incrementally improved efficiency and speed of transactions, and associated cost reductions.
More complex and new types of transactions may continue to be handled by enterprise systems within healthcare organizations connected to blockchains, but over time the fraction of transactions handled off chain are likely to decrease since there are such compelling benefits in efficiency and speed with handling as many transactions as possible using smart contracts executing directly on the blockchains.
The rise of artificial intelligence and machine learning has been spectacular and continues to accelerate and promises to deliver major value across a broad variety of healthcare applications from personalized and precision medicine, to many kinds of image analysis, enhanced treatments, chatbots and virtual assistants, cybersecurity, and many more. These technologies are enabled and powered by data, by vast quantities of data, and their accuracy, usefulness, and benefits improve as more data is made available to them.
The fact that much of this data is spread out across and locked within multiple silos across multiple healthcare organizations, and the sharing of such data is either very limited or non-existent, means that today the maximum value of AI and ML cannot be fully realized. Blockchain and smart contracts enable secure and efficient data sharing and processing across B2B networks of healthcare organizations, and these technologies pave the way for increased discovery and access to healthcare data across these networks to power AI and ML.
What opportunities and challenges are you seeing with blockchain, smart contracts, artificial intelligence, and machine learning in healthcare? Intel Health and Life Sciences is actively working in these areas of innovation. Message me on LinkedIn if you would like to connect, discuss, and explore synergies and opportunities. Advanced features of this website require that you enable JavaScript in your browser. Healthcare Data in Silos Today, healthcare data is mostly in silos within enterprises across providers, payers, pharmaceuticals, life sciences, and increasingly also with patients and consumer health organizations.
Blockchain Paves the Way for Secure Sharing In the near term, blockchain, or decentralized ledger technology, can be used across a broad variety of existing B2B networks of health and life sciences organizations to enable secure discovery, location, and sharing of healthcare data.
Smart Contracts Automate Transactions, Improving Efficiency and Speed A critical mass of healthcare B2B networks using blockchains, and a critical mass of healthcare data on these blockchains, will lead to the ability to improve the efficiency and speed of transactions by automating the processing of such transactions right on the blockchain using code stored on the blockchain.
Artificial Intelligence and Machine Learning Enable New Insights The rise of artificial intelligence and machine learning has been spectacular and continues to accelerate and promises to deliver major value across a broad variety of healthcare applications from personalized and precision medicine, to many kinds of image analysis, enhanced treatments, chatbots and virtual assistants, cybersecurity, and many more.
Collaboration What opportunities and challenges are you seeing with blockchain, smart contracts, artificial intelligence, and machine learning in healthcare? Customer Experiences in Retail Worth Personalizing. Proving the concept — adopting PoCs in the analytics journey.