Google’s DeepMind developing blockchain-like tech to track health dataMar 12, 2017
DeepMind, the Google-owned artificial intelligence company, is developing a new technology similar to blockchain for secure tracking of patient health data.
In a blog post, London-based DeepMind said its new Verifiable Data Audit project could be the first steps toward a “a service that could give mathematical assurance about what is happening with each individual piece of personal data, without possibility of falsification or omission.
“The aim is to enable hospitals, and eventually patients, to gain real-time insight into where and how data is being used.”For example, an organization holding health data can’t simply decide to start carrying out research on patient records being used to provide care, or repurpose a research dataset for some other unapproved use,” according to DeepMind. “It’s not just where the data is stored, it’s what’s being done with it that counts. We want to make that verifiable and auditable, in real-time, for the first time.”
In DeepMind’s capacity as data processor for hospitals, the currently creates an auditable log any time it comes into contact with patient information. With Verifiable Data Audit, it will expand on that: “Each time there’s any interaction with data, we’ll begin to add an entry to a special digital ledger. That entry will record the fact that a particular piece of data has been used, and also the reason why – for example, that blood test data was checked against the NHS national algorithm to detect possible acute kidney injury.”
Company officials note that the ledger system shares similarities with the concept of blockchain in that the ledger will be “append-only,” meaning that once data use is recorded, it can’t be erased. The ledger will also enable third parties to verify that the entries have not been tampered with or altered.
The end result, according to DeepMind will be “an improved version of the humble audit log: a fully trustworthy, efficient ledger that we know captures all interactions with data, and which can be validated by a reputable third party in the healthcare community.
“The goals: a way to enable providers to run automated queries on the data, set alarms to be triggered if anything looks amiss and, eventually, give others – such as patients – the opportunity to check in on the data processing.
There are many technical and other hurdles along the way, said DeepMind, but “we’re hoping to be able to implement the first pieces of this later this year.”