New Technology is the Only Way to Deliver Healthcare Solutions While Protecting Data Privacy

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By Karanjot Jaswal

Unless you’re an epidemiologist or work in a particularly niche field of digital technology, you’ve probably never heard of contact tracing until a few months ago. But successfully and safely operating a business in the age of COVID-19 requires a bit of a crash course in epidemiology, and one of the first things you learn is how contact tracing is essential for monitoring outbreaks and assessing risk. 

It’s also a hot-button issue for personal privacy—after all, we’re talking about keeping tabs on where people have been and who they’ve been in contact with. It’s easy to imagine the Orwellian implications, especially in conjunction with other data privacy-eroding efforts like the battle against encryption, or the argument for law enforcement to have “backdoor access” to our mobile devices.

People feel like their privacy is at risk, and they’re right. But they’d be right even if lawmakers weren’t arguing for improved encryption and other privacy protections, because today’s data technology simply can’t ensure data privacy.

Even the most sophisticated applications today rely on an outdated model of data, one that’s essentially unchanged since the 1970s. If you’re familiar with data integration projects, you know exactly what I’m talking about. “Data integration” really means “data copying,” and data copying will never be 100 percent secure. Every copy is another vulnerability, and many enterprises count their data copies in the tens of thousands.

It is, however, 100 percent required. Every major tech solution involves some level of data integration, where data is copied from the old platform to the new one. The only way to eliminate data copying and actually allow for data privacy is to invent a new way for data to work. 

Luckily, that’s already happened. It’s called Data Fabric. 

Controlled access instead of copies

With databases, data lakes, and data warehouses—which are all fundamentally the same idea at different scales—data is tied to the application that creates it. This is where all the copying comes from, as it’s the only way to get two applications to play nice with the same sets of data. 

A Data Fabric separates data from applications, allowing it to be used without making copies. Instead of a data integration project for every new application, you simply have a one-time integration to your Data Fabric and you can immediately use your data with any other integrated data source. 

Instead of copies, a good Data Fabric relies on controlled access permissions. No matter where data shows up, it will retain the same permissions about who can read, edit, or share it. Set those permissions once, and your teams can concentrate on creating solutions instead of worrying about data privacy.

All of this cuts out an incredible amount of time when it comes to creating new solutions. Projects that used to take months can now happen in weeks, or even days. It becomes possible to deliver solutions in real-time, allowing you the agility to keep up with demands even when there’s a global pandemic that’s totally rewriting the way our population lives, works, and plays.

Applying Data Collaboration to manage contact tracing

Speaking of our ongoing health crisis, here’s what a possible Data Collaboration-based solution to our contact tracing problem could look like: 

  • Create an app that sends location data from mobile devices to a centralized Data Fabric.
  • As soon as data enters the fabric, it will be protected by data-level permissions. This means personal identification information will remain secure no matter how it is used.
  • Your location data—and only your location data—will be fed to a contact tracing solution, allowing researchers to monitor the possible spread of the disease. Because your information is secured within the Data Fabric, any personally identifying data is protected even if the same data is used to fuel multiple solutions.
  • By feeding data toa secured artificial intelligence solution, users could be verified without sacrificing anonymity. This would allow them to receive test results and other important notifications without ever sacrificing their privacy.

Under the old way of doing things, every step of the above plan would be a potential privacy nightmare. The only way to implement such a solution without sacrificing privacy protections is to use a Data Fabric.

Adapting solutions for the future

Contact tracing is just one piece of the solution. Widespread adoption of Data Fabric technology will allow for a comprehensive Data Collaboration Command Center that connects hospitals, researchers, equipment manufacturers, government agencies, and individual users in one controlled, collaborative environment.

Fighting a major pandemic involves a lot of moving pieces, each with its own collection of associated data. All of this data can coexist within a Data Fabric, from test results to PPE logistics. All of it will be protected at the data level, with no copies, so it can power new solutions without the privacy concerns prevalent under our current system.

Beyond fighting COVID-19, this wealth of interconnected data will help to battle whatever comes next. That includes familiar enemies, like seasonal flu outbreaks, as well as the next novel virus. Healthcare providers can use this anonymized data for more research, capacity funding, local tracing for predicting hospital bed availability, managing PPE supply, and everything else that goes into battling an outbreak. (See, we did all become amateur epidemiologists over the past few months, didn’t we?)

But the only way this happens is by making Data Fabrics the go-to choice for healthcare data management. They are the only way so many different data sources can work together in creating something new, and the only hope for protecting personal privacy while doing it.

Karanjot Jaswal is the CTO and co-founder of Cinchy, the global leader in enterprise Data Fabric and Data Collaboration technology.

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