Fueling Innovation in Healthcare by Scaling Access to Protected Data

The following is a guest article by Dr. Suraj Kapa, Chief Medical Officer at TripleBlind

Data is arguably the most critical driver of innovation in healthcare today. When you think about it, everything in healthcare hinges on having access to the right data: From developing new drugs and medical devices to allocating scarce resources amidst supply chain issues.

Getting your hands on the data necessary to make breakthroughs in healthcare is a significant challenge given its sensitive nature. Essentially, we need a way to have our cake (access raw health data to drive life-saving advances in medical care) and eat it too (maintain said data’s privacy).

Historically, organizations have tried to get around this by using synthetic, abstracted, or pre-anonymized datasets, but that strategy just doesn’t cut it. Best case scenario, it can result in higher costs to healthcare systems. Worst case scenario, it can result in flawed insights if the data contains errors or is missing key elements. 

Thankfully, new solutions have emerged that let organizations safely collaborate with sensitive data and algorithms using federated analytics. Keeping health data secure yet accessible offers the best of both worlds: Total privacy without any barriers to innovation. 

With all that said, let’s look at the state of health data, current practices, and how new solutions are letting us have our cake and eat it too. Grab your fork. 

Healthcare has a Data Problem: Here’s How We’ve Been Trying to Tackle It

It’s no secret that having continuous access to raw health data is invaluable—that fact is well established. However, recent advances in analytics, machine learning, and artificial intelligence have brought us to a tipping point where healthcare can no longer ignore the value of having access to this data. 

We need this data to drive the next wave of innovation—people’s health and well-being depend on it. We can only achieve this if the data is kept private to maintain patient privacy and the intellectual property rights of healthcare companies and their industry partners. 

Over the years, initiatives have emerged to address this. Everyone has heard of HIPAA, which was enacted to protect patients’ health information from disclosure without their consent or knowledge. It also features standards designed to improve efficiency in the healthcare industry. The less-talked-about Sentinel Initiative was created to monitor the safety of medical products via direct access to patients’ electronic health records. Despite legislation and initiatives to help with this problem, the challenge remains and will only become more amplified as health data grows in volume and complexity. 

Organizations have been shooting themselves in the foot by relying on manually de-identifying, abstracting, or normalizing data to get the insights they need. It’s nearly impossible to obtain meaningful, accurate, real-time insights from health data in this manner. This outdated method is hardware dependent, poses potential risks for re-identification, offers only partial security, and generally only works on structured or specific types of data. 

New Tech, New Opportunities

Privacy-enhancing technologies (PETs) emerged just in time to make gleaning insights from health data scalable, accurate, and secure: a true win-win. One PET we’re truly excited about? Federated analytics.

Federated analytics improves upon prior PETs and keeps health data safe in three ways. First, the data is secured at its point of residence so that external parties cannot access it in any meaningful way. Second, the data is kept secure as parties collaborate to decrease the risk of interception. Finally, the data is secured during computation, reducing the risk of sensitive information extraction. Organizations can also track how the data is used to ensure it is only leveraged for its intended purpose.

Federated analytics software lowers the risks associated with sharing health data by eliminating decryption and movement of raw data, while allowing privacy-intact computations to occur. Additionally, technology improvements driven by federated analytics minimize the computational load necessary to analyze data, which reduces hardware dependency and increases scalability.

Other benefits include access to raw data beyond just structured data, including video, images, and voice data; more secure internal (across regulatory boundaries) collaboration and external (between organizations) collaboration; and a lower chance of non-compliance due to simplified, more cohesive contracting processes. 

Federated analytics is driving healthcare towards the future. By safely scaling access to raw health data, organizations can optimize processes for clinical trials, develop and deploy groundbreaking AI algorithms, and bolster pharmacovigilance. Thanks to the development of federated analytics solutions, there is no longer a need to choose between gaining powerful insights that will shape the future of healthcare and keeping patient data private.

About Dr. Suraj Kapa

As its chief medical officer, Dr. Suraj Kapa, leads healthcare strategy for TripleBlind, the leader in automated, real-time data de-identification. In addition, Dr. Kapa is a board-certified cardiologist with subspecialty certification in cardiac electrophysiology at Mayo Clinic.  Dr. Kapa has published over 200 peer-reviewed articles and book chapters, given hundreds of guest lectures, and filed over 30 patents that serve as the foundation for healthcare startups.

   

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