Problem solved: How we built a trusted data platform that produces accurate healthcare insights

So far in this blog series, I’ve shared the key differences between a data platform and a healthcare data platform in part one. In part two, I dove deeper into why interoperability, data normalization and knowledge management - along with AI - are critical capabilities that must be built into a healthcare data platform.

In the final installment of this series, I want to share why healthcare data platforms must be designed with data privacy, compliance and security as strategic priorities and not just tactical necessities. 

Why are data privacy, compliance and security crucial components of a healthcare data platform?

Health data is some of the most personal information in a patient’s life. In the modern healthcare ecosystem, that data is widely dispersed across health system networks, labs, physician offices, online portals, and increasingly in the cloud. 

Patients need to trust in the security and privacy of their data—just as much as they need to trust those who care for them. 

It’s therefore paramount that healthcare data platforms include data privacy and compliance safeguards, including access management, data life cycle management, data de-identification, service management that supports user experience, measurement and monitoring, and more. Platforms also need the flexibility to grow and adapt to new regulatory requirements as compliance issues are fluid and ever-changing. 

Moreover, it’s becoming increasingly common for attackers to use sophisticated AI tools in their malicious efforts to gain access to patient data, which is why healthcare data platforms need to “fight fire with fire,” incorporating AI into their information security strategies. The risks involved with super-intelligent AI attacks could be potentially more damaging than traditional cybersecurity threats. 

In the end, privacy and security must be thought of as strategic priorities and not just tactical necessities. They should be embedded in your platform and engineered to scale with the evolving threat landscape.

When patients can rest assured their personal data is highly secured and protected, they'll feel better about their overall care experience. And that can only lead to improved outcomes.

When patients can rest assured their personal data is highly secured and protected, they’ll feel better about their overall care experience. And that can only lead to improved outcomes. 

As data has become integral to health, so too has platform technology to enable the use of that data. But traditional platforms are not structured to meet the needs of ever more complex healthcare data ecosystems.

A strategy is required in which platforms are dedicated to the challenges faced by health systems and life science companies. Platforms must be engineered, from the ground up, to incorporate innovative technologies such as interoperability, data normalization and knowledge management. As well as data quality capabilities that leverage tools such as artificial intelligence, machine learning, natural language processing and more. 

If the intent is to gain deeper insights into every patient’s journey and to use those insights to advance care and save lives, such platforms are not just hypothetical—they are a must-have as data becomes more and more integral to the delivery of care. And they are here today. 

Discover how Syapse Raydar, the Syapse data platform, was designed to transform real-world data into actionable insights that reduce the fear and burden of serious disease. Learn more about Raydar here: https://info.syapse.com/syapse-raydar