One of the biggest hurdles health providers face is harnessing the multitude of data to ask and answer important questions – and ultimately improve the care they provide.
Healthcare data are among the most sensitive and protected information in our society. Regulations, data structure and technical resources make it challenging to ensure that patient privacy and confidentiality are protected while making data available to physicians, scientists, and healthcare administrators for analyses that can improve patient care and streamline hospital or clinic operations.
Often, investigators must wait weeks or months to begin research projects involving real patients. Synthetic data speed up that process, accelerating the future of healthcare delivery.
What is synthetic data?
A synthetic data set has the same statistical characteristics as original patient data from which it is derived, but there are no real patients in the synthetic data set and no identifying information that would allow it to be connected back to individual patients.
To preserve patient privacy, MDClone creates synthetic derivatives of healthcare data collected from actual patient populations. The synthetic datasets share virtually identical statistical properties as the original data, so they can be analyzed as if they were the original data but without any patient privacy concerns.
How is synthetic data created?
Synthetic data is created from data collected from actual patient populations.
The innovative MDClone ADAMS platform creates a new population that mirrors the statistical characteristics of the original population, but it is populated with synthetic patients.
Why is synthetic data important?
Understanding data can lead to better patient outcomes as well as significant cost and resource savings for hospitals and health systems.
Synthetic data accelerates discovery. Because any research conducted from synthetic data derivatives are not considered to be that of human subjects, researchers can often test ideas without institutional review board (IRB) approval. This gives researchers and clinicians the ability to fast-track research and test theories immediately.
“The beauty of synthetic data is that it allows us to quickly create data sets that look and feel just like the real data that are generated every time we interact with patients,” said Philip R.O. Payne, PhD, FACMI, FAMIA, director of Washington University’s Institute of Informatics. “Synthetic data is really a game changer.”
How is synthetic data different from de-identified data?
De-identified data strips certain data elements away to protect patient privacy. It may sometimes be possible to re-identify an individual from de-identified data by inferring characteristics, cross-referencing data similarities or reversing the data approach.
Synthetic does not strip any critical data elements away. The synthetic patient population has the same overall characteristics as the original patients, but patients cannot be re-identified because there is no one-to-one correspondence between patients in the synthetic populations and those in the original. Therefore, the data is statistically accurate, protects patients and creates tremendous opportunity to advance patient outcomes at a rapid pace.
What are the benefits of synthetic data?
Synthetic data provides a remarkable benefit to researchers, clinicians and hospitals, who, for decades, have been balancing patient privacy, legal, compliance and security issues in their quest to improve patient care and enhance clinical care.
Synthetic data allows for rapid discovery and prototyping of heavily regulated and protected data. It empowers researchers to quickly organize and access information, explore ideas and find insights that power research, drive better patient outcomes and create impactful healthcare innovation.
It is the maximum use of the data without risk to patient privacy, therefore reducing the timeline of discovery from years to days or even to hours.
Access to comprehensive patient data is critical for healthcare advancement. However, clinicians and healthcare organizations have struggled to access and manage the volume and variety of data available.
The MDClone ADAMS Platform overcomes these common obstacles by allowing users to safely and securely access and share information using synthetic data.
With synthetic data, you can:
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Explore data with generally fewer IRB constraints
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Access data instantly
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Explore data dynamically
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Maintain patient privacy
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Share synthetic data worldwide
“The fact that we have a research tool now that also protects patient privacy is inspiring,” said Dr. Alan Forster, Vice President of Innovation & Quality at The Ottawa Hospital. “Synthetic data, along with the MDClone data engine, is a game changer. I do not think that other products can boast what they’ve done.”
Unlike traditional analytics platforms, the MDClone ADAMS Platform is the only global, self-service environment that enables a dynamic process for exploration, collaboration and action.
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Synthetic data capabilities for healthcare opens a world of opportunities for both internal and external benefits, impacting all areas of healthcare. Research has proven it’s reliability and organizations worldwide are already benefiting from this powerful feature to unlock their data.
Want to dive in and see synthetic data in action? Schedule a demo and we’ll walk you through the process:
