Generating and Sharing Computationally Derived, Privacy-preserving Synthetic Clinical Health Data
BE’ER-SHEVA, Israel – June 16, 2020 – In a first-of-its-kind effort, we are excited to share that the National Institutes of Health (NIH) is partnering with MDClone to support national scientific exploration in response to the COVID-19 pandemic. Using MDClone’s platform, NIH will aim to rapidly aggregate clinical health data from multiple regions across the United States and generate non-identifiable synthetic clinical health data for research. This unique public-private collaboration leverages “synthetic data” to protect individual patient privacy while drastically speeding up the compilation and analysis of healthcare data, enabling the development of solutions to combat the pandemic.
Through the NIH and MDClone partnership, a network of academic healthcare sites will generate and share the computationally derived, privacy-preserving synthetic data. Preserving distributions and correlations inside the data, synthetic data makes it possible to conduct complex statistical analyses.
Synthetic data will be used in COVID-19 research priorities, including:
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Types of patients for whom COVID-19 testing can and should impact clinical management
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Predictive models that can anticipate the severity of disease and potential response to therapies
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Clinical best practices to promote better outcomes in utilization and mortality rates
In order to develop these approaches and models, massive volumes of longitudinal patient data, including treatments and outcomes, are needed in amounts that exceed the volume available at an individual hospital. Even if data is compiled across numerous sites, patient privacy regulations generally restrict access to such data. This partnership and the use of synthetic data will create a platform where data can be shared across sites, increasing both the depth and breadth of data that is accessible to researchers. The end result of leveraging MDClone is access to a wider, more useful dataset without privacy risk.
Learn more about the National COVID Cohort Collaborative here.
