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Maximize Data Utility - National Cancer Plan

Goal: Secure sharing of privacy-protected health data is standard practice throughout research, and researchers share and use available data to achieve rapid progress against cancer.

A wealth of clinical, genomic, and other health data is collected from patients each day. Ensuring patient privacy and improving data sharing could make these data more readily accessible to researchers, who can use them to find connections or see trends and patterns that could accelerate their research.

A yellow, circular icon with a photo of two women looking over notes. Above them are the words Maximize Data Utility.

The state of maximizing data utility today

Cancer research data may come from experiments, clinical trials, electronic health records (EHRs), and other sources. EHRs, for example, allow a range of patients to provide data from routine clinical care. With EHRs, it is now possible to directly engage patients in data sharing, respect their wishes for how their data are used, and return results to them. However, issues with how data from EHRs are collected and formatted still limit how much they are used in research.

Additionally, new software tools are revolutionizing how we collect, organize, and use data for biomedical research. For example, machine learning algorithms can identify patterns in large, complex datasets and evaluate the likely outcomes of different treatments. However, machine learning tools are only as good as the data they are trained on, so they must be powered by accurate and reliable data that represents the diversity of all of society.

Creating a national data ecosystem for equitably and responsibly collecting and sharing cancer data will also enable scientists and research participants to contribute, access, combine, and analyze diverse data related to cancer.

Strategies to maximize data utility

  • Provide structure to enable data sharing throughout cancer research and build tools that make it easier to use and analyze data to achieve rapid progress.
  • Build and maintain a secure Cancer Research Data Ecosystem that protects patient privacy while collecting, standardizing, and providing access to a broad range of research data.
  • Develop data quality standards, metrics, and practices to promote the use of routine health care data more in research.
  • Engage patients directly in data sharing and respect their wishes for data use.
  • Return individual and study results to research participants.
  • Enable underserved communities and health care organizations with limited resources to engage with and benefit from available data and related scientific advances.

Examples of NCI-supported research to achieve this goal

Examples of activities across the government to achieve this goal

  • The Biomedical Data Fabric Toolbox will help make research data more accessible for the development of advanced health innovations and breakthroughs. ARPA-H is partnering with the National Institutes of Health, NCI, and other agencies to advance this initiative.
  • NCI and the Department of Veterans Affairs have established a data-sharing partnership to exchange cancer registry information, which will support cancer treatment and research efforts.
  • MOSSAIC: Modeling Outcomes Using Surveillance Data and Scalable Artificial Intelligence for Cancer aims to deliver advanced computational and informatics solutions needed to support a comprehensive, scalable, and cost-effective national cancer surveillance program. This is a collaboration between NCI and the Department of Energy.
  • The Research Data Framework (RDaF) Version 2.0, released by the National Institute of Standards and Technology, provides a road map for making health data findable, accessible, interoperable, and reusable to improve cancer research innovation and patient care.
  • USCDI+ Cancer has been launched by the Office of the National Coordinator for Health Information Technology, NCI, and other federal partners to further cancer prevention, diagnosis, treatment, research, and care through the power of standardized data.

Learn more about this goal
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