- The National Institutes of Health has adopted a five-pronged strategy to modernize its biomedical data ecosystem and keep pace with advances in data science.
- The agency’s strategic plan, released Monday, points in particular to the rapid growth in EHR and genomic data. And it calls for better data analysis tools for basic scientists and clinicians.
- “Our nation and the world stand at a unique moment of opportunity in biomedical research, and data science is an integral contributor,” the plan states. “Understanding basic biological mechanisms through NIH-funded research depends upon vast amounts of data and has propelled biomedicine into the sphere of ‘Big Data’ along with other sectors of the national and global economies.”
NIH and the biomedical research community face a number of challenges in managing and using the growing amounts of biomedical data, according to the plan. These include the costs of managing data, the current siloing of data within different parts of the ecosystem, lack of interoperability between disparate formats making it difficult to share and find datasets, and co-mingling of funding for tool development and data resources.
Data science is also challenged by the lack of a general system to transform novel algorithms and tools into “enterprise-ready resources that meet industry standards of ease of us and efficiency of operation,” the plan says.
Those themes echo what Allscripts CEO Paul Black said last month at the HLTH inaugural conference in Las Vegas. If data’s potential are to be maximized, they must be both useful and relevant to how physicians practice and presented in a format users enjoy.
He didn't stop there. Ideally, consumers should be connected with their genetic information to better understand and take responsibility for their health. “The connection of the digital framework with interoperability getting all the data in a way that makes sense to caregivers and to consumers, and getting consumers connected to their DNA, will have a transformative effect long term,” Black said.
The NIH plan envisions five key goals:
- Develop a highly efficient and effective biomedical research data infrastructure.
- Promote modernization of the data-resources ecosystem.
- Support development and dissemination of advanced data management, analytics and visualization tools.
- Enhance workforce development for biomedical data science.
- Enact appropriate policies to promote stewardship and sustainability.
The plan also calls for biomedical research data to adhere to FAIR principles — or findable, accessible, interoperable and reusable.
“The ability to experiment with new ways to optimize technology-intensive research will inform decisions regarding future policies, approaches, and business practices, and will allow NIH to adopt more cost-effective ways to capture, access, sustain, and reuse high-value biomedical data resources in the future,” the plan states. “To this end, NIH must weave its existing data-science efforts into the larger data ecosystem and fully intends to take advantage of current and emerging data-management and technological expertise, computational platforms, and tools available from the commercial sector through a variety of innovative public-private partnerships.”
To accomplish these goals, NIH is hiring a chief data strategist who will collaborate with working groups of the NIH Scientific Data Council and NIH Data Science Policy Council, as well as other public and private stakeholders both in the U.S. and abroad. A major aspect of the plan is industry engagement and drawing on industry expertise in information technology, NIH said.