Healthcare data are plentiful now. Why isn't it easier for researchers to use it?

Data from electronic health records was supposed to revolutionize research. But U.S. regulations around healthcare data are holding the market back, according to a recent study published in the Journal of the American Medical Informatics Association.

Lack of interoperability between EHRs is only part of the problem, the study said. 

U.S. regulatory standards also aren't set up to enable evidence-based medicine (EBM) and evidence-generating medicine (EGM) data. Multisite research is hard to pull off when the sites' data standards are incompatible.

"Agreement on standards is foundational to realizing the potential benefits of IT. As tools for care delivery, EHRs are not readily configured to facilitate EGM or supplemental uses of patient data for research, even when a patient explicitly wants to enable that use," AMIA researchers wrote in the study.

To make matters worse, the clinical and research workforce isn't sufficiently trained in informatics. Even institutional review board staff and data governors usually aren't explicitly trained in informatics-driven research methodologies, the study said.

"The healthcare and research enterprise envisioned for the 21st century will require a workforce competence beyond the mechanics of health IT and health information management," researchers wrote. "'Informatics literacy' includes awareness of specific data standards and their importance to multisite research, the mechanics of data sharing, and the fulfillment of user needs that are specific to EBM, EGM and learning cycles."

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AMIA suggested several policies the U.S. could adopt to improve the landscape for research on health data:

  • Develop standards for the vocabulary, format and transport of healthcare data. This would properly configure EHRs to facilitate EGM, the researchers said.
  • Fund recruitment and educational programs through federal appropriations. Informatics professionals should be spread across all IRBs and data stewards, the study said, but that depends on having a trained workforce.
  • Standardize technical aspects of data governance like metadata and patient identifiers. These frameworks can be informed by the NIH Health Care Systems Research Collaboratory, the study recommended.
  • Fund large-scale infrastructure that can be shared among private sector and federal agencies. 
  • Enable the reuse of data through sharing plans and "harmonized data management." The benefits of federally funded research should be as diffuse as possible, the study said, rather than centralized on the awardees that conducted the research.

AMIA defined EGM as the “systematic incorporation of research and quality improvement considerations into the organization and practice of healthcare in order to advance biomedical science and thereby improve the health of individuals and populations.” 

By furthering data standards in the ways suggested, the government can increasingly converge research and clinical decision-making.