Electronic Health Records

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AMIA Challenges FDA over EHR Data Quality Claims

Concerns over EHR data integrity and reliability stem from lack of standardization, certification of health information technology.

By Kyle Murphy, PhD

The American Medical Informatics Association (AMIA) is raising concerns over EHR data quality in current systems in comments on draft guidance issued by the Food & Drug Administration (FDA) for the use of EHR data for clinical investigations.

“As a picture of the future state, this guidance provides an important window into how interoperable EHRs and electronic data capture systems or electronic case reporting forms could be leveraged to simplify data collection, reduce errors and provide healthcare professionals new opportunity to treat emerging issues that arise as part of investigations,” writes AMIA President & CEO Doug Fridsma, MD, PhD, and Board Chair Thomas Payne, MD. “However, we strongly caution FDA from assuming that most EHRs are readily configurable for clinical investigations, even among more advanced institutions.”

At the crux of AMIA’s comments are concerns about EHR data integrity and the role of the federal program for health IT certification in ensuring EHR data reliability.

As the AMIA letter states, the primary purpose of the federal agency’s guidance is to help researchers purpose EHR data as a potential source for FDA-regulated clinical research. The problematic is the fact that EHR data pertains to specific individuals and does not abide by acceptable research standards:

For example, blood pressure (BPs) recordings in the context of RCTs usually have a strict protocol for how values should be taken, time between checks, position of the patient, cuff type, etc. In EHRs, most BPs are recorded in the same field no matter how, when, where or by whom they were recorded. This lack of standardization will be a tremendous challenge for high-quality, rigorous research. Further, ensuring data integrity and tracking data provenance in clinical settings is incredibly complicated because multiple, authorized individuals contribute to the EHR and the specificity of audit logs varies widely. If FDA is interested in which data populated the EDC system or eCRF and where they originated along the continuum of care, the answer could prove extremely difficult and burdensome.

AMIA is advocating instead using data warehouses to ensure data integrity and enable data provenance tracking.

Another provision of the FDA guidance warranted reconsideration according to AMIA is its assumptions about the role of the Health IT Certification Program at the Office of the National Coordinator for Health Information Technology (ONC) in ensuring the reliability of EHR data:

ONC’s Health IT Certification Program is not designed to ensure data “reliability” or integrity. Indeed, such integrity and reliability is generally the result of the policies, procedures and actions of the EHR users rather than the technology itself, and we see this guidance overstating the ability of certification to deliver clinical investigation-quality data as a byproduct of care delivery. Further, our members note a general lack of consensus on IT standards used by private sector actors to render clinical data useful for research, which adds to the variability of data quality and potential approaches meant to mitigate data integrity deficiencies.

What’s needed, says AMIA, is collaboration between FDA and ONC to determine the role of certification in making robust standardized EHR data available for clinical investigations.

Among other criticisms of the FDA guidance, AMIA lists compliance confusion stemming from an inability to track EHR data modifications and purpose future use cases (e.g., genomics, precision medicine) that would warrant updates to any federal guidance on the uses of EHR data beyond the provision of patient care.

Given reported high rates of EHR adoption by hospitals and physicians and the stores of data these systems must maintain, the time appears ripe for ensuring that secondary and tertiary uses of EHR data don’t prove fruitless.




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