Study Identifies Barriers to EHR Usage for Pragmatic Clinical Trials

Oct. 8, 2021
NIH Collaboratory survey finds inadequate collection of patient-centered data, lack of functionality for structured data collection and lack of standardization

A National Institutes of Health Collaboratory study has identified several challenges encountered when using the electronic health record (EHR) for pragmatic clinical research.

Since 2012, the NIH’s Health Care Systems Research Collaboratory has served as the resource coordinating center for 21 pragmatic clinical trial demonstration projects. (Pragmatic trials evaluate the effectiveness of interventions in real-life practice conditions.)

The EHR Core working group invited these demonstration projects to complete a written semi-structured survey and used an inductive approach to review responses and identify EHR-related challenges and suggested EHR enhancements.

The challenges identified by the projects included inadequate collection of patient-centered data, lack of functionality for structured data collection, lack of standardization, lack of resources to support customization, difficulties aggregating data from multiple sites, and difficult and inefficient access to EHR data.

The goal of the study was to elucidate challenges and develop solutions—or prerequisites for pragmatic research—to enable healthcare system leaders, policy makers, and EHR designers to improve the national capacity for generating real-world evidence.

An article on the survey and analysis was recently published in the Journal of American Medical Informatics Association (JAMIA).

Researchers from the NIH Collaboratory’s EHR Core and colleagues from the Patient-Centered Outcomes and the Health Care Systems Interactions Core Working Groups worked on possible solutions. The authors developed the following prerequisites for the conduct of pragmatic research:

  • Integrate collection of patient-centered data into EHR systems
  • Facilitate structured research data collection by leveraging standard EHR functions, usable interfaces, and standard workflows
  • Support creation of high-quality research data by using standards
  • Ensure adequate IT staff to support embedded research
  • Create aggregate, multidata type resources for multisite trials
  • Create reusable and automated queries

The authors argue for the ability to tailor EHR systems to enable the collection of patient-centered outcomes and the extraction of high-quality, standardized data. Although the primary uses of the data are for clinical care and billing, the authors noted, high-quality data from the EHR also have the potential to improve clinical care and population health by providing reliable evidence and to support pragmatic research and learning within and across healthcare systems.

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