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AI-Powered Clinical Documentation Tool Reduces EHR Time for Clinicians


 

TOPLINE:

An artificial intelligence (AI)-powered clinical documentation tool helped reduce time spent on electronic health records (EHR) at home for almost 48% physicians, and nearly 45% reported less weekly time spent on EHR tasks outside of normal work hours.

METHODOLOGY:

  • Researchers recruited 112 clinicians from family medicine, internal medicine, and general pediatrics in North Carolina and Georgia.
  • Patients were divided into an intervention group (n = 85) and control group (n = 55), with the intervention group receiving a 1-hour training program on a commercially available AI tool.
  • A seven-question survey was administered to participants before and 5 weeks after the intervention to evaluate their experience.

TAKEAWAY:

  • The researchers found 47.1% of clinicians in the intervention group reported spending less time on the EHR at home compared with 14.5% in the control group (P < .001); 44.7% reported decreased weekly time on the EHR outside normal work hours compared with 20% in the control group (P = .003).
  • The study revealed 43.5% of physicians who used the AI instrument reported spending less time on documentation after visits compared with 18.2% in the control group (P = .002).
  • Further, 44.7% reported less frustration when using the EHR compared with 14.5% in the control group (P < .001).

IN PRACTICE:

“Approximately half of clinicians using the AI-powered clinical documentation tool based on interest reported a positive outcome, potentially reducing burnout. However, a significant subset did not find time-saving benefits or improved EHR experience,” the authors of the study wrote.

SOURCE:

The study was led by Tsai-Ling Liu, PhD, Center for Health System Sciences, Atrium Health in Charlotte, North Carolina. It was published online in JAMA Network Open.

LIMITATIONS:

The researchers reported potential selection and recall bias in both groups. Additional research is needed to find areas of improvement and assess the effects on clinician groups and health systems, they said.

DISCLOSURES:

Andrew McWilliams, MD, MPH, reported receiving grants from the Agency for Healthcare Research Quality, the National Institutes of Health, and the Duke Endowment unrelated to this work. Ajay Dharod, MD, reported his role as an electronic health record consultant for the Association of American Medical College CORE program. Jeffrey Cleveland, MD, disclosed his participation on the Executive Client Council, a noncompensated advisory group, for Nuance/Microsoft.

This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article first appeared on Medscape.com.

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