Scientific Reports (Jun 2022)

Leveraging electronic medical record functionality to capture adenoma detection rate

  • Blake Jones,
  • Frank I. Scott,
  • Jeannine Espinoza,
  • Sydney Laborde,
  • Micah Chambers,
  • Sachin Wani,
  • Steven Edmundowicz,
  • Gregory Austin,
  • Jonathan Pell,
  • Swati G. Patel

DOI
https://doi.org/10.1038/s41598-022-13943-2
Journal volume & issue
Vol. 12, no. 1
pp. 1 – 5

Abstract

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Abstract Measuring the adenoma detection rate (ADR) is critical to providing quality care, however it is also challenging. We aimed to develop a tool using pre-existing electronic health record (EHR) functions to accurately and easily measure total ADR and to provide real-time feedback for endoscopists. We utilized the Epic EHR. With the help of an Epic analyst, using existing tools, we developed a method by which endoscopy staff could mark whether an adenoma was detected for a given colonoscopy. Using these responses and all colonoscopies performed by the endoscopist recorded in the EHR, ADR was calculated in a report and displayed to endoscopists within the EHR. One endoscopist piloted the tool, and results of the tool were validated against a manual chart review. Over the pilot period the endoscopist performed 145 colonoscopies, of which 78 had adenomas. The tool correctly identified 76/78 colonoscopies with an adenoma and 67/67 of colonoscopies with no adenomas (97.4% sensitivity, 100% specificity, 98% accuracy). There was no difference in ADR as determined by the tool compared to manual review (53.1% vs. 53.8%, p = 0.912). We successfully developed and pilot tested a tool to measure ADR using existing EHR functionality.