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Leveraging electronic medical record functionality to capture adenoma detection rate.
Jones, Blake; Scott, Frank I; Espinoza, Jeannine; Laborde, Sydney; Chambers, Micah; Wani, Sachin; Edmundowicz, Steven; Austin, Gregory; Pell, Jonathan; Patel, Swati G.
Afiliación
  • Jones B; Division of Gastroenterology & Hepatology, Department of Medicine, University of Colorado School of Medicine, Aurora, CO, USA.
  • Scott FI; Division of Gastroenterology & Hepatology, Department of Medicine, University of Colorado School of Medicine, Aurora, CO, USA.
  • Espinoza J; Division of Gastroenterology & Hepatology, Department of Medicine, University of Colorado School of Medicine, Aurora, CO, USA.
  • Laborde S; Rocky Mountain Regional Veterans Affairs Medical Center, Aurora, CO, USA.
  • Chambers M; Division of Gastroenterology & Hepatology, Department of Medicine, University of Colorado School of Medicine, Aurora, CO, USA.
  • Wani S; Division of Gastroenterology & Hepatology, Department of Medicine, University of Colorado School of Medicine, Aurora, CO, USA.
  • Edmundowicz S; Division of Gastroenterology & Hepatology, Department of Medicine, University of Colorado School of Medicine, Aurora, CO, USA.
  • Austin G; Division of Gastroenterology & Hepatology, Department of Medicine, University of Colorado School of Medicine, Aurora, CO, USA.
  • Pell J; Division of Gastroenterology & Hepatology, Department of Medicine, University of Colorado School of Medicine, Aurora, CO, USA.
  • Patel SG; Division of Hospital Medicine, Department of Medicine, University of Colorado School of Medicine, Aurora, CO, USA.
Sci Rep ; 12(1): 9679, 2022 06 11.
Article en En | MEDLINE | ID: mdl-35690660
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.
Asunto(s)

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Neoplasias Colorrectales / Adenoma Tipo de estudio: Diagnostic_studies / Screening_studies Límite: Humans Idioma: En Revista: Sci Rep Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Neoplasias Colorrectales / Adenoma Tipo de estudio: Diagnostic_studies / Screening_studies Límite: Humans Idioma: En Revista: Sci Rep Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos