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Development and Validation of an Automated, Real-time Adenoma Detection Rate and Colonoscopy Quality Metrics
Todd A Brenner1, Branislav Bujnak2, Matthew Alverson3
1Division of Gastroenterology, Johns Hopkins Hospital, Baltimore, Maryland.
Background And Aims:
High-quality colonoscopy reduces the risk of death from colorectal cancer. The adenoma detection rate (ADR) is the principal measure of colonoscopy quality but is onerous to calculate. We report the development of a fully automated platform for calculation of the ADR and other key colonoscopy quality indicators without the need for manual data entry.
Methods:
Endoscopy and pathology reports from 6 centers were collected over a 3-month period and collated using a novel data transfer interface. Text-based classification parameters were developed to identify average-risk screening colonoscopies, adenomatous pathology, cecal intubation, and withdrawal time. Automated quality metrics calculators based on these classifications were built into a web-based reporting platform, and the resulting quality metrics were benchmarked against those produced through a manual record review. Confirmation of the calculator's performance was performed in a validation cohort with data collected over a 1-month period, 6 months after the initial study.
Results:
The study included 3809 colonoscopies (mean age 56.1 ± 6.40 years, 53.7% female, 38 endoscopists). The automated calculator yielded an ADR of 45.1% compared with 44.3% on manual review. Correct classification of ADR-qualifying screening colonoscopies was achieved with high predictive value, with a sensitivity of 0.918 and specificity of 1.0. The cecal intubation rate was 95.8%, and the average withdrawal time was 10:05 minutes.
Conclusion:
We demonstrate the feasibility and performance of a colonoscopy quality reporting platform capable of calculating the ADR and other key metrics using novel, fully automated pathology report integration and a text query-based classification accessible in a wide range of practice settings.
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