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Detection and Isolation of Cancer in Prostate Biopsies Using Stimulated Raman Histology and Artificial Intelligence

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An Accurate and Automated Method for Adenoma Detection Rate and Report Card Generation Utilizing Common Electronic

Eric K Ganguly¹, Luke Purvis², Nathan Reynolds³

¹Division of Gastroenterology and Hepatology.

Journal of Clinical Gastroenterology

|August 30, 2023

Summary

An automated method was developed to calculate Adenoma Detection Rate (ADR) using electronic health records (EHRs), improving colonoscopy quality assessment. This system accurately measures ADR and generates report cards, enhancing colorectal cancer screening efficiency.

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Area of Science:

Gastroenterology
Health Informatics
Medical Quality Improvement

Background:

Adenoma Detection Rate (ADR) is a key colonoscopy quality metric linked to reduced colorectal cancer incidence.
Measuring and disseminating ADR is challenging due to fragmented electronic data systems.

Purpose of the Study:

To create an automated system for calculating ADR and generating report cards.
To leverage common electronic health records (EHRs) for improved quality assessment.

Main Methods:

Integrated data from endoscopy software (Endosoft) and pathology systems (Beaker) within Epic EHR.
Developed a natural language processing (NLP) algorithm to identify adenomatous polyps in pathology reports.
Automated ADR calculation and report card generation using Epic's Crystal Reports feature.

Main Results:

The NLP algorithm achieved 100% sensitivity, specificity, and accuracy for ADR identification.
Automatically calculated ADR for 12 endoscopists, with an overall ADR of 34% from 2,276 procedures.
Successfully generated and distributed ADR report cards via secure email within the EHR.

Conclusions:

Developed an accurate, automated, and scalable process for ADR calculation and reporting using integrated EHR data.
This methodology enhances colonoscopy quality care by streamlining ADR data collection and report dissemination.