ArticleJournal of the American Medical Informatics Association : JAMIA2011
Developing a natural language processing application for measuring the quality of colonoscopy procedures.
Article in Journal of the American Medical Informatics Association : JAMIA, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
55 citing papers in PubMed, 1 synthesis or guideline pooled it, 100 citations in OpenAlex.
- Emerging applications of NLP and large language models in gastroenterology and hepatology: a systematic review.Frontiers in medicine · 2024Pooled it
- Relationship between detection of adenomas by flexible sigmoidoscopy and interval distal colorectal cancer.Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association · 2013Trial
- Large language models for extracting histopathologic diagnoses of colorectal cancer and dysplasia from electronic health records.BMJ open gastroenterology · 2025Article
- Closing the Gap: A Critical Examination of Adherence, Inconsistency, and Improvements in Colonoscopy Reporting Practices.Digestion · 2024Article
- Development and Validation of an Automated, Real-time Adenoma Detection Rate and Colonoscopy Quality Metrics Calculator.Techniques and innovations in gastrointestinal endoscopy · 2024Article
- Article
- Natural Language Processing-Assisted Classification Models to Confirm Monoclonal Gammopathy of Undetermined Significance and Progression in Veterans' Electronic Health Records.JCO clinical cancer informatics · 2023Article
- Performance of natural language processing in identifying adenomas from colonoscopy reports: a systematic review and meta-analysis.iGIE : innovation, investigation and insights · 2023Article
- Natural Language Processing Can Automate Extraction of Barrett's Esophagus Endoscopy Quality Metrics.medRxiv : the preprint server for health sciences · 2023Article
- Deep learning approach to detection of colonoscopic information from unstructured reports.BMC medical informatics and decision making · 2023Article
- Leveraging Natural Language Processing to Extract Features of Colorectal Polyps From Pathology Reports for Epidemiologic Study.JCO clinical cancer informatics · 2023Article
- A deep learning and natural language processing-based system for automatic identification and surveillance of high-risk patients undergoing upper endoscopy: A multicenter study.EClinicalMedicine · 2022Article
- Tasks as needs: reframing the paradigm of clinical natural language processing research for real-world decision support.Journal of the American Medical Informatics Association : JAMIA · 2022Article
- Leveraging electronic medical record functionality to capture adenoma detection rate.Scientific reports · 2022Article
- Leveraging Electronic Health Records to Measure Low-Value Screening Colonoscopy.The American journal of medicine · 2022Article
- Natural Language Processing for Information Extraction of Gastric Diseases and Its Application in Large-Scale Clinical Research.Journal of clinical medicine · 2022Article
- Natural Language Processing for Assessing Quality Indicators in Free-Text Colonoscopy and Pathology Reports: Development and Usability Study.JMIR medical informatics · 2022Article
- Application of Artificial Intelligence to Clinical Practice in Inflammatory Bowel Disease - What the Clinician Needs to Know.Journal of Crohn's & colitis · 2022Article
- Ascertainment of Delirium Status Using Natural Language Processing From Electronic Health Records.The journals of gerontology. Series A, Biological sciences and medical sciences · 2022Article
- The h-ANN Model: Comprehensive Colonoscopy Concept Compilation Using Combined Contextual Embeddings.Biomedical engineering systems and technologies, international joint conference, BIOSTEC ... revised selected papers. BIOSTEC (Conference) · 2022Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
Abstract
objectiveThe quality of colonoscopy procedures for colorectal cancer screening is often inadequate and varies widely among physicians. Routine measurement of quality is limited by the costs of manual review of free-text patient charts. Our goal was to develop a natural language processing (NLP) application to measure colonoscopy quality. MATERIALS AND
methodsUsing a set of quality measures published by physician specialty societies, we implemented an NLP engine that extracts 21 variables for 19 quality measures from free-text colonoscopy and pathology reports. We evaluated the performance of the NLP engine on a test set of 453 colonoscopy reports and 226 pathology reports, considering accuracy in extracting the values of the target variables from text, and the reliability of the outcomes of the quality measures as computed from the NLP-extracted information.
resultsThe average accuracy of the NLP engine over all variables was 0.89 (range: 0.62-1.0) and the average F measure over all variables was 0.74 (range: 0.49-0.89). The average agreement score, measured as Cohen's κ, between the manually established and NLP-derived outcomes of the quality measures was 0.62 (range: 0.09-0.86). DISCUSSION: For nine of the 19 colonoscopy quality measures, the agreement score was 0.70 or above, which we consider a sufficient score for the NLP-derived outcomes of these measures to be practically useful for quality measurement.
conclusionThe use of NLP for information extraction from free-text colonoscopy and pathology reports creates opportunities for large scale, routine quality measurement, which can support quality improvement in colonoscopy care.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.