ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2019
Natural Language Processing Accurately Identifies Dysphagia Indications for Esophagogastroduodenoscopy Procedures in a Large US Integrated Healthcare System: Implications for Classifying Overuse and Quality Measurement.
Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
What it found
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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
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A foundation systematic review of natural language processing applied to gastroenterology & hepatology.BMC gastroenterology · 2025Pooled it
- Unstructured Electronic Health Records of Dysphagic Patients Analyzed by Large Language Models.IEEE journal of translational engineering in health and medicine · 2025Article
- Developing an electronic health record measure of low-value esophagogastroduodenoscopy for GERD at a large academic health system.BMJ open quality · 2023Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recent evidence suggests almost half of repeat esophagogastroduodenoscopy procedures (EGDs) are overused; this prior research relied on administrative data that are often inaccurate. Our primary objective was to determine and compare the accuracy of natural language processing and administrative data to manual chart review to identify dysphagia indications for EGD procedures within the national VA healthcare system. From 396,856 EGD notes identified from 2008-2014, we classified 119,920 as "index" procedures in 2010-2012. We compared the performance of our NLP to ICD codes to correctly identify dysphagia indications in the index EGD procedures and in repeat EGD procedures. We used linked pathology data to describe esophageal biopsies performed during these EGDs. NLP performed significantly better and identified significantly more index and repeat EGD procedures with dysphagia indications than ICD codes, which has critical implications for determining appropriateness of EGD procedures.
Identifiers
31259022PMC6568132What OpenQuestion holds
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.