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determining post-test risk in a national sample of stress nuclear myocardial perfusion imaging reports: implications for natural language processing tools
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نویسنده
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levy andrew e. ,shah nishant r. ,matheny michael e. ,reeves ruth m. ,gobbel glenn t. ,bradley steven m.
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منبع
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journal of nuclear cardiology - 2019 - دوره : 26 - شماره : 6 - صفحه:1878 -1885
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چکیده
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Reporting standards promote clarity and consistency of stress myocardial perfusion imaging (mpi) reports, but do not require an assessment of post-test risk. natural language processing (nlp) tools could potentially help estimate this risk, yet it is unknown whether reports contain adequate descriptive data to use nlp. among va patients who underwent stress mpi and coronary angiography between 1, 2009 and 31, 2011, 99 stress test reports were randomly selected for analysis. two reviewers independently categorized each report for the presence of critical data elements essential to describing post-test ischemic risk. few stress mpi reports provided a formal assessment of post-test risk within the impression section (3%) or the entire document (4%). in most cases, risk was determinable by combining critical data elements (74% impression, 98% whole). if ischemic risk was not determinable (25% impression, 2% whole), inadequate description of systolic function (9% impression, 1% whole) and inadequate description of ischemia (5% impression, 1% whole) were most commonly implicated. post-test ischemic risk was determinable but rarely reported in this sample of stress mpi reports. this supports the potential use of nlp to help clarify risk. further study of nlp in this context is needed.
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کلیدواژه
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facilitated reporting ,nuclear cardiology ,electronic clinical decision support ,natural language processing
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آدرس
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university of colorado school of medicine, division of cardiology, department of medicine, usa. denver, brown university alpert medical school, division of cardiology, department of medicine, usa. brown university school of public health, center for evidence synthesis in health, department of health services, usa, health services research & development, va tennessee valley healthcare system, usa. vanderbilt university school of medicine, department of biomedical informatics, usa, health services research & development, va tennessee valley healthcare system, usa. vanderbilt university school of medicine, department of biomedical informatics, usa, health services research & development, va tennessee valley healthcare system, usa. vanderbilt university school of medicine, department of biomedical informatics, usa, cardiovascular medicine, va eastern colorado healthcare system, usa. minneapolis heart institute, center for healthcare delivery innovation, usa
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Authors
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