Determining post-test risk in a national sample of stress nuclear myocardial perfusion imaging reports: Implications for natural language processing tools

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 descript...

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Bibliographic Details
Published in:Journal of nuclear cardiology 2019-12, Vol.26 (6), p.1878-1885
Main Authors: Levy, Andrew E., Shah, Nishant R., Matheny, Michael E., Reeves, Ruth M., Gobbel, Glenn T., Bradley, Steven M.
Format: Article
Language:English
Subjects:
Cardiology
Coronary Angiography
Electronic clinical decision support
Exercise Test
Facilitated reporting
Heart Diseases - diagnostic imaging
Humans
Imaging
Medicine
Medicine & Public Health
Myocardial Infarction - diagnostic imaging
Myocardial Ischemia - diagnostic imaging
Myocardial Perfusion Imaging
Natural Language Processing
Nuclear cardiology
Nuclear Medicine
Original Article
Radiology
Risk Assessment - methods
United States
United States Department of Veterans Affairs
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Summary: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 January 1, 2009 and December 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.
ISSN:1071-3581
1532-6551
DOI:10.1007/s12350-018-1275-y