2017
DOI: 10.1007/s10278-017-9989-y
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Impact of a Health Information Technology Intervention on the Follow-up Management of Pulmonary Nodules

Abstract: Lung cancer is the leading cause of cancer deaths in the USA. The most common abnormalities suspicious for lung cancer on CT scan include pulmonary nodules. Recommendations to improve care for patients with pulmonary nodules require follow-up management. However, transitions in care, especially for patients undergoing transitions to ambulatory care sites from the emergency department (ED) and inpatient settings, can exacerbate failures in follow-up testing and compromise patient safety. We evaluate the impact … Show more

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Cited by 17 publications
(12 citation statements)
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“…VATS has been fully proved to be effective in removing lesions due to its high safety and minimal invasion [6]. However, due to the limitations of VATS, it is di cult to accurately locate small nonsuper cial pulmonary nodules, which leads to the occurrence of residual nodules after surgery and jeopardize the prognosis [7]. Therefore, how to locate small pulmonary nodules accurately, e ciently and noninvasively becomes one of the keys to successful operation.…”
Section: Discussionmentioning
confidence: 99%
“…VATS has been fully proved to be effective in removing lesions due to its high safety and minimal invasion [6]. However, due to the limitations of VATS, it is di cult to accurately locate small nonsuper cial pulmonary nodules, which leads to the occurrence of residual nodules after surgery and jeopardize the prognosis [7]. Therefore, how to locate small pulmonary nodules accurately, e ciently and noninvasively becomes one of the keys to successful operation.…”
Section: Discussionmentioning
confidence: 99%
“…VATS has been fully proved to be effective in removing lesions due to its high safety and minimal invasion [6]. However, due to the limitations of VATS, it is difficult to accurately locate small non-superficial pulmonary nodules, which leads to the occurrence of residual nodules after surgery and jeopardize the prognosis [7]. Therefore, how to locate small pulmonary nodules accurately, efficiently and noninvasively becomes one of the keys to successful operation.…”
Section: Discussionmentioning
confidence: 99%
“…We used a previously validated information retrieval toolkit, Information from Searching Content with an Ontology-Toolkit (iScout, Boston, Massachusetts), to identify radiology reports for patients with pulmonary nodules and exclude those reports that mentioned lung cancer [19,20]. Lung cancer patients were excluded because they might have a higher follow-up recommendation rate and therefore skew the overall follow-up recommendation rate.…”
Section: Report Classification Using Artificial Intelligencementioning
confidence: 99%
“…To identify which reports contained follow-up recommendations for pulmonary nodules, we used a previously developed support vector machine algorithm to perform natural language processing [21]. We performed a power calculation (33% prevalence [19], power: 0.80, estimated sensitivity: 0.85), yielding a size of 340 testing samples for validation of the machine learning algorithm on our patient cohort. A total of 400 reports were randomly selected and manually annotated for the presence of any follow-up recommendations specifically for pulmonary nodules.…”
Section: Report Classification Using Artificial Intelligencementioning
confidence: 99%