National Health Insurance Service Ilsan Hospital Reports Findings in Pneumothorax (Impact of Deep Learning-Based Computer-Aided Detection and Electronic Notification System for Pneumothorax on Time to Treatment: Clinical Implementation): Respiratory Tract Diseases and Conditions - Pneumothorax - Insurance News | InsuranceNewsNet

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November 28, 2024 Newswires
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National Health Insurance Service Ilsan Hospital Reports Findings in Pneumothorax (Impact of Deep Learning-Based Computer-Aided Detection and Electronic Notification System for Pneumothorax on Time to Treatment: Clinical Implementation): Respiratory Tract Diseases and Conditions – Pneumothorax

South Korea Daily Report

2024 NOV 28 (NewsRx) -- By a News Reporter-Staff News Editor at South Korea Daily Report -- New research on Respiratory Tract Diseases and Conditions - Pneumothorax is the subject of a report. According to news reporting out of Goyang, South Korea, by NewsRx editors, research stated, “To assess whether the implementation of deep learning (DL) computer-aided detection (CAD) that screens for suspected pneumothorax (PTX) on chest radiography (CXR) combined with an electronic notification system (ENS) that simultaneously alerts both the radiologist and the referring clinician would affect time to treatment (TTT) in a real-world clinical practice. In May 2022, a commercial deep learning-based CAD and ENS (DL-CAD-ENS) was introduced for all CXRs at an 818-bed general hospital, with 33 attending doctors and their residents using ENS, while 155 others used only CAD.”

Our news journalists obtained a quote from the research from National Health Insurance Service Ilsan Hospital, “We used difference-in-differences estimates to compare TTT between the CAD and ENS group and the CAD-only group for the period from January 2018 to April 2022 and from May 2022 to April 2023. A total of 603,028 CXRs from 140,841 unique patients were included, with a PTX prevalence of 2.0%. There was a significant reduction in TTT for supplemental oxygen therapy for the CAD and ENS group compared with the CAD-only group in the post-implementation period (-143.8 min; 95% confidence interval [CI], -277.8 to -9.9; P = .035). However, there was no significant difference in TTT for other treatments, including aspiration or tube-thoracostomy (14.4 min; 95% CI, -35.0 to 63.9) and consultation with the thoracic and cardiovascular surgery department (86.3 min; 95% CI, -175.1 to 347.6).”

According to the news editors, the research concluded: “The introduction of a DL-CAD-ENS reduced the time to initiate oxygen supplementation for patients with PTX.”

This research has been peer-reviewed.

For more information on this research see: Impact of Deep Learning-Based Computer-Aided Detection and Electronic Notification System for Pneumothorax on Time to Treatment: Clinical Implementation. Journal of the American College of Radiology, 2024. Journal of the American College of Radiology can be contacted at: Elsevier Science Inc, Ste 800, 230 Park Ave, New York, NY 10169, USA. (Elsevier - www.elsevier.com; Journal of the American College of Radiology - http://www.journals.elsevier.com/journal-of-the-american-college-of-radiology/)

Our news journalists report that additional information may be obtained by contacting Si Nae Oh, Dept. of Family Medicine, National Health Insurance Service Ilsan Hospital, Goyang, South Korea. Additional authors for this research include Hyungkook Yang, Chun Kyon Lee, Sang-Hoon Park, Chang-Hoon Han, Ho Heo and Young Sung Kim.

Publisher contact information for the Journal of the American College of Radiology is: Elsevier Science Inc, Ste 800, 230 Park Ave, New York, NY 10169, USA.

(Our reports deliver fact-based news of research and discoveries from around the world.)

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