P-1371. Real-World Performance of the "TB or Not TB" Tuberculosis Diagnostic Clinical Decision Support System
Caitlin Dugdale, Kimon C Zachary, Lindsay Germaine, Chloe V Green, Rocio M Hurtado, Emily P Hyle, Michelle S Jerry, Jacob E Lazarus, Stephen Maxfield, Molly Paras, Katherine Swanson, Erica S Shenoy

TL;DR
A tuberculosis diagnostic tool was tested in real-world settings and showed high accuracy in identifying TB cases.
Contribution
The study evaluates the real-world performance of the TBorNotTB CDSS in a low-prevalence setting.
Findings
The CDSS had 100% sensitivity and 60% specificity in detecting tuberculosis.
The area under the curve (AUC) of the CDSS was 0.84.
The tool could help reduce nosocomial TB transmission risks and infection control workload.
Abstract
We implemented a validated clinical decision support system (CDSS) to guide clinicians through the diagnostic evaluation of individuals with suspected active tuberculosis across the Mass General Brigham System (MGB) in August 2024. TBorNotTB assigns points based on epidemiologic risk factors, tuberculosis history, symptoms, chest imaging, and sputum/bronchoscopy results. If the CDSS score is < 1, the evaluation is complete and airborne infection isolation (AII) precautions are discontinued; otherwise, additional evaluation is recommended, including review by infection control personnel. Our objective was to assess early real-world CDSS performance. We conducted a prospective study of MGB patients for whom the TBorNotTB CDSS was used from August 2024-January 2025. We evaluated the frequency of CDSS use and the sensitivity, specificity, and the area under the curve (AUC) of the CDSS to…
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Taxonomy
TopicsTuberculosis Research and Epidemiology · COVID-19 diagnosis using AI · Clinical Reasoning and Diagnostic Skills
