• Ronilda Lacson, Laila Cochon, Patrick R Ching, Eseosa Odigie, Neena Kapoor, Staci Gagne, Mark M Hammer, and Ramin Khorasani.
• Center for Evidence-Based Imaging, Department of Radiology, Brigham and Women's Hospital, Boston, Massachusetts, USA.
• J Am Med Inform Assoc. 2021 Jan 15; 28 (1): 80-85.

ObjectiveQuantify the integrity, measured as completeness and concordance with a thoracic radiologist, of documenting pulmonary nodule characteristics in CT reports and assess impact on making follow-up recommendations.Materials And MethodsThis Institutional Review Board-approved, retrospective cohort study was performed at an academic medical center. Natural language processing was performed on radiology reports of CT scans of chest, abdomen, or spine completed in 2016 to assess presence of pulmonary nodules, excluding patients with lung cancer, of which 300 reports were randomly sampled to form the study cohort. Documentation of nodule characteristics were manually extracted from reports by 2 authors with 20% overlap. CT images corresponding to 60 randomly selected reports were further reviewed by a thoracic radiologist to record nodule characteristics. Documentation completeness for all characteristics were reported in percentage and compared using χ2 analysis. Concordance with a thoracic radiologist was reported as percentage agreement; impact on making follow-up recommendations was assessed using kappa.ResultsDocumentation completeness for pulmonary nodule characteristics differed across variables (range = 2%-90%, P < .001). Concordance with a thoracic radiologist was 75% for documenting nodule laterality and 29% for size. Follow-up recommendations were in agreement in 67% and 49% of reports when there was lack of completeness and concordance in documenting nodule size, respectively.DiscussionEssential pulmonary nodule characteristics were under-reported, potentially impacting recommendations for pulmonary nodule follow-up.ConclusionLack of documentation of pulmonary nodule characteristics in radiology reports is common, with potential for compromising patient care and clinical decision support tools.© The Author(s) 2020. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.

25 keywords...

hide…