Abstract
To describe the implementation of a standardized code system for notification of relevant expected or incidental findings in imaging exams and use of an automated textual mining tool of radiological report narratives, created to facilitate directing patients to specific lines of care, reducing the waiting time for interventions, consultations, and minimizing delays to treatment. We report our 12-month initial experience with the process. A standardized code was attached to every radiology report when a relevant finding was observed. On a daily basis, the notifications was sent to a dedicated medical team to review the notified abnormality and decide a proper action. Between October 1, 2020, and September 30, 2021, 40,296 sectional examinations (CT and MR scans) were evaluated in 35,944 patients. The main findings reported were calcified plaques on the trunk of the left coronary artery or trunk like, pulmonary nodule/mass and suspected liver disease. Data of follow-up was available in 10,019 patients. The age ranged from 24 to 101 years (mean of 71.3 years) and 6,626 were female (66.1%). In 2,548 patients a complementary study or procedure was indicated, and 3,300 patients were referred to a specialist. Customized database searches looking for critical or relevant findings may facilitate patient referral to specific care lines, reduce the waiting time for interventions or consultations, and minimize delays to treatment.
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All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by ENOF, FPM and MFAA. The first draft of the manuscript was written by FPM, MFAA and PNVPB. All authors read and approved the final manuscript.
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This research received approval from the institution’s Research Ethics Committee (CAAE 43084721.0.0000.8114, approved on February 24, 2021).
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de Oliveira Filho, E.N., Machado, F.P., Almeida, M.F.A. et al. Automated Notification of Relevant Expected or Incidental Findings in Imaging Exams in a Verticalized Healthcare System. J Med Syst 46, 55 (2022). https://doi.org/10.1007/s10916-022-01842-y
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DOI: https://doi.org/10.1007/s10916-022-01842-y