Nodule net: A centralized prospective lung nodule tracking and safety-net program. (February 2022) - Singh, Harpreet; Koster, Megan; Jani, Chinmay; Rupal, Arashdeep; Walker, Alexander; Khoory, Joseph; Tewari, Arti; Casasola, Marcel; Ranker, Lynsie R.; Thomson, Carey
Abstract: Background: Inadequate follow-up of suspicious lung nodules can result in diagnostic delays and potential progression to advanced lung cancer. In 2015, a multidisciplinary lung nodule management program, Nodule Net, was implemented to increase the timely follow-up rate. In this study, we sought to evaluate the effectiveness of the program. Methods: 2398 chest CT reports were reviewed for the presence of a lung nodule. Baseline demographics, nodule characteristics, and follow-up recommendations were collected. For reports that did not include structured recommendations, Fleischner Society guidelines were applied if appropriate. The rate of follow-up imaging was recorded and compared with historical rates. Results: Lung nodules were reported on 1367 (57%) of scans. Of the 632 participants with recommendations for follow-up, the Nodule Net nurse navigator was notified on 523 (83%). Of these, 408 (78%) completed follow-up, compared to 57/109 (52%) in those who were not reported to Nodule Net tracking system (risk ratio: 1.49, 95% CI: 1.24–1.79, p-value < 0.05). Out of these 408, nodule net outreach was required to prompt the follow-up in 116 (28%). Of these, a lung malignancy was diagnosed in 4 (4%). Conclusions: Management of lung nodules is a complex process. Implementation of a lung nodule tracking program led to a significant increase in the completion of recommended follow-up imaging compared with usual care. Developing a comprehensive lung nodule program using an automated software system rather than manual processes to refer and track incidental findings may further reduce barriers to completion of follow-up. Highlights: Management of indeterminate lung nodules is a complex process. Only one-third of lung nodules receive appropriate and timely surveillance. A multidisciplinary lung nodule tracking program improves quality of surveillance. Artificial intelligence can ensure efficient identification and tracking.