Nodule net: A prospective safety net program to reduce loss to follow-up and increase early detection of lung cancer.

Authors

Harpreet Singh

Harpreet Singh

Froedtert and Medical College of Wisconsin, Milwaukee, WI

Harpreet Singh , Chinmay Jani , Arashdeep Rupal , Arti Tewari , Alexander Walker , Marcel Casasola , Joseph Khoory , Lynsie Ranker , Megan Koster , Carey Thomson

Organizations

Froedtert and Medical College of Wisconsin, Milwaukee, WI, Department of Medicine, Mount Auburn Hospital, Cambridge, MA, Harvard Medical School, Boston, MA, Mayo Clinic, Rochester, MN, Mount Auburn Hospital, Cambridge, MA, Institute of Community Health, Boston, MA

Research Funding

No funding received
None

Background: Inadequate follow-up of suspicious lung nodules can result in a delay in diagnosis and potential progression to advanced staged lung cancer. A multidisciplinary lung nodule program entitled "Nodule Net" was implemented in 2017 to provide a safety net, increase the rate of follow-up, streamline management. The program consisted of a multidisciplinary team with EMR notification by the radiologist to a centralized nurse navigator for inclusion in a follow-up database, outreach with reminders to the primary care provider if follow-up was not completed, and referral for management where appropriate. In this study, we sought to evaluate program effectiveness in tracking and rate of follow-up imaging of suspicious pulmonary nodules. Methods: 2,398 chest CT scans were reviewed between January and May 2018 for the presence of a lung nodule that required follow-up. Nodules known to be inflammatory or associated with a metastatic malignancy were excluded. Baseline demographics, medical history, primary care affiliation, type of imaging scan, nodule characteristics, and presence and specifics of follow-up recommendations were collected. For reports that did not include a follow-up recommendation, Fleischner’s recommendations were applied or an independent pulmonologist’s review was completed. The rate of follow-up imaging was recorded and compared with historical rates prior to Nodule Net implementation. Prevalence ratios were generated for each comparison. Results: 1,367 (57%) reported lung nodules. Recommendations for follow-up imaging were recorded in 632 (46.2%), and 523 (82.8%) of these were reported to the program navigator. The rate of follow-up completion of those referred to the program was significantly higher [408 (78%)] than standard of care prior to program implementation [442/1202 (36.8%), (2.90, 95% CI: 2.65-3.18)]. Out of 408 patients who completed follow-up, nodule net outreach was required in 116 (28.4%). Of these 116, malignancy was identified in 4/116 (3.4%). Increased nodule size requiring referral was identified in 17 (14.7%). Out of 109 who were not transmitted to the program navigator and not present in the database, 57 (52.3%) had completed the recommended follow-up compared with 78% among those referred (1.49, 95% CI:1.23-1.79). Conclusions: Management of lung nodules is a complex process with poor follow-up completion reported in prior studies (29%-33%). Implementation of a multidisciplinary lung nodule care program for tracking lung nodules led to a significant increase in completion of recommended follow-up imaging. Developing a comprehensive lung nodule management program using software and navigation may further enhance detection, reduce human errors, augment the necessary follow-up for suspicious lung nodules, and ultimately the prevalence of advanced stage lung cancer.

Disclaimer

This material on this page is ©2024 American Society of Clinical Oncology, all rights reserved. Licensing available upon request. For more information, please contact licensing@asco.org

Abstract Details

Meeting

2021 ASCO Annual Meeting

Session Type

Poster Session

Session Title

Care Delivery and Regulatory Policy

Track

Care Delivery and Quality Care

Sub Track

Clinical Research Design

Citation

J Clin Oncol 39, 2021 (suppl 15; abstr 1564)

DOI

10.1200/JCO.2021.39.15_suppl.1564

Abstract #

1564

Poster Bd #

Online Only

Abstract Disclosures

Similar Abstracts

First Author: Matthew Smeltzer

First Author: Jianzheng Wang

First Author: Shuo Hu

First Author: Pan-Chyr Yang