Jonathan Shelver1, Chris H Wendt2, Melissa McClure1, Brian Bell3, Angela E Fabbrini3, Thomas Rector3, Kathryn Rice3. 1. Department of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Minnesota, Minneapolis, Minnesota. 2. VA Medical Center, Minneapolis, Minnesota; Department of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Minnesota, Minneapolis, Minnesota. Electronic address: wendt005@umn.edu. 3. VA Medical Center, Minneapolis, Minnesota.
Abstract
OBJECTIVE: Following incidental lung nodules with interval CT scanning is an accepted method to detect early lung cancer, but delayed tracking or failure to track is reported in up to 40% of patients. METHODS: Our institution developed and implemented an automated lung nodule registry tracking system. This system uses a code at the time that a suspicious nodule is discovered to populate the registry. Suspicious nodules were defined as any nodule, solid or ground glass, <3 cm that the radiologist recorded as a potential malignancy or recommended for follow-up imaging. We exported the system to eight other Veterans Administration Medical Centers (VAMCs) with over 10,000 patients enrolled. We retrospectively reviewed 200 sequential CT scan reports containing incidental nodule(s) from two tertiary care university-affiliated VAMCs, both before and after the implementation of the registry tracking system. The primary outcome was the rate of tracking failure, defined as suspicious nodules that had no follow-up imaging or whose follow-up was delayed when compared with published guidelines. Secondary outcomes were predictors of tracking failure and reasons for tracking failure. RESULTS: After implementation of the registry tracking system in the two VAMCs, we found a significant decrease in tracking failure, from a preimplementation rate of 74% to a postimplementation rate of 10% (P < .001). We found that age, nodule size, number, and nodule characteristics were significant predictors. CONCLUSIONS: The automated lung nodule registry tracking system can be exported to other health care facilities and significantly reduces the rate of tracking failure. Published by Elsevier Inc.
OBJECTIVE: Following incidental lung nodules with interval CT scanning is an accepted method to detect early lung cancer, but delayed tracking or failure to track is reported in up to 40% of patients. METHODS: Our institution developed and implemented an automated lung nodule registry tracking system. This system uses a code at the time that a suspicious nodule is discovered to populate the registry. Suspicious nodules were defined as any nodule, solid or ground glass, <3 cm that the radiologist recorded as a potential malignancy or recommended for follow-up imaging. We exported the system to eight other Veterans Administration Medical Centers (VAMCs) with over 10,000 patients enrolled. We retrospectively reviewed 200 sequential CT scan reports containing incidental nodule(s) from two tertiary care university-affiliated VAMCs, both before and after the implementation of the registry tracking system. The primary outcome was the rate of tracking failure, defined as suspicious nodules that had no follow-up imaging or whose follow-up was delayed when compared with published guidelines. Secondary outcomes were predictors of tracking failure and reasons for tracking failure. RESULTS: After implementation of the registry tracking system in the two VAMCs, we found a significant decrease in tracking failure, from a preimplementation rate of 74% to a postimplementation rate of 10% (P < .001). We found that age, nodule size, number, and nodule characteristics were significant predictors. CONCLUSIONS: The automated lung nodule registry tracking system can be exported to other health care facilities and significantly reduces the rate of tracking failure. Published by Elsevier Inc.
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