Shelver Jonathan, Wendt Chris H, McClure Melissa, Bell Brian, Fabbrini Angela E, Rector Thomas, Rice Kathryn
Department of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Minnesota, Minneapolis, Minnesota.
VA Medical Center, Minneapolis, Minnesota; Department of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Minnesota, Minneapolis, Minnesota.
J Am Coll Radiol. 2017 Jun;14(6):773-777. doi: 10.1016/j.jacr.2017.02.001. Epub 2017 Apr 21.
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.
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.
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.
The automated lung nodule registry tracking system can be exported to other health care facilities and significantly reduces the rate of tracking failure.
采用间隔CT扫描对偶然发现的肺结节进行随访是检测早期肺癌的一种公认方法，但据报道，高达40%的患者存在随访延迟或未能进行随访的情况。
我们的机构开发并实施了一个自动肺结节登记随访系统。该系统在发现可疑结节时使用一个代码来填充登记册。可疑结节被定义为任何实性或磨玻璃样结节，直径<3 cm，放射科医生将其记录为潜在恶性病变或建议进行后续影像学检查。我们将该系统推广至其他八家退伍军人事务部医疗中心（VAMC），共有超过10,000名患者登记入组。我们回顾性分析了来自两家大学附属医院三级医疗中心的200份连续CT扫描报告，这些报告包含偶然发现的结节，涵盖登记随访系统实施前后两个阶段。主要结局是随访失败率，定义为与已发表指南相比，没有进行后续影像学检查或随访延迟的可疑结节。次要结局是随访失败的预测因素和随访失败的原因。
在两家VAMC实施登记随访系统后，我们发现随访失败率显著降低，从实施前的74%降至实施后的10%（P < .001）。我们发现年龄、结节大小、数量和结节特征是显著的预测因素。
自动肺结节登记随访系统可以推广至其他医疗机构，并显著降低随访失败率。
