Dissemination and implementation of a corrective intervention to improve mediasti

描述（由申请人提供）：美国每年约有60,000人接受肺癌手术。对于这些患者，肿瘤是否已经扩散到淋巴结是其预后的主要决定因素，并指导术后治疗决策。不幸的是，在美国进行的大多数肺癌手术没有提供足够的淋巴结样本来准确确定病理淋巴结分期。因此，更多的患者死于肺癌，而不是他们的术后阶段所预测的。检查肺癌手术切除的质量在大孟菲斯大都会区显示接近接近美国全国护理质量差距。采用专门设计的淋巴结标本采集试剂盒用于肺癌切除术，可显著提高病理淋巴结分期的质量，增加淋巴结转移患者的检出率。我们现在想测试在阿肯色州东部、密西西比州北部和田纳西州西部的三州地区常规使用这种独特的标本采集试剂盒的实施情况，该地区具有挑战性的社会经济人口统计数据和美国一些最高的肺癌死亡率。基于我们之前的工作，我们假设这种手术淋巴结标本采集试剂盒的成功实施将提高肺癌病理分期的质量，并增加由不同机构的不同外科医生手术的不同患者的淋巴结转移的检测。我们的目标是研究该试剂盒在美国人口结构多样化、肺癌高发病率地区的常规使用过程，以最大限度地发挥其在未来传播中的作用。我们建议通过以下具体目标来实现这一目标：招募至少90%的符合条件的医院（在我们确定的集水区内每年进行50例肺切除手术的医院）和外科医生参与肺癌切除淋巴结标本采集试剂盒的实施研究；2)。采用交错实施、多基线研究设计，评估该试剂盒在不同机构手术中的有效性；3.） 使用Reach， Effectiveness, Adoption, implementation and Maintenance （RE-AIM）框架研究实施过程。我们的研究将证明在实践环境的异质性中显著提高肺癌手术治疗的质量和结果的实际可能性。病理分期的普遍改善将通过优化肿瘤、淋巴结和转移（TNM）分期系统的使用，为未来开发独立预后基因和蛋白质表达谱的翻译工作奠定基础，TNM是目前我们最好的风险分层系统。该项目的最终目标是提供临床基础设施，以支持这些预后分子特征的未来研究，这些特征将补充并最终取代目前的TNM分期系统。

DESCRIPTION (provided by applicant): About 60,000 individuals undergo surgery for lung cancer in the US annually. For these patients, whether, or not, cancer has spread to their lymph nodes is the main determinant of their prognosis and guides post- operative treatment decision-making. Unfortunately, most lung cancer operations done in the US do not provide a sufficient sample of lymph nodes to make an accurate determination of pathologic lymph node stage. Therefore, a larger number of patients die of lung cancer than would have been predicted by their post- operative stage. Examination of the quality of lung cancer surgical resections in the greater Memphis Metropolitan Area reveals close approximation to the US national quality-of-care gap. Deploying a specially designed lymph node specimen collection kit for use in lung cancer resections significantly improves the quality of pathologic lymph node staging and increases the detection of patients with lymph node metastasis. We now want to test the implementation of the routine use of this unique specimen collection kit in the tri-state area of Eastern Arkansas, Northern Mississippi and Western Tennessee, which has the combination of challenging socio-economic demographics and some of the highest lung cancer mortality rates in the US. Based on our prior work, we hypothesize that successful implementation of this surgical lymph node specimen collection kit will improve the quality of pathologic staging of lung cancer and increase the detection of lymph node metastasis in a diverse mix of patients operated on by a diverse mix of surgeons in a diverse mix of institutions. Our objective is to study the implementation process of routine use of this kit in a demographically diverse, high lung cancer incidence region of the US, in order to maximize its impact in future dissemination. We propose to achieve this by performing the following Specific Aims: 1.) Recruit at least 90% of eligible hospitals (those within our defined catchment area with >5 lung resection operations annually) and surgeons to participate in an implementation study of the lymph node specimen collection kit for lung cancer resections; 2.) Evaluate the effectiveness of the kit in surgery performed in a diverse mix of institutions, using a staggered implementation, multiple baseline study design; 3.) Study the implementation process using the Reach, Effectiveness, Adoption, Implementation and Maintenance (RE-AIM) framework. Our study will demonstrate the practical possibility of significantly improving the quality and outcomes of surgical lung cancer care across heterogeneity of practice settings. General improvement in pathologic staging will set the stage for future translational work on development of independently prognostic gene and protein expression profiles by optimizing the use of the Tumor, Node, and Metastasis (TNM) staging system, which is currently our best risk stratification system. The ultimate goal of this project i to provide the clinical infrastructure to support future studies of such prognostic molecular signatures that will supplement, and eventually supersede the current TNM staging system.