Senior Vice Chair, Strategy and Clinical Operations, Department of Radiology, Stanford University School of Medicine, Stanford, California; and Chair, ACR Commission on Quality and Safety.
Department of Radiology, Stanford University School of Medicine, Stanford, California.
J Am Coll Radiol. 2023 Mar;20(3):369-376. doi: 10.1016/j.jacr.2023.01.004.
The ACR Learning Network was established to test the viability of the learning network model in radiology. In this report, the authors review the learning network concept, introduce the ACR Learning Network and its components, and report progress to date and plans for the future.
Patterned after institutional programs developed by the principal investigator, the ACR Learning Network was composed of four distinct improvement collaboratives. Initial participating sites were solicited through broad program advertisement. Candidate programs were selected on the basis of assessments of local leadership support, experience with quality improvement initiatives, intraorganizational relationships, and access to data and analytic support. Participation began with completing a 27-week formal quality improvement training and project support program, with local teams reporting weekly progress on a common performance measure.
Four improvement collaborative topics were chosen for the initial cohort with the following numbers of participating sites: mammography positioning (6), prostate MR image quality (6), lung cancer screening (6), and follow-up on recommendations for management of incidental findings (4). To date, all sites have remained actively engaged and have progressed in an expected fashion. A detailed report of the results of the improvement phase will be provided in a future publication.
To date, the ACR Learning Network has successfully achieved planned milestones outlined in the program's plan, with preparation under way for the second and third cohorts. By providing a shared platform for improvement training and knowledge sharing, the authors are optimistic that the network may facilitate widespread performance improvement in radiology on a number of topics for years to come.
ACR 学习网络的建立旨在检验放射学学习网络模型的可行性。在本报告中，作者回顾了学习网络的概念，介绍了 ACR 学习网络及其组成部分，并报告了迄今为止的进展和未来的计划。
ACR 学习网络是仿照首席研究员制定的机构计划而建立的，由四个不同的改进协作组成。最初通过广泛的项目广告征求参与站点。候选计划是根据当地领导支持、质量改进计划经验、组织内关系以及获取数据和分析支持的能力进行评估后选择的。参与从完成 27 周的正式质量改进培训和项目支持计划开始，当地团队每周报告一次共同绩效指标的进展情况。
为初始队列选择了四个改进协作主题，参与的站点数量如下：乳腺摄影定位（6 个）、前列腺磁共振图像质量（6 个）、肺癌筛查（6 个）和对偶然发现的管理建议的随访（4 个）。迄今为止，所有站点都保持积极参与，并按预期进展。改进阶段的详细结果报告将在未来的出版物中提供。
迄今为止，ACR 学习网络已成功实现了计划中概述的计划里程碑，第二和第三队列的准备工作正在进行中。通过提供一个改进培训和知识共享的共享平台，作者乐观地认为，该网络可能在未来几年内促进放射学领域的许多主题的广泛绩效改进。
