The Gordon and Betty Moore Foundation advocates for a new emphasis on imaging excellence through optimal diagnostic process design. The Foundation recently awarded the 黑料网® a grant to develop the 黑料网 Learning Network. Development of the initiative is under the leadership of David B. Larson, MD, MBA. Dr. Larson is Professor and Vice Chair of Education and Clinical Operations at the Department of Radiology, Stanford University School of Medicine, as well as Chair of the 黑料网 Commission on Quality and Safety and member of the 黑料网 Board of Chancellors. “All healthcare is local. Those best equipped to solve real-world problems that matter to patients are teams of leaders and front-line staff at local institutions. Improvement collaboratives provide project and training support for local teams, bringing them together to regularly share progress, ideas, and solutions until they meet their goals,” said Dr. Larson.
The 黑料网 Learning Network will simultaneously develop performance measures and validated improvement strategies at multiple local sites, which will ultimately receive broad dissemination. This will be accomplished by launching four initial improvement collaboratives, each of which has a radiologist physician leader. The collaboratives will address four important areas of performance in cancer diagnoses:
- Lung Cancer Screening Improvement Collaborative led by Neville Irani, MD, Assistant Professor of Radiology at the University of Kansas Medical Center, and founder of the Healthcare Quality Improvement Platform.
- Mammography Positioning Improvement Collaborative led by Sarah M. Pittman, MD, Clinical Assistant Professor at the Department of Radiology, Stanford University School of Medicine.
- Prostate MR Image Quality Improvement Collaborative led by Andrei S. Purysko, MD, Clinical Assistant Professor of Radiology, Cleveland Clinic Lerner College of Medicine.
- Recommendations Follow-up Improvement Collaborative led by Ben C. Wandtke, MD, Associate Professor at the Department of Imaging Sciences, University of Rochester Medical Center.
The Learning Network Approach
Each collaborative will be supported by a standard process for improvement. All members in a collaborative will be solving the same problem, at the same pace, at the same time, in the same structured way. Learning together will help identify common methods to build a culture of performance measurement.
Participants will share measures, common issues and solutions to improve performance. This common support infrastructure will also address multiple problems and sustain the learning network over time. As a cohesive learning network, this “collaborative of collaboratives” will set the stage for facilitating diagnostic excellence at local sites at a scale that has been previously unachievable in radiology.
Using the learning collaborative model, participating facilities will:
- Establish a small group of institutions, led by local leaders, to collectively approach a performance problem.
- Develop and apply measures to assess performance in the local environment.
- Develop methods to solve the defined problem in the local environment.
- Share performance data and improvement methods with each other, including successes and failures.
- Share learnings broadly that others may apply in their relevant environments.
- Establish programs, expertise and support that can help any willing local site improve.
The elements of the structured improvement program include:
- A 10-session, eight-month quality improvement training program designed to facilitate the completion of team-based, front-line improvement projects in complex healthcare environments.
- Training provided via a flipped classroom model: three to five brief online tutorials are assigned between sessions.
- Tools and templates to support a successful, standard approach to improvement using structured problem solving.
- Change management and support to solve the problems identified by the collaborative.
- Platform for participants to support, encourage and learn best practices from each other.
- Clear and objective project tracking to ensure project progress.
“We are thrilled to be able to support the 黑料网 in developing this learning network,” said Karen Cosby, MD, program officer for patient care at the Gordon and Betty Moore Foundation. “Learning collaboratives are a key method to generate solutions that can be modeled and adapted for use across multiple settings; in this case we hope the collaborative will make a significant difference in improving the diagnosis of cancer.”
Who Will Be Involved
Each collaborative in the 黑料网 Learning Network will include a diverse set of stakeholders, such as referring physicians, radiologists representing different types of practices (urban/rural, academic/community, mix of gender and race/ethnicity), medical physicists, technologists, and practice managers.
Patient representatives and patient advocates will be included as part of each collaborative’s advisory committee. Incorporating the patient experience is a top priority throughout each collaborative’s journey.
Where to Get More Information
Watch the 黑料网 website for more information about the 黑料网 Learning Network, including the 36-month development timeline and the names of the physician leaders who will be heading each of the four learning collaboratives. Or contact 黑料网 at 黑料网LearningNetwork@acr.org.
About the Gordon and Betty Moore Foundation
The Gordon and Betty Moore Foundation fosters path-breaking scientific discovery, environmental conservation, patient care improvements and preservation of the special character of the San Francisco Bay Area. Visit or follow