Lung Cancer Screening Improvement Collaborative
Mammography Positioning Improvement Collaborative
Prostate MR Image Quality Improvement Collaborative
Recommendations Follow-Up Improvement Collaborative

About the Learning Network

The ACR® Learning Network pursues improvement in diagnostic imaging through a learning health systems approach characterized by strong leadership, effective use of data in the clinical setting, and both a culture and a workforce committed to continuous learning and improvement.  

Where to Find Information

The ACR website provides overall program details and updates including information about the work being carried out by the learning network's four improvement collaboratives, the facilities participating in the improvement collaborative cohorts and continuing education offerings.  

The knowledge base provides improvement collaborative participants with information and resources to support their participation success in the 10-session improvement course designed to facilitate the completion of their team-based improvement projects.

The Learning Network HUB provides participants a space to enter weekly project data and interact with their project's control charts.  The HUB is password protected.  Learning Network staff will work with participants to access the HUB and their team's control chart(s).

Learning Network Participant Experience

The following publications contain quotes and experiences from participants who graduated from the ImPower program.

  1. Cohort Brochure:
    1. Cohort 1 Brochure
    2. Cohort 2 Brochure
  2. Bulletin Articles:
    1. August 2023: Collaborating on Quality Prostate MR Image Quality collaborative experience defined through the perspectives of four members of various teams.  
    2. October 2023: The ACR Learning Network: In it for the Long Haul Highlighting the importance of technologists and patient positioning in mammography. 
    3. November 2023: Value over Volume Focusing on the future of lung cancer screening.
    4. December 2023: Following Patients Through Incidental Findings A case study on Hudson Valley Radiologists P.C. in Poughkeepsie, N.Y.  
  3. Peer-reviewed Publications:
    1. Recent Publications

Principles and Commitments

  1. Leaders’ commitment to improvement: We will make the investments in personnel time, process changes, training, data analytics tools, and infrastructure necessary to reach sustained world-class performance in the collaborative’s area of focus, while also being wise stewards of limited resources.
  2. Transparency: We will freely and regularly share our performance data with other members of the network, even when it does not cast us in the best of light.
  3. Data and information stewardship: We will be respectful of all information shared with us, keeping sensitive information confidential and only publishing results according to established policies.
  4. Commitment to the success of all in the community: Our mutual goal is the success of every network member and of the community as a whole. The failure or success of one member organization is a failure or success for every member organization.
  5. All teach, all learn: We will freely share with and humbly learn from others in the network. We will provide appropriate acknowledgment and attribution for our sources. As we reach our performance goals, we will help other network members achieve their goals. 
  6. Collaboration, not competition: We will not use the learning network for competitive advantage, meaning in a way that makes our organization look good at another’s expense.
  7. Reliable solutions enabling sustained improvement: We recognize that consistent excellent performance is the result of well-designed and well-managed processes. We will work to understand which solutions are most closely linked with desired outcomes that can be maintained in perpetuity.
  8. Freely share our learnings with the world: As we learn and improve, we will freely share those learnings with others outside the network, in a way that is respectful to all members.
  9. Commitment to remain engaged: We will continue to actively participate in the network, share our performance data, and contribute to building and preserving the community as long as we remain a member.


The start-up of the Learning Network program was funded by a three-year grant from the Gordon and Betty Moore Foundation (Grant Number 10476).

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