The ACR Mammography Positioning Improvement Collaborative: A Multi-Center Improvement Program within a Learning Network Framework.

ABSTRACT

PURPOSE/OBJECTIVE: To share the experience and results of the first cohort of the ACR Mammography Positioning Improvement Collaborative, in which participating sites aimed to increase the mean percentage of screening mammograms meeting the established positioning criteria to 85% or greater and show at least modest evidence of improvement at each site by the end of the improvement program. METHODS: The sites comprising the first cohort of the Collaborative were selected on the basis of strength of local leadership support, intra-organizational relationships, access to data and analytic support, and experience with quality improvement (QI) initiatives. During the improvement program, participating sites organized their teams, developed goals, gathered data, evaluated their current state, identified key drivers and root causes of their problems, and developed and tested interventions. A standardized image quality scoring system was also established. The impact of the interventions implemented at each site was assessed by tracking the percentage of screening mammograms meeting overall passing criteria over time. RESULTS: Six organizations were selected to participate as the first cohort, beginning with participation in the improvement program. Interventions developed and implemented at each site during the program resulted in improvement in the average percentage of screening mammograms meeting overall passing criteria per week from a collaborative mean of 51% to 86%, with four of six sites meeting or exceeding the target mean performance of 85% by the end of the improvement program. Afterwards, all respondents to the post-program survey indicated that the program was a positive experience. CONCLUSION: Using a structured improvement program within a learning network framework, the first cohort of the Collaborative demonstrated that improvement in mammography positioning performance can be achieved at multiple sites simultaneously, and validated the hypothesis that local sites' shared experiences, insights, and learnings would not only improve performance but would also build a community of improvers collaborating to create the best experience for technologists, staff, and patients.