Abstract

Implementation of primary care models involving expanded scope of work and redesigned workflows for medical assistants (MAs) as primary care team members can be challenging. Implementation strategies and participatory evaluation informed by implementation science frameworks may inform organizational decisions about model scale-up and sustainment. This paper reports implementation strategies and qualitative evaluation of a primary care redesign (PCR) model implementation that included an expanded scope of work for MAs. Qualitative evaluation of implementation strategies and clinician and staff experience with implementation of PCR using semi-structured key informant interviews. The evaluation was guided by the RE-AIM framework and the Consolidated Framework for Implementation Research. Sixty-nine clinicians, staff, practice leaders, and administrators from 7 primary care practices (4 general internal medicine, 3 family medicine) implementing PCR. The PCR model included enhanced rooming and documentation support. The health system used multiple strategies to implement PCR, including rapid improvement events, changing clinic space configurations, developing electronic health record templates and performance dashboards, and practice coaching. The Consolidated Framework for Implementation Research and the RE-AIM evaluation and planning framework guided development of semi-structured interview guides. A deductive, structural coding approach was used for analysis. PCR implementation was facilitated by clear communication about the intervention source, mechanisms for feedback about model goals, and physical environments and electronic health record (EHR) systems that supported the added staff and modified clinic workflow. Clinicians and staff benefited from the ability to see the model in action prior to go-live and opportunities for consistent provider-MA pairings. The PCR model can support achieving the Quadruple Aim when fully implemented with paired MAs and clinicians who are well prepared to follow redesigned workflows and function as a team. Implementation can be effectively supported by a participatory evaluation guided by implementation science frameworks.

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