Primary Care 2.0: A Prospective Evaluation of a Novel Model of Advanced Team Care With Expanded Medical Assistant Support
PURPOSE Assess effectiveness of Primary Care 2.0: a team-based model that incorporates increased medical assistant (MA) to primary care physician (PCP) ratio, integration of advanced practice clinicians, expanded MA roles, and extended the interprofessional team.
METHODS Prospective, quasi-experimental evaluation of staff/clinician team development and wellness survey data, comparing Primary Care 2.0 to conventional clinics within our academic health care system. We surveyed before the model launch and every 6-9 months up to 24 months post implementation. Secondary outcomes (cost, quality metrics, patient satisfaction) were assessed via routinely collected operational data
RESULTS Team development significantly increased in the Primary Care 2.0 clinic, sustained across all 3 post implementation time points (+12.2, +8.5, + 10.1 respectively, vs baseline, on the 100-point Team Development Measure) relative to the comparison clinics. Among wellness domains, only “control of work” approached significant gains (+0.5 on a 5-point Likert scale, P = .05), but was not sustained. Burnout did not have statistically significant relative changes; the Primary Care 2.0 site showed a temporal trend of improvement at 9 and 15 months. Reversal of this trend at 2 years corresponded to contextual changes, specifically, reduced MA to PCP staffing ratio. Adjusted models confirmed an inverse relationship between team development and burnout (P <.0001). Secondary outcomes generally remained stable between intervention and comparison clinics with suggestion of labor cost savings.
CONCLUSIONS The Primary Care 2.0 model of enhanced team-based primary care demonstrates team development is a plausible key to protect against burnout, but is not sufficient alone. The results reinforce that transformation to team-based care cannot be a 1-time effort and institutional commitment is integral.
Jonathan G. Shaw, Marcy Winget, Cati Brown-Johnson, Timothy Seay-Morrison, Donn W. Garvert, Marcie Levine, Nadia Safaeinili and Megan R. Mahoney