Implementing team-based primary care models: a mixed-methods comparative case study in a large, integrated health care system.

Misra-Hebert AD1,2,3, Perzynski A4, Rothberg MB5,6, Fox J6, Mercer MB7, Liu X8, Hu B8, Aron DC9, Stange KC10.

Author information

1: Department of Internal Medicine, Cleveland Clinic, Cleveland, OH, USA. misraa@ccf.org.
2: Center for Value-Based Care Research, Cleveland Clinic, Cleveland, OH, USA. misraa@ccf.org.
3: Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH, USA. misraa@ccf.org.
4: Center for Health Care Research and Policy, Case Western Reserve University at MetroHealth, Cleveland, OH, USA.
5: Department of Internal Medicine, Cleveland Clinic, Cleveland, OH, USA.
6: Center for Value-Based Care Research, Cleveland Clinic, Cleveland, OH, USA.
7: Office of Patient Experience, Cleveland Clinic, Cleveland, OH, USA.
8: Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH, USA.
9: Louis Stokes Cleveland Veterans Affairs Medical Center, Cleveland, OH, USA.
10: Center for Community Health Integration, and Departments of Family Medicine and Community Health, Population and Quantitative Health Sciences, Oncology and Sociology, Case Western Reserve University, Cleveland, OH, USA.

Abstract

BACKGROUND:

Successful implementation of new care models within a health system is likely dependent on contextual factors at the individual sites of care.

OBJECTIVE:

To identify practice setting components contributing to uptake of new team-based care models.

DESIGN:

Convergent mixed-methods design.

PARTICIPANTS:

Employees and patients of primary care practices implementing two team-based models in a large, integrated health system.

MAIN MEASURES:

Field observations of 9 practices and 75 interviews, provider and staff surveys to assess adaptive reserve and burnout, analysis of quality metrics, and patient panel comorbidity scores. The data were collected simultaneously, then merged, thematically analyzed, and interpreted by a multidisciplinary team.

KEY RESULTS:

Based on analysis of observations and interviews, the 9 practices were categorized into 3 groups-high, partial, and low uptake of new team-based models. Uptake was related to (1) practices' responsiveness to change and (2) flexible workflow as related to team roles. Strength of local leadership and stable staffing mediated practices' ability to achieve high performance in these two domains. Higher performance on several quality metrics was associated with high uptake practices compared to the lower uptake groups. Mean Adaptive Reserve Measure and Maslach Burnout Inventory scores did not differ significantly between higher and lower uptake practices.

CONCLUSION:

Uptake of new team-based care delivery models is related to practices' ability to respond to change and to adapt team roles in workflow, influenced by both local leadership and stable staffing. Better performance on quality metrics may identify high uptake practices. Our findings can inform expectations for operational and policy leaders seeking to implement change in primary care practices.