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Trends in primary care encounters across professional roles in PCMH.

Annis AM, Harris M, Kim HM, Rosland AM, Krein SL. Trends in primary care encounters across professional roles in PCMH. The American journal of managed care. 2018 Jul 1; 24(7):e222-e229.

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Abstract:

OBJECTIVES: Team-based care models, including the patient-centered medical home (PCMH), are increasingly promoted to improve the delivery of primary care. However, evaluation measures are often reported at a clinic or primary care provider (PCP) level, creating challenges in describing and analyzing the use and impact of non-PCP clinician team members. Thus, we aimed to measure clinician-specific care delivery trends and determine whether trends were responsive to systemwide PCMH implementation. STUDY DESIGN: Interrupted time-series analysis of 57 million primary care encounters among 5 million veterans at 764 Veterans Health Administration primary care clinics from 2009 to 2013. METHODS: Retrospective data identified patient encounters attributable to 12 types of clinicians, yielding an encounters-by-clinician metric. Negative binomial regression modeled the monthly clinic-level rates of encounters for each type of clinician, before and during PCMH implementation. RESULTS: Over 5 years, the percentage of encounters by non-PCP clinicians increased from 29% to 35%. Monthly encounter rates for nurses and social workers significantly increased by 0.5% and 1.3%, respectively, after the introduction of PCMH, whereas PCP encounter rates significantly decreased over time. Encounter trends for pharmacists, nutritionists, and behavioral health clinicians did not significantly change. CONCLUSIONS: This study demonstrated the feasibility of capturing care delivered by a full complement of team members using routinely collected data. Findings suggest that the proportions of care delivered by non-PCP clinicians were sensitive to a change in care delivery model. As team-based care models expand, availability and use of metrics that account for care by all team members are critical for inferring clinician-related effects on outcomes.





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