Abstract
BACKGROUND: Primary care for a panel of patients is a central component of population health, but the optimal panel size is unclear. PURPOSE: To review evidence about the association of primary care panel size with health care outcomes and provider burnout. DATA SOURCES: English-language searches of multiple databases from inception to October 2019 and Google searches performed in September 2019. STUDY SELECTION: English-language studies of any design, including simulation models, that assessed the association between primary care panel size and safety, efficacy, patient-centeredness, timeliness, efficiency, equity, or provider burnout. DATA EXTRACTION: Independent, dual-reviewer extraction; group consensus rating of certainty of evidence. DATA SYNTHESIS: Sixteen hypothesis-testing studies and 12 simulation modeling studies met inclusion criteria. All but 1 hypothesis-testing study were cross-sectional assessments of association. Three studies each provided low-certainty evidence that increasing panel size was associated with no or modestly adverse effects on patient-centered and effective care. Eight studies provided low-certainty evidence that increasing panel size was associated with variable effects on timely care. No studies assessed the effect of panel size on safety, efficiency, or equity. One study provided very-low-certainty evidence of an association between increased panel size and provider burnout. The 12 simulation studies evaluated 5 models; all used access as the only outcome of care. Five and 2 studies, respectively, provided moderate-certainty evidence that adjusting panel size for case mix and adding clinical conditions to the case mix resulted in better access. LIMITATION: No studies had concurrent comparison groups, and published and unpublished studies may have been missed. CONCLUSION: Evidence is insufficient to make evidence-based recommendations about the optimal primary care panel size for achieving beneficial health outcomes.
This resource is found in our Actionable Strategies for Health Organizations: Improving Workload & Workflows (Safe & Appropriate Staffing).
