In this study of VA primary care employees working in PCMH teams, burnout was associated with several workload and staffing characteristics. Inadequate staffing, team member turnover, and patient panel overcapacity were all associated with burnout among all occupations within the team. The associations with burnout were statistically significant, large, and additive. Observed burnout for employees on a fully staffed team with no turnover and a panel within capacity was an absolute 30.1% lower than that for employees on understaffed teams, with turnover, and with patient panel overcapacity.
An important finding from this paper is that, while the overall prevalence of burnout was lower for nurse care managers, clinical associates, and administrative clerks relative to PCPs, the associations with workload and staffing variables did not differ significantly by occupation. Prior literature has rarely included team members such as clinical associates or clerks.
Among those with patient appointments outside traditional business hours, working extended hours on the weekend, but not during the week, was associated with higher burnout, something for clinics to consider when assessing options to provide more convenient hours of operation for patients. Working extended hours with one’s team was associated with lower odds of burnout, which is consistent with the supposition that team-based primary care is a more supportive work environment and may reduce burnout. Alternatively, clinics able to schedule teams to work extended hours together may be different in other ways not captured in the model, such as how well the clinic is managed and overall staffing availability (as opposed to team-specific staffing). Those factors may be associated with lower burnout and may be unobserved confounders. In addition, there are ways that PCPs and staff work outside regular business hours, such as charting and responding to patient messages, that we do not capture with this item. These may be important correlates of burnout as well.
We found no association between burnout and working on multiple teams, working extended hours during the week, clinic location (hospital- vs. community-based), or patient panel complexity.
These findings make several contributions to the current literature on burnout and team-based primary care. We linked individual survey data on burnout to team-level administrative data on panel size and average patient complexity, whereas previous studies in primary care settings have relied on self-reported workload,20
35 which introduces the risk of method bias.36 Examining clinic-level rather than team-level patient complexity and panel size may mask important variations among teams, and may explain why a previous analysis observed no association between clinics with average panel size overcapacity and burnout among their employees.29
Our findings highlight the potential importance of stable team membership and adequate staffing. A recent study of 29 high-performing primary care practices using team-based care models identified stable team structure and adequate staffing ratios as among the nine key success factors.37 Finally, while most of the literature on burnout in primary care has focused on physicians and RNs,18
35 our findings also include other members of the primary care team including LPNs, medical technicians, and administrative clerks, and we found similar patterns of associations among these members of the primary care team.
The most important limitation of this study is potential response bias, with an estimated response rate of 21% for primary care personnel. When we compared respondents to non-respondents using administrative data, we found that non-response was associated with occupation, VA tenure, and clinic location, with lower response rates for administrative clerks, those with longer VA tenure, and those at VA medical center-based clinics (as opposed to community-based clinics). Consequently, we adjusted for these three variables in all complete-case regression models, since regression coefficients are not subject to response bias if the probability of non-response depends only on observed variables accounted for in the regression.38 As an additional sensitivity analysis, we used propensity score models to examine the effect of non-response on our initial findings, and found that model coefficients remained significant and in the same direction, but with more extreme ORs. While we cannot rule out the possibility that unobserved differences between respondents and non-respondents affected the results, the propensity score results suggest that our initial findings may be conservative.
These findings do not demonstrate causality. These were cross-sectional analyses, focused on a relatively small set of workplace variables and testing a relatively limited set of associations. Burnout is highly complex and is likely a function of interactions among a range of variables, including relationships with patients, clinician social support, and innate resilience. These findings are influenced both by unobserved confounders, such as the quality of the clinic leadership, and imperfect measurement, such as an inability to distinguish between turnover when a poor performer leaves and that from failure to retain a needed team member.
VA primary care settings differ from other primary care settings in ways that may limit the generalizability of the findings, such as lower average panel sizes, higher patient comorbidities, longer visit times, and a salaried structure with a quality metric-based performance system.39
Finally, there are concerns about endogeneity. Burnout is a known precursor to turnover, and the conditions that lead to burnout likely affect the primary care team broadly. Therefore, turnover on the teamlet might be as much a consequence of burnout as a cause.