Defining "Swarming" as a New Model to Optimize Efficiency and Education in an Academic Emergency Department.

BACKGROUND

Academic emergency medicine is a constant balance between efficiency and education. We developed a new model called swarming, where the bedside nurse, resident, and attending/fellow simultaneously evaluate the patient, including initial vital signs, bedside triage, focused history and physical examination, and discussion of the treatment plan, thus creating a shared mental model.

OBJECTIVES

To combine perceptions from trainee physicians, supervising physicians, nurses, and families with in vivo measurements of emergency department swarms to better conceptualize the swarming model.

METHODS

This mixed methods study was conducted using a convergent design. Qualitative data from focus groups with nurses, residents, and attendings/fellows were analyzed using directed content analysis. Swarming encounters were observed in real time; durations of key aspects and family satisfaction scores were analyzed using descriptive statistics. The qualitative and quantitative findings were integrated a posteriori.

RESULTS

From the focus group data, 54 unique codes were identified, which were grouped together into five larger themes. From 39 swarms, mean (±SD) time (minutes) spent in patient rooms: nurses = 6.8 (±3.0), residents = 10.4 (±4.1), and attendings/fellows = 9.4 (±4.3). Electronic documentation was included in 67% of swarms, and 39% included orders initiated at the bedside. Mean (±SD) family satisfaction was 4.8 (±0.7; Likert scale 1-5).

CONCLUSIONS

Swarming is currently implemented with significant variability but results in high provider and family satisfaction. There is also consensus among physicians that swarming improves trainee education in the emergency setting. The benefits and barriers to swarming are underscored by the unpredictable nature of the ED and the observed variability in implementation. Our findings provide a critical foundation for our efforts to refine, standardize, and appraise our swarming model.