Emergency clinician output in a district hospital emergency centre: a cross-sectional analysis

Abstract

Introduction: Appropriate and efficient staffing is a cornerstone of emergency centre performance. There is however a paucity of literature describing clinician output in low- and middle-income countries with current staffing models based on anecdotal evidence. This study aimed to assess clinician output at a district level emergency centre, and how it varied depending on shift, clinician, and workload factors. Methods: We conducted a retrospective cross-sectional study using an existing electronic patient registry, to determine the patients consulted per hour (PPH) during each clinician shift and how this is affected by various clinician, shift, and workload factors. Data was collected over three non-contiguous randomly selected four-week cycles from Mitchells Plain Hospital's electronic patient registry. Associations between PPH and various factors were assessed using ANOVA with post-hoc adjustments where appropriate. The correlation between PPH and workload metrics was calculated with the Pearson's Rank correlation test. Statistical significance was defined as p<0.05. Results: A total of 1 289 clinician shifts were analysed with an overall PPH of 0.7. A significant association between PPH and shift type (p=0.021), clinician category (p<0.001) and cumulative shifts (p<0.001) were shown. There was a decline in clinician output during a shift and output was significantly decreased by the number of boarders in the emergency centre but increased with higher numbers of patients waiting at the start of the shift. Conclusion: This study describes a relatively low clinician output as compared to evidence from high-income countries and has highlighted several associations with various shift, clinician, and workload factors. The results from this study will form the basis of quality improvement interventions to improve patient throughput and will inform staff scheduling and surge planning strategies.

Keywords

• Emergency medicine
• Low- to middle-income country
• Crowding
• Patient flow
• Output