Purpose: In outpatient continuity clinics, incoming trainees may receive caseloads that are unbalanced in terms of the mental workload required from each resident. When significant, these imbalances may compromise resident learning and patient safety. Using data from psychiatric outpatient continuity clinics, this study tested a method for balancing initial caseloads.
Method: Adapting prior research on mental workload, the authors developed and implemented a workload-balancing method to balance initial caseloads regarding factors contributing to mental workload: number of patients, number of acute patients, complexity/time demands outside clinic, visits per month, and collaboration demands. For academic years 2006–2007, 2007–2008, 2008–2009, and 2009–2010, they compared these balanced caseloads with those that would have been created by the clinic's traditional method of largely preserving prior caseloads (with some redistribution to balance only the number of patients). The outcome measure was the intercaseload coefficient of variation for each of the chosen mental workload factors and for all factors combined.
Results: Compared with the traditional method, the workload-balancing method generated lower intercaseload variation for each mental workload factor. Also, this method reduced overall intercaseload variation for all factors combined by 50% to 61% in each of the intervention years.
Conclusions: The workload-balancing method evenly distributes among resident panels factors known to contribute to mental workload. This method may reduce errors and stress likely to occur when residents inherit unbalanced caseloads that are overly challenging and, thus, may improve patient safety and resident learning. This model could be applicable to other caseload situations.