Small Patients but a Heavy Lift: Workload and Burnout of Advanced Practice Providers and Physicians in a Level IV Neonatal Intensive Care Unit.

OBJECTIVE: This study explored the association between workload and the level of burnout reported by clinicians in our neonatal intensive care unit (NICU). A qualitative analysis was used to identify specific factors that contributed to workload and modulated clinician workload in the NICU. STUDY DESIGN: We conducted a study utilizing postshift surveys to explore workload of 42 NICU advanced practice providers and physicians over a 6-month period. We used multinomial logistic regression models to determine associations between workload and burnout. We used a descriptive qualitative design with an inductive thematic analysis to analyze qualitative data. RESULTS: Clinicians reported feelings of burnout on nearly half of their shifts (44%), and higher levels of workload during a shift were associated with report of a burnout symptom. Our study identified 7 themes related to workload in the NICU. Two themes focused on contributors to workload, 3 themes focused on modulators of workload, and the final 2 themes represented mixed experiences of clinicians' workload. CONCLUSION: We found an association between burnout and increased workload. Clinicians in our study described common contributors to workload and actions to reduce workload. Decreasing workload and burnout along with improving clinician well-being requires a multifaceted approach on unit and systems levels.

Workload In Neonatology (WORKLINE): Validation and feasibility of a system for measuring clinician workload integrated into the electronic health record.

OBJECTIVE: The purpose of the study was to validate WORKLINE, a NICU specific clinician workload model and to evaluate the feasibility of integrating WORKLINE into our EHR. STUDY DESIGN: This was a prospective, observational study of the workload of 42 APPs and physicians in a large academic medical center NICU over a 6-month period. We used regression models with robust clustered standard errors to test associations of WORKLINE values with NASA Task Load Index (NASA-TLX) scores. RESULTS: We found significant correlations between WORKLINE and NASA-TLX scores. APP caseload was not significantly associated with WORKLINE scores. We successfully integrated the WORKLINE model into our EHR to automatically generate workload scores. CONCLUSION: WORKLINE provides an objective method to quantify the workload of clinicians in the NICU, and for APPs, performed better than caseload numbers to reflect workload. Integrating the WORKLINE model into the EHR was feasible and enabled automated workload scores.