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1.
J Perinat Neonatal Nurs ; 38(2): 192-200, 2024.
Article in English | MEDLINE | ID: mdl-38758274

ABSTRACT

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.


Subject(s)
Burnout, Professional , Intensive Care Units, Neonatal , Workload , Humans , Burnout, Professional/psychology , Burnout, Professional/epidemiology , Workload/psychology , Workload/statistics & numerical data , Female , Male , Infant, Newborn , Adult , Qualitative Research , Surveys and Questionnaires
2.
J Perinatol ; 43(7): 936-942, 2023 07.
Article in English | MEDLINE | ID: mdl-37131049

ABSTRACT

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.


Subject(s)
Neonatology , Workload , Humans , Electronic Health Records , Prospective Studies , Feasibility Studies
3.
Jt Comm J Qual Patient Saf ; 47(10): 654-662, 2021 10.
Article in English | MEDLINE | ID: mdl-34284954

ABSTRACT

BACKGROUND: Quality improvement (QI) methods have been widely adopted in health care. Although theoretical frameworks and models for organizing successful QI programs have been described, few reports have provided practical examples to link existing QI theory to building a unit-based QI program. The purpose of this report is to describe the authors' experience in building QI infrastructure in a large neonatal ICU (NICU). METHODS: A unit-based QI program was developed with the goal of fostering the growth of high-functioning QI teams. This program was based on six pillars: shared vision for QI, QI team capacity, QI team capability, actionable data for improvement, culture of improvement, and QI team integration with external collaboratives. Multiple interventions were developed, including a QI dashboard to align NICU metrics with unit and hospital quality goals, formal training for QI leaders, QI coaches imbedded in project teams, a day-long QI educational workshop to introduce QI methodology to unit staff, and a secure, Web-based QI data infrastructure. RESULTS: Over a five-year period, this QI infrastructure brought organization and support for individual QI project teams and improved patient outcomes in the unit. Two case studies are presented, describing teams that used support from the QI infrastructure. The Infection Prevention team reduced central line-associated bloodstream infections from 0.89 to 0.36 infections per 1,000 central line-days. The Nutrition team decreased the percentage of very low birth weight infants discharged with weights less than the 10th percentile from 51% to 40%. CONCLUSION: The clinicians provide a pragmatic example of incorporating QI organizational and contextual theory into practice to support the development of high-functioning QI teams and build a unit-based QI program.


Subject(s)
Intensive Care Units, Neonatal , Quality Improvement , Delivery of Health Care , Hospitals , Humans , Infant, Newborn , Motivation
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