Nursing is a high workload profession, and excessive workload has been shown to have an adverse effect on patient care. This problem has been compounded by shortages of qualified nurses in hospitals, resulting in increased workload of the existing nursing staff. Prior research has focused on patient-staff ratios and skill mix to analyze the relationship of workload and degradation of care. The current research implemented a multi-dimensional model for analyzing nurses’ workload in a large general hospital. This method afforded the researcher the opportunity to examine a work domain from multiple angles. Nurses play versatile roles, and workload extends beyond the care of the patient with team and organizational responsibilities. The current research expanded on the concept of a multi-dimensional approach to workload in nursing. Workload drivers were introduced as multiple, unique factors that contributed to the totality of nursing workload. Prior research examined such factors as organizational and environmental factors (patient acuity) and factors that vary within a nurse’s shift (time pressure). The current study engaged in a systematic examination of these concepts, in addition to extracting workload drivers that were specific to the observation setting (different departments at Rochester General Hospital). A Cognitive Work Analysis (CWA) was conducted to map out the work domain of nurses, and identified sources of workload. This was a detailed and multi-stage investigation of nursing in terms of goals, functions, tasks, physical resources, and mental states and processes (decision making). The output was a collection of diagrams, tables, and interviews that illustrated areas in nursing that produced the most workload. A detailed integration of the material supported an estimation of workload experienced by nurses.
Library of Congress Subject Headings
Nurses--Workload--Research; Job analysis
Experimental Psychology (MS)
Department, Program, or Center
Esa M. Rantanen
Umansky, Jonathan, "Workload in Nursing: A Descriptive Study Using Cognitive Work Analysis" (2015). Thesis. Rochester Institute of Technology. Accessed from
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