Supreeta Amin

Doctoral Dissertation Announcement

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Candidate: Supreeta Amin

Degree of: Doctor of Philosophy

Department: Industrial and Manufacturing Engineering

Title: A Study to Determine the Influence of Workload on Nursing Personnel

Committee:
Dr. Tycho Fredericks, Chair
Dr. Steven Butt
Dr. Christopher Cheatham
Dr. Larry Mallak

Date: Tuesday, March 8, 2011 Noon to 2:00 p.m.
Parkview Campus, Room D210

Abstract:
The alarming number of adverse medical events and associated costs has placed immense importance toward the safety and health of both patients and medical personnel. A shrinking nurse workforce and an aging patient and nursing population, coupled with a mismatch between hospital demands and the available nursing staff, have created a situation detrimental to both patient and nursing personnel. Long working hours, working more than one job, low staffing ratios, high patient acuity, minimal social support, low experience level, complicated equipment, complex procedures and varying workload are some factors that may have a negative impact on the quality of care provided by nursing personnel. Research directed toward investigating the effects of workload, comprising of types of activities, interruptions and distractions on nursing personnel is limited. Hence, the objective of this study was primarily to determine the influence of the workload on nursing personnel.
Two pilot studies were conducted to establish parameters for this study. Objective and
subjective measures were used to determine the workload over a 12-hour nursing shift at a local hospital. It was determined that some activities took less time to perform but were performed frequently, while other activities took more time to perform but were performed less frequently. It was also determined that nursing activities included both physical and cognitive components. The results also suggest that nursing workload in the Neonatal Intensive Care Unit may be classified as requiring low to moderate levels of physical exertion, and the cognitive loading was influenced by task complexity and task manipulations. Distractions, interruptions and common physical posture adopted by nurses placed more demands on the nurses. The potential consequence of increased demands on the nurses could result in a faster onset of fatigue, which may negatively influence performance. Several prediction equations for physical workload and mental workload, based on various measures, were also developed. The results and developed models could be used by hospital administrators to balance nursing workload in order to reduce fatigue and in turn reduce adverse medical events.