Abstract

Nursing workload encompasses the full range of tasks nurses must complete, including direct and indirect patient care and workplace responsibilities.1 High workload has been associated with increased stress, reduced job satisfaction, and a greater risk of patient harm.2-3 Excessive workloads limit time for assessments, critical thinking, and effective communication, all essential to preventing harm.4-5 Shifting from patient acuity to workload metrics is a strategy for managing nurse workloads and supporting better outcomes. In a pediatric hospital, nurse leaders transitioned from a patient acuity system to one incorporating nurse workload for nurse assignments. The project aimed to validate a nursing workload tool and create more balanced assignments.

A group of veteran bedside nurses were recruited to collaborate with electronic medical record (EMR) specialists. Bedside nurses and EMR specialists evaluated each medication, order, and flowsheet to quantify the time required for each task. This resulted in an automated nurse workload score calculated by the EMR and updated hourly. Nurses piloted the tool on 3 units, assessing its practicality and validating the acceptable range for workload scores. Nurses provided feedback on score accuracy through surveys. The project team addressed documented discrepancies in scores. Nurse leaders rounded weekly, gathering bedside nurses’ perceptions of their workload using 3 categories (low, medium/appropriate, and high). Team leaders and a biostatistician analyzed nurses' perceptions and calculated workload scores to identify the ideal workload range.

After a 60-day pilot, 342 nurse assignments were evaluated. Assignments categorized as low, medium, and high were compared to their corresponding workload scores. Cross tabulation showed that 24.6% of assignments were perceived as low, 52.6% as medium, and 22.8% as high. Among low assignments, 66% had scores of 7.9 or below, while 62.72% of medium assignments fell within the range of 8-12. High assignments were reported in 62.75% of cases with scores of 12.1 or above.

After the pilot, the workload tool was implemented across all inpatient units. Nurses received education on using the tool to support safe staffing, with a target workload range of 8-12 per nurse. Ongoing surveys further validated the score ranges for low, medium, and high assignments. A key takeaway was that involving bedside nurses in decision-making ensures staffing solutions align with real clinical needs.

Notes

References: Ivziku D, Ferramosca FMP, Filomeno L, Gualandi R, De Maria M, Tartaglini D. Defining nursing workload predictors: A pilot study. J Nurs Manag. 2022;30(2):473-481. doi:10.1111/jonm.13523

Maghsoud, F., Rezaei, M., Asgarian, F.S. et al. Workload and quality of nursing care: the mediating role of implicit rationing of nursing care, job satisfaction and emotional exhaustion by using structural equations modeling approach. BMC Nurs 21, 273 (2022). https://doi.org/10.1186/s12912-022-01055-1

Inegbedion H, Inegbedion E, Peter A, Harry L. Perception of workload balance and employee job satisfaction in work organizations. Heliyon. 2020;6(1):e03160. https://doi.org/10.1016/j.heliyon.2020.e03160.

Cho SH, Lee JY, You SJ, Song KJ, Hong KJ. Nurse staffing, nurses prioritization, missed care, quality of nursing care, and nurse outcomes. Int J Nurs Pract. 2020;26(1):e12803. https://doi.org/10.1111/ijn.12803.

Dhaini SR, Simon M, Ausserhofer D, Al Ahad MA, Elbejjani M, Dumit N, et al. Trends and variability of implicit rationing of care across time and shifts in an acute care hospital: a longitudinal study. J Nurs Manag. 2020;28(8):1861–72. https://doi.org/10.1111/jonm.13035.

Description

As patient complexity and nurses' cognitive strain continue to increase, as does nurse stress, burnout, and increased patient harm risks. To address this, a pediatric hospital transitioned from a patient acuity system to a workload-based tool for nurse assignments. This tool, developed through collaboration with bedside nurses and EMR specialists, was piloted and validated, improving assignment balance. The workload tool is now used to support safe staffing across the hospital.

Author Details

Dr. Kaylan Branson, DNP, RN, CPN, CNL & Dr. Julie Van Orne, PhD, RN, CPN, CNL

Sigma Membership

Delta Theta

Type

Poster

Format Type

Text-based Document

Study Design/Type

Other

Research Approach

Other

Keywords:

Instrument or Tool Development, Acute Care, Workforce, Workload

Conference Name

36th International Nursing Research Congress

Conference Host

Sigma Theta Tau International

Conference Location

Seattle, Washington, USA

Conference Year

2025

Rights Holder

All rights reserved by the author(s) and/or publisher(s) listed in this item record unless relinquished in whole or part by a rights notation or a Creative Commons License present in this item record.

Review Type

Abstract Review Only: Reviewed by Event Host

Acquisition

Proxy-submission

Click on the above link to access the poster.

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Validation of a Nursing Workload Tool to Improve Staffing in a Pediatric Hospital

Seattle, Washington, USA

Nursing workload encompasses the full range of tasks nurses must complete, including direct and indirect patient care and workplace responsibilities.1 High workload has been associated with increased stress, reduced job satisfaction, and a greater risk of patient harm.2-3 Excessive workloads limit time for assessments, critical thinking, and effective communication, all essential to preventing harm.4-5 Shifting from patient acuity to workload metrics is a strategy for managing nurse workloads and supporting better outcomes. In a pediatric hospital, nurse leaders transitioned from a patient acuity system to one incorporating nurse workload for nurse assignments. The project aimed to validate a nursing workload tool and create more balanced assignments.

A group of veteran bedside nurses were recruited to collaborate with electronic medical record (EMR) specialists. Bedside nurses and EMR specialists evaluated each medication, order, and flowsheet to quantify the time required for each task. This resulted in an automated nurse workload score calculated by the EMR and updated hourly. Nurses piloted the tool on 3 units, assessing its practicality and validating the acceptable range for workload scores. Nurses provided feedback on score accuracy through surveys. The project team addressed documented discrepancies in scores. Nurse leaders rounded weekly, gathering bedside nurses’ perceptions of their workload using 3 categories (low, medium/appropriate, and high). Team leaders and a biostatistician analyzed nurses' perceptions and calculated workload scores to identify the ideal workload range.

After a 60-day pilot, 342 nurse assignments were evaluated. Assignments categorized as low, medium, and high were compared to their corresponding workload scores. Cross tabulation showed that 24.6% of assignments were perceived as low, 52.6% as medium, and 22.8% as high. Among low assignments, 66% had scores of 7.9 or below, while 62.72% of medium assignments fell within the range of 8-12. High assignments were reported in 62.75% of cases with scores of 12.1 or above.

After the pilot, the workload tool was implemented across all inpatient units. Nurses received education on using the tool to support safe staffing, with a target workload range of 8-12 per nurse. Ongoing surveys further validated the score ranges for low, medium, and high assignments. A key takeaway was that involving bedside nurses in decision-making ensures staffing solutions align with real clinical needs.