Kathleen R Meyer1, Paulette B Fraser, Rebecca T Emeny. 1. Author Affiliations: Director of Staff Education and Informatics (Ms Meyer), Mt Ascutney Hospital and Health Center, Windsor, Vermont; and Informatics Nurse Specialist (Ms Fraser), Dartmouth-Hitchcock Medical Center; and Research Scientist (Dr Emeny), The Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire.
Abstract
OBJECTIVE: To determine a just and consistent practice for creating nursing assignments. BACKGROUND: Traditional methods of assigning patients to nurses may lead to unbalanced nursing workload. This article describes the ongoing, hospital-wide effort to evaluate and implement a nursing assignment tool based on electronic health record (EHR) functionality and auto-calculated nursing workload scores. METHODS: EHR records of individual patient workload scores from all hospital units were collected from August 2017 to June 2018. A nurse-specific total workload score was summed for each staff. Then, each hospital unit's mean nurse workload score and standard deviation, along with the unit's nurse-to-patient ratio, were used to calculate levels of high, medium, and low nursing workload measurement (NWM). RESULTS: Mean patient-specific workload scores varied greatly across hospital units. Unit-specific nurse-to-patient ratios were factored into NWM scores to create ranges for assignments that were relatively consistent across the institution. CONCLUSION: The use of objective, electronically generated nursing workload scores, combined with traditional nurse-to-patient ratios, provides accurate real-time nurse staffing needs that can inform best practice in staffing. The confirmation of individual patient workload scores and an appreciation for the complexity of EHR vendor rules are necessary for successful implementation. Automation ensures patient safety, staff satisfaction, and optimal resource allocation.
OBJECTIVE: To determine a just and consistent practice for creating nursing assignments. BACKGROUND: Traditional methods of assigning patients to nurses may lead to unbalanced nursing workload. This article describes the ongoing, hospital-wide effort to evaluate and implement a nursing assignment tool based on electronic health record (EHR) functionality and auto-calculated nursing workload scores. METHODS: EHR records of individual patient workload scores from all hospital units were collected from August 2017 to June 2018. A nurse-specific total workload score was summed for each staff. Then, each hospital unit's mean nurse workload score and standard deviation, along with the unit's nurse-to-patient ratio, were used to calculate levels of high, medium, and low nursing workload measurement (NWM). RESULTS: Mean patient-specific workload scores varied greatly across hospital units. Unit-specific nurse-to-patient ratios were factored into NWM scores to create ranges for assignments that were relatively consistent across the institution. CONCLUSION: The use of objective, electronically generated nursing workload scores, combined with traditional nurse-to-patient ratios, provides accurate real-time nurse staffing needs that can inform best practice in staffing. The confirmation of individual patient workload scores and an appreciation for the complexity of EHR vendor rules are necessary for successful implementation. Automation ensures patient safety, staff satisfaction, and optimal resource allocation.
Authors: Darja Jarošová; Renáta Zeleníková; Ilona Plevová; Eva Mynaříková; Miroslava Kachlová Journal: Int J Environ Res Public Health Date: 2022-04-26 Impact factor: 4.614
Authors: María Elisa Moreno-Fergusson; William Javier Guerrero Rueda; Germán A Ortiz Basto; Indira Alba Lucia Arevalo Sandoval; Beatriz Sanchez-Herrera Journal: J Nurs Scholarsh Date: 2021-10-19 Impact factor: 3.928