Computer simulation as a macroergonomic approach to assessing nurse workload and biomechanics related to COVID-19 patient care.

Digital human modeling Discrete event simulation Healthcare ergonomics Macroergonomics Pandemic planning Sociotechnical systems

Journal

Applied ergonomics
ISSN: 1872-9126
Titre abrégé: Appl Ergon
Pays: England
ID NLM: 0261412

Informations de publication

Date de publication:
Jan 2024
Historique:
received: 19 01 2023
revised: 19 08 2023
accepted: 22 08 2023
medline: 13 11 2023
pubmed: 2 9 2023
entrez: 1 9 2023
Statut: ppublish

Résumé

This study uses Digital Human Modelling (DHM) and Discrete Event Simulation (DES) to examine how caring for COVID-19-positive (C+) patients affects nurses' workload and care-quality. DHM inputs include: nurse anthropometrics, task postures, and hand forces. DES inputs include: unit-layout, patient care data, COVID-19 status & impact on tasks, and task execution-logic. The study shows that reducing nurses' biomechanical workload increases mental workload and decreases direct patient care, potentially leading to stress, burnout, and errors. Compared to pre-pandemic conditions, when nurses were assigned five C+ patients, cumulative bilateral shoulder moments and lumbar load decreased by 38%, 36%, and 46%, respectively. However, this was accompanied by increases in mental workload (242%), task waiting-time (70%), and missed-care (353%). These effects were driven by the large increase in required infection control routines. Combining DHM and DES can help evaluate workplace/task designs and provide valuable insights for healthcare system design-policy setting and operational management decision-making.

Identifiants

pubmed: 37657241
pii: S0003-6870(23)00162-X
doi: 10.1016/j.apergo.2023.104124
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

104124

Informations de copyright

Copyright © 2023 Elsevier Ltd. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Sadeem Munawar Qureshi (SM)

Human Factors Engineering Lab, Department of Mechanical and Industrial Engineering, Toronto Metropolitan University (formerly Ryerson University), Toronto, Ontario, Canada. Electronic address: s1qureshi@torontomu.ca.

Michael A Greig (MA)

Human Factors Engineering Lab, Department of Mechanical and Industrial Engineering, Toronto Metropolitan University (formerly Ryerson University), Toronto, Ontario, Canada.

Sue Bookey-Bassett (S)

Daphne Cockwell School of Nursing, Toronto Metropolitan University (formerly Ryerson University), Toronto, Canada.

Nancy Purdy (N)

Daphne Cockwell School of Nursing, Toronto Metropolitan University (formerly Ryerson University), Toronto, Canada.

Helen Kelly (H)

University Health Network, Toronto, Ontario, Canada.

Anne vanDeursen (A)

Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.

W Patrick Neumann (WP)

Human Factors Engineering Lab, Department of Mechanical and Industrial Engineering, Toronto Metropolitan University (formerly Ryerson University), Toronto, Ontario, Canada.

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Classifications MeSH