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

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.

Automated summary

This study utilizes Digital Human Modelling (DHM) and Discrete Event Simulation (DES) to examine the impact of caring for COVID-19-positive patients on nurses' workload and care-quality. The findings show that reducing nurses' biomechanical workload increases mental workload and decreases direct patient care, potentially leading to stress, burnout, and errors.