Developing a simulation tool to quantify biomechanical load and quality of care in nursing

Abstract

Nursing is a high musculoskeletal disorder (MSD) risk job with high workload demands. This study combines Digital Human Modelling (DHM) and Discrete Event Simulation (DES) to address the need for tools to better manage MSD risk. This novel approach quantifies physical-workload, work-performance, and quality-of-care, in response to varying geographical patient-bed assignments, patient-acuity levels, and nurse-patient ratios. Lumbar loads for 86 care-delivery tasks in an acute care hospital unit were used as inputs in a DES model of the care-delivery process, creating a shift-long time trace of the biomechanical load. Peak L4/L5 compression and moment were 3574 N and 111.58 Nm, respectively. This study reports trade-offs in all three experiments: (i) increasing geographical patient-bed assignment distance decreased L4/L5 compression (8.8%); (ii) increased patient-acuity decreased L4/L5 moment (4%); (iii) Increased nurse-patient ratio decreased L4/L5 compression (10%) and moment (17%). However, in all experiments, Quality of care indicators deteriorated (20, 19, and 29%, respectively).

Practitioner Summary: This research has the potential to support decision-makers by developing a simulation tool that quantifies the impact of varying operational and design-policies in terms of biomechanical-load and quality of care. The demonstrator-model reports: as geographical patient-bed distance, patient-acuity levels, and nurse-patient ratios increase, biomechanical-load reduces, and quality of care deteriorates.

Keywords:

• Digital human modelling
• discrete event simulation
• MSD risk
• human factors
• healthcare ergonomics

Acknowledgments

The authors would like to acknowledge all the wonderful nurses and support staff that assisted us in making this study a reality. Special thanks to the nurse that volunteered to participate in the 8-h video recording study.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Ethical approval

The study was approved by the Ryerson Research Ethics Board (REB # 2017-340) and the Field study site’s Research Ethics Board (# 17-6084).

Additional information

Funding

This research was funded by NSERC (Natural Sciences and Engineering Research Council of Canada) under Discovery Grants (RGPIN 2018-05956 and Grant # 341664); and the Centre of Research Expertise for the Prevention of Musculoskeletal Disorders (CRE-MSD) under the Research Seed Grant # 2017-18.