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December 15, 2025The Japanese Journal of ErgonomicsOpen Access

Construction of a Model to Estimate Nurse Workload in Real-Time and Proactively under Fluctuating Conditions

Yuki MEKATA Aika KISHIGAMI Jun Hamaguchi Miwa NAKANISHI

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Key Points

The model predicts ICU nurse workload in real-time using various collected data, enhancing operational efficiency.
Key accuracy metrics showed that the GBDT model achieved nearly 80% accuracy when small differences were allowed.
The analysis leveraged 130 features from NASA-TLX scores and data from nurses and simulators over simulated tasks.
Incorporating data from other nurses and patients significantly improves workload level predictions.

Implication

Observational analysis estimates nurse workload in ICU, indicating machine learning applications.

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Cite This Study

MEKATA et al. (2025) studied this question.

synapsesocial.com/papers/69a75ec4c6e9836116a29abb https://doi.org/10.5100/jje.61.355

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