Predicting nurse fatigue from measures of work demands

Fatigue arising from excessive work demands is a known safety challenge in hospital nurses. This study aimed to determine which measures of work demands during nursing work are most predictive of hospital nurse fatigue levels at the end of the work shift. Measures of work demands of registered nurses from two hospital units in the United States were collected from organizational data sources, wearable sensors, and questionnaires. Fatigue levels were measured at the start and end of each shift using the Brief Fatigue Inventory. Multilevel linear regression analysis was used to predict end of shift fatigue based on work demand variables. The best fit model included multiple variables from organizational data sources and a physical activity variable measured by a wearable sensor. Organizational data can be used to create dynamic measures of work demands as they occur and predict end of shift fatigue levels in hospital nurses.

Automated summary

This study investigated the impact of work demands on hospital nurse fatigue levels by collecting data from registered nurses and using multilevel linear regression analysis. The results indicated that organizational data and wearable sensors can be used to predict fatigue levels in hospital nurses at the end of their shifts.