Workplace Predictors of Quality and Safe Patient Care Delivery Among Nurses Using Machine Learning Techniques.

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Date: Apr. 2022
From: Journal of Nursing Care Quality(Vol. 37, Issue 2)
Publisher: Lippincott Williams & Wilkins, WK Health
Document Type: Survey; Brief article
Length: 198 words

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Abstract :

Byline: Farinaz Havaei, University of British Columbia (UBC) School of Nursing, Vancouver, British Columbia, Canada (Dr Havaei); UBC Department of Educational and Counselling Psychology and Special Education, Vancouver, British Columbia, Canada (Dr Ji); and McMaster University School of Nursing, Hamilton, Ontario, Canada (Dr Boamah).; Xuejun Ryan Ji; Sheila A. Boamah Abstract BACKGROUND: Working in unhealthy environments is associated with negative nurse and patient outcomes. Previous body of evidence in this area is limited as it investigated only a few factors within nurses' workplaces. PURPOSE: The purpose of this study was to identify the most important workplace factors predicting nurses' provision of quality and safe patient care using a 13-factor measure of workplace conditions. METHODS: A cross-sectional correlational survey study involving 4029 direct care nurses in British Columbia was conducted using random forest data analytics methods. RESULTS: Nurses' reports of healthier workplaces, particularly workload management, psychological protection, physical safety and engagement, were associated with higher ratings of quality and safe patient care. CONCLUSION: These workplace conditions are perceived to impact patient care through influencing nurses' mental health. To ensure a high standard of patient care, data-driven policies and interventions promoting overall nurse mental health and well-being are urgently required.

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Gale Document Number: GALE|A694678299