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

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 pr...

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Detalles Bibliográficos
Autores principales: Havaei, Farinaz, Ji, Xuejun Ryan, Boamah, Sheila A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer Health, Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8860211/
https://www.ncbi.nlm.nih.gov/pubmed/34593739
http://dx.doi.org/10.1097/NCQ.0000000000000600
Descripción
Sumario: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.