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

J Nurs Care Qual. 2022 Apr-Jun;37(2):103-109. doi: 10.1097/NCQ.0000000000000600.

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.

MeSH terms

  • Cross-Sectional Studies
  • Humans
  • Machine Learning
  • Nurses*
  • Nursing Staff, Hospital* / psychology
  • Patient Care
  • Surveys and Questionnaires
  • Workplace