Abstract
There is a growing recognition of the impact of a multi-dimensional safety culture on patient safety practices within healthcare organizations. Despite this awareness, understanding the relationships among safety culture dimensions and their relative importance in dynamic and complex healthcare delivery remains unclear. To address this gap, we developed a Bayesian Belief Network (BBN) model to quantitatively assess the significance of various safety culture dimensions in influencing patient safety. Utilizing Hospital Survey on Patient Safety Culture (HSOPSC) SOPS Hospital Survey 2.0 data from U.S. teaching hospitals, this study provides insights into the strength of influence among interconnected variables, explores primary factors contributing to the patient safety, and offers guidance for decision-makers on optimal resource utilization by prioritizing safety culture dimensions based on their relative importance. Our findings identify three leading dimensions of safety culture for their significant association with patient safety ratings: ’communication openness,’ ’supervisor support for patient safety,’ and ’organizational learning – continuous support’. This analysis supports decision-making, providing insights into the relative priority of safety culture dimensions for optimal resource allocation. The BBN is a novel methodology, providing a visual representation of the probabilistic relationships and potential approaches for enhancing patient safety within healthcare settings.
| Original language | British English |
|---|---|
| Article number | 106817 |
| Journal | Safety Science |
| Volume | 186 |
| DOIs | |
| State | Published - Jun 2025 |
Keywords
- Artificial intelligence
- Bayesian Belief Network
- Healthcare analytics
- Machine learning
- Patient safety
- Safety culture
- SOPS hospital survey 2.0
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