Artificial intelligence integration and patient safety culture: a cross-sectional study of healthcare professionals...

This cross-sectional study investigates healthcare practitioners' perceptions of the implementation of artificial intelligence (AI) to enhance patient safety culture in Riyadh, Saudi Arabia, conducted from March to June 2025. The focus is on understanding how AI is perceived in the context of improving patient safety culture and aligning with Saudi Vision 2030 goals.

The study employed a cross-sectional design and administered self-administered online surveys via convenience sampling among healthcare practitioners across multiple healthcare settings in Riyadh. The study targeted a population including doctors, nurses, and allied health professionals. A structured questionnaire was developed to assess perceptions of AI, including key variables such as perceived AI benefits, concerns about data privacy, and the necessity of training. Descriptive statistics were computed to characterize the sample, including age, gender, and profession.

Findings revealed that most participants perceived AI as supportive of patient safety through improved diagnostic accuracy, reduced medical errors, and streamlined workflows, which participants believed may contribute to a stronger patient safety culture. Descriptive analyses suggested variation in perceptions across professional groups.

The study found that healthcare practitioners in Riyadh generally perceived AI as a potentially valuable tool for supporting patient safety culture, particularly through improving diagnostic accuracy and reducing errors; however, concerns about data privacy and insufficient training remain significant barriers that must be addressed to ensure effective and safe AI integration.

This study highlighted healthcare practitioners' positive perception of AI's role in enhancing patient safety culture in Riyadh. While AI is seen as beneficial in improving accuracy and reducing errors, challenges such as data privacy concerns and a lack of training were identified as barriers to its implementation.

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