Medication-Related Errors Among Nurses by Unit Adaptation Levels: Bayesian Network-Based Exploratory Study

Area of Science:

• Nursing Science
• Patient Safety
• Healthcare Education

Background:

• Medical errors are more frequent in healthcare than other industries.
• Challenges in patient safety education for nurses and students contribute to errors.
• Medication-related errors are preventable and highlight the need for data-driven safety education.

Purpose of the Study:

• To investigate the relationship between unit experience and the structure of medication-related errors.
• To explore the role of adaptive performance in nursing error occurrence.
• To inform data-driven patient safety education and nursing student instruction.

Main Methods:

• Mixed methods study utilizing qualitative root cause analysis of medication error reports.
• Bayesian network modeling (an AI approach) to visualize error-generation flows.
• Comparison of error models based on nurses' years of experience within their current unit.

Main Results:

• Internal medicine and surgical departments reported the highest number of medication errors.
• Lower unit adaptation was associated with more complex error structures and higher vulnerability.
• Extensive clinical experience did not consistently prevent errors and was linked to verification lapses.

Conclusions:

• Unit adaptation is a critical factor in shaping medication error pathways.
• Nurses with lower unit adaptation exhibit more complex error structures.
• Total nursing experience does not always reduce risk and may be associated with verification behavior lapses.