Bridging generational gaps in medication safety: insights from nurses, students, and generative AI models

Area of Science:

• Nursing Practice
• Medical Education
• Health Informatics

Background:

• Investigated medication dose calculation accuracy in nurses, nursing students, and Generative AI (GenAI).
• Examined error prevention strategies across different generational cohorts in healthcare.
• Addressed persistent challenges in medication calculation within nursing practice.

Purpose of the Study:

• To compare medication dose calculation accuracy among nurses, students, and GenAI.
• To identify and analyze error prevention strategies related to medication dosage.
• To explore generational differences in approaches to medication safety.

Main Methods:

• Cross-sectional study conducted from June to August 2024.
• Involved 101 pediatric/neonatal nurses, 91 nursing students, and four GenAI models.
• Utilized questionnaires for proficiency assessment and qualitative analysis for attitudes and perceptions.

Main Results:

• 70% of nurses reported prior medication errors versus 19.5% of students.
• Six key error prevention areas identified: double-checking, calculation methods, environment, training, drug configuration, and technology.
• Students suggested GenAI integration; nurses prioritized double-checking.

Conclusions:

• Generational differences exist in medication safety strategies.
• GenAI shows potential as an additional verification layer for medication dosing.
• Findings support integrating technology into nursing education and practice to enhance medication safety.