Artificial Intelligence in Pharmacy Services: A Comparative Bibliometric Analysis of United States and Global Research Trends.

Objectives

Artificial intelligence (AI) technologies offer transformative potential to address pharmacy workforce challenges and enhance patient safety. This study aimed to characterize the global landscape of AI research in pharmacy services and identify gaps between research activity and patient safety priorities.

Methods

A bibliometric analysis was conducted on AI-pharmacy services publications indexed in Web of Science (2015-2025). Performance analysis and science mapping techniques were applied using Bibliometrix software to compare United States and non-U.S. research output, thematic evolution, and collaboration patterns.

Results

A total of 4426 documents met inclusion criteria, comprising 1619 (36.58%) United States and 2807 (63.42%) non-U.S. publications. Both corpora exhibited exponential growth. The United States contributed 29.30% of global output with higher international coauthorship rates (35.08% versus 19.91%). Thematic mapping identified "prediction" and "risk" as motor themes in U.S. research. However, co-word analysis revealed a significant translational gap: critical patient safety themes-medication error prevention and workflow optimization-were conspicuously underrepresented. Neither "medication error" nor "patient safety" appeared among high-frequency keywords despite substantial clinical relevance.

Conclusions

Current AI-pharmacy research prioritizes algorithmic development over patient safety implementation. Strategic realignment toward medication error prevention and safety-focused applications is warranted to realize AI's potential in enhancing pharmaceutical care quality.