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TRUVACE RECORD VERSION
record: TRV-2026-2171
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-10-22T18:13:03.321755Z
status: published
lens: p_space
sector: health
headline: Artificial Intelligence in Pharmacy Services: A Comparative Bibliometric Analysis of United States and Global Research Trends
dek: 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 Bibl…
gain_title: (none)
problem_title: Research on AI in pharmacy services focuses on algorithm development while medication error prevention and patient safety themes are underrepresented, leaving a translational gap.
trace_subject: (none)
gain_reading: (none)
gain_evidence: (none)
problem_reading: Research on AI in pharmacy services focuses on algorithm development while medication error prevention and patient safety themes are underrepresented, leaving a translational gap.
problem_evidence: critical patient safety themes-medication error prevention and workflow optimization-were conspicuously underrepresented | Current AI-pharmacy research prioritizes algorithmic development over patient safety implementation.
quick_read: Researchers analyzed 4426 Web of Science documents on AI in pharmacy services published between 2015 and 2025, comparing United States output with work from elsewhere. Both groups of publications grew exponentially, and the United States produced 1619 of the documents, or 36.58% of the corpus.

The findings matter because AI is often presented as a way to ease pharmacy workforce strain and improve patient safety, yet the research record shows little focus on the safety problems it is meant to address. The study is a map of publication patterns, so it does not show how AI tools perform in actual pharmacies.
limitation: 
tag: Evidence-backed problem
key_points: The dataset covered 4426 Web of Science documents from 2015 to 2025, with 63.42% from outside the United States. | US research had higher international coauthorship than non-US research, at 35.08% versus 19.91%. | Prediction and risk were motor themes in US research. | Neither medication error nor patient safety appeared among high-frequency keywords. | The authors call for realignment toward medication error prevention and safety-focused applications.
rundown: The study used performance analysis and science mapping with Bibliometrix software. It compared US and non-US research output, how themes changed over time, and collaboration patterns.

The results showed that the US contributed 29.30% of global output. Its research had a stronger international coauthorship rate than the rest of the world.

Co-word analysis found that workflow optimization and medication error prevention were underrepresented, despite their clinical relevance. The authors conclude that research priorities should shift toward safety-focused implementation to improve pharmaceutical care quality.
sources:
- peer_reviewed | Journal of Patient Safety | https://doi.org/10.1097/pts.0000000000001600 | 2026-10-20
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