Pharmacy Practice NewsPharmacists Step Up To Monitor AI Algorithms

Artificial intelligence implementation in pharmacy practice has evolved from basic autocomplete functions to complex medication management systems requiring specialized oversight. The emerging concept of “algorithmovigilance” positions pharmacists as essential monitors of AI algorithm accuracy and safety, paralleling traditional pharmacovigilance roles in drug safety surveillance.

⚕️ Key Clinical Considerations ⚕️

• Human-in-the-loop requirement: AI serves as decision support tool, with pharmacists maintaining final clinical judgment and prescription authority.
• Algorithmovigilance emergence: New professional responsibility involving continuous monitoring and adjustment of AI algorithms for optimal dosing accuracy.
• Expanded data mining capabilities: AI systems can process significantly more clinical data than traditional decision support tools for personalized recommendations.
• Genotype-specific dosing: Advanced AI applications can provide medication recommendations based on individual genetic profiles and optimal timing.
• Continuum of complexity: AI applications range from simple prescription autocomplete to sophisticated drug-drug interaction prevention and dose optimization.

🎯 Clinical Practice Impact 🎯

• Patient Communication: Pharmacists must explain AI-assisted recommendations while emphasizing their professional oversight and final decision-making authority.
• Practice Integration: Implementation requires training in algorithmovigilance principles and establishing protocols for monitoring AI system performance and accuracy.
• Risk Management: Continuous oversight of AI algorithms prevents potential dosing errors and ensures recommendations align with current evidence-based practices.
• Action Items: Develop competency in AI tool evaluation and establish systematic approaches for algorithm performance monitoring and adjustment.

More in Clinical Decision Support