PHARMACOVIGILANCE AND PATIENT SAFETY IN PAKISTAN: EVALUATING AI-DRIVEN ADVERSE DRUG REACTION MONITORING IN HOSPITAL SETTINGS

Abstract

The rising incidence of adverse drug reactions (ADRs) poses a significant challenge to patient safety in hospital settings, particularly in low- and middle-income countries such as Pakistan. This study evaluated the effectiveness of AI-driven pharmacovigilance systems in monitoring and managing ADRs across selected tertiary care hospitals. Using a mixed-methods approach, quantitative analysis measured ADR detection rates, response times, and severity reduction, while qualitative feedback assessed clinician perceptions and system usability. The findings revealed a substantial increase in ADR detection efficiency, a reduction in moderate and severe ADRs, and positive clinician acceptance of AI integration. These results underscore the potential of AI tools to enhance patient safety, streamline pharmacovigilance workflows, and support evidence-based clinical decision-making. The study provides practical recommendations for institutional adoption, training, and policy development, highlighting pathways for broader implementation in healthcare systems.