Using shared clinical decision support to reduce adverse drug events and improve patient safety

Medications, while essential therapeutic tools in modern healthcare, carry the inherent risk of causing adverse drug events (ADEs) that can result in significant morbidity, mortality, and healthcare costs. Despite substantial research efforts in this domain, the majority of ADEs remain undetected due to reliance on voluntary reporting systems and inadequate surveillance mechanisms. Consequently, the true scope and impact of ADEs are likely far greater than currently recognized.

To examine the role of shared clinical decision support (SCDS) in reducing adverse drug events and enhancing patient safety outcomes through systematic integration of clinical decision support systems with shared decision-making frameworks.

We conducted a narrative review of literature published up to June 2025, utilizing validated patient safety frameworks to identify contextual factors, systemic challenges, and evidence-based strategies that influence adverse drug event occurrence and prevention.

Multiple interconnected factors contribute to ADE susceptibility, including healthcare provider competencies (inadequate monitoring, symptom recognition failures), clinical environment characteristics (technology workarounds, equipment complexity), pharmacy system factors (high-risk medication storage, limited pharmacist involvement), and patient-specific variables (polypharmacy, multimorbidity, age-related physiological changes). Critical risk determinants include provider fatigue and burnout, inadequate monitoring protocols, medication administration errors, and systemic communication failures. Successful implementations require multifaceted approaches integrating health information technology components, stakeholder engagement, customized clinical decision rules, and continuous quality improvement processes.

Shared clinical decision support represents a paradigm shift toward patient empowerment, enabling active patient participation in healthcare decisions while leveraging technology-enhanced clinical guidance. The most promising approach to ADE elimination involves a comprehensive integration of educational initiatives, human factors engineering, robust shared clinical decision support systems, and multidisciplinary collaborative care models.