ReviewFrontiers in digital health2025
Using shared clinical decision support to reduce adverse drug events and improve patient safety.
Review in Frontiers in digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Digital health technology burden and frustration among patients with multimorbidity.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- Integrating clinical decision support systems, nursing vigilance, and physician prescribing patterns to reduce preventable adverse drug events: a structured evidence-based narrative review on human-AI interface in medication safety.Frontiers in digital health · 2026Review
- Identifying Digital Health Technology Engagement and Frustration Phenotypes in Patients with Multiple Chronic Conditions: Evidences from a Nationally Representative Cross-Sectional Study.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: 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. Objective: 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. Methods: 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. Results: 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. Conclusions: 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.
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Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.