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A Review on Cdss Alerts Optimization: Balancing Precision and Relevance.

Zaib Un Nisa Khosa¹, Maryati Mohd Yusof¹

¹Faculty of Information Science and Technology, University Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia.

Studies in Health Technology and Informatics

|August 8, 2025

Summary

This summary is machine-generated.

Optimizing clinical decision support systems (CDSS) alerts is crucial for reducing medication errors. Tailoring alerts with patient-specific data enhances their precision and clinical relevance, improving patient safety.

Keywords:

Clinical decision support system alert alert fatigue alert precision clinical relevance evaluation framework

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Area of Science:

Health Informatics
Patient Safety
Clinical Decision Support

Background:

Clinical decision support systems (CDSS) aim to minimize medication errors but face challenges like alert fatigue and high override rates.
Ineffective CDSS alerts reduce their impact on improving patient safety and medication error reduction.
Existing frameworks offer insights but require integration for comprehensive alert optimization.

Purpose of the Study:

To review challenges in CDSS alert effectiveness for medication error reduction.
To explore optimization strategies for CDSS alerts using socio-technical frameworks.
To propose a practical pathway for enhancing CDSS alert precision and clinical relevance.

Main Methods:

Review of literature on CDSS challenges and optimization strategies.
Analysis of socio-technical frameworks: HOPT-fit, TDF, and GUIDES.
Application of the five rights principle and a four-stage validation strategy.
Emphasis on tailoring alerts with patient-specific and context-sensitive data.

Main Results:

Identified key challenges: alert fatigue, irrelevant alerts, and high override rates.
Highlighted the importance of alert specificity, sensitivity, and clinician engagement.
Demonstrated the utility of socio-technical frameworks in addressing CDSS alert issues.
Proposed a strategy for enhancing CDSS alert effectiveness through data tailoring.

Conclusions:

Optimizing CDSS alerts requires addressing socio-technical factors and improving alert design.
Tailoring alerts with patient-specific and context-sensitive data is essential for enhancing precision and relevance.
This approach offers a practical method to improve CDSS alert effectiveness and patient outcomes.