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ZENODO
Article . 2024
License: CC BY
Data sources: ZENODO
ZENODO
Article . 2024
License: CC BY
Data sources: Datacite
ZENODO
Article . 2024
License: CC BY
Data sources: Datacite
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Reducing Medication Errors through Clinical Decision Support Systems: A Collaborative Approach between Pharmacists and Health Informaticians

Authors: Faisal E. Aljwuaied; Abdullah I. Hamran; Abdulellah S. Almutairi; Samer A. Al Shahrani; Shatha H. Abujabah; Hadeel M. Alharbi; Raed K. Almalki; +1 Authors

Reducing Medication Errors through Clinical Decision Support Systems: A Collaborative Approach between Pharmacists and Health Informaticians

Abstract

This study evaluates the impact of Clinical Decision Support Systems (CDSS) on reducing medication errors and enhancing patient safety in a tertiary hospital. A mixed-methods approach was employed, including a retrospective analysis of medication error rates and qualitative insights from pharmacists and health informaticians. Quantitative findings revealed a 50% reduction in total medication errors post-CDSS implementation, with significant decreases in drug-drug interaction and allergy-related errors. Qualitative analysis highlighted themes such as improved patient safety, enhanced workflow efficiency, and challenges like alert fatigue and technical barriers. Collaboration between pharmacists and health informaticians emerged as a key factor in optimizing CDSS utility. Recommendations include tailoring alerts, ongoing training, and robust system design to address identified challenges. These findings underscore the potential of CDSS in improving medication safety and healthcare delivery in tertiary hospital settings.

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    popularity
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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green