Understanding prescribing errors for system optimisation: the technology-related error mechanism classification.

Area of Science:

• Health Informatics
• Medication Safety
• Clinical Systems

Background:

• Technology-related errors (TREs) diminish the benefits of computerized provider order entry (CPOE) for medication safety.
• Understanding TRE mechanisms is crucial for optimizing CPOE systems.
• A prior classification of TRE mechanisms was developed using adult hospital data.

Purpose of the Study:

• To update the existing TRE mechanism classification using pediatric prescribing error data.
• To evaluate the reliability of independent reviewers applying the updated classification.
• To inform CPOE optimization strategies in pediatric settings.

Main Methods:

• Analysis of 1696 prescribing errors from a tertiary pediatric hospital (2016-2017).
• Identification and investigation of technology-related errors (TREs).
• Classification of underlying mechanisms using an updated system, including simulation in a CPOE testing environment.

Main Results:

• The updated Technology-Related Error Mechanism (TREM) classification includes six mechanism categories and one contributing factor.
• Specific categories identified include incorrect system configuration, wrong patient record selection, construction errors, editing errors, workflow differences, and hybrid system use.
• The classification comprises 19 subcategories detailing specific error types.

Conclusions:

• TREs continue to pose a critical challenge within CPOE systems.
• The updated TREM classification offers a systematic approach to assess and monitor TREs.
• This classification, now validated in the pediatric setting, can guide CPOE system improvements and prioritize interventions.