Indication-based prescribing prevents wrong-patient medication errors in computerized provider order entry (CPOE).

Area of Science:

• Health Informatics
• Patient Safety
• Clinical Decision Support

Background:

• Wrong-patient medication errors pose a significant risk in healthcare.
• Clinical decision support systems aim to mitigate such errors.
• Indication-based alerts are a type of clinical decision support.

Purpose of the Study:

• To evaluate the effectiveness of indication-based computer order entry alerts in intercepting wrong-patient medication errors.
• To quantify the rate at which these alerts prevent such errors.

Main Methods:

• A clinical decision support system was developed and implemented at an academic medical center.
• Alerts prompted clinicians for medication indications when not coded on the problem list.
• Instances where a prescriber ordered the same medication for different patients within a time frame were reviewed to identify intercepted errors.

Main Results:

• Over six years, 127,320 alerts fired, resulting in 32 intercepted wrong-patient errors.
• The interception rate was 0.25 per 1000 alerts.
• Prescriber location or type did not influence the interception rate; 59% of intercepted errors involved prescribers with both patients' charts open.

Conclusions:

• Indication-based alerts, linked to the problem list, demonstrate a new benefit beyond improving problem list completion.
• These alerts effectively intercept wrong-patient medication errors, with a quantifiable interception rate.
• Indication-based alerts represent a valuable strategy for reducing wrong-patient medication errors, usable alone or with other methods.