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An algorithm for integrating contraindications into electronic prescribing decision support.

Robin E Ferner¹, Jamie J Coleman

¹West Midlands Centre for Adverse Drug Reactions, City Hospital, Birmingham, UK. r.e.ferner@bham.ac.uk

|October 22, 2010

Summary

This summary is machine-generated.

An algorithm was developed to classify drug contraindications, ensuring alerts are relevant for prescribers. Most contraindications involve co-morbid conditions, requiring clinical data for contextual alerts in prescribing systems.

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Improving IV Insulin Administration in a Community Hospital

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Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

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Published on: May 15, 2020

Improving IV Insulin Administration in a Community Hospital

Improving IV Insulin Administration in a Community Hospital

Published on: June 11, 2012

Area of Science:

Medical Informatics
Clinical Pharmacology

Background:

Contraindications are critical safety information for medication use.
Computerized prescribing systems aim to alert clinicians to potential contraindications.
Effective alerts require relevance to the specific clinical context.

Purpose of the Study:

To develop an algorithm for classifying contraindications.
To enable context-aware display of contraindication alerts in computerized systems.

Main Methods:

Algorithm development from first principles.
Refinement through classification of additional datasets.
Testing on 95 contraindication phrases.

Main Results:

Successfully classified 94 out of 95 contraindication phrases.
Identified 13 contraindications related to age/sex and 4 to allergies.
The majority of contraindications were linked to co-morbid conditions.

Conclusions:

A practical algorithm for classifying contraindication alerts has been created.
The algorithm facilitates context-relevant alert display.
Effective contextual alerts for co-morbid condition contraindications depend on integrated clinical data access.