An algorithm for integrating contraindications into electronic prescribing decision support.
BACKGROUND
Contraindications to medicines define circumstances in which the medicines must not be given. Computerized prescribing systems with decision support should display alerts to warn prescribers of contraindications. However, for such systems to be effective, alerts should only be displayed when relevant.


OBJECTIVE
We set out to construct an algorithm that would classify contraindications according to the data available to a computerized system, and allow them to be displayed in context as far as possible.


METHODS
We drafted an initial algorithm from first principles, refined it by classifying further datasets, and then tested it on a further set of 95 phrases for contraindications.


RESULTS
We were able to classify 94 of the 95 phrases; 13 related to age or sex and four related to allergies, but the majority depended on co-morbid conditions.


CONCLUSIONS
We have constructed a practicable algorithm for classifying alerts to contraindications. The classification used will allow alerts to be displayed when relevant. However, most contraindications relate to co-morbid conditions, and prescribing systems will only be able to display these in context if they have access to relevant clinical data.
West Midlands Centre for Adverse Drug Reactions, City Hospital, Birmingham, UK. r.e.ferner@bham.ac.uk
Robin E
RE
Ferner
Jamie J
JJ
Coleman
D000465:Algorithms; D015897:Comorbidity; D000075202:Contraindications; D020000:Decision Support Systems, Clinical; D004346:Drug Information Services; D004358:Drug Therapy; D064420:Drug-Related Side Effects and Adverse Reactions; D055695:Electronic Prescribing; D006801:Humans; D050316:Medical Order Entry Systems; D016347:Medical Records Systems, Computerized; D009626:Terminology as Topic