Tailoring of alerts substantially reduces the alert burden in computerized clinical decision support for drugs that should be avoided in patients with renal disease.
OBJECTIVE
Electronic alerts are often ignored by physicians, which is partly due to the large number of unspecific alerts generated by decision support systems. The aim of the present study was to analyze critical drug prescriptions in a university-based nephrology clinic and to evaluate the effect of different alerting strategies on the alert burden.


METHODS
In a prospective observational study, two advanced strategies to automatically generate alerts were applied when medication regimens were entered for discharge letters, outpatient clinic letters, and written prescriptions and compared to two basic reference strategies. Strategy A generated alerts whenever drug-specific information was available, whereas strategy B generated alerts only when the estimated glomerular filtration rate of a patient was below a drug-specific value. Strategies C and D included further patient characteristics and drug-specific information to generate even more specific alerts.


RESULTS
Overall, 1012 medication regimens were entered during the observation period. The average number of alerts per drug preparation in medication regimens entered for letters was 0.28, 0.080, 0.019, and 0.011, when using strategy A, B, C, or D (P<0.001, for comparison between the strategies), leading to at least one alert in 87.5%, 39.3%, 13.5%, or 7.81 % of the regimens. Similar average numbers of alerts were observed for medication regimens entered for written prescriptions.


CONCLUSIONS
The prescription of potentially hazardous drugs is common in patients with renal impairment. Alerting strategies including patient and drug-specific information to generate more specific alerts have the potential to reduce the alert burden by more than 90 %.
Department of Clinical Pharmacology and Pharmacoepidemiology, University Hospital Heidelberg, Heidelberg, Germany david.czock@med.uni-heidelberg.de.
David
D
Czock
Department of Clinical Pharmacology and Pharmacoepidemiology, University Hospital Heidelberg, Heidelberg, Germany.
Michael
M
Konias
Department of Clinical Pharmacology and Pharmacoepidemiology, University Hospital Heidelberg, Heidelberg, Germany Cooperation Unit Clinical Pharmacy, University Hospital Heidelberg, Heidelberg, Germany.
Hanna M
HM
Seidling
Department of Clinical Pharmacology and Pharmacoepidemiology, University Hospital Heidelberg, Heidelberg, Germany.
Jens
J
Kaltschmidt
Department of Nephrology, University Hospital Heidelberg, Heidelberg, Germany.
Vedat
V
Schwenger
Department of Nephrology, University Hospital Heidelberg, Heidelberg, Germany.
Martin
M
Zeier
Department of Clinical Pharmacology and Pharmacoepidemiology, University Hospital Heidelberg, Heidelberg, Germany.
Walter E
WE
Haefeli
D000075202:Contraindications; D020000:Decision Support Systems, Clinical; D004358:Drug Therapy; D004360:Drug Therapy, Computer-Assisted; D005858:Germany; D005919:Glomerular Filtration Rate; D006785:Hospitals, University; D006801:Humans; D050316:Medical Order Entry Systems; D008508:Medication Errors / Q000517:prevention & control; D011446:Prospective Studies; D051437:Renal Insufficiency / Q000188:drug therapy*
clinical decision support systems; contraindications; medical order entry systems; renal insufficiency