E-prescriptions may be vulnerable to error, study finds

About 10% of electronically generated prescriptions in a recent study included at least one error, and one-third of these mistakes had potential for harm.

Researchers conducted a retrospective cohort study of 3,850 e-prescriptions received by a commercial outpatient pharmacy chain across three states over four weeks in 2008. All the prescriptions were from ambulatory care clinicians. A panel reviewed them for medication errors, potential adverse drug events, and rate of prescribing errors by type and by prescribing system. Results were published online June 29 by the Journal of the American Medical Informatics Association.

Of the 3,850 prescriptions, 452 (11.7%) contained 466 errors, of which 163 (35%) were potential adverse drug events. Of the potential adverse drug events, 95 (58.3%) were significant, 68 (41.7%) were serious and none were life-threatening.

The most common cause for error was omitted information (60.7% of total errors and 50.9% of potential adverse drug events). The most likely omissions were duration, dose, or frequency. Omitted dose was the most likely error to result in a potential adverse drug event, and accounted for 35% of all potential adverse drug events. Other types of errors were information that was unclear (16.1% of total errors, 19.6% of potential adverse drug events), conflicting (15.7% of total errors, 16.0% of potential adverse drug events), or clinically incorrect (7.5% of total errors, 13.5% of potential adverse drug events).

There was a significant variation by prescribing system in the types of prescribing errors (P<0.001) and the potential for adverse drug events (P<0.002). Prescribing error rates ranged from 5.1% (95% CI, 0.3% to 9.9%) to 37.5% (95% CI, 23.5% to 51.5%) among the different systems.

The researchers noted that the error rates seen with e-prescribing in their study were similar to those reported in the literature for handwritten prescriptions. They suggested some computer-based and clinician-based strategies to minimize the errors associated with computer-generated prescriptions. Computer-based strategies include forcing functions, specific drug decision-support systems such as maximum dose checkers, and calculators. Clinician-based strategies may include rigorous vendor selection, increased financial incentives and better training.