Of these prescriptions, 452 (11.7%) contained a total of 466 errors and 163 (35.0%) of these errors were classified as potential adverse drug events (ADEs). Of the potential ADEs, 95 (58.3%) were classified as significant and 68 (41.7%) were classified as serious. However, none were life-threatening. The most common drug classes associated with the prescription errors were antimicrobials (40.3%), nervous-system drugs (13.9%), and respiratory-system drugs (8.6%). The most common drug classes associated with potential ADEs were nervous-system drugs (27.0%), cardiovascular drugs (13.5%), and antimicrobials (12.3%). About 60% of the potential errors were related to missing or omitted information. The researchers noted that error frequency with electronic prescriptions was consistent with outpatient handwritten and electronic prescription error rates reported in the literature.
The researchers identified interventions to reduce the error rate of outpatient electronic prescriptions, which include forcing functions, specific drug decision-support systems such as maximum dose checkers, and integration of calculators. Forcing functions, for example, can be used to prevent omitted information, such as incomplete drug names, medications that need patient instructions, and inappropriate abbreviations. The researchers noted that forcing functions could have eliminated 71.7% of total errors and 63.2% of potential ADEs.