Objective: To assess if the amount of time a pharmacist spends verifying medication orders increases as medication orders become more complex.

Materials and methods: The study was conducted by observing pharmacist verification of adult medication orders in an academic medical center. Drug order complexity was prospectively defined and validated using a classification system derived from 3 factors: the degree of order variability, ISMP high-alert classification, and a pharmacist perception survey. Screen capture software was used to measure pharmacist order review time for each classification. The annualized volume of low complexity drug orders was used to calculate the potential time savings if these were verified using an alternate system that did not require pharmacist review.

Results: The primary study hypothesis was not achieved. Regression results did not show statistical significance for moderate (n = 30, 23.7 seconds, sd = 23.3) or high complexity (n = 30, 18.6 seconds, sd = 23.1) drugs relative to the low complexity drugs (n = 30, 8.0 seconds, sd = 14.4) nor for moderate vs high complexity; (βmoderate vs low = 15.6, P = .113), (βhigh vs low = 10.3, P = .235), (βmoderate vs high = 5.3, P = .737). The sensitivity analysis showed statistical significance in the high vs low comparison (βhigh vs low = 13.8, P = .017).

Discussion: This study showed that verifying pharmacists spent less time than projected to verify medication orders of different complexities, but the time did not correlate with the classifications used in our complexity scale. Several mitigating factors, including operational aspects associated with timing antimicrobial orders, likely influenced order verification time. These factors should be evaluated in future studies which seek to define drug order complexity and optimize pharmacist time spent in medication order verification.

Conclusion: The findings suggest that there may be other factors involved in pharmacist decision-making that should be considered when categorizing drugs by perceived complexity.