Background: Collaboration between oncology providers and pharmacy teams has improved the safety of oral antineoplastic (OA) prescribing, but opportunities remain for improvements in care delivery. To this end, starting in March 1, 2021, the Dana Farber Cancer Institute Specialty Pharmacy implemented a new workflow - clinical verification of new specialty prescriptions by dedicated OA clinical pharmacists (OAPs) prior to prescription processing. To reduce the impact of initial prescription errors on efficiency and safety, one component of clinical verification was to expand the purview of OAPs to make certain modifications to prescriptions that could be automatically processed without requiring prescriber re-signing. Automatically processed prescription modifications include corrections to quantity or days supply, indication of cycle length or days on/off therapy, and clarification of directions. Here we report on the impact of this portion of the clinical verification program. Methods: OAP prescription modification (OAP-PM) was introduced on November 1, 2022. To assess the impact on efficiency, we conducted a pre-post analysis of the proportion of prescription modifications taking > 60 minutes to complete for 6 months before and after OAP-PM introduction. Using prescription-level data, we analyzed co-variates including pre-/post-OAP-PM, patient age (continuous), site (academic vs. network), communication with someone other than the primary prescriber (y/n), and medication category (anti-neoplastic vs. supportive). We used control charts to explore the contribution of specific medications and sites that might share best practices or be the focus of subsequent, more focused improvement projects. Results: From May 1, 2022 to May 1, 2023, 458 prescription modifications were completed, 180 pre- and 278 post-OAP-PM. The proportion of prescriptions requiring > 60 minutes to complete decreased from 29.4% to 19.8% (p = 0.0184). In multivariable regression, the significant predictors of prescription taking > 60 minutes to complete were pre-OAP-PM (LR 4.9, p = 0.027); network (LR 20.8, p < 0.0001); and communication with someone other than the primary provider (LR 18.6, p < 0.0010). Control charts demonstrated all sites were within 3-sigma limits pre- and post-OAP-PM, but with wide limits at many sites. Individual medications could not be meaningfully analyzed due to the small sample sizes. Conclusions: OAP-PM successfully reduced the proportion of OA prescriptions taking more than an hour to modify. This may be a useful workflow change for other specialty pharmacies to adopt to improve the efficiency of OA care. Additional work is needed to understand whether site-, provider- or medication-specific changes can improve upon this model.