The development and evaluation of a predictive productivity model in the ambulatory oncology infusion setting

Purpose: Accurately describing pharmacy productivity in the ambulatory oncology infusion setting is important to ensure appropriate labor utilization. The purpose of this study was to develop a productivity model utilizing weighted medication complexity and prospective schedule data to determine if predicted productivity corresponds to actual productivity across 6 ambulatory oncology infusion sites.Methods: This study was a 2-part analysis. Part 1 was to modify the historic productivity model from dispense code weighting to individual medication complexity weighting. Medicationspecific relative value units were determined by analyzing 12 months of historic timestamp data from the electronic health record and gravimetric technology software. The productivity model containing updated relative value units was compared to the historic model to determine if the difference in total calculated full-time equivalents (FTEs) was within 2.0 FTEs. Part 2 applied prospective infusion schedule data to the updated model to determine if predicted productivity corresponded to actual productivity (within 2.0 FTEs) for pharmacy infusion services.Results: The mean difference in total calculated FTEs for infusion during the study period was 2.46 (standard deviation = 1.87) and was within the range of 2.0 FTEs (P = 0.54), indicating that the updated model was not statistically different from the historic model. The mean difference in total calculated FTEs between the predictive and actual productivity model for infusion was 18.28 (standard deviation = 1.00) and was out of the range of 2.0 FTEs (P < 0.001), indicating that predicted productivity was statistically different from the actual productivity.Conclusion: Medication complexity weighting can be used to provide a comprehensive assessment of workload and productivity across pharmacy infusion services. The methodology used to assess predictive productivity should be explored further. (c) 2022 American Pharmacists Association (R). Published by Elsevier Inc. All rights reserved.