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. Medication-specific 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.

Coronavirus 2019 work-from-home productivity of inpatient and infusion pharmacists at a comprehensive cancer center.

PURPOSE: To evaluate inpatient and infusion pharmacist order verification productivity when working from home and to report their perceptions of a flexible workplace setting. METHODS: Order verification data were pulled from the electronic medical record from April 27, 2020, to June 30, 2020, matched to the pharmacist schedule on the basis of work setting and reported as average orders verified per day. Pharmacist perceptions were gathered via a survey to evaluate practice setting background, workplace setting preference, and perceived changes in workflow and their productivity. RESULTS: There was an overall increase in order verification productivity when working from home. Inpatient pharmacists, on average, verified 152 orders per day from home and 133 orders per day onsite. Infusion pharmacists, on average, verified 144 orders per day working from home and 117 orders per day working onsite. Fifty-nine percent of pharmacists reported preferring the mix of onsite and home workplace setting and noted little change in workflow. In addition, 57% of the pharmacists perceived themselves as being more productive, 32% as maintaining the same level of productivity, and 10% felt that they are less productive when working from home. The order verification data showed a greater increase in productivity for infusion shifts worked from home than inpatient shifts. CONCLUSION: The coronavirus 2019 pandemic prompted pharmacy departments to re-evaluate their ability to provide an option for a flexible workplace for pharmacists. Our study demonstrates that pharmacists, on average, verified more orders when working from home, and they also perceive themselves as being more productive. The results of this study support long-term applicability of a flexible work schedule for inpatient and infusion pharmacists.

Longitudinal magnetic resonance imaging quantitation of rat liver regeneration after partial hepatectomy.

This report demonstrates the advantages of using a noninvasive soft tissue imaging technique--magnetic resonance imaging (MRI)--to monitor liver regeneration after 70% partial hepatectomy in the rat in a longitudinal manner. Six animals were scanned prior to and on 6 subsequent occasions up to 9 days after surgical removal of the median and left lateral lobes. Within the observed time frame liver volumes were restored to approximately 88% of presurgery values. Final liver volumes correlated well with postmortem liver weights (R = 0.93). Regeneration is well-quantified empirically by a 4 parameter logistic equation: % Regeneration = 84 - (84/(1 + (Days/2.31)(2.34))) The rate of regeneration was maximal at 1.5 days, which coincided with the maximum increase of Mitotic Index--a measure of cell proliferation, determined in a subsequent study. Pre- and postpartial hepatectomy measurements remove two potentially confounding unknowns--the presurgery liver volume, and the amount of liver actually excised. 3D reconstructions of the liver effectively illustrate the morphological changes associated with the procedure, and the regrowth of liver tissue.