Development of an inpatient operational pharmacy productivity model [Practice Report]

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Development of an inpatient operational pharmacy productivity model Ryan W. Naseman?, Ben R. Lopez, Ryan A. Forrey, Robert J. Weber and Kris M. Kipp

Ryan W. Naseman, Pharm.D., M.S., is Assistant Director of Pharmacy and Infusion; Ben R. Lopez, Pharm.D., M.S., M.H.A., is Assistant Director of Pharmacy and Infusion; and Ryan A. Forrey, Pharm.D., M.S., is Associate Director of Pharmacy and Infusion, The Ohio State University (OSU) James Cancer Center and Solove Research Institute, Columbus. Robert J. Weber, Pharm.D., M.S., is Administrator, Pharmacy Services, OSU Wexner Medical Center, and Assistant Dean, OSU College of Pharmacy, Columbus. Kris M. Kipp, M.S.N., is Executive Director, Patient Services, and Chief Nursing Officer, OSU James Cancer Hospital and Solove Research Institute. Address correspondence to Dr. Naseman (ryan.naseman{at}osumc.edu). Abstract Purpose An innovative model for measuring the operational productivity of medication order management in inpatient settings is described.

Methods Order verification within a computerized prescriber order-entry system was chosen as the pharmacy workload driver. To account for inherent variability in the tasks involved in processing different types of orders, pharmaceutical products were grouped by class, and each class was assigned a time standard, or “medication complexity weight” reflecting the intensity of pharmacist and technician activities (verification of drug indication, verification of appropriate dosing, adverse-event prevention and monitoring, medication preparation, product checking, product delivery, returns processing, nurse/provider education, and problem-order resolution). The resulting “weighted verifications” (WV) model allows productivity monitoring by job function (pharmacist versus technician) to guide hiring and staffing decisions. A 9-month historical sample of verified medication orders was analyzed using the WV model, and the calculations were compared with values derived from two established models—one based on the Case Mix Index (CMI) and the other based on the proprietary Pharmacy Intensity Score (PIS).

Results Evaluation of Pearson correlation coefficients indicated that values calculated using the WV model were highly correlated with those derived from the CMI-and PIS-based models (r = 0.845 and 0.886, respectively). Relative to the comparator models, the WV model offered the advantage of less period-to-period variability.

Conclusion The WV model yielded productivity data that correlated closely with values calculated using two validated workload management models. The model may be used as an alternative measure of pharmacy operational productivity.

Copyright ? 2015 by the American Society of Health-System Pharmacists, Inc. All rights reserved. CiteULike Delicious Digg Facebook Google+ Reddit Twitter What's this?

? Previous | Next Article ? Table of Contents This Article doi: 10.2146/ajhp130803 American Journal of Health-System Pharmacy February 1, 2015 vol. 72 no. 3 206-211 ? Abstract Full Text Full Text (PDF) Classifications Print Content Practice Report Services Email this article to a colleague Alert me when this article is cited Alert me if a correction is posted Alert me when eLetters are published Similar articles in this journal Similar articles in Web of Science Similar articles in PubMed Download to citation manager eLetters Submit an eLetter No eLetters published Citing Articles Load citing article information Google Scholar Articles by Naseman, R. W. Articles by Kipp, K. M. PubMed PubMed citation Articles by Naseman, R. W. Articles by Kipp, K. M. Related Content Load related web page information Social Bookmarking CiteULike Delicious Digg Facebook Google+ Reddit Twitter What's this?

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