Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.orhc.2013.11.002
Title: Enhancement of patient and staff experience at outpatient pharmacy via optimization of drug-shelf reallocation
Authors: Oh, H.C. 
Wong, J.A.
Tan, M.C.
Keywords: Drug
Outpatient pharmacy
Safety
Shelf allocation
Staff
Issue Date: Mar-2014
Citation: Oh, H.C., Wong, J.A., Tan, M.C. (2014-03). Enhancement of patient and staff experience at outpatient pharmacy via optimization of drug-shelf reallocation. Operations Research for Health Care 3 (1) : 15-21. ScholarBank@NUS Repository. https://doi.org/10.1016/j.orhc.2013.11.002
Abstract: The drug-shelf allocation planning problem of an outpatient pharmacy entails assignment of drugs to shelves. It is a challenging combinatorial problem due to its underlying safety precautionary measures and operational constraints, such as that drugs of similar names should not be placed together, oral drugs should not be placed together with non-oral drugs, and mixtures must not be placed above non-mixtures. A good drug-shelf allocation plan is critical to an outpatient pharmacy due to its impact on both patients and pharmacy staff. Despite the importance of the drug-shelf allocation planning problem, it has received limited attention in the literature. This paper aims to fill this research gap by introducing a new three-stage solution framework to solve the drug-shelf allocation planning problem where the latter is decomposed into three sub-problems. Respectively, they aim to determine (1) the drug-shelf allocation plan of selected drugs which requires the minimal number of shelves, (2) the drug-shelf allocation plan of the remaining drugs which maximizes the number of prescriptions which can be filled from one shelf, and (3) the drug storage plan of each shelf which minimizes the distance travelled by its packer. In our solution framework, the first sub-problem is solved manually while the other two sub-problems are addressed by solving two integer linear programming models. To illustrate its practical relevance and effectiveness, this paper also shares the computational experience of the new solution framework on a drug-shelf allocation planning problem of a new outpatient pharmacy at a Singapore tertiary hospital. © 2013 Elsevier Ltd.
Source Title: Operations Research for Health Care
URI: http://scholarbank.nus.edu.sg/handle/10635/117006
ISSN: 22116923
DOI: 10.1016/j.orhc.2013.11.002
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