Shelf-space optimization models in decentralized automated dispensing cabinets

Nazanin Esmaili, Bryan A. Norman, Jayant Rajgopal

Research output: Contribution to journalArticle

3 Scopus citations

Abstract

We propose a mixed integer programming (MIP) model to help clinicians store medications and medical supplies optimally in space-constrained, decentralized Automated Dispensing Cabinets (ADCs) located on hospital patient floors. We also propose a second MIP model that addresses human errors associated with the selection of pharmaceuticals from floor storage, and not only selects the best set of medications for storage but also determines their optimal layout within the cabinet. To improve the computational performance of these MIP models, we investigate several valid inequalities and relaxations that allow us to solve large, real-world instances in reasonable times. These models are applicable to very general ADCs and are illustrated using real-world data from ADCs at hospitals. Our results indicate that using these models can significantly reduce the time spent by clinical staff on routine logistical functions, while making efficient use of limited space and decreasing risks associated with errors in the selection of medication.

Original languageEnglish
Pages (from-to)92-106
Number of pages15
JournalOperations Research for Health Care
Volume19
DOIs
StatePublished - Dec 2018

Keywords

  • ADCs
  • MIP models
  • Patient safety
  • Point of use inventory management
  • Shelf space optimization

Fingerprint Dive into the research topics of 'Shelf-space optimization models in decentralized automated dispensing cabinets'. Together they form a unique fingerprint.

  • Cite this