TY - GEN
T1 - Strategic territorial deployment of hospital pharmacy robots using a stochastic p-robust optimization approach
AU - Franco, Carlos
AU - Augusto, Vincent
AU - Garaix, Thierry
AU - Alfonso-Lizarazo, Edgar
AU - Bourdelin, Magali
AU - Bontemps, Hervé
N1 - Funding Information:
ACKNOWLEDGMENT We thank pharmacists of Hopital Nord Ouest that gave us support in this research. Also we thank the bachelor student Aurélie Mélinand who was involved in the project. The first author would like to thank the Universidad del Rosario for their assistance in providing financial support in the research project, to the Universidad de la Sabana for providing partial financial support in his Ph.D program and also to Mines Saint-Étienne for hosting him during the research project.
Publisher Copyright:
© 2018 IEEE.
Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.
PY - 2018/12/4
Y1 - 2018/12/4
N2 - Automation in healthcare is a major challenge to improve quality of service while compressing costs. In particular, correct administration of medicines to patients is crucial to ensure quality of care during hospitalization and minimize medication errors. Mistakes are more likely to happen when medicine administration is done manually (dispensing, ordering or administrating). To reduce the risks related to medication errors, automation of the pharmacy processes appears as an appropriately tool to solve this situation. In this paper, we have proposed a new mathematical model to optimize the processes related to unit-doses management and prescriptions preparation in a network of hospitals. To model the uncertainty associated with the demand of medicines, the concept of p-robustness is included; the concept of resilience is also considered to model the risk of centralized distribution processes.
AB - Automation in healthcare is a major challenge to improve quality of service while compressing costs. In particular, correct administration of medicines to patients is crucial to ensure quality of care during hospitalization and minimize medication errors. Mistakes are more likely to happen when medicine administration is done manually (dispensing, ordering or administrating). To reduce the risks related to medication errors, automation of the pharmacy processes appears as an appropriately tool to solve this situation. In this paper, we have proposed a new mathematical model to optimize the processes related to unit-doses management and prescriptions preparation in a network of hospitals. To model the uncertainty associated with the demand of medicines, the concept of p-robustness is included; the concept of resilience is also considered to model the risk of centralized distribution processes.
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U2 - 10.1109/COASE.2018.8560374
DO - 10.1109/COASE.2018.8560374
M3 - Conference contribution
AN - SCOPUS:85059988525
T3 - IEEE International Conference on Automation Science and Engineering
SP - 390
EP - 395
BT - 2018 IEEE 14th International Conference on Automation Science and Engineering, CASE 2018
PB - IEEE Computer Society
T2 - 14th IEEE International Conference on Automation Science and Engineering, CASE 2018
Y2 - 20 August 2018 through 24 August 2018
ER -