Decision support for the capacity management of bronchoscopy devices: Optimizing the cost-efficient mix of reusable and single-use devices through mathematical modeling

Edenharter, Günther M., Gartner, Daniel ORCID: https://orcid.org/0000-0003-4361-8559 and Pförringer, Dominik 2017. Decision support for the capacity management of bronchoscopy devices: Optimizing the cost-efficient mix of reusable and single-use devices through mathematical modeling. Anesthesia & Analgesia 124 (6) , pp. 1963-1967. 10.1213/ANE.0000000000001729

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Abstract

BACKGROUND: Increasing costs of material resources challenge hospitals to stay profitable. Particularly in anesthesia departments and intensive care units, bronchoscopes are used for various indications. Inefficient management of single- and multiple-use systems can influence the hospitals’ material costs substantially. Using mathematical modeling, we developed a strategic decision support tool to determine the optimum mix of disposable and reusable bronchoscopy devices in the setting of an intensive care unit. METHODS: A mathematical model with the objective to minimize costs in relation to demand constraints for bronchoscopy devices was formulated. The stochastic model decides whether single-use, multi-use, or a strategically chosen mix of both device types should be used. A decision support tool was developed in which parameters for uncertain demand such as mean, standard deviation, and a reliability parameter can be inserted. Furthermore, reprocessing costs per procedure, procurement, and maintenance costs for devices can be parameterized. RESULTS: Our experiments show for which demand pattern and reliability measure, it is efficient to only use reusable or disposable devices and under which circumstances the combination of both device types is beneficial. CONCLUSIONS: To determine the optimum mix of single-use and reusable bronchoscopy devices effectively and efficiently, managers can enter their hospital-specific parameters such as demand and prices into the decision support tool.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Mathematics
Subjects:	Q Science > QA Mathematics
Publisher:	Lippincott, Williams & Wilkins
ISSN:	0003-2999
Date of First Compliant Deposit:	20 October 2017
Date of Acceptance:	4 October 2016
Last Modified:	22 Nov 2024 15:00
URI:	https://orca.cardiff.ac.uk/id/eprint/101234

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