Calibration of a decision-making process in a simulation model by a bicriteria optimization problem

Azcárate, Cristina; Giménez, Ferran; Barado, Julio

doi:10.1109/wsc.2012.6465078

Cited by 2 publications

(1 citation statement)

References 15 publications

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“…In order to obtain valid simulation models, it is necessary to include the process of physicians' patient-discharge decision-making [45,46]. Azcárate et al [47] perform a sensitivity analysis of the effects of such discharge decisions on ICU rejection rates and LoS of patients. Mallor et al [32] assess by simulation modeling the optimal discharge strategies obtained in [33].…”

Section: Simulation In Icumentioning

confidence: 99%

Safely learning Intensive Care Unit management by using a Management Flight Simulator

Garcia-Vicuña

Esparza²,

Giménez

2020

Operations Research for Health Care

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Section: Simulation In Icumentioning

confidence: 99%

Safely learning Intensive Care Unit management by using a Management Flight Simulator

Garcia-Vicuña

Esparza²,

Giménez

2020

Operations Research for Health Care

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Optimal control of ICU patient discharge: from theory to implementation

Giménez

Azcárate

Barado

2015

Health Care Manag Sci

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This paper deals with the management of scarce health care resources. We consider a control problem in which the objective is to minimize the rate of patient rejection due to service saturation. The scope of decisions is limited, in terms both of the amount of resources to be used, which are supposed to be fixed, and of the patient arrival pattern, which is assumed to be uncontrollable. This means that the only potential areas of control are speed or completeness of service. By means of queuing theory and optimization techniques, we provide a theoretical solution expressed in terms of service rates. In order to make this theoretical analysis useful for the effective control of the healthcare system, however, further steps in the analysis of the solution are required: physicians need flexible and medically-meaningful operative rules for shortening patient length of service to the degree needed to give the service rates dictated by the theoretical analysis. The main contribution of this paper is to discuss how the theoretical solutions can be transformed into effective management rules to guide doctors' decisions. The study examines three types of rules based on intuitive interpretations of the theoretical solution. Rules are evaluated through implementation in a simulation model. We compare the service rates provided by the different policies with those dictated by the theoretical solution. Probabilistic analysis is also included to support rule validity. An Intensive Care Unit is used to illustrate this control problem. The study focuses on the Markovian case before moving on to consider more realistic LoS distributions (Weibull, Lognormal and Phase-type distribution).

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Calibration of a decision-making process in a simulation model by a bicriteria optimization problem

Cited by 2 publications

References 15 publications

Safely learning Intensive Care Unit management by using a Management Flight Simulator

Safely learning Intensive Care Unit management by using a Management Flight Simulator

Optimal control of ICU patient discharge: from theory to implementation

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