Please use this identifier to cite or link to this item: http://ir.mu.ac.ke:8080/jspui/handle/123456789/5790
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dc.contributor.authorChemweno, Peter-
dc.contributor.authorThijs, Vincent-
dc.contributor.authorPintelon, Liliane-
dc.contributor.authorVan Horenbeek, Adriaan-
dc.date.accessioned2022-01-25T08:30:10Z-
dc.date.available2022-01-25T08:30:10Z-
dc.date.issued2014-
dc.identifier.urihttps://doi.org/10.1016/j.simpat.2014.07.006-
dc.identifier.urihttp://ir.mu.ac.ke:8080/jspui/handle/123456789/5790-
dc.description.abstractHospitals aim at delivering efficient and effective healthcare. This requires high quality medical care, provided by highly trained and motivated professionals. Also the way operations are organized can contribute to a smoother healthcare delivery. An important point here is patient flow and waiting times during the patient trajectory diagnosis-therapy-care. Due to the large variability that exist between patients care needs, even for patients with a similar pathology, predicting the waiting times is very challenging. Traditional analytical optimization models like queuing theory cannot cope with the complexity of the pathways followed by patients and the interrelationships between the resources they need. Discrete event simulation can help to provide insight into the impact of operational changes, e.g. concerning available scanner capacity, on the timing of the patient’s trajectory in a hospital unit. This paper focuses on the diagnostic part of the stay of stroke patients in a stroke unit of a university hospital. With the help of discrete event simulation this patient flow is analyzed and the impact of potential changes in the capacity profile of test resources is investigated. The paper describes the steps taken in the study and the challenges met. The structure of the simulation program is explained and the results of the scenario analysis are discussed. The paper starts with a brief exploration of the use of discrete event simulation in healthcare and ends with general observations on the subject.en_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.subjectStroke patienten_US
dc.subjectPatient trajectoryen_US
dc.subjectTest resourcesen_US
dc.subjectDiscrete event simulationen_US
dc.titleDiscrete event simulation case study: Diagnostic path for stroke patients in a stroke uniten_US
dc.typeArticleen_US
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