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Patient mix optimisation for inpatient planning with multiple resources

Vissers, Jan; Bekkers, Jos; Jeunet, Jully; Dellaert, Nico; Adan, Ivo (2012), Patient mix optimisation for inpatient planning with multiple resources, in Elena Tànfani, Angela Testi, Advanced Decision Making Methods Applied to Health Care, Springer : Berlin Heidelberg, p. 213-236. 10.1007/978-88-470-2321-5_13

Type
Chapitre d'ouvrage
Date
2012
Book title
Advanced Decision Making Methods Applied to Health Care
Book author
Elena Tànfani, Angela Testi
Publisher
Springer
Published in
Berlin Heidelberg
ISBN
978-88-470-2320-8
Pages
213-236
Publication identifier
10.1007/978-88-470-2321-5_13
Metadata
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Author(s)
Vissers, Jan

Bekkers, Jos
Erasmus University Rotterdam
Jeunet, Jully
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Dellaert, Nico
Department of Operations Management
Adan, Ivo
Department of mathematics and computing science [Eindhoven]
Abstract (EN)
This contribution addresses the planning of admissions of surgical patients, requiring different resources such as beds and nursing capacity at wards, operating rooms and operating theatre personnel at an operating theatre, intensive care beds and intensive care nursing capacity at an intensive care ward. We developed a modelling approach for this planning problem, starting from a very simplified base model with deterministic resource requirements only for elective patients to a model with also stochastic resource requirements and finally a model extended to emergency patients. We developed the consecutive models over a period of 6 years together with a cardiothoracic surgeon who acted as problem owner and user of the model in healthcare practice. Each of the steps taken in the development of the models provided new insights and added to the knowledge of the planning problem and approach. We present the steps taken and the models developed, show the results obtained and the lessons learned.
Subjects / Keywords
admission planning; operating theatre planning; patient mix; resource allocation; integer linear programming; simulation

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