89784 20210902121659.0 doi 10.3390/app10061937 sideral 117895 ART-2020-117895 eng (orcid)0000-0001-8545-6688 Clavel, D. A decision support system for elective surgery scheduling under uncertain durations 2020 Access copy available to the general public Unrestricted The operation room (OR) is one of the most expensive material resources in hospitals. Additionally, the demand for surgical service is increasing due to the aging population, while the number of surgical interventions performed is stagnated because of budget reasons. In this context, the importance of improving the efficiency of the surgical service is accentuated. The main objective of this work is to propose and to evaluate a Decision Support System (DSS) for helping medical staff in the automatic scheduling of elective patients, improving the efficiency of medical teams'' work. First, the scheduling criteria are fixed and then the scheduling problem of elective patients is approached by a mathematical programming model. A heuristic algorithm is proposed and included in the DSS. Moreover, other different features are implemented in a software tool with a friendly user interface, called CIPLAN. Considering realistic data, a simulation comparison of the scheduling obtained using the approach presented in this paper and other similar approaches in the bibliography is shown and analyzed. On the other hand, a case study considering real data provided by the Orthopedic Surgical Department (OSD) of the "Lozano Blesa" hospital in Zaragoza (HCU) is proposed. The simulation results show that the approach presented here obtains similar occupation rates and similar confidence levels of not exceeding the available time than approaches in the bibliography. However, from the point of view of respecting the order of the patients in the waiting list, the approach in this paper obtains scheduling much more ordered. In the case of the Orthopedic Surgical Department of the "Lozano Blesa" hospital in Zaragoza, the occupation rate may be increased by 2.83%, which represents a saving of 110, 000 euros per year. Moreover, medical doctors (who use this tool) consider CIPLAN as an intuitive, rapid and efficient software solution that can make easier the corresponding task. info:eu-repo/grantAgreement/ES/CICYT-FEDER/DPI2014-57252-R info:eu-repo/semantics/openAccess by http://creativecommons.org/licenses/by/3.0/es/ 2.679 2020 PHYSICS, APPLIED 73 / 160 = 0.456 2020 Q2 T2 ENGINEERING, MULTIDISCIPLINARY 38 / 91 = 0.418 2020 Q2 T2 CHEMISTRY, MULTIDISCIPLINARY 101 / 178 = 0.567 2020 Q3 T2 MATERIALS SCIENCE, MULTIDISCIPLINARY 201 / 333 = 0.604 2020 Q3 T2 0.435 2020 Computer Science Applications 2020 Q2 Engineering (miscellaneous) 2020 Q2 Process Chemistry and Technology 2020 Q2 Instrumentation 2020 Q2 Materials Science (miscellaneous) 2020 Q2 Fluid Flow and Transfer Processes 2020 Q2 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion (orcid)0000-0003-0056-2225 Mahulea, C. Universidad de Zaragoza (orcid)0000-0003-4489-3130 Albareda, J. Universidad de Zaragoza (orcid)0000-0001-8631-8770 Silva, M. Universidad de Zaragoza 5007 520 Universidad de Zaragoza Dpto. Informát.Ingenie.Sistms. Área Ingen.Sistemas y Automát. 1013 830 Universidad de Zaragoza Dpto. Cirugía Área Traumatología y Ortopedia 10, 6 (2020), 1937 [21 pp] Appl. sci. APPLIED SCIENCES-BASEL 2076-3417 699650 http://zaguan.unizar.es/record/89784/files/texto_completo.pdf Versión publicada 494487 http://zaguan.unizar.es/record/89784/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:89784 articulos driver 2021-09-02-09:13:16 ARTICLE