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200 10$aOperations Research for Health Care in Red Zone$b[electronic resource] $eORAHS 2022, Bergamo, Italy, July 17?22 /$fedited by Roberto Aringhieri, Francesca Maggioni, Ettore Lanzarone, Melanie Reuter-Oppermann, Giovanni Righini, Maria Teresa Vespucci
205   $a1st ed. 2023.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2023.
215   $a1 online resource (87 pages)
225 1 $aAIRO Springer Series,$x2523-7055 ;$v10
311 08$aPrint version: Aringhieri, Roberto Operations Research for Health Care in Red Zone Cham : Springer International Publishing AG,c2023 9783031385360 
320   $aIncludes bibliographical references.
327   $aA comparison of fairness metrics for health care problems  -- An overview of benefits and limitations of the process model notation applied for modeling patient healthcare trajectory -- Machine Learning based Classication Models for COVID-19 Patients -- Integrating decision support tools in the COD-19 platform -- A semi-online ambulance routing and scheduling problem with complex patient-vehicle relations -- Towards a unified framework for routing and scheduling planning in an Integrated Continuous Care Unit.
330   $aThe book contains selected contributions from the 48th Annual Meeting of the EURO Working Group on Operational Research Applied to Health Services (ORAHS 2022) held in Bergamo, Italy, July 2022. ORAHS 2022 provided a network for researchers involved in the application of systematic and quantitative analyses to support planning and management in the health services sector, with the ultimate goal of pursuing good health and well-being. It was the ORAHS in the red zone, focused on the organization and reaction of health systems in the face of emergency situations such as the COVID pandemic. The questions addressed were, for example, how can hospitals and public authorities react to extreme scenarios by reorganizing their resources? How and to what extent do local health systems integrate hospitals to deal with a pandemic? How can Decision Support Systems for diagnosis and treatment help when battling a new virus for the first time? Contributions included a variety of methodological viewpoints (optimization, simulation, data analysis, predictive models, decision science, mathematical programming, machine learning, ...) and health services applications (hospital management, therapy calibration, analysis of statistical and epidemiological data, minimization of logistics costs, ...). This work strongly contributes to the Sustainable Development Goals (SDG) Programme.
410  0$aAIRO Springer Series,$x2523-7055 ;$v10
606   $aOperations research
606   $aHealth services administration
606   $aMedical economics
606   $aManagement science
606   $aMathematical optimization
606   $aMedical informatics
606   $aOperations Research and Decision Theory
606   $aHealth Care Management
606   $aHealth Economics
606   $aOperations Research, Management Science 
606   $aOptimization
606   $aHealth Informatics
615  0$aOperations research.
615  0$aHealth services administration.
615  0$aMedical economics.
615  0$aManagement science.
615  0$aMathematical optimization.
615  0$aMedical informatics.
615 14$aOperations Research and Decision Theory.
615 24$aHealth Care Management.
615 24$aHealth Economics.
615 24$aOperations Research, Management Science .
615 24$aOptimization.
615 24$aHealth Informatics.
676   $a362.18
702   $aAringhieri$b Roberto
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910743683303321
996   $aOperations Research for Health Care in Red Zone$93565804
997   $aUNINA