Outpatient scheduling with unpunctual patients and no-shows

DOI10.1016/j.ejor.2017.07.006zbMath1374.90188OpenAlexW2726086762MaRDI QIDQ1681337

Matthias Deceuninck, Stijn De Vuyst, Dieter Fiems

Publication date: 23 November 2017

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ejor.2017.07.006

zbMATH Keywords

stochastic programmingOR in health servicesappointment schedulingunpunctuality

Mathematics Subject Classification ID

Stochastic programming (90C15) Stochastic scheduling theory in operations research (90B36) Case-oriented studies in operations research (90B90)

Related Items (10)

Appointment-driven queueing systems with non-punctual customers ⋮ Managing interruptions in appointment schedules via patient notification ⋮ Using stochastic programming to solve an outpatient appointment scheduling problem with random service and arrival times ⋮ Adaptive scheduling in service systems: a dynamic programming approach ⋮ Generating outpatient chemotherapy appointment templates with balanced flowtime and makespan ⋮ Online appointment scheduling for a nuclear medicine department in a Chinese hospital ⋮ Appointment scheduling and real-time sequencing strategies for patient unpunctuality ⋮ A distributionally robust optimization approach for outpatient colonoscopy scheduling ⋮ Analysis of models for the stochastic outpatient procedure scheduling problem ⋮ Appointment scheduling for medical diagnostic centers considering time-sensitive pharmaceuticals: a dynamic robust optimization approach

Cites Work

• Computationally efficient evaluation of appointment schedules in health care
• An extension of Osuna's model to observable queues
• The psychological cost of waiting
• Outpatient appointment systems in healthcare: a review of optimization studies
• The optimal allocation of server time slots over different classes of patients
• A computational approach to optimized appointment scheduling
• Outpatient appointment scheduling given individual day-dependent no-show predictions

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