Stable annual scheduling of medical residents using prioritized multiple training schedules to combat operational uncertainty

  • For educational purposes, medical residents often have to pass through many departments, which place different requirements on them. They are informed about the upcoming departments by an annual training schedule which keeps the individual departments’ service level as constant as possible. Due to poor planning and uncertain events, deviations in the schedule can occur. These deviations affect the service level in the departments, as well as the training progress and satisfaction of the residents. This article analyzes the impact of priorities on residents’ annual planning based on department assignments to combat uncertainty that might result in departmental changes. We present a novel two-stage formulation that combines residents’ tactical planning with duty and daily scheduling’s operational level. We determine an analytical bound for the problem that is superior to the LP bound. Additionally, we approximate a bound based on the solution approach using the objective value of theFor educational purposes, medical residents often have to pass through many departments, which place different requirements on them. They are informed about the upcoming departments by an annual training schedule which keeps the individual departments’ service level as constant as possible. Due to poor planning and uncertain events, deviations in the schedule can occur. These deviations affect the service level in the departments, as well as the training progress and satisfaction of the residents. This article analyzes the impact of priorities on residents’ annual planning based on department assignments to combat uncertainty that might result in departmental changes. We present a novel two-stage formulation that combines residents’ tactical planning with duty and daily scheduling’s operational level. We determine an analytical bound for the problem that is superior to the LP bound. Additionally, we approximate a bound based on the solution approach using the objective value of the deterministic solution of an instance and the absences in each scenario. In a computational study, we analyze the performance of various bounds, our solution approach, and the effects of additional priorities in residents’ annual planning. We show that additional priorities can significantly reduce the number of unexpected department assignments. Finally, we derive a practical number of priorities from the results.show moreshow less

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Metadaten
Author:Sebastian Kraul, Jens O. BrunnerORCiDGND
URN:urn:nbn:de:bvb:384-opus4-1020260
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/102026
ISSN:0377-2217OPAC
Parent Title (English):European Journal of Operational Research
Publisher:Elsevier BV
Place of publication:Amsterdam
Type:Article
Language:English
Year of first Publication:2023
Publishing Institution:Universität Augsburg
Release Date:2023/02/15
Tag:Information Systems and Management; Management Science and Operations Research; Modeling and Simulation; General Computer Science; Industrial and Manufacturing Engineering
Volume:309
Issue:3
First Page:1263
Last Page:1278
DOI:https://doi.org/10.1016/j.ejor.2023.02.007
Institutes:Wirtschaftswissenschaftliche Fakultät
Wirtschaftswissenschaftliche Fakultät / Institut für Betriebswirtschaftslehre
Wirtschaftswissenschaftliche Fakultät / Institut für Betriebswirtschaftslehre / Lehrstuhl für Health Care Operations / Health Information Management
Dewey Decimal Classification:3 Sozialwissenschaften / 33 Wirtschaft / 330 Wirtschaft
Licence (German):CC-BY 4.0: Creative Commons: Namensnennung (mit Print on Demand)