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Authors: Norman Spangenberg 1 ; Moritz Wilke 1 ; Christoph Augenstein 1 and Bogdan Franczyk 2

Affiliations: 1 Leipzig University, Germany ; 2 Leipzig University and Wrocław University of Economics, Germany

ISBN: 978-989-758-298-1

Keyword(s): Online Surgery Scheduling, Decision Support System, Operating Room Management, Real-time Architecture.

Abstract: The operating room area is still one of the most expensive sections in the hospital due to its high and cost-intensive resource requirements. Further, several uncertainties like complications, cancellations and emergencies as well as the need to monitor and control the interventions during execution distinguish the operational planning tasks of surgery scheduling from more tactical and strategical planning activities. However there are few solutions that support monitoring and decision-making in operating room management at this level since they focus on creation of initial schedules or the efficient resource allocation. In this paper we describe a solution approach for supporting online surgery scheduling by a real-time decision support system. It allows the rescheduling based on intra-surgical information about the current surgical phases and predictions about remaining intervention times and further allows replanning due to emergent or canceled patients.

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Paper citation in several formats:
Spangenberg, N.; Wilke, M.; Augenstein, C. and Franczyk, B. (2018). Online Surgery Rescheduling - A Data-driven Approach for Real-time Decision Support.In Proceedings of the 20th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-298-1, pages 336-343. DOI: 10.5220/0006805103360343

@conference{iceis18,
author={Norman Spangenberg. and Moritz Wilke. and Christoph Augenstein. and Bogdan Franczyk.},
title={Online Surgery Rescheduling - A Data-driven Approach for Real-time Decision Support},
booktitle={Proceedings of the 20th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2018},
pages={336-343},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006805103360343},
isbn={978-989-758-298-1},
}

TY - CONF

JO - Proceedings of the 20th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Online Surgery Rescheduling - A Data-driven Approach for Real-time Decision Support
SN - 978-989-758-298-1
AU - Spangenberg, N.
AU - Wilke, M.
AU - Augenstein, C.
AU - Franczyk, B.
PY - 2018
SP - 336
EP - 343
DO - 10.5220/0006805103360343

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