Clustering surgical procedures for master surgical scheduling

Kressner, Alexander; Schimmelpfeng, Katja

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Kressner, Alexander ; Schimmelpfeng, Katja

Clustering surgical procedures for master surgical scheduling

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URN: urn:nbn:de:bsz:100-opus-14123
URL: http://opus.uni-hohenheim.de/volltexte/2017/1412/

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SWD-Schlagwörter:

Krankenhaus , Operation , Ablaufplanung

Freie Schlagwörter (Englisch):

master surgery scheduling (MSS) , stochastic surgery duration , surgery types , clustering

Institut:

Institut für Interorganisational Management & Performance

DDC-Sachgruppe:

Sozialwissenschaften, Soziologie, Anthropologie

Dokumentart:

ResearchPaper

Schriftenreihe:

Hohenheim discussion papers in business, economics and social sciences

Bandnummer:

2017,28

Sprache:

Englisch

Erstellungsjahr:

2017

Publikationsdatum:

28.09.2017

Lizenz:

Veröffentlichungsvertrag mit der Universitätsbibliothek Hohenheim

Kurzfassung auf Englisch:

The sound management of operating rooms is a very important task in each hospital. To use this crucial resource efficiently, cyclic master surgery schedules are often developed. To derive sensible schedules, high-quality input data are necessary. In this paper, we focus on the (elective) surgical procedures’ stochastic durations to determine reasonable, cyclically scheduled surgical clusters. Therefore, we adapt the approach of van Oostrum et al (2008), which was specifically designed for clustering surgical procedures for master surgical scheduling, and present a two-stage solution approach that consists of a new construction heuristic and an improvement heuristic. We conducted a numerical study based on real-world data from a German hospital. The results reveal clusters with considerably reduced variability compared to those of van Oostrum et al(2008).