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dc.contributor.authorKargar, ZS
dc.contributor.authorKhanna, S
dc.contributor.authorSattar, A
dc.contributor.editorKhanna,S., Sattar,A., Hansen, D.
dc.date.accessioned2017-10-11T12:30:36Z
dc.date.available2017-10-11T12:30:36Z
dc.date.issued2012
dc.date.modified2013-07-12T01:29:58Z
dc.identifier.issn1613-0073
dc.identifier.refurihttp://www.aehrc.com/centre-events/icalrepeat.detail/2012/12/04/33/-/second-australian-workshop-on-artificial-intelligence-in-health-aih-2012
dc.identifier.urihttp://hdl.handle.net/10072/52402
dc.description.abstractStochastic activity durations, uncertainty in the arrival process of patients, and coordination of multiple activities are some key features of surgery planning and scheduling. In this paper we provide an overview of challenges around elective surgery scheduling and propose a predictive model for elective surgery scheduling to be evaluated in a major tertiary hospital in Queensland. The proposed model employs waiting lists, peri-operative information, workload predictions, and improved procedure time estimation models, to optimise surgery scheduling. It is expected that the resulting improvement in scheduling processes will lead to more efficient use of surgical suites, higher productivity, and lower labour costs, and ultimately improve patient outcomes.
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.format.extent597160 bytes
dc.format.mimetypeapplication/pdf
dc.languageEnglish
dc.publisherRedaktion Sun SITE, Informatik V
dc.publisher.placeGermany
dc.publisher.urihttp://ceur-ws.org/Vol-941/
dc.relation.ispartofstudentpublicationN
dc.relation.ispartofconferencenameAIH 2012
dc.relation.ispartofconferencetitleCEUR Workshop Proceedings
dc.relation.ispartofdatefrom2012-12-04
dc.relation.ispartofdateto2012-12-04
dc.relation.ispartoflocationSydney, Australia
dc.relation.ispartofpagefrom83
dc.relation.ispartofpageto87
dc.relation.ispartofvolume941
dc.rights.retentionY
dc.subject.fieldofresearchArtificial intelligence not elsewhere classified
dc.subject.fieldofresearchcode460299
dc.titleUsing Prediction to Improve Elective Surgery Scheduling
dc.typeConference output
dc.type.descriptionE1 - Conferences
dc.type.codeE - Conference Publications
gro.facultyGriffith Sciences, School of Information and Communication Technology
gro.rights.copyright© The Editors 2012. The attached file is reproduced here in accordance with the copyright policy of the publisher. For information about this conference please refer to the conference’s website or contact the authors.
gro.date.issued2012
gro.hasfulltextFull Text
gro.griffith.authorSattar, Abdul


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  • Conference outputs
    Contains papers delivered by Griffith authors at national and international conferences.

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