LEADER 02145oam 2200421zu 450 001 996202055003316 005 20210807002657.0 010 $a1-5090-8690-0 035 $a(CKB)1000000000331073 035 $a(SSID)ssj0000451855 035 $a(PQKBManifestationID)12140694 035 $a(PQKBTitleCode)TC0000451855 035 $a(PQKBWorkID)10463377 035 $a(PQKB)11718263 035 $a(NjHacI)991000000000331073 035 $a(EXLCZ)991000000000331073 100 $a20160829d2007 uy 101 0 $aeng 135 $aur||||||||||| 181 $ctxt 182 $cc 183 $acr 200 00$a20th IEEE International Symposium on Computer-Based Medical Systems (CBMS 2007): Maribor, Slovenia 20-22 June 2007 210 31$a[Place of publication not identified]$cIEEE Computer Society Press$d2007 215 $a1 online resource (750, 118 papers pages) $cillustrations 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a0-7695-2905-4 330 $aIn this paper, we present a modelling framework for patient flow in a healthcare system using semi-open queueing network models, which introduces a total bed constraint, above which new patients will be refused admission. Hence this model provides a realistic representation of a real system. This approach enables us to have access to a range of established methods that deals with queueing network models. We demonstrate the usefulness of the model in the context of a geriatric department and show that hospital managers can use this model to gain better understanding of the dynamics of patient flow and to study potential long-term impacts of policy changes. 606 $aArtificial intelligence$xMedical applications$vCongresses 606 $aMedicine$xData processing$vCongresses 615 0$aArtificial intelligence$xMedical applications 615 0$aMedicine$xData processing 676 $a610.28563 801 0$bPQKB 906 $aPROCEEDING 912 $a996202055003316 996 $a20th IEEE International Symposium on Computer-Based Medical Systems (CBMS 2007): Maribor, Slovenia 20-22 June 2007$92415643 997 $aUNISA