Predictive / Reactive Planning and Scheduling of a Surgical Suite with Emergency Patient Arrival.
This paper surveys the problem of predictive / reactive scheduling of an integrated operating theatre with two types of demand for surgery: 1) elective or known demand; 2) emergency or uncertain demand. The stochastic arrival of emergency patients with uncertain surgery time enforces the scheduler t...
| Publicado en: | Journal of Medical Systems Vol. 40; no. 1; pp. 1 - 10 |
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| Autores principales: | , |
| Formato: | equations & formulas research tables/charts Journal Article |
| Publicado: |
Springer Nature
Jan2016
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=115925243&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 115925243 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01485598 4N0 jtl: Journal of Medical Systems issn: 01485598 maglogo: N pubinfo: dt: Jan2016 vid: 40 iid: 1 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 115925243 115925243 115925243 10.1007/s10916-015-0385-1 115925243 ppf: 1 ppct: 9 formats: fmt: @attributes: type: P tig: atl: Predictive / Reactive Planning and Scheduling of a Surgical Suite with Emergency Patient Arrival. aug: au: Heydari, Mehdi Soudi, Asie affil: Iran University of Science and Technology, Tehran Iran sug: subj: Emergency Service Surgery, Operative Planning Techniques Appointments and Schedules Operating Rooms Decision Making, Clinical Workflow Organizations, Nonprofit Hospitals Postoperative Care Mathematics Descriptive Statistics Comparative Studies Wilcoxon Signed Rank Test P-Value Uncertainty Time Factors Simulations Models, Statistical ab: This paper surveys the problem of predictive / reactive scheduling of an integrated operating theatre with two types of demand for surgery: 1) elective or known demand; 2) emergency or uncertain demand. The stochastic arrival of emergency patients with uncertain surgery time enforces the scheduler to react to disruption and modify scheduling plan of elective patients. We focus on this predictive / reactive scheduling problem which has not been investigated in such way before. As in hospitals, at the time of occurrence a disruption in a surgical suite, the scheduler has not enough time to make the best decision; we propose a new approach based on two-stage stochastic programming model with recourse which determines the best recourse strategy in advance of any disruption occurrence. Using the proposed approach, the primary schedule is generated in such a way that it can absorb disruption with minimum effect on planned elective surgeries. For the first time in operating theatre planning, two new significant sets of performance measures comprising 'robustness' and 'stability' measures are considered in generation of primary schedule which will be shown to be of great importance in efficiency of surgical suite planning. Computational experiments performed on sets of generated problem based on the data obtained from a non-profit hospital. In order to demonstrate efficiency of the proposed method, computational results of the proposed approach are compared with classic approach. pubtype: Academic Journal doctype: equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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