Stochastic integer programming for multi-disciplinary outpatient clinic planning.
Scheduling appointments in a multi-disciplinary clinic is complex, since coordination between disciplines is required. The design of a blueprint schedule for a multi-disciplinary clinic with open access requirements requires an integrated optimization approach, in which all appointment schedules are...
| Publicado en: | Health Care Management Science Vol. 22; no. 1; pp. 53 - 68 |
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| Autores principales: | , , |
| Formato: | equations & formulas research tables/charts Journal Article |
| Publicado: |
Springer Nature
Mar2019
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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=134562617&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 134562617 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 13869620 BSE jtl: Health Care Management Science issn: 13869620 maglogo: N pubinfo: dt: Mar2019 vid: 22 iid: 1 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 134562617 134562617 NLM29124483 134562617 10.1007/s10729-017-9422-6 NLM29124483 134562617 ppf: 53 ppct: 15 formats: tig: atl: Stochastic integer programming for multi-disciplinary outpatient clinic planning. aug: au: Leeftink, A. G. Vliegen, I. M. H. Hans, E. W. affil: Center for Healthcare Operations Improvement and Research (CHOIR), University of Twente, P.O. Box 217, 7500, Enschede, AE, the Netherlands sug: subj: Ambulatory Care Facilities Administration Algorithms Neoplasms Therapy Appointments and Schedules Models, Statistical Personnel Staffing and Scheduling Administration Statistics Netherlands Multidisciplinary Care Team Administration Funding Source ab: Scheduling appointments in a multi-disciplinary clinic is complex, since coordination between disciplines is required. The design of a blueprint schedule for a multi-disciplinary clinic with open access requirements requires an integrated optimization approach, in which all appointment schedules are jointly optimized. As this currently is an open question in the literature, our research is the first to address this problem. This research is motivated by a Dutch hospital, which uses a multi-disciplinary cancer clinic to communicate the diagnosis and to explain the treatment plan to their patients. Furthermore, also regular patients are seen by the clinicians. All involved clinicians therefore require a blueprint schedule, in which multiple patient types can be scheduled. We design these blueprint schedules by optimizing the patient waiting time, clinician idle time, and clinician overtime. As scheduling decisions at multiple time intervals are involved, and patient routing is stochastic, we model this system as a stochastic integer program. The stochastic integer program is adapted for and solved with a sample average approximation approach. Numerical experiments evaluate the performance of the sample average approximation approach. We test the suitability of the approach for the hospital's problem at hand, compare our results with the current hospital schedules, and present the associated savings. Using this approach, robust blueprint schedules can be found for a multi-disciplinary clinic of the Dutch hospital. pubtype: Academic Journal doctype: equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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