File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: A queueing model to evaluate the impact of patient "batching" on throughput and flow time in a medical teaching facility

TitleA queueing model to evaluate the impact of patient "batching" on throughput and flow time in a medical teaching facility
Authors
KeywordsBatching
Concurrent Service
Finite Buffer
Flow Time Versus Throughput
Tandem Queues
Issue Date2012
PublisherI N F O R M S. The Journal's web site is located at http://www.msom.org/
Citation
Manufacturing And Service Operations Management, 2012, v. 14 n. 4, p. 584-599 How to Cite?
AbstractWe consider the work flow in a medical teaching facility, examining the process that involves an initial patient exam by a resident physician, a subsequent conference between the resident and the attending physician, and the attending physician's visit with the patient. We create an analytical model of a tandem queue with finite buffer space to analyze the impact of different work prioritization policies on the throughput and the flow time of patients in the facility-measures that influence both the facility's finances and patients' satisfaction. We derive throughput-optimal policies and show that these policies involve dynamic batching. This finding is interesting because our model does not include any setup times, and setup times normally imply batching; rather it is the uncertain service times and the requirement for simultaneous service in the conference step that make batching optimal. The optimal dynamic batching policy is complex, so we consider a simpler static batching policy. We show that, in systems with limited buffer space, large batches can sometimes degrade efficiency by simultaneously increasing flow time and decreasing throughput. However, in general, both flow time and throughput increase with batch size. Flow time increases at a faster rate than throughput, so hospital management may want to consider what batch size is optimal given the value it places on the two measures. © 2012 INFORMS.
Persistent Identifierhttp://hdl.handle.net/10722/178088
ISSN
2015 Impact Factor: 1.966
2015 SCImago Journal Rankings: 4.609
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorDobson, Gen_US
dc.contributor.authorLee, HHen_US
dc.contributor.authorSainathan, Aen_US
dc.contributor.authorTilson, Ven_US
dc.date.accessioned2012-12-19T09:41:51Z-
dc.date.available2012-12-19T09:41:51Z-
dc.date.issued2012en_US
dc.identifier.citationManufacturing And Service Operations Management, 2012, v. 14 n. 4, p. 584-599en_US
dc.identifier.issn1523-4614en_US
dc.identifier.urihttp://hdl.handle.net/10722/178088-
dc.description.abstractWe consider the work flow in a medical teaching facility, examining the process that involves an initial patient exam by a resident physician, a subsequent conference between the resident and the attending physician, and the attending physician's visit with the patient. We create an analytical model of a tandem queue with finite buffer space to analyze the impact of different work prioritization policies on the throughput and the flow time of patients in the facility-measures that influence both the facility's finances and patients' satisfaction. We derive throughput-optimal policies and show that these policies involve dynamic batching. This finding is interesting because our model does not include any setup times, and setup times normally imply batching; rather it is the uncertain service times and the requirement for simultaneous service in the conference step that make batching optimal. The optimal dynamic batching policy is complex, so we consider a simpler static batching policy. We show that, in systems with limited buffer space, large batches can sometimes degrade efficiency by simultaneously increasing flow time and decreasing throughput. However, in general, both flow time and throughput increase with batch size. Flow time increases at a faster rate than throughput, so hospital management may want to consider what batch size is optimal given the value it places on the two measures. © 2012 INFORMS.en_US
dc.languageengen_US
dc.publisherI N F O R M S. The Journal's web site is located at http://www.msom.org/en_US
dc.relation.ispartofManufacturing and Service Operations Managementen_US
dc.subjectBatchingen_US
dc.subjectConcurrent Serviceen_US
dc.subjectFinite Bufferen_US
dc.subjectFlow Time Versus Throughputen_US
dc.subjectTandem Queuesen_US
dc.titleA queueing model to evaluate the impact of patient "batching" on throughput and flow time in a medical teaching facilityen_US
dc.typeArticleen_US
dc.identifier.emailLee, HH: hhlee@hku.hken_US
dc.identifier.authorityLee, HH=rp01556en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1287/msom.1120.0380en_US
dc.identifier.scopuseid_2-s2.0-84868243947en_US
dc.identifier.hkuros214296-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-84868243947&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume14en_US
dc.identifier.issue4en_US
dc.identifier.spage584en_US
dc.identifier.epage599en_US
dc.identifier.eissn1526-5498-
dc.identifier.isiWOS:000310102500011-
dc.publisher.placeUnited Statesen_US
dc.identifier.scopusauthoridDobson, G=7005490648en_US
dc.identifier.scopusauthoridLee, HH=35757543400en_US
dc.identifier.scopusauthoridSainathan, A=36006734000en_US
dc.identifier.scopusauthoridTilson, V=23989462200en_US

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats