Linked Life Data

10895421

Source:http://linkedlifedata.com/resource/pubmed/id/10895421

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2000-11-3
pubmed:abstractText
A nonpreemptive queuing system based upon operations management theory is used to evaluate expected steady state wait periods for traditional and distributed CT scheduling models. Both models are constructed using two classes of patient service--emergent and nonemergent. The former model uses only one point of service per scanner while the latter employs multiple points of service in order to accomplish all of the functions necessary to complete a CT scan. Sample data are drawn from a tertiary care hospital-based system using a traditional service model. Comparison of a traditional and distributed service system, each with emergent and nonemergent service classes, shows that breaking as many activities as possible out of the scanner should provide substantial improvements in cost efficiency and service for patients having CT scans. Nonemergent patients may experience as much as an 89% reduction in steady-state wait times while emergent patients may experience as much as a 59% reduction in wait times. The cost efficiencies recognized either through increased scanner utilization or reduced scanner needs, even with only modest improvements, should more than offset any additional personnel needed to implement a distributed model. Proper implementation of a distributed scheduling model for CT scanning can provide substantial cost efficiencies and improvements in service for both nonemergent and emergent CT scans.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Apr
pubmed:issn
0148-5598
pubmed:author
pubmed:issnType
Print
pubmed:volume
24
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
61-76
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
2000
pubmed:articleTitle
A proposed scheduling model to improve use of computed tomography facilities.
pubmed:affiliation
Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri 63110, USA. reinus@mir.wustl.edu
pubmed:publicationType
Journal Article, Comparative Study, Validation Studies