Linked Life Data

12648112

Source:http://linkedlifedata.com/resource/pubmed/id/12648112

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
2003-3-21
pubmed:abstractText
Using average number of patients expected in a year, average length of stay and a target occupancy level to calculate the number of critical care beds needed is mathematically incorrect because of nonlinearity and variability in the factors that control length of stay. For a target occupancy in excess of 80%, this simple calculation will typically underestimate the number of beds required. More seriously, it provides no quantitative guidance information about other aspects of critical care demand such as the numbers of emergency patients transferred, deferral rates for elective patients and overall utilisation. The combination of appropriately analysing raw data and detailed mathematical modelling provides a much better method for estimating numbers of beds required. We describe this modelling approach together with evidence of its performance.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
AIM
pubmed:status
MEDLINE
pubmed:month
Apr
pubmed:issn
0003-2409
pubmed:author
pubmed:issnType
Print
pubmed:volume
58
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
320-7
pubmed:dateRevised
2004-11-17
pubmed:meshHeading
pubmed:year
2003
pubmed:articleTitle
Mathematical modelling and simulation for planning critical care capacity.
pubmed:affiliation
Faculty of Mathematical Studies, University of Southampton, Southampton SO17 1BJ, UK.
pubmed:publicationType
Journal Article, Validation Studies