Linked Life Data

2105904

Source:http://linkedlifedata.com/resource/pubmed/id/2105904

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
1990-3-19
pubmed:abstractText
Medicare's use of diagnosis-related groups and the frequent acceptance of length of stay as an indicator of resource utilization has caused a surge of interest in the predictability of length of hospital stay for psychiatric inpatients. By constructing a weighted least squares regression model using data from the 1980 Hospital Discharge Survey, the authors were able to account for an increased amount of variance in length of stay for the major diagnostic categories of mental disorder and substance abuse for Medicare and Blue Cross/Blue Shield patients. The enhanced ability to predict length of stay is attributed to a carefully constructed data base and an increased number of predictor variables, particularly comorbidity. Knowledge of the presence or absence of a chemical dependency unit in the hospitals from which patients were discharged substantially increased the proportion of variance accounted for in the analysis.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Feb
pubmed:issn
0022-1597
pubmed:author
pubmed:issnType
Print
pubmed:volume
41
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
149-54
pubmed:dateRevised
2009-11-11
pubmed:meshHeading
pubmed:year
1990
pubmed:articleTitle
Predicting length of hospital stay for psychiatric inpatients.
pubmed:affiliation
Vanderbilt University, Nashville, TN 37240.
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S.