Linked Life Data

9783623

Source:http://linkedlifedata.com/resource/pubmed/id/9783623

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
1998-10-30
pubmed:abstractText
This project is designed to develop and validate a predictive model that is a useful benchmarking and quality of care assessment tool based on International Classification of Diseases, Ninth Revision (ICD-9), diagnoses and procedures. This model, the ICD-9-Based Illness Severity Score (ICISS), was developed from the Agency for Health Care Policy Research's Health Care Utilization Project database and is used to predict hospital survival, hospital length of stay, and hospital charges of injured patients admitted to University of North Carolina Hospitals. The study also compared the outcome predictions of ICISS with those of the long-established diagnosis-related groups (DRG) and the 3M product APR-DRG systems.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
AIM
pubmed:status
MEDLINE
pubmed:month
Oct
pubmed:issn
0022-5282
pubmed:author
pubmed:issnType
Print
pubmed:volume
45
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
791-9
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
1998
pubmed:articleTitle
The ICD-9-based illness severity score: a new model that outperforms both DRG and APR-DRG as predictors of survival and resource utilization.
pubmed:affiliation
Department of Surgery, University of North Carolina at Chapel Hill 27599-7210, USA. rrutledg@med.unc.edu
pubmed:publicationType
Journal Article, Comparative Study