rdf:type |
|
lifeskim:mentions |
|
pubmed:issue |
8 Pt 1
|
pubmed:dateCreated |
1995-8-30
|
pubmed:abstractText |
Aggregate databases are increasingly being used to evaluate appropriateness of care, and, for cesarean sections, Anderson and Lomas' International Classification of Diseases, 9th Revision (ICD-9), coding hierarchy is a widely used tool. The aim of this study was to assess the validity of the hierarchy and expand its applicability to repeat cesareans. Hospital records of 1885 singleton cesareans were reviewed. Clinical indications and ICD-9 hierarchical codes were concordant for 83% of primary and 86% of repeat cesareans; modification allowed elective repeat cesareans to be distinguished from indicated procedures. The Anderson and Lomas ICD-9 hierarchy is a valid tool for assessing indications for cesarean. The current modification improves its clinical utility and expands its application to repeat procedures.
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pubmed:commentsCorrections |
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pubmed:language |
eng
|
pubmed:journal |
|
pubmed:citationSubset |
AIM
|
pubmed:status |
MEDLINE
|
pubmed:month |
Aug
|
pubmed:issn |
0090-0036
|
pubmed:author |
|
pubmed:issnType |
Print
|
pubmed:volume |
85
|
pubmed:owner |
NLM
|
pubmed:authorsComplete |
Y
|
pubmed:pagination |
1143-6
|
pubmed:dateRevised |
2009-11-18
|
pubmed:meshHeading |
pubmed-meshheading:7625515-Breech Presentation,
pubmed-meshheading:7625515-Cesarean Section,
pubmed-meshheading:7625515-Cesarean Section, Repeat,
pubmed-meshheading:7625515-Female,
pubmed-meshheading:7625515-Hospitals, Teaching,
pubmed-meshheading:7625515-Humans,
pubmed-meshheading:7625515-Los Angeles,
pubmed-meshheading:7625515-Obstetric Labor Complications,
pubmed-meshheading:7625515-Pregnancy,
pubmed-meshheading:7625515-Risk Assessment,
pubmed-meshheading:7625515-Surgical Procedures, Elective,
pubmed-meshheading:7625515-Trial of Labor
|
pubmed:year |
1995
|
pubmed:articleTitle |
Using ICD-9 codes to identify indications for primary and repeat cesarean sections: agreement with clinical records.
|
pubmed:affiliation |
Cedars Sinai Research Institute, University of California, Los Angeles, School of Medicine, USA.
|
pubmed:publicationType |
Journal Article,
Research Support, Non-U.S. Gov't
|