Systematic review of validation studies of the use of administrative data to identify serious infections

Clicks: 197
ID: 272836
2013
Free PDF
Article Quality & Performance Metrics
Overall Quality Improving Quality
0.0 /100
Combines engagement data with AI-assessed academic quality
AI Quality Assessment
Not analyzed
Abstract
Algorithms for identifying infections using administrative data should be selected based on the purpose of the study, with careful consideration as to whether a high sensitivity or PPV is required.
Reference Key
c2013arthritissystematic Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Barber C;Lacaille D;Fortin PR;;
Journal arthritis care & research
Year 2013
DOI
DOI not found
URL
http://www.ncbi.nlm.nih.gov/pubmed/23335588
Keywords
systematic review National Center for Biotechnology Information NCBI NLM MEDLINE review humans pubmed abstract nih national institutes of health national library of medicine research support non-u.s. gov't algorithms rheumatic diseases / epidemiology* bacterial infections / epidemiology* validation studies as topic pmid:23335588 doi:10.1002/acr.21959 claire barber diane lacaille paul r fortin opportunistic infections / epidemiology

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.