pubmed-article:21324188 | rdf:type | pubmed:Citation | lld:pubmed |
pubmed-article:21324188 | lifeskim:mentions | umls-concept:C0030705 | lld:lifeskim |
pubmed-article:21324188 | lifeskim:mentions | umls-concept:C0024117 | lld:lifeskim |
pubmed-article:21324188 | lifeskim:mentions | umls-concept:C0805701 | lld:lifeskim |
pubmed-article:21324188 | lifeskim:mentions | umls-concept:C2349101 | lld:lifeskim |
pubmed-article:21324188 | lifeskim:mentions | umls-concept:C1137111 | lld:lifeskim |
pubmed-article:21324188 | lifeskim:mentions | umls-concept:C2600053 | lld:lifeskim |
pubmed-article:21324188 | pubmed:dateCreated | 2011-3-9 | lld:pubmed |
pubmed-article:21324188 | pubmed:abstractText | Administrative data is often used to identify patients with chronic obstructive pulmonary disease (COPD), yet the validity of this approach is unclear. We sought to develop a predictive model utilizing administrative data to accurately identify patients with COPD. | lld:pubmed |
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pubmed-article:21324188 | pubmed:language | eng | lld:pubmed |
pubmed-article:21324188 | pubmed:journal | http://linkedlifedata.com/r... | lld:pubmed |
pubmed-article:21324188 | pubmed:citationSubset | IM | lld:pubmed |
pubmed-article:21324188 | pubmed:status | MEDLINE | lld:pubmed |
pubmed-article:21324188 | pubmed:issn | 1472-6963 | lld:pubmed |
pubmed-article:21324188 | pubmed:author | pubmed-author:AuDavid HDH | lld:pubmed |
pubmed-article:21324188 | pubmed:author | pubmed-author:JohnsonEricE | lld:pubmed |
pubmed-article:21324188 | pubmed:author | pubmed-author:LeeTodd ATA | lld:pubmed |
pubmed-article:21324188 | pubmed:author | pubmed-author:UdrisEdmunds... | lld:pubmed |
pubmed-article:21324188 | pubmed:author | pubmed-author:AndersonSteph... | lld:pubmed |
pubmed-article:21324188 | pubmed:author | pubmed-author:CookeColin... | lld:pubmed |
pubmed-article:21324188 | pubmed:author | pubmed-author:JooMin JMJ | lld:pubmed |
pubmed-article:21324188 | pubmed:issnType | Electronic | lld:pubmed |
pubmed-article:21324188 | pubmed:volume | 11 | lld:pubmed |
pubmed-article:21324188 | pubmed:owner | NLM | lld:pubmed |
pubmed-article:21324188 | pubmed:authorsComplete | Y | lld:pubmed |
pubmed-article:21324188 | pubmed:pagination | 37 | lld:pubmed |
pubmed-article:21324188 | pubmed:dateRevised | 2011-7-26 | lld:pubmed |
pubmed-article:21324188 | pubmed:meshHeading | pubmed-meshheading:21324188... | lld:pubmed |
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pubmed-article:21324188 | pubmed:meshHeading | pubmed-meshheading:21324188... | lld:pubmed |
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pubmed-article:21324188 | pubmed:meshHeading | pubmed-meshheading:21324188... | lld:pubmed |
pubmed-article:21324188 | pubmed:year | 2011 | lld:pubmed |
pubmed-article:21324188 | pubmed:articleTitle | The validity of using ICD-9 codes and pharmacy records to identify patients with chronic obstructive pulmonary disease. | lld:pubmed |
pubmed-article:21324188 | pubmed:affiliation | Division of Pulmonary and Critical Care Medicine, University of Michigan, Ann Arbor, USA. cookecr@umich.edu | lld:pubmed |
pubmed-article:21324188 | pubmed:publicationType | Journal Article | lld:pubmed |
pubmed-article:21324188 | pubmed:publicationType | Research Support, U.S. Gov't, Non-P.H.S. | lld:pubmed |
pubmed-article:21324188 | pubmed:publicationType | Research Support, Non-U.S. Gov't | lld:pubmed |
pubmed-article:21324188 | pubmed:publicationType | Validation Studies | lld:pubmed |