| pubmed-article:16776836 | rdf:type | pubmed:Citation | lld:pubmed |
| pubmed-article:16776836 | lifeskim:mentions | umls-concept:C1513822 | lld:lifeskim |
| pubmed-article:16776836 | lifeskim:mentions | umls-concept:C0035168 | lld:lifeskim |
| pubmed-article:16776836 | lifeskim:mentions | umls-concept:C1880171 | lld:lifeskim |
| pubmed-article:16776836 | lifeskim:mentions | umls-concept:C0684224 | lld:lifeskim |
| pubmed-article:16776836 | lifeskim:mentions | umls-concept:C1511726 | lld:lifeskim |
| pubmed-article:16776836 | lifeskim:mentions | umls-concept:C1137112 | lld:lifeskim |
| pubmed-article:16776836 | lifeskim:mentions | umls-concept:C1137110 | lld:lifeskim |
| pubmed-article:16776836 | lifeskim:mentions | umls-concept:C0549179 | lld:lifeskim |
| pubmed-article:16776836 | lifeskim:mentions | umls-concept:C1512888 | lld:lifeskim |
| pubmed-article:16776836 | pubmed:dateCreated | 2006-7-20 | lld:pubmed |
| pubmed-article:16776836 | pubmed:abstractText | Health administrative data are frequently used for health services and population health research. Comparative research using these data has been facilitated by the use of a standard system for coding diagnoses, the International Classification of Diseases (ICD). Research using the data must deal with data quality and validity limitations which arise because the data are not created for research purposes. This paper presents a list of high-priority methodological areas for researchers using health administrative data. | lld:pubmed |
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| pubmed-article:16776836 | pubmed:language | eng | lld:pubmed |
| pubmed-article:16776836 | pubmed:journal | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:16776836 | pubmed:citationSubset | IM | lld:pubmed |
| pubmed-article:16776836 | pubmed:status | MEDLINE | lld:pubmed |
| pubmed-article:16776836 | pubmed:issn | 1472-6963 | lld:pubmed |
| pubmed-article:16776836 | pubmed:author | pubmed-author:TuJack VJV | lld:pubmed |
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| pubmed-article:16776836 | pubmed:author | pubmed-author:QuanHudeH | lld:pubmed |
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| pubmed-article:16776836 | pubmed:author | pubmed-author:WUL YLY | lld:pubmed |
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| pubmed-article:16776836 | pubmed:author | pubmed-author:LixLisa MLM | lld:pubmed |
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| pubmed-article:16776836 | pubmed:author | pubmed-author:RoosLeslieL | lld:pubmed |
| pubmed-article:16776836 | pubmed:issnType | Electronic | lld:pubmed |
| pubmed-article:16776836 | pubmed:volume | 6 | lld:pubmed |
| pubmed-article:16776836 | pubmed:owner | NLM | lld:pubmed |
| pubmed-article:16776836 | pubmed:authorsComplete | Y | lld:pubmed |
| pubmed-article:16776836 | pubmed:pagination | 77 | lld:pubmed |
| pubmed-article:16776836 | pubmed:dateRevised | 2009-11-18 | lld:pubmed |
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| pubmed-article:16776836 | pubmed:year | 2006 | lld:pubmed |
| pubmed-article:16776836 | pubmed:articleTitle | Identifying priorities in methodological research using ICD-9-CM and ICD-10 administrative data: report from an international consortium. | lld:pubmed |
| pubmed-article:16776836 | pubmed:affiliation | Department of Community Health Sciences, University of Calgary, Calgary, Canada. decoster@ucalgary.ca | lld:pubmed |
| pubmed-article:16776836 | pubmed:publicationType | Journal Article | lld:pubmed |
| pubmed-article:16776836 | pubmed:publicationType | Research Support, Non-U.S. Gov't | lld:pubmed |
| pubmed-article:16776836 | pubmed:publicationType | Consensus Development Conference | lld:pubmed |
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