pubmed-article:18625922 | rdf:type | pubmed:Citation | lld:pubmed |
pubmed-article:18625922 | lifeskim:mentions | umls-concept:C0969726 | lld:lifeskim |
pubmed-article:18625922 | lifeskim:mentions | umls-concept:C0026336 | lld:lifeskim |
pubmed-article:18625922 | lifeskim:mentions | umls-concept:C1527148 | lld:lifeskim |
pubmed-article:18625922 | lifeskim:mentions | umls-concept:C0175673 | lld:lifeskim |
pubmed-article:18625922 | lifeskim:mentions | umls-concept:C1519941 | lld:lifeskim |
pubmed-article:18625922 | lifeskim:mentions | umls-concept:C0009248 | lld:lifeskim |
pubmed-article:18625922 | lifeskim:mentions | umls-concept:C0439234 | lld:lifeskim |
pubmed-article:18625922 | lifeskim:mentions | umls-concept:C0809949 | lld:lifeskim |
pubmed-article:18625922 | pubmed:issue | 13 | lld:pubmed |
pubmed-article:18625922 | pubmed:dateCreated | 2008-7-15 | lld:pubmed |
pubmed-article:18625922 | pubmed:abstractText | Current international health policy has emphasized the importance of managing long-term conditions in the community with the aim of preventing emergency hospitalizations. Previous algorithms and rules have been developed but are limited to those older than 65 years and generally only for readmission. Our aim was to develop an algorithm to predict emergency hospital admissions in the whole population of those 40 years or older. | lld:pubmed |
pubmed-article:18625922 | pubmed:language | eng | lld:pubmed |
pubmed-article:18625922 | pubmed:journal | http://linkedlifedata.com/r... | lld:pubmed |
pubmed-article:18625922 | pubmed:citationSubset | AIM | lld:pubmed |
pubmed-article:18625922 | pubmed:status | MEDLINE | lld:pubmed |
pubmed-article:18625922 | pubmed:month | Jul | lld:pubmed |
pubmed-article:18625922 | pubmed:issn | 1538-3679 | lld:pubmed |
pubmed-article:18625922 | pubmed:author | pubmed-author:MorrisAndrew... | lld:pubmed |
pubmed-article:18625922 | pubmed:author | pubmed-author:DonnanPeter... | lld:pubmed |
pubmed-article:18625922 | pubmed:author | pubmed-author:DorwardDavid... | lld:pubmed |
pubmed-article:18625922 | pubmed:author | pubmed-author:MutchBillB | lld:pubmed |
pubmed-article:18625922 | pubmed:issnType | Electronic | lld:pubmed |
pubmed-article:18625922 | pubmed:day | 14 | lld:pubmed |
pubmed-article:18625922 | pubmed:volume | 168 | lld:pubmed |
pubmed-article:18625922 | pubmed:owner | NLM | lld:pubmed |
pubmed-article:18625922 | pubmed:authorsComplete | Y | lld:pubmed |
pubmed-article:18625922 | pubmed:pagination | 1416-22 | lld:pubmed |
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pubmed-article:18625922 | pubmed:year | 2008 | lld:pubmed |
pubmed-article:18625922 | pubmed:articleTitle | Development and validation of a model for predicting emergency admissions over the next year (PEONY): a UK historical cohort study. | lld:pubmed |
pubmed-article:18625922 | pubmed:affiliation | Epidemiology and Biostatistics, Tayside Centre for General Practice, Community Health Sciences, University of Dundee, Dundee, Scotland. p.t.donnan@chs.dundee.ac.uk | lld:pubmed |
pubmed-article:18625922 | pubmed:publicationType | Journal Article | lld:pubmed |
pubmed-article:18625922 | pubmed:publicationType | Research Support, Non-U.S. Gov't | lld:pubmed |
pubmed-article:18625922 | pubmed:publicationType | Validation Studies | lld:pubmed |
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