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Automated identification of implausible values in growth data from pediatric electronic health records

OBJECTIVE: Large electronic health record (EHR) datasets are increasingly used to facilitate research on growth, but measurement and recording errors can lead to biased results. We developed and tested an automated method for identifying implausible values in pediatric EHR growth data. MATERIALS AND...

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Detalles Bibliográficos
Publicado en:J Am Med Inform Assoc
Main Authors: Daymont, Carrie, Ross, Michelle E, Russell Localio, A, Fiks, Alexander G, Wasserman, Richard C, Grundmeier, Robert W
Formato: Artigo
Idioma:Inglês
Publicado: Oxford University Press 2017
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Acceso en liña:https://ncbi.nlm.nih.gov/pmc/articles/PMC7651915/
https://ncbi.nlm.nih.gov/pubmed/28453637
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/jamia/ocx037
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