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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Detalhes bibliográficos
Publicado no: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 em: Oxford University Press 2017
Assuntos:
Research and Applications
Acesso em linha: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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