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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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Bibliografische gegevens
Gepubliceerd in:J Am Med Inform Assoc
Hoofdauteurs: Daymont, Carrie, Ross, Michelle E, Russell Localio, A, Fiks, Alexander G, Wasserman, Richard C, Grundmeier, Robert W
Formaat: Artigo
Taal:Inglês
Gepubliceerd in: Oxford University Press 2017
Onderwerpen:
Online toegang: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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