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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Bibliografiska uppgifter
I publikationen:J Am Med Inform Assoc
Huvudupphovsmän: Daymont, Carrie, Ross, Michelle E, Russell Localio, A, Fiks, Alexander G, Wasserman, Richard C, Grundmeier, Robert W
Materialtyp: Artigo
Språk:Inglês
Publicerad: Oxford University Press 2017
Ämnen:
Research and Applications
Länkar: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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