Using Electronic Health Record Data to Rapidly Identify Children with Glomerular Disease for Clinical Research.

Michelle R DenburgHanieh RazzaghiL Charles BaileyDanielle E SorannoAri H PollackVikas R DharnidharkaMark M MitsnefesWilliam E SmoyerMichael J G SomersJoshua J ZaritskyJoseph T FlynnDonna J ClaesBradley P DixonMaryjane BentonLaura H MarianiChristopher B ForrestSusan L Furth

Published in: Journal of the American Society of Nephrology : JASN (2019)

The authors developed an EHR-based algorithm and demonstrated that it had excellent classification accuracy across PEDSnet. This tool may enable faster identification of cohorts of pediatric patients with glomerular disease for observational or prospective studies.

Keyphrases

electronic health record
clinical decision support
machine learning
deep learning
adverse drug
diabetic nephropathy
young adults
high glucose
cross sectional
data analysis