1294-P: A Novel Electronic Medical Record (EMR) Search Method to Identify Atypical Diabetes Patients

Introduction & Objectives: Efficient automated EMR review methods to identify people with atypical diabetes (DM) for research are lacking. We aimed to develop a novel Python-based Expeditious Program for EMR Review (PEPPER) and assess its efficiency. Methods: We extracted the list of 1660 youth...

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Veröffentlicht in:	Diabetes (New York, N.Y.) N.Y.), 2024-06, Vol.73 (Supplement_1), p.1
Hauptverfasser:	AHMED, MAAZ, KUBOTA-MISHRA, ELIZABETH A., SILLER, ALEJANDRO F., DAVIS, ANSLEY E., MIGACZ, ILIANA, SISLEY, STEPHANIE, FARUQI, JORDANA, SAEED, ZEB I., AHMED, SARAH, PHILIPSON, LOUIS H., REDONDO, MARIA J., BALASUBRAMANYAM, ASHOK, TOSUR, MUSTAFA, STUDY GROUP, RADIANT
Format:	Artikel
Sprache:	eng
Schlagworte:	Autoantibodies Beta cells Diabetes Diabetes mellitus Diagnosis Electronic medical records Ketoacidosis
Online-Zugang:	Volltext
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Beschreibung
Zusammenfassung:	Introduction & Objectives: Efficient automated EMR review methods to identify people with atypical diabetes (DM) for research are lacking. We aimed to develop a novel Python-based Expeditious Program for EMR Review (PEPPER) and assess its efficiency. Methods: We extracted the list of 1660 youth (
ISSN:	0012-1797 1939-327X
DOI:	10.2337/db24-1294-P