Automated Diabetes Case Identification Using Electronic Health Record Data at a Tertiary Care Facility

Objective: To develop and validate a phenotyping algorithm for the identification of patients with type 1 and type 2 diabetes mellitus (DM) preoperatively using routinely available clinical data from electronic health records. Patients and Methods: We used first-order logic rules (if-then-else rules...

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Bibliographic Details
Main Authors:	Sudhi G. Upadhyaya, MS, Dennis H. Murphree, Jr., PhD, Che G. Ngufor, PhD, Alison M. Knight, MS, Daniel J. Cronk, MS, Robert R. Cima, MD, Timothy B. Curry, MD, PhD, Jyotishman Pathak, PhD, Rickey E. Carter, PhD, Daryl J. Kor, MD, MSc
Format:	Article
Language:	English
Published:	Elsevier 2017-07-01
Series:	Mayo Clinic Proceedings: Innovations, Quality & Outcomes
Online Access:	http://www.sciencedirect.com/science/article/pii/S2542454817300085

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http://www.sciencedirect.com/science/article/pii/S2542454817300085

Automated Diabetes Case Identification Using Electronic Health Record Data at a Tertiary Care Facility

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