American Diabetes Association
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Detection of Diabetes Status and Type in Youth using Electronic Health Records: The SEARCH for Diabetes in Youth Study

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Version 2 2020-09-21, 20:37
Version 1 2020-07-31, 18:02
posted on 2020-09-21, 20:37 authored by Brian J. Wells, Kristin M. Lenoir, Lynne E. Wagenknecht, Elizabeth J. Mayer-Davis, Jean M. Lawrence, Dana Dabelea, Catherine Pihoker, Sharon Saydah, Ramon Casanova, Christine Turley, Angela D. Liese, Debra Standiford, Michael G. Kahn, Richard Hamman, Jasmin Divers
Objective: Diabetes surveillance often requires manual medical chart reviews to confirm status and type. This project aimed to create an electronic health record (EHR)-based procedure for improving surveillance efficiency through automation of case identification.

Research Design and Methods: Youth (< 20 years) with potential evidence of diabetes (N=8,682) were identified from EHRs at three children’s hospitals participating in the SEARCH for Diabetes in Youth Study. True diabetes status/type was determined by manual chart reviews. Multinomial regression was compared with an ICD-10 rule-based algorithm in the ability to correctly identify diabetes status and type. Subsequently, the investigators evaluated a scenario of combining the rule based algorithm with targeted chart reviews where the algorithm performed poorly.

Results: The sample included 5308 true cases (89.2% type 1 diabetes). The rule-based algorithm outperformed regression for overall accuracy (0.955 vs 0.936). Type 1 diabetes was classified well by both methods: sensitivity (Se) (>0.95), specificity (Sp) (>0.96), and positive predictive value (PPV) (>0.97). In contrast, the PPVs for type 2 diabetes were 0.642 and 0.778 for the rule-based algorithm and the multinomial regression, respectively. Combining the rule-based method with chart reviews (n=695, 7.9%) of persons predicted to have non type 1 diabetes resulted in perfect PPV for the cases reviewed, while increasing overall accuracy (0.983). The sensitivity, specificity, and PPV for type 2 diabetes using the combined method were >=0.91.

Conclusions: An ICD-10 algorithm combined with targeted chart reviews accurately identified diabetes status/type and could be an attractive option for diabetes surveillance in youth.


Grant Support (SEARCH 3): SEARCH for Diabetes in Youth is funded by the Centers for Disease Control and Prevention (PA numbers 00097, DP-05-069, and DP-10-001) and supported by the National Institute of Diabetes and Digestive and Kidney Diseases.