ArticleJournal of the Endocrine Society2026
Identifying diabetic ketoacidosis encounters at diagnosis among children with type 1 diabetes in claims data.
Article in Journal of the Endocrine Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Quantify the performance of claims data in identifying diabetic ketoacidosis (DKA) cases and estimate healthcare resource utilization among newly diagnosed type 1 diabetes patients with and without DKA. Methods: We matched individuals <18 years of age from the Barbara Davis Center for Diabetes Registry to the Colorado all-payer claims database to estimate variation in the performance of claims (ie, type 1 diabetes and DKA codes in emergency department [ER] and inpatient [IP] settings) in identifying DKA cases from 2014 to 2019. We estimated the unadjusted and adjusted associations of laboratory-confirmed DKA with resource utilization using encounters and incidence rate ratios with 95% confidence intervals. Results: After applying algorithms for identifying type 1 diabetes with continuous enrollment criteria, n = 728 (62% match of the sample) represented an insured population residing in Colorado. Mean age at onset was approximately 9.48 years, with a proportion of DKA events at diagnosis of 56%. Strict coding definitions of DKA (DKA and type 1 diabetes) had lower sensitivity (63%) and higher specificity (76%) than looser definitions (type 1 diabetes or DKA), which had higher sensitivity (89%) and lower specificity (60%). Laboratory-confirmed DKA was associated with over 5 times the rate of IP encounters compared with no confirmed DKA (incidence rate ratio [IRR], 5.49; 95% confidence interval, 4.03-7.47) but fewer ER-only encounters (IRR, 0.36; 95% confidence interval, 0.24-0.54). Conclusion: Claims data may not capture all DKA encounters at type 1 diabetes diagnosis. Future research should provide sensitivity analyses across coding and settings to estimate the burden of DKA.
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