Identifying Diabetic Ketoacidosis Encounters at Diagnosis Among Children with Type 1 Diabetes in Claims Data
R Brett McQueen, Nai-Chia Chen, Eric J Gutierrez, Kelly E Anderson, Todd AlonsoAbstract
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 (BDC) Registry to the Colorado all-payer claims database (APCD) to estimate variation in the performance of claims (i.e., type 1 diabetes and DKA codes in emergency department (ED) and inpatient (IP) settings) in identifying DKA cases from 2014-2019. We estimated unadjusted and adjusted association of laboratory confirmed DKA on resource utilization using encounters and incidence rate ratios (IRRs) with 95% confidence intervals.
Results
After applying algorithms for identifying type 1 diabetes with continuous enrollment criteria, N = 728 (62% match of 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 low sensitivity (63%) and higher specificity (76%) when compared to looser definitions (type 1 diabetes or DKA) with higher sensitivity (89%) and lower specificity (60%). Laboratory confirmed DKA was associated with over five times the rate of IP encounters compared to no confirmed DKA (IRR: 5.49; 95% confidence interval: 4.03-7.47) but fewer ED-only encounters (IRR: 0.36; 95% confidence interval: 0.24-0.54).
Conclusions
Claims data may not capture all DKA encounters at type 1 diabetes diagnosis. Future research should provide sensitivity analyses across coding and setting to estimate the burden of DKA.