Gaps remain in understanding the epidemiology of eosinophilic esophagitis (EoE). Our aim was to identify and validate a national cohort of individuals with EoE utilizing Veterans Health Administration (VHA) data.
We used two validation strategies to develop algorithms that identified adults with EoE between 1999-2020. The first validation strategy applied International Classification of Diseases (ICD) code algorithms to a base cohort of individuals who underwent esophagogastroduodenoscopy with esophageal biopsies. The second applied ICD code algorithms to a base cohort of all individuals in the VHA. For each ICD algorithm applied, a random sample of candidate EoE cases and non-EoE controls were selected and the charts manually reviewed by a blinded reviewer. Each algorithm was iteratively modified until the prespecified diagnostic accuracy endpoint (95% confidence lower bound for a positive predictive value (PPV) >88%) was achieved. We compiled individuals from each strategy’s maximum performance algorithm to construct the VA eosinophilic esophagitis cohort (VA E-O-ECHO).
The maximum performance algorithm from the first validation strategy included ≥2 ICD code encounters for EoE separated by >30 days and achieved 93.3% PPV (lower bound 88.1%) for identifying true EoE cases. The maximum performance algorithm from the second validation strategy included ≥4 ICD code encounters for EoE where two codes were separated by at least 30 days, and similarly achieved 93.3% PPV (lower bound 88.1%). Combining both strategies yielded 6,637 individuals, which comprised the VA E-O-ECHO cohort.
We developed and validated two highly accurate coding algorithms for EoE and established a nationwide VHA cohort of adults with EoE for future studies.
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