Ascertainment of Helicobacter pylori Infection and Eradication Treatment Using a Nationwide Electronic Health Record Database

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Background and Aims There are limited contemporary population-based data on Helicobacter pylori epidemiology and outcomes in the United States. Our primary aim was to create a validated cohort of veterans with H pylori testing or treatment using Veterans Health Administration data. Methods Using Veterans Health Administration structured and unstructured data, we developed and validated 4 algorithms for H pylori infection (3 algorithms) and treatment status (1 algorithm). During the development phase, we iteratively modified each algorithm based on a manual review of random sets of electronic health records (reference standard). The a priori validation goal was to achieve a one-sided 95% confidence lower bound (LB) for positive predictive value (PPV) and/or negative predictive value (NPV) >90%. We applied the Bonferroni correction when both PPV and NPV were relevant. Results For H pylori infection, we achieved 99.0% PPV (LB = 94.6%) and 100% NPV (LB = 96.4%) for discriminating H pylori positive vs negative status using structured (ie, laboratory tests) and 95% PPV (LB = 90.3%) and 97.9% NPV (LB = 93.9%) using unstructured (ie, histopathology reports) data. Diagnostic codes achieved 98% PPV (LB = 93.0%) for H pylori diagnosis. The treatment algorithm was composed of multiple antimicrobial combinations and overall achieved ≥98% PPV (LB = 93.0%) for H pylori treatment, except for amoxicillin/levofloxacin (PPV<60%). Application of these algorithms yielded nearly 1.2 million veterans with H pylori testing and/or treatment between 1999 and 2018. Conclusion We assembled a validated national cohort of veterans who were tested or treated for H pylori infection. This cohort can be used for evaluating H pylori epidemiology and treatment patterns, as well as complications of chronic infection.