Nileesa Gautam

Background: Prior validation studies of claims‐based definitions of chronic kidney disease (CKD) using ICD‐9 codes reported overall low sensitivity, high specificity, and variable but reasonable PPV. No studies to date have evaluated the accuracy of ICD‐10 codes to identify a US patient population with CKD.Methods: We assessed the accuracy of claims‐based algorithms to identify adults with CKD Stages 3–5 compared with laboratory values in a subset (~40%) of a US commercial insurance claims database (Optum's de‐identified Clinformatics® Data Mart Database). We calculated the positive predictive value (PPV) of one or two ICD‐9 (2012–2014) or ICD‐10 (2016–2018) codes for CKD compared with a lab‐based estimated glomerular filtration rate (eGFR) occurring within prespecified windows (±90 days, ±180 days, ±365 days) of the ICD‐based CKD code(s).Results: The study population ranged between 104 774 and 161 305 patients (ICD‐9 cohorts) and between 285 520 and 373 220 patients (ICD‐10 cohorts). The mean age was 74.4 years (ICD‐9) and 75.6 years (ICD‐10) and the median eGFR was 48 ml/min/1.73 m². The algorithm of two CKD codes compared with a lab value ±90 days of the first code achieved the highest PPV (PPV 86.36% [ICD‐9] and 86.07% [ICD‐10]). Overall, ICD‐10 based codes had comparable PPVs to ICD‐9 based codes and all ICD‐10 based algorithms had PPVs >80%. The algorithm of one CKD code compared with laboratory value ±180 days maintained the PPV above 80% but still retained a large number of patients (PPV 80.32% [ICD‐9] and 81.56% [ICD‐10]).Conclusion: An ICD‐10‐based definition of CKD identified with sufficient accuracy a patient population with CKD Stages 3–5. Our findings suggest that claims databases could be used for future real‐world research studies in patients with CKD Stages 3–5.