Abstract
Large administrative databases such as Medicaid billing databases could be used to study care and outcomes of lupus nephritis if these patients could be correctly identified from claims data. We aimed to develop and validate an algorithm for the correct identification of cases of lupus nephritis using ICD-9 billing codes. We used the Research Patient Data Resource query tool at our institution to identify patients with potential lupus nephritis. We compared four ICD-9 code based strategies, identifying patients seen between 2000 and 2007 with Medicaid medical insurance with greater than two claims for a diagnosis of SLE (ICD-9 code 710.0) and a combination of greater than two nephrologist visits and/or renal ICD-9 codes. We assessed performance using the positive predictive value. Two hundred and thirty four subjects were identified and medical records reviewed. Our third strategy, based on a combination of lupus and renal ICD-9 codes and nephrologist encounter claims, had the highest positive predictive value (88%) for the identification of patients with lupus nephritis. This strategy may offer a sound method of identifying patients with lupus nephritis for health services research in addition to serving as a model for using claims data as a way to better understand rare diseases such as lupus.