Soo-Kyung Cho1, Tracy J Doyle2, Hemin Lee3, Yinzhu Jin3, Angela Y Tong3, Adrian J Santiago Ortiz3, Jeffrey A Sparks4, Seoyoung C Kim5. 1. Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States; Division of Rheumatology, Hanyang University Hospital for Rheumatic Diseases, Seoul, South Korea. 2. Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States. 3. Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States. 4. Division of Rheumatology, Immunology and Allergy, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States. 5. Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States; Division of Rheumatology, Immunology and Allergy, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States. Electronic address: sykim@bwh.harvard.edu.
Abstract
OBJECTIVE: To develop and validate claims-based algorithms to identify interstitial lung disease (ILD) in patients with rheumatoid arthritis (RA) METHODS: Using Medicare claims data linked with the electronic medical records (2012-2014), we first selected RA patients based on ≥2 diagnostic codes for RA and ≥1 disease-modifying antirheumatic drugs.Then, to identify ILD in RA, we developed eight claims-based algorithms using a combination of ICD-9 diagnosis codes and procedure codes related to the diagnosis or management of ILD. We assessed the positive predictive value (PPV) for each of the eight algorithms relative to confirmed ILD cases using chest computerized tomography or lung biopsy as the gold standard. RESULTS: A total of 5,214 RA patients were included in the study, and the ILD cases identified by each algorithm ranged from 181 to 993. The PPV of the diagnosis code-based algorithms ranged from 43.4% (≥1 diagnosis code by any physician) to 52.0% (≥2 diagnosis codes by any physician). When the algorithms further required ≥1 procedure code (e.g., imaging, bronchoscopy), the PPV did not improve. However, the algorithms that required ILD diagnosis codes by specialists (i.e., pulmonologist or rheumatologist) had PPVs of 61.5% with ≥1 code; 72.4% with ≥2 codes. CONCLUSIONS: In a cohort of RA patients, our algorithm that required ≥2 ILD diagnosis codes by specialists demonstrated a PPV of 72.4% in ascertaining ILD. Our results support the utility of the claims-based algorithm to identify a population-based cohort of RA patients with ILD using large administrative claims data.
OBJECTIVE: To develop and validate claims-based algorithms to identify interstitial lung disease (ILD) in patients with rheumatoid arthritis (RA) METHODS: Using Medicare claims data linked with the electronic medical records (2012-2014), we first selected RApatients based on ≥2 diagnostic codes for RA and ≥1 disease-modifying antirheumatic drugs.Then, to identify ILD in RA, we developed eight claims-based algorithms using a combination of ICD-9 diagnosis codes and procedure codes related to the diagnosis or management of ILD. We assessed the positive predictive value (PPV) for each of the eight algorithms relative to confirmed ILD cases using chest computerized tomography or lung biopsy as the gold standard. RESULTS: A total of 5,214 RApatients were included in the study, and the ILD cases identified by each algorithm ranged from 181 to 993. The PPV of the diagnosis code-based algorithms ranged from 43.4% (≥1 diagnosis code by any physician) to 52.0% (≥2 diagnosis codes by any physician). When the algorithms further required ≥1 procedure code (e.g., imaging, bronchoscopy), the PPV did not improve. However, the algorithms that required ILD diagnosis codes by specialists (i.e., pulmonologist or rheumatologist) had PPVs of 61.5% with ≥1 code; 72.4% with ≥2 codes. CONCLUSIONS: In a cohort of RApatients, our algorithm that required ≥2 ILD diagnosis codes by specialists demonstrated a PPV of 72.4% in ascertaining ILD. Our results support the utility of the claims-based algorithm to identify a population-based cohort of RApatients with ILD using large administrative claims data.
Authors: Sicong Huang; Vanessa L Kronzer; Paul F Dellaripa; Kevin D Deane; Marcy B Bolster; Vivek Nagaraja; Dinesh Khanna; Tracy J Doyle; Jeffrey A Sparks Journal: Curr Treatm Opt Rheumatol Date: 2020-09-01
Authors: M Meehan; A Shah; J Lobo; J Oates; C Clinton; N Annapureddy; F Xie; J Zhuo; M I Danila; B R England; J R Curtis Journal: Arthritis Res Ther Date: 2022-01-03 Impact factor: 5.606