Development and Validation of a Healthcare Utilization-Based Algorithm to Identify Acute Exacerbations of Chronic Obstructive Pulmonary Disease

Douglas W Mapel,1,* Melissa H Roberts,1,* Susan Sama,2 Priyanka J Bobbili,3 Wendy Y Cheng,3 Mei Sheng Duh,3 Catherine Nguyen,3 Philippe Thompson-Leduc,3 Melissa K Van Dyke,4 Kieran J Rothnie,4 Devi Sundaresan,2 Julia M Certa,5 Thomas S Whiting,5 Jennifer L Brown,5 Douglas W Roblin5 1College of Pharmacy, University of New Mexico, Albuquerque, NM, USA; 2Reliant Medical Group, Inc., Worcester, MA, USA; 3Analysis Group, Inc., Boston, MA, USA; 4GlaxoSmithKline plc., London, UK; 5Kaiser Permanente Mid-Atlantic States (KPMAS), Mid-Atlantic Permanente Research Institute (MAPRI), Rockville, MD, USA*These authors contributed equally to this workCorrespondence: Melissa H RobertsCollege of Pharmacy, University of New Mexico, 2502 Marble Ave, Albuquerque, NM, 87106, USATel +1 505 925-0953Email MHRoberts@salud.unm.eduIntroduction: Acute exacerbations of chronic obstructive pulmonary disease (AECOPD) are important events that may precipitate other adverse outcomes. Accurate AECOPD event identification in electronic administrative data is essential for improving population health surveillance and practice management.Objective: Develop codified algorithms to identify moderate and severe AECOPD in two US healthcare systems using administrative data and electronic medical records, and validate their performance by calculating positive predictive value (PPV) and negative predictive value (NPV).Methods: Data from two large regional integrated health systems were used. Eligible patients were identified using International Classification of Diseases (Ninth Edition) COPD diagnosis codes. Two algorithms were developed: one to identify potential moderate AECOPD by selecting outpatient/emergency visits associated with AECOPD-related codes and antibiotic/systemic steroid prescriptions; the other to identify potential severe AECOPD by selecting inpatient visits associated with corresponding codes. Algorithms were validated via patient chart review, adjudicated by a pulmonologist. To estimate PP