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Accuracy of Administrative Data for Identifying Patients With Pneumonia

Department of Biomedical Informatics & Emergency Medicine, Vanderbilt University, Nashville, Tennessee, dominik.aronsky{at}vanderbilt.edu

Peter J. Haug, MD

Department of Medical Informatics, LDS Hospital, University of Utah, Salt Lake City

Charles Lagor, MD, PhD

Phillips Research, USA

Nathan C. Dean, MD

Division of Pulmonary Medicine, LDS Hospital, University of Utah, Salt Lake City

The goal of this study was to determine the accuracy and the impact of 5 different claims-based pneumonia definitions. Three International Classification of Diseases, Version 9, (ICD-9), and 2 diagnosis-related group (DRG)-based case identification algorithms were compared against an independent, clinical pneumonia reference standard. Among 10748 patients, 272 (2.5%) had pneumonia verified by the reference standard. The sensitivity of claims-based algorithms ranged from 47.8% to 66.2%. The positive predictive values ranged from 72.6% to 80.8%. Patient-related variables were not significantly different from the reference standard among the 3 ICD-9-based algorithms. DRG-based algorithms had significantly lower hospital admission rates (57% and 65% vs 73.2%), lower 30-day mortality (5.0% and 5.8% vs 10.7%), shorter length of stay (3.9 and 4.1 days vs 5.6 days), and lower costs (US $4543 and US $5159 vs US $8585). Claims-based identification algorithms for defining pneumonia in administrative databases are imprecise. ICD-9-based algorithms did not influence patient variables in our population. Identifying pneumonia patients with DRG codes is significantly less precise.

Key Words: pneumonia • claims analysis • International Classification of Diseases • algorithm • sensitivity and specificity • comparative study

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