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Canadian Respiratory Journal
Volume 2016 (2016), Article ID 1690482, 6 pages
Research Article

Identifying Primary Spontaneous Pneumothorax from Administrative Databases: A Validation Study

1Division of Thoracic Surgery, Department of Surgery, Western University, London, ON, Canada N6A 3K7
2Department of Epidemiology and Biostatistics, Western University, London, ON, Canada N6A 3K7
3Division of Pediatric Surgery, Department of Surgery, Western University, London, ON, Canada N6A 3K7
4London Health Sciences Centre, London, ON, Canada N6A 5W9
5Division of Urology, Department of Surgery, Western University, London, ON, Canada N6A 3K7

Received 5 January 2016; Accepted 12 May 2016

Academic Editor: Elisa Giovannetti

Copyright © 2016 Eric Frechette et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Introduction. Primary spontaneous pneumothorax (PSP) is a disorder commonly encountered in healthy young individuals. There is no differentiation between PSP and secondary pneumothorax (SP) in the current version of the International Classification of Diseases (ICD-10). This complicates the conduct of epidemiological studies on the subject. Objective. To validate the accuracy of an algorithm that identifies cases of PSP from administrative databases. Methods. The charts of 150 patients who consulted the emergency room (ER) with a recorded main diagnosis of pneumothorax were reviewed to define the type of pneumothorax that occurred. The corresponding hospital administrative data collected during previous hospitalizations and ER visits were processed through the proposed algorithm. The results were compared over two different age groups. Results. There were 144 cases of pneumothorax correctly coded (96%). The results obtained from the PSP algorithm demonstrated a significantly higher sensitivity (97% versus 81%, ) and positive predictive value (87% versus 46%, ) in patients under 40 years of age than in older patients. Conclusions. The proposed algorithm is adequate to identify cases of PSP from administrative databases in the age group classically associated with the disease. This makes possible its utilization in large population-based studies.