Identifying Primary Spontaneous Pneumothorax from Administrative Databases: A Validation Study. (8th June 2016)

• Record Type: Journal Article
• Authors: Frechette, Eric; Guidolin, Keegan; Seyam, Ayman; Choi, Yun-Hee; Jones, Sarah; McClure, J. Andrew; Winick-Ng, Jennifer; Welk, Blayne; Malthaner, Richard A.
• Other Names: Giovannetti Elisa Academic Editor.
• Is Part Of: Canadian respiratory journal. Volume 2016(2016)
• Publication Date: 2016-06-08
• Subjects: Respiratory organs -- Diseases -- Periodicals; Respiration -- Canada -- Periodicals; Respiration; Respiratory organs -- Diseases; Canada; Respiratory Tract Diseases -- Periodicals; Periodicals; Periodicals; 616.2
• DOI: 10.1155/2016/1690482
• Languages: English
• ISSNs: 1198-2241

Abstract

Abstract : 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%, p = 0.038 ) and positive predictive value (87% versus 46%, p < 0.001 ) 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.