Pulmonary function tests (PFTs) are objective estimates of lung function, but are not reliably stored within the Veteran Health Affairs data systems as structured data. The aim of this study was to validate the natural language processing (NLP) tool developed by the authors—which extracts spirometric values and responses to bronchodilator administration—against expert review, and to estimate the number of additional spirometric tests identified beyond the structured data. In the validation set NLP demonstrated a precision of 98.9%. Although this technology can improve identification of PFTs for epidemiologic research, caution must be taken in assuming that a single domain of clinical data can completely capture the scope of a disease, treatment, or clinical test.