Researchers have implemented and developed a novel method for identifying lung nodules in community-based settings.
The researchers used a combination of ICD-9 codes, CPT codes and an algorithm for natural language processing (NLP) to classify the nodules. This automated method had a 96 percent sensitivity and 86 percent specificity compared to clinician review.
The authors suggest that the automated process, "could be used to study the incidence and prevalence of lung nodules in large populations, with the caveat that approximately 13 percent of cases identified by the automated method would not meet our definition of one or more nodules (e.g., be false-positives)."
Since this study favored sensitivity over specificity, the authors advise that the method "could be used as a sensitive first step to be followed by more specific review of radiology transcripts or actual imaging studies."
As screening programs for lung cancer have proven to be beneficial in specific high-risk populations, this study also provides useful information for the study of screen-detected nodules.