| Summary: | <p>Abstract</p> <p>Background</p> <p>The text descriptions in electronic medical records are a rich source of information. We have developed a Health Information Text Extraction (HITEx) tool and used it to extract key findings for a research study on airways disease.</p> <p>Methods</p> <p>The principal diagnosis, co-morbidity and smoking status extracted by HITEx from a set of 150 discharge summaries were compared to an expert-generated gold standard.</p> <p>Results</p> <p>The accuracy of HITEx was 82% for principal diagnosis, 87% for co-morbidity, and 90% for smoking status extraction, when cases labeled "Insufficient Data" by the gold standard were excluded.</p> <p>Conclusion</p> <p>We consider the results promising, given the complexity of the discharge summaries and the extraction tasks.</p>
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