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Paper Details

Automated identification of postoperative complications within an electronic medical record using natural language processing.
JAMA
312
2011
PATIENTS, acute renal failure, administrative, deep vein thrombosis, myocardial infarction, patient, patients, pneumonia, postoperative myocardial infarction, pulmonary embolism, sepsis, venous thromboembolism
Automation, Cross-Sectional Studies, Diagnosis-Related Groups, Electronic Health Records, Hospitalization, Hospitals, Veterans, Humans, Information Storage and Retrieval, Inpatients, International Classification of Diseases, Myocardial Infarction, Natural Language Processing, Patient Discharge, Pneumonia, Population Surveillance, Postoperative Complications, Pulmonary Embolism, Quality Indicators, Health Care, Renal Insufficiency, Safety, Sensitivity and Specificity, Sepsis, Surgical Procedures, Operative, United States, Venous Thrombosis
Author NameAffiliation
Harvey J MurffTennessee Valley Healthcare System, Veterans Affairs Medical Center
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Release 1.2