Automated linkage of free-text descriptions of patients with a practice guideline.
The process of applying a practice guideline to a patient requires a great deal of clinical data. AAPT (Appropriateness-Assessment Processing from Text) is an experimental computer program that can assess the appropriateness of coronary-artery bypass grafting surgery (CABG) in patients with coronary-artery disease (CAD) and chronic stable angina from the admission summaries of those patients. The AAPT architecture combines natural-language processing (NLP) and probabilistic inference. The NLP module identifies single clinical concepts of interest in the free-text document. The probabilistic inference module, a Bayesian belief network, estimates values for variables not specifically mentioned. AAPT produces a patient's summary of CAD that is similar to a manually generated clinical summary. Work is ongoing to improve AAPT and evaluate it as a tool to assist in the dissemination of guidelines and as a tool to encourage adherence to practice guidelines.
Lenert
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LA
Division of Clinical Pharmacology, Stanford University School of Medicine, CA.
Tovar
M
M
D000787:Angina Pectoris / Q000601:surgery; D001026:Coronary Artery Bypass; D006801:Humans; D016247:Information Storage and Retrieval; D008499:Medical Records; D009323:Natural Language Processing; D017410:Practice Guidelines as Topic; D012984:Software; D012986:Software Validation