Manual reviews of health records to identify possible adverse events are time consuming. We are developing a method based on natural language processing to quickly search electronic health records for common triggers and adverse events. Our results agree fairly well with those obtained using manual reviews, and we therefore believe that it is possible to develop automatic tools for monitoring aspects of patient safety.
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