Automated speech recognition (ASR) is used in many areas of medicine today. However, not many studies have evaluated the usefulness of ASR applications for capturing clinician information needs in noisy environments. We evaluated 72 ASR transcribed clinician-generated questions and assessed them for semantic and syntactic errors. The results showed that basic user training is not sufficient in order to capture the semantics of recordings.