AWS HealthScribe Transcript file
In the transcript file, in addition to standard turn-by-turn transcription output with word level timestamps, AWS HealthScribe provides you with:
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Participant role detection so you can distinguish the patients from the clinicians in the conversation transcript.
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Transcript sectioning, which categorizes transcript dialogues based on their clinical relevance like small talk, subjective, objective, etc. This can be used to show specific portions of the transcript.
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Clinical entities, which includes structured information like medications, medical conditions, and treatments mentioned in the conversation.
In addition, the following insights are provided for each conversation turn:
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Participant role — Each participant is labeled as either a clinician or a patient. If a conversation has more than one participant in each category, each participant is assigned a number. For example,
CLINICIAN_0,CLINICIAN_1andPATIENT_0,PATIENT_1. -
Section — Each dialogue turn is assigned to one of four possible sections based on the content identified.
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Subjective — Information provided by the patient about their health concerns.
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Objective — Information observed by the clinician through physical exam, lab, imaging, or diagnostic tests.
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Assessment and Plan — Information that relates to the doctor's assessment and treatment plan.
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Visit Flow Management — Information related to small talk or transitions.
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Insights — Extract clinically relevant entities (
ClinicalEntity) present in the conversation. AWS HealthScribe detects all clinical entities supported by Amazon Comprehend Medical.
For an example of a transcript from a transcription job, see the transcript output in Transcription job output examples. For an example of a transcript from streaming, see the transcript output in Streaming transcription output examples.
