Medical Note Taking Solutions Cheat Sheet — Industry Jargon Explained

If you read any of our blogs, you may sometimes find yourself getting bogged down in the industry jargon. For those that aren’t deeply enmeshed in this space, the language can be a bit dizzying. It even was for us when we first started. 

In this article, we break down the most common industry devices that we refer to on a regular basis, their identifying factors, and their differences. Understanding this language is critical in understanding the landscape of the entire medical note taking industry.

We’ll be looking at: medical scribes, dictation, medical transcription, speech-to-text, speech recognition, AI medical transcription, and ambient technology.

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Medical Scribe.

A medical scribe is a person (usually with some level of medical training) whose job it is to log all of the information gathered during a patient visit. Sometimes we think of them as being healthcare’s version of a court stenographer. Historically, medical scribes work in person in the exam room, but in the age of COVID-19 and shifting trends, many scribes are now working remotely and tuning in via a secure video connection — those professionals are referred to as virtual scribes.


Dictation tools are small devices that capture a clinician's voice and convert it into an audio file. These tools are typically used in a post-visit setting, where a clinician will dictate the information gathered during a patient encounter. Oftentimes, these audio files are sent to a medical transcriptionist.

Medical Transcription.

A medical transcriptionist is a trained third party professional who converts recorded audio into a written format, often in the form of a medical SOAP note. The best medical transcriptionists allow clinicians to offload some of their note taking burden. We’ve outlined the pros and cons of medical transcriptionists in the past.


Speech-to-text medical devices are small devices that convert spoken audio into written text. These are commonly used as a way for clinicians to substitute their voice for typing. Now, some advanced speech-to-text software is capable of using vocal prompters to fulfill the discrete fields of an EHR. Speech-to-text tools rely on speech recognition technology.

Speech Recognition.

Speech recognition uses acoustic technology to recognize spoken sounds and convert them into text. Advanced iterations of speech recognition tools use logic rules and natural language processing to not only decipher spoken words, but identify who has spoken them, consider the context and then determine what those words mean. Advanced speech recognition is often utilized in more advanced medical devices like AI medical transcription tools.

AI Medical Transcription.

AI medical transcription uses voice recognition and natural language processing to listen into the natural patient-clinician conversation, parse out the medically relevant information, and summarize that information into compliant notes that map back to the appropriate fields of an EHR.

Ambient Technology.

Ambient technology is any device that exists in the background and gathers information without being directly prompted. Ambient technology is used to complete AI-powered medical transcription. Currently, DeepScribe is the only fully ambient technology that is capable of automating all of a clinician's medical documentation.

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