Medical Voice Recognition Software: How Does It Work?
It takes significant mental effort to summarize the verbose language of a conversation into concise, readable documentation. We must quickly sort out what is relevant from the niceties and do so while our memory of the conversation slowly deteriorates. This task is doable if you have just one conversation to keep in mind, but for physicians who meet with upwards of 20 patients a day...it’s nearly impossible.
How we communicate in person differs greatly from the manner in which we communicate through written word. Consider a recent conversation of yours that took place in person. Would that conversation have played out the same over email?
Most likely, the answer is no. This is because oral and written communication follow very different etiquette. While you’d likely get to the point rather quickly in a written message, face-to-face conversations are peppered with small talk, digressions, and filler words that are important for building rapport and establishing trust.
Given this mismatch in communication style, it takes significant mental effort to summarize the verbose language of a conversation into concise, readable documentation. We must quickly sort out what is relevant from the niceties and do so while our memory of the conversation slowly deteriorates. This task is doable if you have just one conversation to keep in mind, but for physicians who meet with upwards of 20 patients a day to discuss their medical concerns, it’s nearly impossible to document every conversation with complete accuracy.
That’s why many doctors now rely on medical voice recognition software to record and translate patient conversations into medical documentation. If you are considering VR software for your practice, but are finding it difficult to navigate the market – look no further! Below we break down everything you need to know about voice recognition: what it is, how it works, and how to differentiate the market’s options.
What Is Voice Recognition Software?
Voice recognition software is a computer program that can understand human speech and convert it into readable text. Beyond simply understanding human language, voice recognition software can use the information within human speech to complete tasks with greater accuracy.
Everyday applications of voice recognition software include voice-activated assistants like Alexa and Siri, who follow voice commands to complete simple tasks, and automated phone bots who interpret spoken responses in order to direct patrons towards the correct service or support function.
How Does Voice Recognition Work?
In general, voice recognition softwares follow four major steps to translate speech to text:
- First, an analog-to-digital converter translates the analog waves emitted by speech into digital data that can be understood by a computer.
- Then, this data is broken down into smaller sound bites and matched to phonemes in the given language.
- The software analyzes the string of selected phonemes and compares them with its database of known words, phrases, and sentences.
- Following this comparison process, the computer makes an inference about what has been said and either translates that information into text or uses it to perform a command.
Medical voice recognition software follows this same speech-to-text translation process, but requires a database of language specific to the medical field. For that reason, there is a learning curve in which physicians must correct mistakes made by the software, thereby providing the algorithm feedback to increase accuracy. As accuracy increases, the need for input lessens allowing physicians to be increasingly hands-off.
What Are The Types Of Medical Voice Recognition Software?
As it applies to medical documentation, there are two main categories of voice recognition software – dictation softwares and AI scribes.
Dictation tools use a microphone to capture speech and transcribe what it hears word-for-word in real time. Given this process, it is a best practice for doctors to dictate summaries of their patient visits exactly how they would like them to be recorded in their notes.
AI scribes take this process many steps further. After transcribing audio input word-for-word, AI scribes use natural language processing (NLP) to parse out the medically relevant information while removing small talk and filler words. This allows the physician to carry out a natural conversation with their patient as the software listens, transcribes, and summarizes their notes.
Here’s a side-by-side comparison of dictation tools and DeepScribe’s AI scribe. You will notice that while both employ voice recognition to transcribe notes, DeepScribe layers in NLP algorithms to generate compliant notes mapped to the fields found in an EHR as well the appropriate diagnostic coding needed to meet insurance and billing standards:
Remember earlier when we discussed the difficulty of summarizing in-person conversations into concise notes, particularly at the scale required of physicians? Using a dictation tool, physicians will still need to complete this time-consuming task on their own. Only AI scribes manage note-taking autonomously, providing physicians complete relief from documentation.
So the final verdict? If you are feeling overwhelmed by administrative demands, and just want to get back to being a doctor, AI-powered voice recognition is the more effective solution.