The Benefits of Voice Recognition Software in Healthcare
Most of us use voice recognition everyday when we talk to Siri, Alexa, or a Google Assistant. But what about voice recognition software in healthcare? Its applications and potential are becoming brighter by the day, and it's becoming tclear that advanced voice recognition software, when coupled with AI, has real potential to shake up how our care providers document patient encounters and interact with their EHRs.
Benefits of Voice Recognition Software in Healthcare
Broadly, voice recognition software (sometimes referred to as speech recognition) is technology that allows people to use their voice to complete tasks. Ten years ago most cellphone users were introduced to voice recognition software right in their pocket when Apple released “Siri.” Amazon’s Alexa and Google Assistant followed in the years after and introduced similarly pedestrian iterations of voice recognition software designed to complete everyday tasks. Voice recognition continues to iterate and improve, and today, voice recognition software in healthcare seems to be one of the most promising technological advancements in the industry.
The most common application of voice recognition software in healthcare is within the world of documentation, EHRs, and mundane data entry. Voice recognition software helps streamline these tedious tasks by allowing the clinician to use their voice to complete them.
Voice Recognition and Dictation
Similar to how a cellphone user might ask Siri to set an alarm for them, many voice recognition technologies in healthcare rely on a similar form of dictation to complete tasks. For example, a provider would likely use voice recognition to document the information gathered during a patient encounter and produce a note, leveraging their voice to complete the different fields of their medical note.
Rather than documenting a patient encounter by hand and then typing it into the patient’s electronic health record, the provider can use voice recognition software to simply dictate to a device that records their voice and transcribes it into a text document. In more rudimentary applications, the provider would then have to translate that document into their EHR either through an import or integration, or by typing it by hand.
Today, there are more and more voice recognition technologies in healthcare that are leveraging AI in an attempt to automate more of the process. This type of software works by integrating with a provider's EHR and relying on their voice to not only document the encounter, but to apply that dictated information into the specific fields of the EHR. This software uses voice recognition, speech-to-text, and some language processing models to decipher the provider’s voice and produce completed documentation.
The drawback to this sort of voice recognition technology is that it relies on an exhausting level of dictation. The nature of the software means that the care providers must not only dictate every element of the encounter, but also every element of punctuation and formatting. Providers often feel that the technology simply replaces writing and typing notes with dictating them, and the benefit of expedited documentation are not as drastic as promised.
Voice Recognition and AI for bedside care and at-home care
With COVID-19 continuing to stretch our healthcare organizations and providers thin, the development of voice recognition software in patient-facing environments may be the key to efficient care. In a 2016 conference hosted by Boston Children’s Hospital, innovators, patients, and hospital staff all came together to brainstorm ideas of how voice recognition and AI could assist in both bedside care and at-home care.
On the patient side, some guests discussed the potential of voice recognition devices to manage simple hospital room tasks like dimming the lights, turning up the heat, and turning on the TV, among others. Without summoning an actual provider to complete these simple tasks, health organizations might begin to run more efficiently and without constant interruptions.
On the provider side, clinicians brainstormed about the potential benefits of voice recognition software. Some of the ideas included announcing patient vitals like heart rate or helping clinician quickly find out how much blood to draw from a patient.
On the home-care side, parents of BCH patients discussed and were exposed to the possibility of being walked through routine at-home care like flushing a catheter. If an AI device is capable of fielding questions and walking the patient or guardian through each step of that process, care efficiency would likely go-up, and the need for an around-the-clock at-home nurse might go down, diminishing the cost of care.
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Voice Recognition and AI Medical Scribes
Voice recognition software really has a golden opportunity to transform healthcare by coupling the existing technology with more robust AI models that are capable of automating much more of the medical documentation process. At DeepScribe, we’ve developed an AI scribe that relies on voice recognition, machine learning, natural language processing, and other models to help create an all-encompassing solution that truly automates documentation.
The system works by listening in on a patient encounter through the microphone on a provider’s cellphone and creating a high fidelity recording. From there, the AI uses natural language processing to autonomously extract the medically relevant information from the small talk before producing a complete medical note that then integrates directly into the fields of the provider’s EHR.
The benefit here is not only that clinicians no longer have to endure the burdens of medical documentation, but they no longer have to dictate at all during their encounter or after. The provider can simply speak naturally during the encounter, and DeepScribe takes care of the rest. Focus on the patient, deliver care, review the note, sign off. That’s it.