Pros and Cons of Speech Recognition Systems in Healthcare
While some providers may find advanced speech recognition tools helpful, there are a growing number of clinicians who are looking for more advanced applications of artificial intelligence and natural language processing.
Pros and Cons of Speech Recognition Systems in Healthcare
Speech recognition technology is becoming more commonplace in the medical industry as hospitals and healthcare providers strive to cut costs and adopt more efficient workflows. Speech recognition systems allow for hands-free control of medical devices and can expedite medical documentation by using the provider's voice to log information into the electronic health record system. While there are many benefits to using speech recognition in healthcare, there are also some disadvantages that should be considered.
How Does Speech Recognition Software for EHR's Work?
Speech recognition systems use advanced computer science and machine learning programs to convert spoken word into written text and understand vocal cues to complete tasks. This software uses large speech pattern databases in combination with an AI subfield called natural language processing to extract context and meaning from ordinary human speech. When integrated directly into an electronic health record system, speech recognition works both as a transcriptionist and an assistant, and allows providers to complete their entire medical note using only their voice. This means that not only can the device process and log new information, but it can be vocally prompted to complete a variety of tasks within the EHR itself. For example, using speech recognition this technology can "create a new note," "start a standard order set," and "pull up patient's record."
The benefit to using speech recognition systems within the electronic health record system is that it can help to reduce documentation time and reduce costs (as these systems are often cheaper than a scribe or transcriptionist). Additionally, these tools immediately convert the speech to text, which means any typos or documentation errors can be corrected in real time rather than forcing the provider to endure lengthy turnaround times like they would with a traditional transcription service.
However, the reality is that these speech recognition tools are not perfect, and there are several potential disadvantages that providers should consider before deciding to use this technology in their medical practice.
Recommended Reading: Advantages and Disadvantages to Speech Recognition for EHRs
Drawbacks of Speech Recognition Systems in Healthcare
One of the biggest potential problems with speech recognition is information recall. When you dictate your notes using speech recognition, you may not remember all of the details that you discussed during your visit with the patient. If you have a day with a heavy patient load, then you may be waiting until the end of the day to complete all of the final documentation, which may pose a risk to the efficacy and accuracy of your patient documentation.
Another potential disadvantage is the cost. speech recognition technology can be expensive to implement, and it may require special hardware or software in order to work properly. In addition, speech recognition systems may require a significant amount of training for medical providers in order to use them effectively.
Finally, there is the potential for the dictation and vocal prompting itself to be burdensome for providers. The task of dictating medical information is highly involved into the EHR system is highly involved, and because the speech recognition technology often requires the provider to dictate even the most basic punctuation, the process can feel exhausting.
When considered altogether, the biggest drawback to advanced speech recognition systems in healthcare is that they don't truly alleviate the burden of medical documentation. Of the available Physician Lifestyle Reports by MedScape, a top online medical journal, administrative tasks like documentation are the primary contributor to burnout among clinicians. The problem with current speech recognition tools is while they may speed up documentation to a degree, they don't necessarily make documentation significantly easier. These tools simply replace the task of typing medical notes with dictating them, and that isn't necessarily a viable method to reducing the administrative burden that has plagued physicians for the last decade. It simply repackages that task into a different box. Voice activated instead of keyboard activated.
While some providers may find these advanced speech recognition tools to be helpful, there are a growing number of clinicians who are looking for more advanced applications of artificial intelligence and natural language processing — one that truly allows them to reduce their administrative burden and focus on the patient rather than on the medical documentation.
AI-powered Medical Scribes vs. Speech Recognition Software
Of the documentation solutions on the market today, only DeepScribe is capable of completing clinical documentation entirely in the background. DeepScribe is different than even the most advanced speech recognition systems because it uses proprietary AI technology and NLP to extract medical information right from the natural patient conversation, and then use that information to write complete medical notes directly inside your EHR, making it an AI-powered medical scribe rather than a more simplistic documentation aid.
DeepScribe's AI-medical scribe is superior to other tools not just because of the advanced technology and ease of documentation, but because it allows providers to save time and focus on their patients — a combination that can't be found in other documentation tools.
Because DeepScribe produces notes in the background, all the provider has to do is converse with their patient like normal and then review and sign-off when the note is complete. Provider's don't need to take any notes during the visit, dictate afterwords, or stress about the quality of their notes. Simply wait for the finished note to upload into your EHR, then review and sign off. Providers who adopt DeepScribe can save up to 3 hours per day on their documentation.
Focus on Your Patients
Instead of typing notes into the EHR during the visit or scribbling onto a notepad, you can focus on your patients and confidently leave the documentation up to DeepScribe. Our AI takes care of your documentation and our quality assurance teams make sure that information isn't slipping through the cracks or being mislabeled, a process which actually trains our AI to be better thanks to our built in machine learning algorithms.
DeepScribe brings the joy of care back to medicine by allowing providers to engage in authentic, empathic, face-to-face care with their patients — without the stress of messy documentation tools. DeepScribe relieves the burden of clinical documentation, and allows you to focus on what you do best, delivering care.
If you're interested in learning how DeepScribe can automate your documentation, reach out to us today!