Healthcare AI-enabled voice assistants can take over several basic tasks of clinicians. As a result, they get more time and space to work on other important tasks.
Voice assistants can bridge the language gaps and allow physicians access to information on patients with hearing impairments. These assistants can answer simple questions for the users sharing authentic information. As this technology makes inroads into the healthcare sector, let’s see what the future of healthcare AI and voice AI holds.
Future Applications of AI-Enabled Voice Technologies
The foundation for AI to integrate with the healthcare sector has already been laid. As new developments emerge in this domain, the benefits will be seen in several components of the healthcare sector. Here are a few developments to look after in the future.
1. Smart Speakers to Work as Smart Assistants
Google has already shown how its smart assistant can talk to customers and clients for booking appointments. Going into the future the same technology will become more widespread as it gets widely adopted.
Devices like Alexa Echo, Apple Home Pod, and Google Home will find their spot in healthcare premises. They will provide an alternative user interface to interact with patients for refilling prescriptions, schedule doctor appointments, and manage some work for the physicians.
These assistants can take notes for the doctor in the OPD or the operating room, among other places. They can even record and store medical histories and share specific information when asked.
2. Automated Speed Recognition to be Available at Scale
Continuous developments in ASR technology have helped researchers achieve human parity. Today ASR’s function is similar to how a human would, especially in documentation.
Effective documentation is pivotal to recording and gaining accurate clinical data, which becomes the basis for treatment and research in healthcare.
Moreover, text-to-speech (TTS) will also gain additional momentum and work together with ASR to deliver additional benefits.
The existing ASR models and technologies largely use English data sets, but in the future, they might do the same for other languages. So, we can expect to see ASR models specifically built for French, Spanish, and German languages.
3. Voice Chatbots will continue to Improve Customer Engagement
Voice AI chatbots are currently used to build customized applications and chatbots. Some of these solutions are powered by GPT, BERT and other large language models.
However, with expected advances in these technologies and improvements in the language models, we can see better chatbots in the future. The development of chatbots also rests on the availability of documented, voice, and speech data sets and variant dialects.
As these language models get access to more comprehensive data sets, we will see better versions of the same leading to even better customer engagement.
These voice chatbots can be employed for patient recovery and guide them towards a personalized recovery journey. From using the technology to perform rudimentary tasks like switching on the lights, and drawing curtains to getting answers in real-time, voice AI applications will continue to expand.
4. Clinical Documentation Will Be Faster and More Accurate
Clinical documentation is significant in delivering effective treatment, research, and accurate diagnosis. With healthcare AI tools taking care of the documentation part, we can expect the same to be completed at speed in the future.
Even today some healthcare institutions have switched from manual to automated documentation, but its large-scale adoption is yet to be seen. With speech recognition, clinical documentation can be quickly transcribed from speech to text.
As a result, it will save time and effort of nurses and doctors allowing them to focus more on patient care.
5. Voice Assistants Deployed at Front Desk Operations
To improve patient experience, voice AI assistants can be deployed at the front desk of all patient-centred departments. Voice assistants in emergency care can help the patients with details like wait time, relay patient information to the physician, and share distance to the emergency room, etc.
We can expect these smart assistants to take a proactive role in prioritizing patient care based on their symptoms and real-time condition. In addition to this, these systems can also extract records of patients with similar symptoms and use that information to allocate priority.
A medical person does the same, but it takes more time. No doctor or nurse can process every medical file and document within the limited time they have to treat patients. But an AI model can do it with speed and provide accurate responses.
AI in healthcare is helping doctors, physicians, and nurses to notice problems sooner than before. With all the data available on the cloud and ready for access, cloud-enabled voice AI assistants are giving them room to work more efficiently on patient care.
To Sum it Up
Voice technologies are still relatively new technologies and we are still working to get a good grasp over the solutions offered with them. In a time-sensitive healthcare setting, efficiency and accuracy are of paramount importance.
Healthcare AI technologies like voice AI, and voice chatbots, among others, can take care of several tasks that nurses or doctors are doing manually. Using these technologies healthcare professionals can provide better patient care and streamline their work, which gives them time and mental capacity to focus on other important tasks.