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Technology is advancing rapidly, powered by artificial intelligence. Voice User Interface (VUI) technologies are just one example of how consumers, businesses, and healthcare providers are harnessing the power of the spoken word to get answers faster than ever before.
What is Natural Language Processing (NLP)?
At the heart of this new technology is Natural Language Processing, or NLP for short. Natural Language Processing is a type of artificial intelligence that enables computers to understand, interpret, and provide conclusions from written or spoken human language. Through machine learning algorithms, the computer is trained to identify words, phrases, and appropriate responses based on context clues.
How Natural Language Processing is Used Already
People use natural language processing applications every day. Every time your phone or laptop performs spell check, provides autocomplete recommendations, or makes keyword suggestions, it’s using natural language processing.
It takes unstructured data including emails, speech, online search requests, social media posts, product reviews, surveys, and customer support tickets, and categorizes the data to gain insights and generate predictive analytics.
The applications are endless.
Google Translate was one of the earliest commercial examples of voice-activated natural language processing. And hundreds of millions of people were introduced to the concept of an AI-powered virtual assistant through the Marvel Comics superhero Iron Man and J.A.R.V.I.S. (Just A Rather Very Intelligent System).
Now there are more than 110 million virtual assistant users in the United States alone, according to Statista. Alexa, Siri and Google Assistant are among the most popular. They take spoken commands and carry out tasks, such as turning on lights, or provide answers for the user.
The rise in NLP technology created a sea change in consumer behavior. More than 30% of online browsing was through voice search in 2019, according to Mobisoft, and analysts predict voice e-commerce will reach $40 billion by 2022.
Moving Beyond Alexa, Siri and Google Assistant
About one in four U.S. adults now own a smart speaker and there are more than 157 million of these devices in American homes and businesses, according to Marketing Land. More than half of Americans over the age of 18 have used voice commands, and 24% of that group uses voice commands daily, the report found.
This year will see an explosion of voice-activated commands in the workplace. Gartner, Inc, a world-renowned research and advisory company, predicts 25% of digital workers will use virtual employee assistants (VEAs) daily by the end of 2021. It also predicts that by 2023, 25% of employee interactions with applications will be via voice, up from just 3% in 2019.
Amazon’s Alexa for Business already helps employees delegate tasks such as scheduling meetings and logistics. The telecommunications giant Nokia Corporation developed its own virtual assistant program called MIKA to help engineers find answers and solve complex problems.
How Does Natural Language Processing Help Patients?
In healthcare, medical and dental providers are using voice-activated technology to dictate their notes into patient electronic medical records (EMR) and to access radiographs and other images hands-free. They’re also using natural language processing when they use voice commands to research symptoms, diagnostics, and treatment options.
Artificial intelligence programs are trained by using millions of data points that were categorized by humans already. That teaches the program how to recognize what it’s seeing. Then the AI programs use machine learning to extrapolate results and apply the information to future data. One healthcare application is having the computer generate a second opinion based on comparing the data from one patient with the data sets of thousands of other patients.
Healthcare companies like Mayo Clinic have developed their own voice technology products. Mayo Clinic launches its app on Alexa in 2017. Patients can describe their symptoms to help self-diagnose and determine whether they need medical attention. They can also use the app to receive answers to common first aid questions, such as how to treat a burn. This is particularly helpful when people need information quickly and hands-free.
How Dental Technology Companies use AI to Improve Patient Acquisition
Artificial intelligence helps patients even in their first interactions with healthcare providers. Companies like Patient Prism leverage Natural Language Processing algorithms and machine learning to quickly identify why patients called, the services they requested, the associated revenue, and whether the call ended in a booked appointment.
Designed specifically for dental practices, dentists use the data for everything from front office training to winning back unscheduled callers to determining whether their marketing efforts are driving the right kinds of calls.
This technology analyzes the conversation and draws conclusions about the caller’s intent. It pinpoints the moment where the caller decides not to move forward with scheduling, and provides actionable insights and call coaching within minutes back to the practice. That gives the dental practice team the relevant information it needs to follow up with the potential patient, address the caller’s concerns with effective phrasing, and convert the caller into a booked appointment.
It also provides key insights into the calls, including call volume, voicemail, and on-hold data which can influence phone coverage and staffing decisions. Plus, dentists can use the powerful keyword data cross-referenced with booking percentages and revenue opportunity to determine whether to adjust hours, services, or insurance carriers to better meet the needs of their patient base.
Using Natural Language Processing for Sales Enablement & ROI
In sales terms, this is called sales enablement. It gives the dental team the resources it needs to book more appointments by providing the right content, knowledge, information and tools when they need it.
Most dentists don’t think of their front desk team or their call center agents as sales people or of their patients as customers. But sales is simply the exchange of money for goods, services, or something else of value. A first-class salesperson enables this to happen by answering questions the consumer may have and helping them receive the goods or services they need.
Natural Language Processing technology enables the call-handling team to immediately identify patterns and improve customer service skills. It teaches the dental team members how to create better rapport with callers, how to build trust, and how to gently overcome objections about cost, insurance, and other obstacles to patient care. Through sales enablement and rapid call coaching, dental practices increase the number of scheduled patients and patient revenue.
That, in turn, increases return on investment. Dentists spend money on marketing to attract patients. Patient Prism converts those callers into booked appointments. When a dentist spends the same amount of money on marketing, but now schedules more appointments, it lowers the customer acquisition cost (CAC) and increases return on investment (ROI).
And when the dental team has the customer service skills to wow its patients from the first phone call through the entire patient visit, it increases the likelihood that patient will return to the practice in the future. That increases the Customer Lifetime Value (LTV). The typical patient stays with a practice for just under six years, and has about 11.76 visits, according to an article in Dentistry Today. To determine the Customer Lifetime Value of a patient in dollars, multiply the number of visits by the average production per visit by the collection rate.
What Is the Future of Natural Language Processing in Dentistry and Healthcare?
The power of natural language processing lies in analyzing what has happened and using that data to make predictions about what will happen in the future.
Using call data as an example, natural language processing can determine why a potential patient did not schedule and provide fast insights into what a team member should say during a follow up call to win them back.
Call data analytics will also show which team members are best at call conversion and which need more training. By identifying customer service issues quickly and fixing them, the practice provides a better patient experience.
And through conversation keyword analytics, dental practices can identify operational changes, such as the potential to expand hours, services, or insurance carriers to meet the needs of their community.
Natural Language Processing also has powerful potential for improving patient care and customer service during the office visit. Voice-activated commands allow dentists to pull up patient charts, radiographs, and images without having to use their hands. They’ll be able to have the computer run diagnostics and probabilities without having to type in the requests. And they’ll be able to speak and have their notes transcribed directly into the patient electronic health record.
Natural Language Processing is just one component of artificial intelligence. The power is in the data analytics that use advanced algorithms to predict future outcomes based on data patterns. This will be an incredible decade for healthcare breakthroughs.
Written by Amol Nirgudkar, Founder & CEO, Patient Prism
As a certified public accountant, business consultant, author, entrepreneur, and former owner of several dental practices, he has 20 years of experience working with dental practices, both large and small. He founded Patient Prism in 2015. The service uses both A.I. and American call coaches to evaluate the way dental offices handle phone calls, identify the callers that didn’t schedule, and teach the team how to win them back – all within 30 minutes of the failed call. Amol co-invented the patented technologies used in Patient Prism. One eliminates the need to listen to recorded phone calls by providing the information visually. The other technology details specific words spoken by the patient during the call so dentists and managers know which services callers are requesting and the revenue opportunity associated with each call. Amol continues to work with artificial intelligence and machine learning to empower dental teams to deliver a better patient experience and build even more successful practices.
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