The Top 9 Use Cases for Conversational AI in Healthcare
New tools and technology have always played an enormous role in medicine. From the artificial leeches, ancient syringes, and shiver-inducing trepanning devices of the past to the advanced telemedicine and robotic surgeries of today, medical technology has definitely come a long way. One of the more exciting new developments is the emergence of artificial intelligence systems like conversational AI for healthcare.
It should come as no surprise that AI is taking the world by storm, transforming the way we live and work, and healthcare is no exception. In fact, a report by Accenture found that a whopping 40% of executives consider AI to be the technology that will have the greatest impact on their organizations within the next three years.
But what about conversational AI? And what impact will it have on the future of healthcare?
What is Conversational AI for Healthcare?
Firstly, it’s important to establish that conversational AI is not a chatbot. The terms chatbot, virtual assistant, and conversational AI are often used interchangeably and while it's true they are all related, they're not all created equal. For example, chatbots are simply applications that automate chats. This means a user can ask the chatbot a question and receive an instant reply without the need for a human to intervene. However, chatbots don't have to involve artificial intelligence, and many of them don't. In fact, most of today's chatbots use scripted, pre-defined responses and rule-based programming to deliver simple answers to a specific set of questions.
In other words, chatbots tend to be clunky and rarely fool anyone into thinking they're talking to an actual human.
So then, what is true conversational AI? For the first time in history, we finally have the computing power, storage capabilities, and technological maturity to create cost-efficient and human-like conversational experiences with machines. Conversational AI utilizes advanced automation, artificial intelligence, and natural language processing (NLP) to make machines capable of understanding and responding to human language. Think of it as the brain behind the chat window — like a human brain, it has the flexibility, processing power, and learning ability to engage in complex conversation.
Conversational AI is primed to create a massive impact in the healthcare industry, and in many places, it's already doing just that. When implemented in the right way, conversational AI can improve operational efficiencies, patient outcomes, and make life easier for healthcare professionals.
With this in mind, let's look at some of the top use cases for conversational AI in healthcare.
The Top 9 Use Cases of Conversational AI In Healthcare
1. Answering Frequently Asked Questions (FAQ)
"How do I access my medical records?"
"What time does the clinic open?"
"How does electronic prescribing work?"
Patients often have pressing questions that require immediate answers but don't necessarily demand the attention of a staff member. The good news for personnel-strapped healthcare organizations is that most customers actually prefer self-service over speaking to a person. According to Zendesk, a whopping 91% of customers would use an online knowledge base if one were available and personalized to their needs.
Conversational AI is the optimal method of self-service in healthcare because it overcomes many of the typical challenges of FAQ sections on healthcare providers’ websites. For example, using the website search function, users might struggle to find the most relevant answer to their question because they aren't using the exact same terminology as the FAQ. Alternatively, they may have several questions that would involve navigating to multiple pages.
Intelligent conversational interfaces solve this problem by using NLP to deliver engaging responses to any question without forcing the patient to look elsewhere. Additionally, conversational AI is capable of matching the correct answer to a question even if the way it is asked does not correlate with the exact terminology on-site and varies significantly between users.
2. Appointment Scheduling
Managing appointments is one of the most taxing but critical operations in a healthcare facility. And while appointment scheduling systems are now commonplace, they are often inflexible and unintuitive, leading many patients to dismiss them in favor of calling the healthcare facility.
By contrast, conversational AI systems allow patients to schedule appointments easily without the frustrations of a complicated user interface. Patients can seamlessly book an appointment with their preferred provider or reschedule or cancel an existing appointment. In addition, advanced AI platforms can integrate with other key applications and informational systems so appointments are updated in real-time, eliminating any risk of frustrating scheduling conflicts.
Beyond simply booking, rescheduling, or canceling appointments, conversational AI can also deliver appointment reminders and other crucial information, like whether a patient needs to bring specific documents with them to the appointment or if they will need to bring someone to assist them following a procedure.
3. Symptom Checking and Medical Triaging
Picture the scene: you feel a headache coming on and some achiness in your bones. You know that something is amiss but aren’t quite sure what the problem could be. Smartphone in hand, you take to Google to search for the cause of your malaise, only to come away alarmed at the results that you find.
In other words, the internet is an excellent source of medical information, but it doesn't offer personalized advice.
Conversational AI can be applied for symptom checking and medical triaging, assigning the priority of care as needed. Such systems can be used as step-by-step diagnosis tools, leading the customer through a series of questions and allowing them to input their symptoms in a logical sequence. Some symptoms may point to something serious that requires immediate escalation, but often it's a matter of getting a quick and accurate diagnosis or scheduling an appointment for further review.
Conversational AI systems don't suffer from the same drawbacks in this area that traditional chatbots do. For example, a conventional chatbot might come up blank if symptom descriptions or medical terminology vary between users. For instance, one patient might use the word "flu" but go on to describe the symptoms of a common cold. Additionally, non-native speakers might not know the correct medical terminology for specific body parts or symptoms. Conversational AI is much more flexible in these situations, drawing on a vast bank of data and information resources to avoid diagnostic errors.
According to Accenture’s report on artificial intelligence in healthcare, the current physician shortage is expected to double in the next decade. So, while conversational AI platforms cannot and should not replace doctors, they can offer relief amid the rising labor shortage in the industry.
4. Health Tracking
One of the primary ways AI is transforming healthcare is in its ability to promote patient agency. Visiting a doctor can be a nerve-wracking experience — people often feel anxious about their symptoms and experience a lack of control being at the mercy of healthcare professionals.
Conversational AI can help alleviate this issue by providing the information and tools patients need to take control of their health. One such example is health tracking. Patients can use conversational AI systems to track follow their progress towards their personal health goals, such as body weight, mood, or fertility in addition to requesting specific information, like what specific actions they should be taking to meet their goals or when they need to take their medication. These systems can also prompt users to perform certain actions or issue important reminders to ensure patients stay engaged and motivated in the process.
5. Automation of Administrative Tasks
There are an endless number of administrative tasks that need to happen in healthcare facilities on a daily basis and while they do ultimately get done, they are not always carried out efficiently. For example, employees often have to switch between different applications, search for countless forms, or chase down various departments just to do their jobs, resulting in wasted time, not to mention significant frustration.
An intelligent conversational AI platform can simplify this process by allowing employees to submit requests, send updates, and track statuses, all within the same system and in the form of a natural conversation.
On the patient side, conversational AI can automate and streamline the onboarding process, guide them through requesting prescriptions, allow them to update important information like their address or a change in circumstances, and much more.
6. Invaluable Patient Insights
Say it with us folks: data, data, data. Data is the lifeblood of AI. Whether we're talking text-based or voice AI, it's data that powers the conversational AI engine and makes things happen.
By nature, conversational AI systems constantly collect and track patient mountains of patient data. That information represents a veritable gold mine of invaluable insights for healthcare providers that can be used to help make better decisions that further improve the patient experience and quality of care.
For example, let's say the conversational AI system logs many instances of patients attempting to book appointments with podiatrists but are struggling to do so in a reasonable timeframe. An analysis of the data would reveal this recurring pattern and the healthcare organization can then deduce that they may need to hire more podiatrists to meet patient demand.
Personnel decisions aside, this approach can also apply to medical assets. For instance, the AI system might flag that medical imaging equipment like X-ray, CT, and MRI machines are frequently booked up with long wait times. This could then prompt the organization to prioritize investing in more of these assets.
In addition, by tracking and analyzing how patients interact with the conversational AI system, health providers can easily address any gaps in care. The questions patients ask can tell you a lot about their medical literacy level, whether they find some aspects of visiting the clinic confusing, and so on. This can help inform what type of information you need to deliver front and center to patients and what may be missing to help make their experiences more rewarding and informative.
7. Internal Coordination
Gartner estimates that by 2022, 70% of professionals will interact with conversational platforms every day. But what could this interaction look like for healthcare workers?
Today, healthcare professionals are stretched thin, often having hundreds of tasks to complete before they’ve even had their morning coffee. Unfortunately, rather than helping as it was intended, technology can sometimes stand in the way of getting tasks done, leading to delays and costly errors.
With conversational AI, staff can access a wide range of information, such as lab reports, prescribed medications, and upcoming appointments, with just a few keystrokes. This saves a significant amount of time and frees medical workers up to focus on other more critical tasks. More importantly, it also reduces the interdependence among teams, as staff members can access the information they require immediately without contacting different areas of the organization and waiting for an answer.
Additionally, providers can use conversational AI for internal record-keeping, such as keeping track of medical assets like beds, wheelchairs, otoscopes, blood pressure cuffs, MRI machines, and more.
8. Patient Engagement and Post-Treatment Care
The number of interactions patients have with healthcare professionals can vary greatly depending on their treatment stage. For example, patients in post-treatment (say, following a surgery) may have periodic check-ups with a doctor, but otherwise, they are responsible for following their post-treatment plan.
But, if the patient misunderstands an instruction in the post-care plan or forgets to perform certain activities, it can worsen their recovery outcomes. A conversational AI system can help bridge that communication gap and support patients in their recovery process. For example, the patient could submit details about what post-care actions they have performed and where they are in their treatment plan. In turn, the system could issue reminders for critical actions and alert a physician if needed.
9. Public Health Information Dissemination
One key lesson that came out of the COVID-19 pandemic is that the only thing that spreads faster than a virus is misinformation. However, even without the looming threat of a pandemic, false health information can cause real damage to people and communities.
Conversational AI has the potential to play a prominent role in combating inaccurate health information in multiple ways. For example, in the event of a public health crisis like COVID-19, a conversational AI system can disseminate recommended advice like washing your hands for 20 seconds, how to social distance, and when to wear a face covering. It can also advise when someone needs to visit a healthcare facility and when they should self-isolate, as well as how to manage their symptoms. Advanced conversational AI systems also update in tandem with the latest guidelines, ensuring that the advice is always in line with the latest science and best practices.
What Does the Future of Conversational AI in Healthcare Look Like?
Conversational AI is poised to play a critical role in the future of healthcare, eventually becoming a ubiquitous tool for improving the patient experience. But of course, progress only happens with continuous refinement. Rome certainly wasn't built in a day, but they were laying bricks every hour.
At Hyro, we're constantly working to build the most sophisticated conversational AI solutions to allow organizations to retire clumsy and awkward chatbots. One area we are keenly focused on is Natural Language Understanding (NLU), a branch of NLP concerned with how computers understand text.
By channeling time and energy into NLU, Hyro creates conversational AI for healthcare that is user-friendly and aligned with how people actually communicate. For example, in a conversation with a human, you wouldn't expect to get asked a question like "which of the following 30 symptoms do you have?" — that would be both taxing and off-putting. Likewise, we believe people shouldn't expect questions like that from bots either.
Novel technologies like conversational AI are excellent benefactors for facilitating progress in healthcare — they promote accessibility and enable personalized experiences for patients and providers alike. As the underlying technology continues to advance to increasingly sophisticated levels, benefits will multiply and use cases will continue to expand.