How Can Conversational AI Help the Healthcare Industry?

Conversational AI

New and improved Artificial Intelligence (AI) techniques are the result of rapid growth in computing abilities that enable machines to learn with least human supervision. Particularly in the healthcare industry that is ripe with so many use cases of AI, there is significant headroom for growth.

As per WHO statistics, the world is facing a shortage of 4.3 million doctors, nurses, and other healthcare staff. India, being a part of this existential crisis, is running short of 0.6 million doctors and 2 million nurses, according to estimates. While these numbers forewarn about the loss of quality of healthcare, there is emerging technology bringing more light to the world’s crippling shortage of physicians.

From ancient syringes to the advanced telemedicine of today, healthcare technology has come a long way and has conversational AI as a part of the next exciting developments. It is geared up to redefine the healthcare industry’s bottom lines. As per Accenture’s analysis on this subject, the key clinical healthcare AI applications have the potential to create annual savings of $150 billion by 2026 for the U.S. healthcare economy.

With correct implementation, conversation AI systems can have an enormous impact on the healthcare industry. If you are wondering about the potential of this technology and how it can save the beleaguered healthcare economy, this complete guide to conversation AI for the healthcare industry is meant for you.

What is Conversational AI?

In technical terms, conversational AI is a type of AI that has been designed to enable consumers to interact with human-like computer applications. Primarily, it has taken the form of advanced-level chatbots to enhance the experience of interacting with traditional voice assistants and virtual agents.

A conversational AI-based chatbot can answer FAQs and help troubleshoot common issues contrary to the limited capabilities of a conventional chatbot. 

Here, it is important to highlight the fact that conversational AI is not just a chatbot, though these terms are often used interchangeably. On one hand, chatbots are applications that simply automate chats and provide an instant response to a user without the need for human intervention. Not all chatbots make use of AI and only have scripted, predefined responses that deliver answers to specific questions via rule-based programming.

On the other hand, conversational AI-based chatbots utilize advanced automation, AI, and Natural Language Processing (NLP) to make applications capable of responding to human language. Conversational AI is primed to make a significant impact in the healthcare industry when implemented the right way. It can also improve operational efficiency and patient outcomes while making the lives of healthcare professionals easier.

Now that you have gone through the fundamentals of conversational AI, let’s talk more about its specific use cases.

Top 10 Use Cases of Conversational AI in the Healthcare Industry

Conversational AI

1. FAQ Resolution

Many patients ask pressing questions that require immediate response without demanding the attention of a healthcare professional. The answers to these FAQs, if delivered via a self-service knowledge base, can satisfy frequent queries. A research study on customer experience confirms that 92% of consumers would prefer using a knowledge base for self-support if available.

Conversational AI has turned into an optimal self-service method for the healthcare industry. It helps overcome typical FAQ challenges for medical professionals. For example, many users find it difficult to search for relevant answers via the search function on websites if their queries do not involve the same terminology as in existing FAQs. An intelligent conversational interface backed by AI can solve this problem and deliver engaging responses to the users.

2. Appointment Scheduling

Next to answering patients’ queries, appointment management is one of the most challenging yet critical operations for a healthcare facility. While it is easy to find appointment scheduling software, they are quite inflexible, leading patients to avoid using them in favor of scheduling an appointment via a phone call.

Conversational AI can wave its magic wand to overcome this challenge. It allows patients to schedule appointments without feeling frustrated to use a complicated interface. In addition, they can also reschedule or cancel appointments easily if needed to eliminate the risk of scheduling conflicts.

3. Health Tracking

Another significant transformation in healthcare via conversational AI is related to tracking patients’ health. For many patients, visiting a doctor simply means a lack of control over the self while facing severe symptoms because of an underlying health problem. Other than the in-person consultation with health experts, what they need is easy access to information and tools to take control of their health.

Conversational AI systems tend to alleviate this issue by helping patients to track their progress toward personal health goals. They can also deliver specific information about specific actions to be taken to meet those goals, hence prompting patients to feel engaged.

4. Symptom Checking

While we live in an Internet-backed world with easy access to information of all sorts, we are unable to get personalized healthcare advice with just an online search for medical information. This is where conversational AI tools can be put to use to check symptoms and suggest a step-by-step diagnosis. It can lead a patient through a series of questions in a logical sequence to understand their condition that may require immediate escalation. At times, getting an accurate diagnosis following appointment scheduling is what a patient needs for further review.

Besides this, conversational AI is more flexible than conventional chatbot and will not come up with a blank response if the symptom descriptions vary between users.

5. Automation of Administrative Tasks

Various administrative tasks are handled in healthcare facilities on a daily basis, most of which are carried out inefficiently. For example, medical staff members have to search for countless patient forms and switch between applications, resulting in loss of time and frustration.

An intelligent Ai-based platform can simplify the process at both ends. On the side of medical staff, employees can send updates, submit requests, and track status within one system in the form of conversation. On the other hand, the same system can be used to streamline the patient onboarding process and guide them through the process in an easy way.

6. Patients Insights

In layman’s terms, data is the lifeblood of AI systems. For both text-based and voice-based systems, it is the data that empowers the underlying engine to deliver a satisfactory response. Basically, conversational AI platforms collect and track patients’ data at scale. The information also acts as a goldmine for valuable insights that healthcare service providers can utilise to improve the quality of care offered and the overall patient experience.

Example – an AI system logs frequent instances of attempts made to book appointments with a pediatrician in a certain timeframe. Detailed analysis of this data may reveal the lack of enough pediatricians in the facility which  calls for hiring these professionals to meet the demand.

7. Internal Coordination

These days, healthcare professionals are over-stretched at work and have to deal with hundreds of tasks when at work. But sometimes, technology makes things more complicated for them and results in costly errors than helping them as expected.

With the help of conversational AI, medical staff can access various types of information, such as prescriptions, appointments, and lab reports with a few keystrokes. This helps save significant time and frees them to focus on more critical tasks. Since the team members can access the information they need via the systems, it also reduces interdependence between teams.

8. Post-treatment Care

Patients often undergo periodic checkups with a doctor for post-treatment recovery consultation. However, if they fail to understand instructions in their post-care plan, it can worsen their recovery and may have side effects on health. This is where they need a system that can bridge the communication gap and support them during recovery.

A conversational AI system can come in handy for such needs. For instance, it can issue reminders for critical actions to patients after they have submitted the details of post-care actions followed. Similarly, it can alert the concerned doctor if the need arises.

9. Dissemination of Health Information/Advisory

The worldwide pandemic has made us all realise the fact that misinformation spreads even faster than a virus and can cause real damage to people. To control the spread, conversational AI can be of great help.

This technology has the potential to combat the spread of inaccurate health information in several ways. Example – in case of a public health crisis like the Covid-19, such a system can disseminate recommended advice about washing hands, social distancing, and covering face with masks. It can also advise patients about when to visit a healthcare facility and how to manage their symptoms.

10. Employee Hiring/Training

Healthcare facilities, whether small or big, regularly hire new employees and follow the onboarding process. This involves double-checking their credentials and handling paperwork related to the applications received. With AI-powered chatbots, the job of the HR team in these facilities can become easier. They can use these bots to ask the recruits to subscribe to a channel to get access to information about the organisation. Similarly, the bots can automate sending forms to the recruits for easy onboarding.

Things to Consider Before Using Conversational AI

While conversational AI is highly advantageous, its implementation is no walkover. Its inaccurate implementation can strike many wrong chords. Hence, it is important to consider the following three aspects:

Conversational AI

1. Integration

Conversational AI’s backend is responsible for funneling dialogues and capturing contextual information. It requires an articulated integration model that can empower the contextual capabilities of virtual assistants.

2. Security and Compliance

Conversational AI implementation requires organisations to comply with various data regulations and data security guidelines.

3. Change Management

It also requires transparent communication to consumers interacting with the AI chatbots and employees for swift technology adoption.

Step Into the Future of Healthcare with Ameyo’s Customer Experience AI

Amidst the deepening healthcare crisis, conversational AI brings with it an avenue for change. From helping patients get quality care on time to easing the workload of medical professionals, there are endless possibilities to explore. Join hands with Ameyo for our hi-tech customer experience AI platform that is future-ready to deliver personalized customer service. To know more about its features, click here.

Nishant Kadian

Nishant Kadian takes care of the inbound and content marketing team at Ameyo. He finds enthusiasm in learning and writing about technologies that are transforming customer engagement through contact centers. Drop your hellos to have a nerdy marketing discussion or to throw a challenge for a chess game.