Chatbots in Healthcare: Top 6 Use Cases & Examples in 2023

Automating your marketing campaigns can free up time for your team to focus on other tasks. And by personalizing your messages, you can increase conversion rates and improve the customer experience. You can also inform customers about upcoming events like Q&As or webinars through chatbots.

We identified 3 new chatbots that focused on vaccination, bringing our final sample to 61 chatbots and resulting in 1 additional use-case category and 1 new use case. Chatbots that use analytics and natural language processing can get to know your audience pretty well. This means they’ll be able to identify personalized services to best suit each policyholder and recommend them directly, helping generate leads or upsell opportunities. Despite these benefits, just 49 percent of banking and insurance companies have implemented chat assistants (only 17 percent when it comes to voice assistants).

Healthcare Chatbot Use Cases

Healthcare chatbot algorithms are upskilled on extensive healthcare and medical data, including disease indicators, markers, diagnostics, and available treatments. Public datasets are utilized to upgrade the machine learning of the chatbots constantly. This helps the conversational chatbots with different intelligence levels understand the user’s queries and provide responses based on the pre-defined label in the machine-fed data. They can understand and respond to natural language, making them a powerful tool for engaging with patients.

This automation results in better team coordination while decreasing delays due to interdependence among teams. Daunting numbers and razor-thin margins have forced health systems to do more with less. Many are finding that adding an automation component to the innovation strategy can be a game-changer by cost-effectively improving operations throughout the organization to the benefit of both staff and patients. Embracing new technologies – such as robotic process automation enabled with chatbots – is key to achieving the interdependent goals of reducing costs and serving patients better.

Collecting patients’ data is one of the healthcare chatbot use cases.

A voice bot that has been programmed to answer your FAQs can do so independently. A step further, speech AI is being used to manage patient data, automate procedures, and lessen paperwork. Voice Bots are assisting in the creation of a unified online healthcare ecosystem, and not simply in terms of physical health. Chatbots can also assist with internal communication, which helps different departments work in unison.

If they required medical care when they were in a completely different region of the country (or possibly the entire world). It might be very inconvenient to wait in line at a hospital to schedule and pay for medical consultations. “Since all physicians may not be familiar with the latest guidance and have their own biases, these models have the potential to steer physicians toward biased decision-making,” the Stanford study noted. Most people are caught up in their everyday lives and forget to take medicines on time.

Identifying symptoms – WhatsApp chatbots in healthcare

Chatbot has essential functionality for telehealth app development and is utilized for remote prescriptions and renewal. To refill the prescription, a patient types a quick request into the chat window. The most significant issue in the healthcare sector is that therapists will mostly ask for previous documents when they again visit the doctor to see their improvement in diagnosis.

At ScienceSoft, we know that many healthcare providers doubt the reliability of medical chatbots when it comes to high-risk actions (therapy delivery, medication prescription, etc.). With each iteration, the chatbot gets trained more thoroughly and receives more autonomy in its actions. For example, on the first stage, the chatbot only collects data (e.g., a prescription renewal request).

In some cases, they appeared to reinforce long-held false beliefs about biological differences between Black and white people that experts have spent years trying to eradicate from medical institutions. This also gave medical practitioners access to all the important information (frequency and severity) they needed before connecting with the patients. Offering them interesting and personalized interactions can revolutionize the patient experience. Additionally, they presumably spend around 30 minutes every day reminding patients by the hand of their impending appointments. The workload brought on by substantial medical documentation including pathology reports, x-rays, and scans can be lessened by these hybrid automation systems. ● Keep track of the patient’s symptoms using an accurate medical history as a guide.

• The majority of our chatbots focused on risk assessment or information dissemination and about half involved multiple use cases, mostly combining risk assessment and information dissemination together or with other use cases.
• Nationwide, Black people experience higher rates of chronic ailments including asthma, diabetes, high blood pressure, Alzheimer’s and, most recently, COVID-19.
• Moreover, though many chatbots leveraged risk-assessment criteria from official sources (e.g., CDC), there was variability in criteria across chatbots.
• Once more, these chatbots serve to automate straightforward patient inquiries that do not require a healthcare provider’s attention and do not attempt to replace healthcare providers.

Based on the information they provided, we identified 7 use cases for information dissemination (see Figure 2). While many chatbots leverage risk-assessment criteria from official sources (WHO, CDC, or other government health agency), the questions asked vary significantly across chatbots, and as does the order in which they are asked. Some ask general questions about exposure and symptoms (e.g., Case 7), whereas others also check for preexisting conditions to assess high-risk users (e.g., Case 1). Based on the assessed risk, the chatbot makes behavioral recommendations (e.g., self-monitor, quarantine, etc.).

The proven chatbot use cases we have explored demonstrate the significant impact these AI-driven tools can have on businesses and organizations. From enhancing customer service to optimizing sales and streamlining various processes, chatbots have shown their ability to deliver efficient and personalized results. As technology continues to evolve and businesses recognize the value of chatbots, their popularity is predicted to rise even further.

In fact, Haptik has worked with several healthcare brands to implement such solutions – one of the most successful examples being our work with a leading diagnostics chain, Dr. LalPathLabs. Conversational AI, on the other hand, allows patients to schedule their healthcare appointments seamlessly, and even reschedule or cancel them. Fundamentally, scheduled appointments help reduce patient wait times and improve satisfaction. Healthcare organizations are able to manage healthcare information by utilizing technology like electronic health records (EHR) and healthcare CRMs, along with existing data management tools such as Revenue cycle management (RCM). WhatsApp chatbots to send diet plans to your customers who are looking for suggestions. Stay ahead of the curve with an intelligent AI chatbot for patients or medical staff.

Machine learning can detect when there is unusual traffic visiting a website and recognize the warning signs. A chatbot can warn a customer or a company agent before a cyber attack takes place. For instance, Freshchat helped Klarna achieve a first response time of just 60 seconds by increasing how many users were serviced via chat, thereby decreasing the pressure on phone support. For example, you can send a customer who’s just purchased a pair of jeans a message that says, “Hey! You might also like this product.” And include a link to a top that pairs well with the jeans.

In 2023, businesses may need to embrace not only text chatbots but also voice assistants due to their increasing popularity. Projections indicate that the number of voice chatbots is expected to exceed 8 billion by 2023. The investments start from $70,000 for a relatively simple solution (e.g., providing information support, online scheduling) to $250,000 for a complex AI chatbot (e.g., with advanced clinical decision support functionality). Taking the lead in AI projects since 1989, ScienceSoft’s experienced teams identified challenges when developing medical chatbots and worked out the ways to resolve them. ScienceSoft’s software engineers and data scientists prioritize the reliability and safety of medical chatbots and use the following technologies. To accelerate care delivery, a chatbot can collect required patient data (e.g., address, symptoms, insurance details) and keep this information in EHR.

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