Healthcare Chatbots: Benefits, Use Cases, and Top Tools

• susanti
• May 15, 2025
• 0

Why Chatbots are Healthcare’s Future: Insights

To do that, the application must employ NLP algorithms and have the latest knowledge base to draw insights. Most chatbots (we are not talking about AI-based ones) are rather simple and their main goal is to answer common questions. Hence, when a patient starts asking about a rare condition or names symptoms that a bot was not trained to recognize, it leads to frustration on both sides. A bot doesn’t have an answer and a patient is confused and annoyed as they didn’t get help. So in case you have a simple bot and don’t want your patients to complain about its insufficient knowledge, either invest in a smarter bot or simply add an option to connect with a medical professional for more in-depth advice. These mental health bots ensure the mental wellness of the users by providing a humanized experience during the conversations.

In this article, we shall focus on the NLU component and how you can use Rasa NLU to build contextual chatbots. Rasa NLU is an open-source library for natural language understanding used for intent classification, response generation and retrieval, entity extraction in designing chatbot conversations. Rasa’s NLU component used to be separate but merged with Rasa Core into a single framework. Healthcare chatbot development can be a real challenge for someone with no experience in the field.

How Healthcare Chatbots are Expanding Automated Medical Care

And while these tools’ rise in popularity can be accredited to the very nature of the COVID-19 pandemic, AI’s role in healthcare has been growing steadily on its own for years — and that’s anticipated to continue. Dr. Liji Thomas is an OB-GYN, who graduated from the Government Medical College, University of Calicut, Kerala, in 2001. Liji practiced as a full-time consultant in obstetrics/gynecology in a private hospital for a few years following chatbots in healthcare industry her graduation. She has counseled hundreds of patients facing issues from pregnancy-related problems and infertility, and has been in charge of over 2,000 deliveries, striving always to achieve a normal delivery rather than operative. One particular chatbot is trying to remedy it by offering a different kind of cognitive behavior therapy (CBT). You can download Woebot on any popular app store to begin chatting with the helpful therapy bot.

• These virtual assistants can provide real-time, personalized advice to people with chronic conditions and offer support for those dealing with tough symptoms or mental health issues.
• However, these kinds of quantitative methods omitted the complex social, ethical and political issues that chatbots bring with them to health care.
• In practice, however, clinicians make diagnoses in a more complex manner, which they are rarely able to analyse logically (Banerjee et al. 2009).
• What’s more interesting about this company’s app is that they’re planning to partner with healthcare payers and insurance providers.
• Table 1 presents an overview of other characteristics and features of included apps.
• This bot is similar to a conversational one but is much simpler as its main goal is to provide answers to frequently asked questions.

This means that hospitals could leverage digital humans as health assistants, capable of providing empathetic, around-the-clock aid to patients, particularly before or after their surgery. Now more than ever, patients find themselves relying on a digital-first approach to healthcare — an arrangement that, at first, might not involve a human on the other end of the exchange. Medical (social) chatbots can interact with patients who are prone to anxiety, depression and loneliness, allowing them to share their emotional issues without fear of being judged, and providing good advice as well as simple company. This would save physical resources, manpower, money and effort while accomplishing screening efficiently.

Top 10 Insurance Chatbots Applications & Use Cases in 2024

Chatbots can handle a large volume of patient inquiries, reducing the workload of healthcare professionals and allowing them to focus on more complex tasks. This increased efficiency can result in better patient outcomes and a higher quality of care. As such, there are concerns about how chatbots collect, store, and use patient data. Healthcare providers must ensure that privacy laws and ethical standards handle patient data. Through chatbots (and their technical functions), we can have only a very limited view of medical knowledge.

An effective UI aims to bring chatbot interactions to a natural conversation as close as possible. And this involves arranging design elements in simple patterns to make navigation easy and comfortable. Some of these platforms, e.g., Telegram, also provide custom keyboards with predefined reply buttons to make the conversation seamless. All these platforms, except for Slack, provide a Quick Reply as a suggested action that disappears once clicked. Users choose quick replies to ask for a location, address, email, or simply to end the conversation.

First, we introduce health chatbots and their historical background and clarify their technical capabilities to support the work of healthcare professionals. Second, we consider how the implementation of chatbots amplifies the project of rationality and automation in professional work as well as changes in decision-making based on epistemic probability. We then discuss ethical and social issues relating to health chatbots from the perspective of professional ethics by considering professional-patient relations and the changing position of these stakeholders on health and medical assessments. We stress here that our intention is not to provide empirical evidence for or against chatbots in health care; it is to advance discussions of professional ethics in the context of novel technologies. Chatbots use software that applies AI to process language from interactions between humans and virtual assistants.

Machine learning (ML) is a subset of AI that improves its performance based on the data provided to a generic algorithm from experience rather than defining rules in traditional approaches [1]. Advancements in ML have provided benefits in terms of accuracy, decision-making, quick processing, cost-effectiveness, and handling of complex data [2]. Chatbots, also known as chatter robots, smart bots, conversational agents, digital assistants, or intellectual agents, are prime examples of AI systems that have evolved from ML.

Future of Chatbots in Healthcare

The bot can also collect the information automatically – though in this case, you will need to make sure that your data privacy policy is visible and clear for users. In this way, a chatbot serves as a great source of patients data, thus helping healthcare organizations create more accurate and detailed patient histories and select the most suitable treatment plans. With the ability to assess symptoms and offer preliminary guidance, these chatbots reduce administrative burdens and enhance patient care efficiency. Furthermore, Chat360’s chatbots facilitate secure communication for telehealth appointments, ensuring a seamless and confidential experience. One example of using AI chatbots in healthcare is the use of a chatbot on Facebook Messenger.

In September 2020, the THL released the mobile contact tracing app Koronavilkku,1 which can collaborate with Omaolo by sharing information and informing the app of positive test cases (THL 2020, p. 14). Healthbots are computer programs that mimic conversation with users using text or spoken language9. The advent of such technology has created a novel way to improve person-centered healthcare.

Despite limitations in access to smartphones and 3G connectivity, our review highlights the growing use of chatbot apps in low- and middle-income countries. Additionally, such bots also play an important role in providing counselling and social support to individuals who might suffer from conditions that may be stigmatized or have a shortage of skilled healthcare providers. Many of the apps reviewed were focused on mental health, as was seen in other reviews of health chatbots9,27,30,33. With the adoption of the chatbots among the doctors, patients, nurses and hospitals, in the coming years, the healthcare industry is expected to scale significant growth. Many experts have emphasised that chatbots are not sufficiently mature to be able to technically diagnose patient conditions or replace the judgements of health professionals.