AI Chatbots in Healthcare Examples + Development Guide

AI Powered Chatbots In Healthcare: Use Cases, Pros And Cons

chatbot in healthcare

If you’re interested in learning about all the benefits of healthcare chatbots, keep on reading through to the next section. Our team of experienced developers and consultants have the skills and knowledge necessary to develop tailored applications that match your needs. With a greater reliance on technology for patient care, there is potential for errors or misunderstandings that could lead to misdiagnoses or incorrect treatments.

While challenges exist in fully understanding complex emotions, technological advancements promise to revolutionize mental healthcare delivery and provide effective support to individuals seeking help. The domain is further bolstered by product launches from key players and the integration of chatbots with other digital health platforms, paving chatbot in healthcare the way for a more comprehensive and personalized approach to mental healthcare delivery. You can foun additiona information about ai customer service and artificial intelligence and NLP. Healthcare chatbots streamline the appointment scheduling process, providing patients with a convenient way to book, reschedule, or cancel appointments. This not only optimizes time for healthcare providers but also elevates the overall patient experience.

Data synthesis

However, there are different levels of maturity to a conversational chatbot – not all of them offer the same depth of conversation. Informative chatbots provide helpful information for users, often in the form of pop-ups, notifications, and breaking stories. Furthermore, hospitals and private clinics use medical chat bots to triage and clerk patients even before they come into the consulting room.

For instance, in the case of a digital health tool called Buoy or the chatbot platform Omaolo, users enter their symptoms and receive recommendations for care options. Both chatbots have algorithms that calculate input data and become increasingly smarter when people use the respective platforms. The increasing use of bots in health care—and AI in general—can be attributed to, for example, advances in machine learning (ML) and increases in text-based interaction (e.g. messaging, social media, etc.) (Nordheim et al. 2019, p. 5).

chatbot in healthcare

Although not specifically an oncology app, another chatbot example for clinicians’ use is the chatbot Safedrugbot (Safe In Breastfeeding) [69]. This is a chat messaging service for health professionals offering assistance with appropriate drug use information during breastfeeding. Promising progress has also been made in using AI for radiotherapy to reduce the workload of radiation staff or identify at-risk patients by collecting outcomes before and after treatment [70]. An ideal chatbot for health care professionals’ use would be able to accurately detect diseases and provide the proper course of recommendations, which are functions currently limited by time and budgetary constraints.

Implement encryption protocols for secure data transmission and stringent access controls to regulate data access. Regularly update the chatbot based on advancements in medical knowledge to enhance its efficiency. This integration streamlines administrative tasks, reducing the risk of data input errors and improving overall workflow efficiency. Chatbots in health care may have the potential to provide patients with access to immediate medical information, recommend diagnoses at the first sign of illness, or connect patients with suitable health care providers (HCPs) across their community [13,14]. Theoretically, in some instances, chatbots may be better suited to help patient needs than a human physician because they have no biological gender, age, or race and elicit no bias toward patient demographics. Chatbots do not get tired, fatigued, or sick, and they do not need to sleep; they are cost-effective to operate and can run 24 hours a day, which is especially useful for patients who may have medical concerns outside of their doctor’s operating hours.

Usage of Health Care Chatbots

Twenty of these apps (25.6%) had faulty elements such as providing irrelevant responses, frozen chats, and messages, or broken/unintelligible English. Three of the apps were not fully assessed because their healthbots were non-functional. Chatbots are a cost-effective alternative to hiring additional healthcare professionals, reducing costs. By automating routine tasks, AI bots can free up resources to be used in other areas of healthcare.

chatbot in healthcare

In most cases, it seems that chatbots have had a positive effect in precisely the same tasks performed in other industries (e.g. customer service). Hopefully, after reviewing these samples of the best healthcare chatbots above, you’ll be inspired by how your chatbot solution for the healthcare industry can enhance provider/patient experiences. The medical chatbot matches users’ inquiries against a large repository of evidence-based medical data to provide simple answers. This medical diagnosis chatbot also offers additional med info for every symptom you input. To develop a chatbot that engages and provides solutions to users, chatbot developers need to determine what types of chatbots in healthcare would most effectively achieve these goals. Therefore, two things that the chatbot developer needs to consider are the intent of the user and the best help the user needs; then, we can design the right chatbot to address these healthcare chatbot use cases.


The framework proposed as well as the insights gleaned from the review of commercially available healthbot apps will facilitate a greater understanding of how such apps should be evaluated. While chatbots offer many benefits for healthcare providers and patients, several challenges must be addressed to implement them successfully. Chatbots provide patients with a more personalized experience, making them feel more connected to their healthcare providers. Chatbots can help patients feel more comfortable and involved in their healthcare by conversationally engaging with them. When using chatbots in healthcare, it is essential to ensure that patients understand how their data will be used and are allowed to opt out if they choose.

Studies were included if they used or evaluated chatbots for the purpose of prevention or intervention and for which the evidence showed a demonstrable health impact. Chatbot becomes a vital point of communication and information gathering at unforeseeable times like a pandemic as it limits human interaction while still retaining patient engagement. Hence, it’s very likely to persist and prosper in the future of the healthcare industry. Patients appreciate that using a healthcare chatbot saves time and money, as they don’t have to commute all the way to the doctor’s clinic or the hospital. When a patient does require human intervention, watsonx Assistant uses intelligent human agent handoff capabilities to ensure patients are accurately routed to the right medical professional.

The development—especially conceptual in nature—of ADM has one of its key moments in the aftermath of World War II, that is, the era of the Cold War. America and the Soviets were both keen (in their own ways) on find ways to automatise and streamline their societies (including decision-making). This was led by people from different fields of science, who were reconceptualising human reason ‘as rationality’ (p. 29), thus creating formal models of functions and processes of biological and artificial organisms, firms, organisations and even societies.

We recommend using ready-made SDKs, libraries, and APIs to keep the chatbot development budget under control. This practice lowers the cost of building the app, but it also speeds up the time to market significantly. Another point to consider is whether your medical AI chatbot will be integrated with existing software systems and applications like EHR, telemedicine platforms, etc.

Chatbots have been implemented in remote patient monitoring for postoperative care and follow-ups. The health care sector is among the most overwhelmed by those needing continued support outside hospital settings, as most patients newly diagnosed with cancer are aged ≥65 years [72]. The integration of this application would improve patients’ quality of life and relieve the burden on health care providers through better disease management, reducing the cost of visits and allowing timely follow-ups.

The programs are offered in-school during the day, which Scott says saves instructional time and relieves parents of the cost and burden of checking their children out of school, and checking them back in. She described Kiwi as “cute as the dickens,” and said Alongside provided immediate support a student can access from a computer or mobile phone. The app includes social-emotional exercises designed by doctoral-level clinicians, self-help videos, a space for journaling and goal-setting tools, she said. The app adheres to the same privacy standards as when a student talks to a counselor or psychologist, Scott said. For the last eight months, she has been talking to an AI chatbot through the app

A brief historical overview, along with the developmental progress and design characteristics, is first introduced. The focus will be on cancer therapy, with in-depth discussions and examples of diagnosis, treatment, monitoring, patient support, workflow efficiency, and health promotion. In addition, this paper will explore the limitations and areas of concern, highlighting ethical, moral, security, technical, and regulatory standards and evaluation issues to explain the hesitancy in implementation. To facilitate this assessment, we develop and present an evaluative framework that classifies the key characteristics of healthbots. Concerns over the unknown and unintelligible “black boxes” of ML have limited the adoption of NLP-driven chatbot interventions by the medical community, despite the potential they have in increasing and improving access to healthcare.

Consequently, promoting a healthy lifestyle early on is imperative to maintain quality of life, reduce mortality, and decrease the risk of secondary cancers [87]. According to the analysis from the web directory, health promotion chatbots are the most commonly available; however, most of them are only available on a single platform. Thus, interoperability on multiple common platforms is essential for adoption by various types of users across different age groups. In addition, voice and image recognition should also be considered, as most chatbots are still text based. With the rapidly increasing applications of chatbots in health care, this section will explore several areas of development and innovation in cancer care.

These AI-powered chatbots offer 24/7 support, personalized conversations, evidence-based interventions, and psychoeducation, addressing growing mental health concerns like depression, anxiety, and stress. It is important to consider continuous learning and development when developing healthcare chatbots. The health bot uses machine learning algorithms to adapt to new data, expanding medical knowledge, and changing user needs. Integrating the chatbot with Electronic Health Records (EHR) is crucial to improving its functionality.

  • The results show a substantial increase in the interest of chatbots in the past few years, shortly before the pandemic.
  • Everyone wants a safe outlet to express their innermost fears and troubles and Woebot provides just that—a mental health ally.
  • This global experience will impact the healthcare industry’s dependence on chatbots, and might provide broad and new chatbot implementation opportunities in the future.
  • The foundation, which is working with an outside technology firm to develop the chatbot, is also considering other steps to help ensure the privacy of users.
  • Beyond cancer care, there is an increasing number of creative ways in which chatbots could be applicable to health care.

Still, it may not work for a doctor seeking information about drug dosages or adverse effects. First, the chatbot helps Peter relieve the pressure of his perceived mistake by letting him know it’s not out of the ordinary, which may restore his confidence; then, it provides useful steps to help him deal with it better. This allows doctors to process prescription refills in batch or automate them in cases where doctor intervention is not necessary.

Chatbots have been used in healthcare settings for several years, primarily in customer service roles. They were initially used to provide simple automated responses to common patient questions, such as office hours or medication refill requests. Over time, chatbots in healthcare became more sophisticated, incorporating machine learning and artificial intelligence (AI) to provide more personalized responses. Chatbots enable healthcare providers to collect this information seamlessly by asking relevant questions and recording patients’ responses.

chatbot in healthcare

Alternatively, you can develop a custom user interface and integrate an AI into a web, mobile, or desktop app. With the use of empathetic, friendly, and positive language, a chatbot can help reshape a patient’s thoughts and emotions stemming from negative places. That provides an easy way to reach potentially infected people and reduce the spread of the infection.

The United States had the highest number of total downloads (~1.9 million downloads, 12 apps), followed by India (~1.4 million downloads, 13 apps) and the Philippines (~1.25 million downloads, 4 apps). Details on the number of downloads and app across the 33 countries are available in Appendix 2. When you are ready to invest in conversational AI, you can identify the top vendors using our data-rich vendor list on voice AI or chatbot platforms.

chatbot in healthcare

This automated approach eliminates the need for manual data entry, reducing errors and saving time for both patients and healthcare professionals. One of the primary use of chatbots in healthcare is their ability to assist in triaging patients at the hospital based on their symptoms, ensuring timely care. Chatbots can act as virtual assistants, gathering information about a patient’s symptoms and providing initial recommendations from a doctor.

This would save physical resources, manpower, money and effort while accomplishing screening efficiently. The chatbots can make recommendations for care options once the users enter their symptoms. Chatbots called virtual assistants or virtual humans can handle the initial contact with patients, asking and answering the routine questions that inevitably come up. During the coronavirus disease 2019 (COVID-19) pandemic, especially, screening for this infection by asking certain questions in a certain predefined order, and thus assessing the risk of COVID-19 could save thousands of manual screenings.

These healthcare-focused solutions allow developing robust chatbots faster and reduce compliance and integration risks. Vendors like Orbita also ensure appropriate data security protections are in place to safeguard PHI. For healthcare chatbots, this comes in the form of ethical issues, data privacy, and the requirement for human oversight. This way, you don’t need to call your healthcare provider to get an appointment anymore. We’ve already discussed the role of top health chatbots, but what are their use cases? Well, you can find anything from a chatbot for medical diagnosis to chatbots for mental health support.

Although preliminary results do indicate positive effects in a number of application domains, reported findings are for the most part mixed. In the light of the huge growth in the deployment of chatbots to support public health provision, there is pressing need for research to help guide their strategic development and application [13]. We examined the evidence for the development and use of chatbots in public health to assess the current state of the field, the application domains in which chatbot uptake is the most prolific, and the ways in which chatbots are being evaluated. Reviewing current evidence, we identified some of the gaps in current knowledge and possible next steps for the development and use of chatbots for public health provision.

Meet the AI chatbot therapists filling the gaps in Europe’s mental health care shortfall – Sifted

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Use case for chatbots in oncology, with examples of current specific applications or proposed designs. All authors contributed to the assessment of the apps, and to writing of the manuscript. Only ten apps (12%) stated that they were HIPAA compliant, and three (4%) were Child Online Privacy and Protection Act (COPPA)-compliant.

In addition, conversational analytics can analyze and extract insights from natural language conversations, typically between customers interacting with businesses through chatbots and virtual assistants. Thorough testing is done beforehand to make sure the chatbot functions well in actual situations. The health bot’s functionality and responses are greatly enhanced by user feedback and data analytics. For medical diagnosis and other healthcare applications, the accuracy and dependability of the chatbot are improved through ongoing development based on user interactions. In the first stage, a comprehensive needs analysis is conducted to pinpoint particular healthcare domains that stand to gain from a conversational AI solution.

Once the primary purpose is defined, common quality indicators to consider are the success rate of a given action, nonresponse rate, comprehension quality, response accuracy, retention or adoption rates, engagement, and satisfaction level. The ultimate goal is to assess whether chatbots positively affect and address the 3 aims of health care. Regular quality checks are especially critical for chatbots acting as decision aids because they can have a major impact on patients’ health outcomes. Healthy diets and weight control are key to successful disease management, as obesity is a significant risk factor for chronic conditions. Chatbots have been incorporated into health coaching systems to address health behavior modifications. For example, CoachAI and Smart Wireless Interactive Health System used chatbot technology to track patients’ progress, provide insight to physicians, and suggest suitable activities [45,46].

chatbot in healthcare

By leveraging AI and natural language processing, chatbots can provide personalized advice, prescription refilling, and reminders to patients that are tailored to their specific needs. Chatbots in healthcare can collect patients’ age, location, and other medical information when providing guidance on how to handle a particular condition or issue. They can even track health data over time, offering increasingly more accurate insights and recommendations based on a patient’s healthcare journey.

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