Top 10 Chatbots in Healthcare: Insights & Use Cases in 2023

The IAB develops industry standards to support categorization in the digital advertising industry; 42Matters labeled apps using these standards40. Relevant apps on the iOS Apple store were identified; then, the Google Play store was searched with the exclusion of any apps that were also available on iOS, to eliminate duplicates. Through chatbots (and their technical functions), we can have only a very limited view of medical knowledge. The ‘rigid’ and formal systems of chatbots, even with the ML bend, are locked in certain a priori models of calculation. Expertise generally requires the intersubjective circulation of knowledge, that is, a pool of dynamic knowledge and intersubjective criticism of data, knowledge and processes (e.g. Prior 2003; Collins and Evans 2007). Therefore, AI technologies (e.g. chatbots) should not be evaluated on the same level as human beings.

Trained in cognitive behavioral therapy (CBT), it helps users through simple conversations. Wysa AI Coach also employs evidence-based techniques like CBT, DBT, meditation, breathing, yoga, motivational chatbot use cases in healthcare interviewing, and micro-actions to help patients build mental resilience skills. Telecom chatbots have modified the way communication service providers interact with customers.

Provide medical information

Another app is Weight Mentor, which provides self-help motivation for weight loss maintenance and allows for open conversation without being affected by emotions [47]. Health Hero (Health Hero, Inc), Tasteful Bot (Facebook, Inc), Forksy (Facebook, Inc), and SLOWbot (iaso heath, Inc) guide users to make informed decisions on food choices to change unhealthy eating habits [48,49]. The effectiveness of these apps cannot be concluded, as a more rigorous analysis of the development, evaluation, and implementation is required.

Based on the information they provided, we identified 7 use cases for information dissemination (see Figure 2). Today, chatbots offer diagnosis of symptoms, mental healthcare consultation, nutrition facts and tracking, and more. For example, in 2020 WhatsApp collaborated with the World Health Organization (WHO) to make a chatbot service that answers users’ questions on COVID-19. Informative, conversational, and prescriptive healthcare chatbots can be built into messaging services like Facebook Messenger, Whatsapp, or Telegram or come as standalone apps. Acropolium has delivered a range of bespoke solutions and provided consulting services for the medical industry. The insights we’ll share in this post come directly from our experience in healthcare software development and reflect our knowledge of the algorithms commonly used in chatbots.

Scheduling appointments and reminders

For example, in the field of psychology, so-called ‘script theory’ provided a formal framework for knowledge (Fischer and Lam 2016). Thus, as a formal model that was already in use, it was relatively easy to turn it into algorithmic form. These expert systems were part of the automated decision-making (ADM) process, that is, a process completely devoid of human involvement, which makes final decisions on the basis of the data it receives (European Commission 2018, p. 20). Conversely, health consultation chatbots are partially automated proactive decision-making agents that guide the actions of healthcare personnel. From enhancing patient experience and helping medical professionals, to improving healthcare processes and unlocking actionable insights, medical or healthcare chatbots can be used for achieving various objectives. Poised to change the way payers, medical care providers, and patients interact with each other, medical chatbots are one of the most matured and influential AI-powered healthcare solutions developed so far.

From collecting patient information to taking into account their history and recording their symptoms, data is essential. It provides a comprehensive overview of the patient before proceeding with the treatment. Chatbots will not replace doctors in medicine anytime soon, but they will likely become indispensable tools in patient care as AI continues to undergo major breakthroughs. The healthcare chatbot’s market size was valued at around $211 million as of 2022. With a CAGR of 15% over the upcoming couple of years, the healthcare chatbot market growth is astonishing. Chatbots like Docus.ai can even validate these diagnoses with top healthcare professionals from the US and Europe.

We identified 78 healthbot apps commercially available on the Google Play and Apple iOS stores. Healthbot apps are being used across 33 countries, including some locations with more limited penetration of smartphones and 3G connectivity. The healthbots serve a range of functions including the provision of health education, assessment of symptoms, and assistance with tasks such as scheduling. Currently, most bots available on app stores are patient-facing and focus on the areas of primary care and mental health. Only six (8%) of apps included in the review had a theoretical/therapeutic underpinning for their approach. Two-thirds of the apps contained features to personalize the app content to each user based on data collected from them.

• This shows that some topics may be embarrassing for patients to discuss face-to-face with their doctor.
• After the request is understood, the requested actions are performed, and the data of interest are retrieved from the database or external sources [15].
• Find out where your bottlenecks are and formulate what you’re planning to achieve by adding a chatbot to your system.
• You probably want to offer customer service for your clients constantly, but that takes a lot of personnel and resources.

Projections indicate that the number of voice chatbots is expected to exceed 8 billion by 2023. But, these aren’t all the ways you can use your bots as there are hundreds of those depending on your company’s needs. This way, you will get more usage out of it and have more tasks taken off your shoulders. And, in the long run, you will be much happier with your investment seeing the great results that the bot brings your company.

These categories are not exclusive, as chatbots may possess multiple characteristics, making the process more variable. Textbox 1 describes some examples of the recommended apps for each type of chatbot but are not limited to the ones specified. Chatbots ask patients about their current health issue, find matching physicians and dentists, provide available time slots, and can schedule, reschedule, and delete appointments for patients.

Decreased wait times in accessing health care services have been found to correlate with improved patient outcomes and satisfaction [59-61]. The automated chatbot, Quro (Quro Medical, Inc), provides presynopsis based on symptoms and history to predict user conditions (average precision approximately 0.82) without a form-based data entry system [25]. In addition to diagnosis, Buoy Health (Buoy Health, Inc) assists users in identifying the cause of their illness and provides medical advice [26]. Another chatbot designed by Harshitha et al [27] uses dialog flow to provide an initial analysis of breast cancer symptoms. It has been proven to be 95% accurate in differentiating between normal and cancerous images. A study of 3 mobile app–based chatbot symptom checkers, Babylon (Babylon Health, Inc), Your.md (Healthily, Inc), and Ada (Ada, Inc), indicated that sensitivity remained low at 33% for the detection of head and neck cancer [28].

Based on Gartner’s research, there is a projected 40% increase in the adoption of chatbot technology, with 38% of organizations planning to implement chatbots within the next two years. Join Master of Code on this journey to discover the boundless potential of chatbots and how they are reshaping the way we interact with technology and information. While healthbots have a potential role in the future of healthcare, our understanding of how they should be developed for different settings and applied in practice is limited. There has been one systematic review of commercially available apps; this review focused on features and content of healthbots that supported dementia patients and their caregivers34. To our knowledge, no review has been published examining the landscape of commercially available and consumer-facing healthbots across all health domains and characterized the NLP system design of such apps.

They can also aid in customer or patient education and provide data about treatments, medications, and other aspects of healthcare. In this article, we share our perspective on how the contemporary chatbot technology can be extended towards a more intelligent, engaging, context-aware, and personalized agent. Furthermore, we underline the importance of contextualization, personalization, and abstraction1 with the use of domain-specific as well as patient-specific knowledge, and present examples of three healthcare applications. If you wish to see how a healthcare chatbot suits your medical services, take a detailed demo with our in-house chatbot experts. Different types of chatbots in healthcare require different advantages, and the strengths of these algorithms are dependent on the training data they are provided.

Which algorithm is used for healthcare chatbot?

It just takes a minute to gauge the details and respond to them, thereby reducing their wait time and expediting the process. Ever since the introduction of chatbots, health professionals are realizing how chatbots can improve healthcare. Let’s dive a little deeper and talk about a couple of the top chatbot use cases in healthcare. It features many tools, such as online doctor consultations, appointment settings, and, most importantly, a symptom checker.

It revolutionizes the quality of patient experience by attending to your patient’s needs instantly. Emerging trends like increasing service demand, shifting focus towards 360-degree wellbeing, and rising costs of quality care are propelling the adoption of new technologies in the healthcare sector. By harnessing the power of Generative Conversational AI, medical institutions are rewriting the rules of patient engagement. We are witnessing a rapid upsurge in the development and implementation of various AI solutions in the healthcare sector. The use of chatbots in health care presents a novel set of moral and ethical challenges that must be addressed for the public to fully embrace this technology. Issues to consider are privacy or confidentiality, informed consent, and fairness.

AI and ML have advanced at an impressive rate and have revealed the potential of chatbots in health care and clinical settings. AI technology outperforms humans in terms of image recognition, risk stratification, improved processing, and 24/7 assistance with data and analysis. However, there is no machine substitute for higher-level interactions, critical thinking, and ambiguity [93]. Chatbots create added complexity that must be identified, addressed, and mitigated before their universal adoption in health care. Design-wise, ease of development, ease of access, and platform penetration have likely contributed to the prevalence of web-based and social media chatbots. For example, the built-in modules for chatbot design on social media platforms allow for fast and easy development.

Family history collection is a proven way of easily accessing the genetic disposition of developing cancer to inform risk-stratified decision-making, clinical decisions, and cancer prevention [63]. The web-based chatbot ItRuns (ItRunsInMyFamily) gathers family history information at the population level to determine the risk of hereditary cancer [29]. We have yet to find a chatbot that incorporates deep learning to process large and complex data sets at a cellular level.

In combination with wearable technology and affordable software, chatbots have great potential to affect patient monitoring solutions. With the rapidly increasing applications of chatbots in health care, this section will explore several areas of development and innovation in cancer care. Various examples of current chatbots provided below will illustrate their ability to tackle the triple aim of health care. The specific use case of chatbots in oncology with examples of actual products and proposed designs are outlined in Table 1. Cancer has become a major health crisis and is the second leading cause of death in the United States [18]. The exponentially increasing number of patients with cancer each year may be because of a combination of carcinogens in the environment and improved quality of care.

These bots can also play a critical role in making relevant healthcare information accessible to the right stakeholders, at the right time. The prevalence of cancer is increasing along with the number of survivors of cancer, partly because of improved treatment techniques and early detection [77]. A number of these individuals require support after hospitalization or treatment periods. Maintaining autonomy and living in a self-sustaining way within their home environment is especially important for older populations [79]. Implementation of chatbots may address some of these concerns, such as reducing the burden on the health care system and supporting independent living. Differences in language even within the same country, differences in local information and guidelines, and differences in popularity of different social media platforms across countries may limit the scope of such efforts.