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

Chatbots have also been proposed to autonomize patient encounters through several advanced eHealth services. In addition to collecting data and providing bookings, Health OnLine Medical Suggestions or HOLMES (Wipro, Inc) interacts with patients to support diagnosis, choose the proper treatment pathway, and provide prevention check-ups [44]. Although the use of chatbots in health care and cancer therapy has the potential to enhance clinician efficiency, reimbursement codes for practitioners are still lacking before universal implementation. In addition, studies will need to be conducted to validate the effectiveness of chatbots in streamlining workflow for different health care settings. Nonetheless, chatbots hold great potential to complement telemedicine by streamlining medical administration and autonomizing patient encounters.

So, it’s now time to put it to practice and show you the 4 top AI-powered chatbots in healthcare you can see today. If you’re interested in learning about all the benefits of healthcare chatbots, keep on reading through to the next section. But, as we move forward, we must remember that medical chatbots should be offered as a complement, not a replacement, to face-to-face interactions with healthcare professionals.

• Patients can inquire about their insurance policies, coverage details, and any other concerns they may have regarding their healthcare plans.
• Engaging in open conversations about health with medical professionals can be challenging for individuals who anticipate encountering stigma or embarrassment upon revealing their symptoms and experiences of health.
• Although not specifically an oncology app, another chatbot example for clinicians’ use is the chatbot Safedrugbot (Safe In Breastfeeding) [69].
• It conducts basic activities like asking about the symptoms, recommending wellness programs, and tracking behavior or weight changes.
• This finding may in part be due to the large variability in chatbot design (such as differences in content, features, and appearance) but also the large variability in the users’ response to engaging with a chatbot.

Nevertheless, chatbots are emerging as a solution for healthy lifestyle promotion through access and human-like communication while maintaining anonymity. The benefits of bots include 24/7 availability for instant support, saving time and effort for users. Chatbots also reduce costs by automating repetitive tasks and providing cost-effective customer service. Additionally, they enhance customer experiences by offering personalized and quick responses. But in the context of healthcare, such bots would allow users to schedule doctor’s appointments easily. For example, a chatbot called Iris can schedule and cancel appointments, receive lab results, and send follow-up reminders.

You can foun additiona information about ai customer service and artificial intelligence and NLP. The bot will then fetch the data from the system, thus making operations information available at a staff member’s fingertips. This automation results in better team coordination while use of chatbots in healthcare decreasing delays due to interdependence among teams. Customer service chatbot for healthcare can help to enhance business productivity without any extra costs and resources.

Chatbots can provide insurance services and healthcare resources to patients and insurance plan members. Moreover, integrating RPA or other automation solutions with chatbots allows for automating insurance claims processing and healthcare billing. However, this aspect is probably also the most problematic, as it raises doubts about the veracity of the information.

Improved patient engagement

Furthermore, chatbots contribute to enhancing patient experience in the healthcare industry by providing round-the-clock support for health systems. Unlike traditional customer service hotlines that operate within limited hours, chatbots are available 24/7. This accessibility ensures that patients in the healthcare industry can seek assistance whenever they need it most, regardless of the time zone or geographical location they are in.

Patients who are not engaged in their healthcare are three times as likely to have unmet medical needs and twice as likely to delay medical care than more motivated patients. Maybe for that reason, omnichannel engagement pharma is gaining more traction now than ever before. Chatbots are programmed by humans and thus, they are prone to errors and can give a wrong or misleading medical advice.

Products and services

They built one of the most highly intuitive AI-powered chatbots in healthcare, which could come up with possible diagnoses for a patient’s symptoms by asking around 20 questions. The best healthcare chatbots available today have different missions, and consequently, different pros and cons. If you’re interested in learning about an alternative source of medical advice or simply want to learn about the top health chatbots that exist today, let us show you the way.

We acknowledge the difficulty in identifying the nature of systemic change and looking at its complex network-like structure in the functioning of health organisations. Nonetheless, we consider it important to raise this point when talking about chatbots and their potential breakthrough in health care. We suggest that new ethico-political approaches are required in professional ethics because chatbots can become entangled with clinical practices in complex ways.

From there, the processed information could be remembered, or more details could be requested for clarification. After the request is understood, the requested actions are performed, and the data of interest are retrieved from the database or external sources [15]. Any advantage of a chatbot can be a disadvantage if the wrong platform, programming, or data are used. Many rely on rule-based systems that automate tasks and provide predefined responses to customer inquiries. Today, chatbots can consistently manage customer interactions 24×7 while continuously improving the quality of the responses and keeping costs down.

Although preliminary results do indicate positive effects in a number of application domains, reported findings are for the most part mixed. Our inclusion criteria were for the studies that used or evaluated chatbots for the purpose of prevention or intervention and for which the evidence showed a demonstrable health impact. We included experimental studies where chatbots were trialed and showed health impacts. We chose not to distinguish between embodied conversational agents and text-based agents, including both these modalities, as well as chatbots with cartoon-based interfaces. 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].

In the aftermath of COVID-19, Omaolo was updated to include ‘Coronavirus symptoms checker’, a service that ‘gives guidance regarding exposure to and symptoms of COVID-19’ (Atique et al. 2020, p. 2464; Tiirinki et al. 2020). 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). The most famous chatbots currently in use are Siri, Alexa, Google Assistant, Cordana and XiaoIce.

During the Covid-19 pandemic, WHO employed a WhatsApp chatbot to reach and assist people across all demographics to beat the threat of the virus. The doctors can then use all this information to analyze the patient and make accurate reports. Chatbots are also great for conducting feedback surveys to assess patient satisfaction. That provides an easy way to reach potentially infected people and reduce the spread of the infection. After training your chatbot on this data, you may choose to create and run a nlu server on Rasa.

They can substantially boost efficiency and improve the accuracy of symptom detection, preventive care, post-recovery care, and feedback procedures. The healthcare sector has turned to improving digital healthcare services in light of the increased complexity of serving patients during a health crisis or epidemic. One in every twenty Google searches is about health, this clearly demonstrates the need to receive proper healthcare advice digitally. I am Paul Christiano, a fervent explorer at the intersection of artificial intelligence, machine learning, and their broader implications for society. Renowned as a leading figure in AI safety research, my passion lies in ensuring that the exponential powers of AI are harnessed for the greater good.

Chatbots Enhance Patient Access

A complete system also requires a ‘back-up system’ or practices that imply increased costs and the emergence of new problems. The crucial question that policy-makers are faced with is what kind of health services can be automated and translated into machine readable form. Many health professionals and experts have emphasised that chatbots are not sufficiently mature to be able to technically diagnose patient conditions or replace health professional assessments (Palanica et al. 2019).

Tidio is one of the most popular options if you are looking for a free chatbot editor. And there you have it—some of the most common use cases of bots across various industries. Keep in mind that this is just a small glimpse into what they can do, and new uses will only continue to emerge over time.

Survivors of cancer, particularly those who underwent treatment during childhood, are more susceptible to adverse health risks and medical complications. 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. This global experience will impact the healthcare industry’s dependence on chatbots, and might provide broad and new chatbot implementation opportunities in the future.

Despite the initial chatbot hype dwindling down, medical chatbots still have the potential to improve the healthcare industry. The three main areas where they can be particularly useful include diagnostics, patient engagement outside medical facilities, and mental health. At least, that’s what CB Insights analysts are bringing forward in their healthcare chatbot market research, generally saying that the future of chatbots in the healthcare industry looks bright. Early cancer detection can lead to higher survival rates and improved quality of life.

In practice, however, clinicians make diagnoses in a more complex manner, which they are rarely able to analyse logically (Banerjee et al. 2009). Unlike artificial systems, experienced doctors recognise the fact that diagnoses and prognoses are always marked by varying degrees of uncertainty. They are aware that some diagnoses may turn out to be wrong or that some of their treatments may not lead to the cures expected. Thus, medical diagnosis and decision-making require ‘prudence’, that is, ‘a mode of reasoning about contingent matters in order to select the best course of action’ (Hariman 2003, p. 5). 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.

Chatbots’ robustness of integrating and learning from large clinical data sets, along with its ability to seamlessly communicate with users, contributes to its widespread integration in various health care components. Given the current status and challenges of cancer care, chatbots will likely be a key player in this field’s continual improvement. More specifically, they hold promise in addressing the triple aim of health care by improving the quality of care, bettering the health of populations, and reducing the burden or cost of our health care system.

This automation reduces the need for staff to handle basic inquiries and administrative duties, allowing them to focus on more complex and critical tasks. In addition, by handling initial patient interactions, chatbots can reduce the number of unnecessary in-person visits, further saving costs. Considering their capabilities and limitations, check out the selection of easy and complicated tasks for artificial intelligence chatbots in the healthcare industry.

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. If you are interested in knowing how chatbots work, read our articles on voice recognition applications and natural language processing.

This bodes well for patients with long-term illnesses like diabetes or heart disease symptoms. Moreover, chatbots simplify appointment scheduling by allowing patients to book appointments online or through messaging platforms. This not only reduces administrative overhead but also ensures that physicians’ schedules are optimized efficiently. As a result, hospitals can maximize their resources by effectively managing patient flow while reducing waiting times. In the realm of post-operative care, AI chatbots help enhance overall recovery processes by using AI technology to facilitate remote monitoring of patients’ vital signs. By integrating with wearable devices or smart home technologies, these chatbots collect real-time data on metrics like heart rate, blood pressure, or glucose levels.

This means, chatbots and the data that they process might be exposed to threat agents and might be a target for cyberattacks. The issue of mental health today is as critical as ever, and the impact of COVID-19 is among the main reasons for the growing number of disorders and anxiety. According to Forbes, the number of people with anxiety disorders grew from 298 million to 374 million, which is really a significant increase. And since not everyone can receive sufficient help for their mental health, chatbots have become a truly invaluable asset. This bot is similar to a conversational one but is much simpler as its main goal is to provide answers to frequently asked questions.

As we mentioned earlier, the collection of information is vital for the healthcare sector as it allows more personalized healthcare and, as a result, leads to more satisfied patients. Hence, these bots are really important as they help healthcare organizations evaluate their services, understand their patients better, and overall gain a better understanding of what might be improved and how. While a chatbot in healthcare can not be considered a 100% trusted and reliable medical consultant, it can at least help patients recognize their symptoms and the urgency of their condition or answer their questions. And the best part is that these actions do not require patients to schedule an appointment or stand in line, waiting for the doctor to respond.

A text-to-text chatbot by Divya et al [32] engages patients regarding their medical symptoms to provide a personalized diagnosis and connects the user with the appropriate physician if major diseases are detected. Rarhi et al [33] proposed a similar design that provides a diagnosis based on symptoms, measures the seriousness, and connects users with a physician if needed [33]. In general, these systems may greatly help individuals in conducting daily check-ups, increase awareness of their health status, and encourage users to seek medical assistance for early intervention.

America and the Soviets were both keen (in their own ways) on find ways to automatise and streamline their societies (including decision-making). In the field of medical practice, probability assessments has been a recurring theme. Mathematical or statistical probability in medical diagnosis has become one of the principal targets, with the consequence that AI is expected to improve diagnostics in the long run. Hacking (1975) has reminded us of the dual nature between statistical probability and epistemic probability. Statistical probability is concerned with ‘stochastic laws of chance processes’, while epistemic probability gauges ‘reasonable degrees of belief in propositions quite devoid of statistical background’ (p. 12). Epistemic probability concerns our possession of knowledge, or information, meaning how much support is given by all the available evidence.

• This also helps medical professionals stay updated about any changes in patient symptoms.
• Speaking with a chatbot and not a person is perceived in some cases to be a positive experience as chatbots are seen to be less “judgmental” [48].
• While all this sounds impressive, it’s better to go one step further and check out the way bots work in action.
• Preventative measures of cancer have become a priority worldwide, as early detection and treatment alone have not been effective in eliminating this disease [22].
• And the best part is that these actions do not require patients to schedule an appointment or stand in line, waiting for the doctor to respond.

This bot uses AI to provide personalized consultations by analyzing the patient’s medical history and while it cannot fully replace a medical professional, it can for sure provide valuable advice and guidance. They provide personalized, easy-to-understand information about diseases, treatments, and preventive measures. This continuous education empowers patients to make informed health decisions, promotes preventive care, and encourages a proactive approach to health. Patients can easily book, reschedule, or cancel appointments through a simple, conversational interface.

Ada Health is a popular healthcare app that understands symptoms and manages patient care instantaneously with a reliable AI-powered database. According to an MGMA Stat poll, about 49% of medical groups said that the rates of ‘no-shows‘ soared since 2021. No-show appointments result in a considerable loss of revenue and underutilize the physician’s time. The healthcare chatbot tackles this issue by closely monitoring the cancellation of appointments and reports it to the hospital staff immediately. A chatbot can offer a safe space to patients and interact in a positive, unbiased language in mental health cases. Mental health chatbots like Woebot, Wysa, and Youper are trained in Cognitive Behavioural Therapy (CBT), which helps to treat problems by transforming the way patients think and behave.

Element Blue works with leading healthcare providers to deploy chatbots and virtual assistants that assist with medical diagnosis, appointment scheduling, data entry, in-patient and outpatient query address, and automation of patient support. While the industry is already flooded with various healthcare chatbots, we still see a reluctance towards experimentation with more evolved use cases. It is partially because conversational AI is still evolving and has a long way to go. As natural language understanding and artificial intelligence technologies evolve, we will see the emergence of more advanced healthcare chatbot solutions. Chatbots enable healthcare providers to collect this information seamlessly by asking relevant questions and recording patients’ responses. This automated approach eliminates the need for manual data entry, reducing errors and saving time for both patients and healthcare professionals.

Overall, the evidence found was positive, showing some beneficial effect, or mixed, showing little or no effect. Most (21/32, 65%) of the included studies established that the chatbots were usable but with some differences in the user experience and that they can provide some positive support across the different health domains. The results show a substantial increase in the interest of chatbots in the past few years, shortly before the pandemic. Half (16/32, 50%) of the research evaluated chatbots applied to mental health or COVID-19. The studies suggest promise in the application of chatbots, especially to easily automated and repetitive tasks, but overall, the evidence for the efficacy of chatbots for prevention and intervention across all domains is limited at present.