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

Chatbots must be regularly updated and maintained to ensure their accuracy and reliability. Healthcare providers can overcome this challenge by investing in a dedicated team to manage bots and ensure they are up-to-date with the latest healthcare information. The system has added a new member to the schools’ support team which already includes social workers, counselors and psychologists. Students can now interact with a llama named Kiwi, an AI chatbot in the app, Alongside, which offers mental health support for middle- and high-school students.

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. As we balance the allure of AI and the need to protect people’s health, medical chatbots have the potential to improve access to health information—especially when it comes to health issues people typically don’t like to discuss. We sought to understand current public perceptions of medical chatbots and the ways people believe they can benefit from this emerging technology. This article discusses medical chatbots, underlining their potential to reshape the healthcare landscape. We address prevalent concerns and highlight recent research findings indicating that chatbots may encourage individuals with sensitive health issues to seek help sooner.

Yes, you can deliver an omnichannel experience to your patients, deploying to apps, such as Facebook Messenger, Intercom, Slack, SMS with Twilio, WhatsApp, Hubspot, WordPress, and more. Our seamless integrations can route patients to your telephony and interactive voice response (IVR) systems when they need them. According to G2 Crowd, IDC, and Gartner, IBM’s watsonx Assistant is one of the best chatbot builders in the space with leading natural language processing (NLP) and integration capabilities. New technologies may form new gatekeepers of access to specialty care or entirely usurp human doctors in many patient cases.

Moreover, regular check-ins from chatbots remind patients about medication schedules and follow-up appointments, leading to improved treatment adherence. In addition to collecting patient data and feedback, chatbots play a pivotal role in conducting automated surveys. These surveys gather valuable insights into various aspects of healthcare delivery such as service quality, satisfaction levels, and treatment outcomes.

How to Develop a Medical Chatbot App?

Importantly, in addition to human-like answers, the perceived human-likeness of chatbots in general can be considered ‘as a likely predictor of users’ trust in chatbots’ (p. 25). Following Pasquale (2020), we can divide the use of algorithmic systems, such as chatbots, into two strands. First, there are those that use ML ‘to derive new knowledge from large datasets, such as improving diagnostic accuracy from scans and other images’.

Studies on the use of chatbots for mental health, in particular anxiety and depression, also seem to show potential, with users reporting positive outcomes on at least some of the measurements taken [33,34,41]. For RCTs, the number of participants varied between 20 to 927, whereas user analytics studies considered data from between 129 and 36,070 users. 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.

With watsonx Assistant, patients arrive at that human interaction with the relevant patient data necessary to facilitate rapid resolution. That means patients get what they need faster and more effectively, without the inefficiency of long wait times and incorrect call routing. Costly pre-service calls were reduced and the experience improved using conversational AI to quickly determine patient insurance coverage.

You have probably heard of this platform, for it boasts of catering to almost 13 million users as of 2023. Ada Health is a popular healthcare app that understands symptoms and manages patient care instantaneously with a reliable AI-powered database. Furthermore, there are work-related and ethical standards in different fields, which have been developed through centuries or longer. For example, as Pasquale argued (2020, p. 57), in medical fields, science has made medicine and practices more reliable, and ‘medical boards developed standards to protect patients from quacks and charlatans’. Thus, one should be cautious when providing and marketing applications such as chatbots to patients. The application should be in line with up-to-date medical regulations, ethical codes and research data.

Conversational chatbots

Learn about how the COVID-19 pandemic rocketed the adoption of virtual agent technology (VAT) into hyperdrive. I reached out to both OpenAI and Google for responses, but had not heard from either at the time of posting. Old data might explain ChatGPT failing to flag the class-action lawsuit against the Boston doctor, reported last October. However, inquiries about other doctors, even those mentioned prominently in a 2017 news story about overbilling, brought the same response about not having specific information.

• Chatbots in healthcare can collect patients’ age, location, and other medical information when providing guidance on how to handle a particular condition or issue.
• With psychiatry-oriented chatbots, people can interact with a virtual mental health ‘professional’ to get some relief.
• 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.
• With a CAGR of 15% over the upcoming couple of years, the healthcare chatbot market growth is astonishing.
• They may also help streamline healthcare services, reducing some of the current pressures on staff.

An AI-driven chatbot can identify use cases by understanding users’ intent from their requests. Use cases should be defined in advance, involving business analysts and software engineers. Data gathered from user interactions may also be used to uncover hidden health patterns, supporting AI applications to enhance our understanding and management of countless medical conditions.

A total of 30% (30/100) of participants indicated that they had direct personal experience with the use of chatbots for health-related issues. Physicians were also given a list of currently available health care chatbots, to chatbot in healthcare examine their familiarity with some of the interfaces that could be potentially accessed by patients. The findings indicated that most of the currently available chatbots were not generally used or heard of by physicians.

Case in point, people recently started noticing their conversations with Bard appear in Google’s search results. This means Google started indexing Bard conversations, raising privacy concerns among its users. So, despite the numerous benefits, the chatbot implementation in healthcare comes with inherent risks and challenges. Chatbots in the healthcare industry provide support by recommending coping strategies for various mental health problems. Recent findings demonstrate that ChatGPT is already capable of delivering highly relevant and interpretable responses to medical queries. Medical chatbots can offer fast, remote information to millions of people simultaneously.

Chatbots can be found across nearly any communication channel, from phone trees to social media to specific apps and websites. The accuracy of its responses is not good enough and there are issues with translation, Jalota said. Users often write questions in a mix of languages and may not provide the chatbot with enough information for it to offer a relevant response. The Myna Mahila Foundation recruited test users like Thatkare to write real questions they have. ” The foundation’s staff then closely monitor the chatbot’s responses, developing a customized database of verified questions and answers along the way that helps improve future responses. The app she uses is powered by artificial intelligence running on OpenAI’s ChatGPT model, that Myna Mahila Foundation, a local women’s organization, is developing.

Also, they will help you define the flow of every use case, including input artifacts and required third-party software integrations. Participants reported that while consultations with doctors were perceived as more accurate, reassuring, trustworthy, and useful, chatbot consultations were considered easier and more convenient. One study found that there was no effect on adherence to a blood pressure–monitoring schedule [39], whereas another reported a positive improvement medication adherence [35]. 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.

FOLLOW US ON SOCIAL MEDIA

Thus, their function is to solve complex problems using reasoning methods such as the if-then-else format. In the early days, the problem of these systems was ‘the complexity of mapping out the data in’ the system (Fischer and Lam 2016, p. 23). Today, advanced AI technologies and various kinds of platforms that house big data (e.g. blockchains) are able to map out and compute in real time most complex data structures.

A secondary factor in persuasiveness, satisfaction, likelihood of following the agent’s advice and likelihood of use was the type of agent, with participants reporting that they viewed chatbots more positively in comparison with human agents. One of the positive aspects is that healthcare organisations struggling to meet user demand for screening services can provide new patient services. However, one of the downsides is patients’ overconfidence in the ability of chatbots, which can undermine confidence in physician evaluations. If health-consulting chatbots are able to evoke feelings of trust among patients, the latter will be more willing to disclose medical information to them and can become more vulnerable to, for example, data hijacking by companies (Pasquale 2020, p. 51).

Chatbots, also known as conversational agents, interactive agents, virtual agents, virtual humans, or virtual assistants, are artificial intelligence programs designed to simulate human conversation via text or speech. Electronic health records have improved data availability but also increased the complexity of the clinical workflow, contributing to ineffective treatment plans and uninformed management [86]. For example, Mandy is a chatbot that assists health care staff by automating the patient intake process [43].

These data are not intended to quantify the penetration of healthbots globally, but are presented to highlight the broad global reach of such interventions. Another limitation stems from the fact that in-app purchases were not assessed; therefore, this review highlights features and functionality only of apps that are free to use. Lastly, our review is limited by the limitations in reporting on aspects of security, privacy and exact utilization of ML. While our research team assessed the NLP system design for each app by downloading and engaging with the bots, it is possible that certain aspects of the NLP system design were misclassified. Personalization was defined based on whether the healthbot app as a whole has tailored its content, interface, and functionality to users, including individual user-based or user category-based accommodations. Personalization features were only identified in 47 apps (60%), of which all required information drawn from users’ active participation.

Chatbots can also communicate in multiple different languages to better suit the needs of individual patients. In a world where an anxiety attack can happen at any time, you can rest easy knowing that you have AI-powered chatbots in healthcare to rely on. They can also take action based on patient queries and provide guidance on the next steps. For example, a chatbot may remind a patient to take their medication or schedule an appointment with their healthcare provider. While this capability offers benefits, such as improved patient outcomes and reduced healthcare costs, there are also potential drawbacks, such as privacy concerns and misinterpretation of patient queries.

First, it can perform an assessment of a health problem or symptoms and, second, more general assessments of health and well-being. Third, it can perform an ‘assessment of a sickness or its risks’ and guide ‘the resident to receive treatment in services promoting health and well-being within Omaolo and in social and health services external to’ it (THL 2020, p. 14). 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 design principles of most health technologies are based on the idea that technologies should mimic human decision-making capacity. These systems are computer programmes that are ‘programmed to try and mimic a human expert’s decision-making ability’ (Fischer and Lam 2016, p. 23).

As an interdisciplinary subject of study for both HCI and public health research, studies must meet the standards of both fields, which are at times contradictory [52]. Methods developed for the evaluation of pharmacological interventions such as RCTs, which were designed to assess the effectiveness of an intervention, are known in HCI and related fields [53] to be limited in the insights they provide toward better design. Due to the rapid digital leap caused by the Coronavirus pandemic in health care, there are currently no established ethical principles to evaluate healthcare chatbots.

This process is inherently uncertain, and the diagnosis may evolve over time as new findings present themselves. Chatbots can be exploited to automate some aspects of clinical decision-making by developing protocols based on data analysis. They can automate bothersome and time-consuming tasks, like appointment scheduling or consultation. An AI chatbot can be integrated with third-party software, enabling them to deliver proper functionality.

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. Beyond cancer care, there is an increasing number of creative ways in which chatbots could be applicable to health care. During the COVID-19 pandemic, chatbots were already deployed to share information, suggest behavior, and offer emotional support. They have the potential to prevent misinformation, detect symptoms, and lessen the mental health burden during global pandemics [111].

By taking this step, you can make sure that the health bot has access to pertinent patient data, enabling tailored responses and precise medical advice. Smooth integration enhances the chatbot’s ability to diagnose medical conditions and enhances the provision of healthcare services in general. With regard to the use of health care chatbots within the occupational role of an HCP, physicians believed that the technology would almost equally help them as well as impede their overall workplace duties. Approximately half of the physicians also believed that health care chatbots would eventually play a more significant role in patients’ health than their HCP.

Today, chatbots can consistently manage customer interactions 24×7 while continuously improving the quality of the responses and keeping costs down. A chatbot can also eliminate long wait times for phone-based customer support, or even longer wait times for email, chat and web-based support, because they are available immediately to any number of users at once. That’s a great user experience—and satisfied customers are more likely to exhibit brand loyalty. When it comes to warning the public about potentially harmful health care, the two most popular artificial intelligence chatbots clam up.

More in Technology

Additionally, the use of healthbots in healthcare is a nascent field, and there is a limited amount of literature to compare our results. Furthermore, we were unable to extract data regarding the number of app downloads for the Apple iOS store, only the number of ratings. This resulted in the drawback of not being able to fully understand the geographic distribution of healthbots across both stores.

In case of alarming changes, the chatbot can trigger alerts to both patients and healthcare professionals, ensuring timely intervention and reducing the risk of complications. One stream of healthcare chatbot development focuses on deriving new knowledge from large datasets, such as scans. This is different from the more traditional image of chatbots that interact with people in real-time, using probabilistic scenarios to give recommendations that improve over time. How do we deal with all these issues when developing a clinical chatbot for healthcare?

While chatbots that serve as symptom checkers could accurately generate differential diagnoses of an array of symptoms, it will take a doctor, in many cases, to investigate or query further to reach an accurate diagnosis. A user interface is the meeting point between men and computers; the point where a user interacts with the design. Depending on the type of chatbot, developers use a graphical user interface, voice interactions, or gestures, all of which use different machine learning models to understand human language and generate appropriate responses. This free AI-enabled chatbot allows you to input your symptoms and get the most likely diagnoses. Trained with machine learning models that enable the app to give accurate or near-accurate diagnoses, YourMd provides useful health tips and information about your symptoms as well as verified evidence-based solutions.

The chatbots then, through EDI, store this information in the medical facility database to facilitate patient admission, symptom tracking, doctor-patient communication, and medical record keeping. Chatbots can be accessed anytime, providing patients support outside regular office hours. This can be particularly useful for patients requiring urgent medical attention or having questions outside regular office hours. • A school behavioral health program in 35 schools that works with three mental health providers, who offer individual and family group counseling; medication management; and consultation and training.

The doctors can then use all this information to analyze the patient and make accurate reports. An AI-powered solution can reduce average handle time by 20%, resulting in cost benefits of hundreds of thousands of dollars. The author(s) declared no potential conflicts of interests with respect to the authorship and/or publication of this article. The HIPAA Security Rule requires that you identify all the sources of PHI, including external sources, and all human, technical, and environmental threats to the safety of PHI in your company. After training your chatbot on this data, you may choose to create and run a nlu server on Rasa. The name of the entity here is “location,” and the value is “colorado.” You need to provide a lot of examples for “location” to capture the entity adequately.

Second, ‘there are user-facing applications […] which interact with people in real-time’, providing advice and ‘instructions based on probabilities which the tool can derive and improve over time’ (p. 55). The latter, that is, systems such as chatbots, seem to complement and sometimes even substitute HCP patient consultations (p. 55). For an effective chatbot application and enjoyable user experience, chatbots must be designed to make interactions as natural as possible; and this requires machine learning models that can enable the bot to understand the intent and context of conversations. 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.

With the growing number of AI algorithms approved by the Food and Drug Administration, they opened public consultations for setting performance targets, monitoring performance, and reviewing when performance strays from preset parameters [102]. You can foun additiona information about ai customer service and artificial intelligence and NLP. The American Medical Association has also adopted the Augmented Intelligence in Health Care policy for the appropriate integration of AI into health care by emphasizing the design approach and enhancement of human intelligence [109]. An area of concern is that chatbots are not covered under the Health Insurance Portability and Accountability Act; therefore, users’ data may be unknowingly sold, traded, and marketed by companies [110]. On the other hand, overregulation may diminish the value of chatbots and decrease the freedom for innovators. Consequently, balancing these opposing aspects is essential to promote benefits and reduce harm to the health care system and society.

The use of chatbots in healthcare has become increasingly prevalent, particularly in addressing public health concerns, including COVID-19 pandemic during previous years. These AI-powered tools have proven to be invaluable in screening individuals for COVID-19 symptoms and providing guidance on necessary precautions. Moreover, chatbots act as valuable resources for patients who require assistance but may not have immediate access to healthcare professionals.

Patients can rely on these conversational agents for quick access to help and guidance. Whether it’s a minor health issue or a crisis situation, chatbots are available 24/7 to address user concerns promptly. AI Chatbots also play a crucial role in the healthcare industry by offering mental health support. They provide resources and guide users through coping strategies, creating a safe space for individuals to discuss their emotional well-being anonymously.

The study focused on health-related apps that had an embedded text-based conversational agent and were available for free public download through the Google Play or Apple iOS store, and available in English. A healthbot was defined as a health-related conversational agent that facilitated a bidirectional (two-way) conversation. Applications that only sent in-app text reminders and did not receive any text input from the user were excluded. Apps were also excluded if they were specific to an event (i.e., apps for conferences or marches). 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.

With the constantly evolving nature of the virus, having access to accurate and timely information is crucial. Chatbots can provide users with a list of nearby testing centers or vaccination sites based on their location, ensuring they have easy access to these important resources. Chatbots minimize the risk of errors and omissions by ensuring that all necessary information is recorded accurately.

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]. The number of studies assessing the development, implementation, and effectiveness are still relatively limited compared with the diversity of chatbots currently available. Further studies are required to establish the efficacy across various conditions and populations.

Pasquale (2020, p. 57) has reminded us that AI-driven systems, including chatbots, mirror the successes and failures of clinicians. However, machines do not have the human capabilities of prudence and practical wisdom or the flexible, interpretive capacity to correct mistakes and wrong decisions. As a result of self-diagnosis, physicians may have difficulty convincing patients of their potential preliminary, chatbot-derived misdiagnosis. This level of persuasion and negotiation increases the workload of professionals and creates new tensions between patients and physicians. Physicians’ autonomy to diagnose diseases is no end in itself, but patients’ trust in a chatbot about the nature of their disease can impair professionals in their ability to provide appropriate care for patients if they disregard a doctor’s view.

Whether it’s explaining symptoms, treatment options, or medication instructions, chatbots serve as virtual assistants that ensure patients are well-informed about their medical concerns. In this respect, the synthesis between population-based prevention and clinical care at an individual level [15] becomes particularly relevant. Implicit to digital technologies such as chatbots are the levels of efficiency and scale that open new possibilities for health care provision that can extend individual-level health care at a population level.