Chatbots in Healthcare 10 Use Cases + Development Guide

Regular quality checks are especially critical for chatbots acting as decision aids because they can have a major impact on patients’ health outcomes. Most would assume that survivors of cancer would be more inclined to practice health protection behaviors with extra guidance from health professionals; however, the results have been surprising. Smoking accounts for at least 30% of all cancer deaths; however, up to 50% of survivors continue to smoke [88]. The cognitive behavioral therapy–based chatbot SMAG, supporting users over the Facebook social network, resulted in a 10% higher cessation rate compared with control groups [50]. Motivational interview–based chatbots have been proposed with promising results, where a significant number of patients showed an increase in their confidence and readiness to quit smoking after 1 week [92].

It costs $14.99/month for the Pro version, which provides unlimited conversations with chatbots, personalized health reports, and grants you early access to new features. Now that you know about the main benefits of chatbots in healthcare, let us tell you about a couple of the best chatbots that exist today. Chatbots in healthcare contribute to significant cost savings by automating routine tasks and providing initial consultations. 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. For example, when a chatbot suggests a suitable recommendation, it makes patients feel genuinely cared for.

Associated Data

Although a wide variety of beneficial aspects were reported (ie, management of health and administration), an equal number of concerns were present. If the limitations of chatbots are better understood and mitigated, the fears of adopting this technology in health care may slowly subside. The Discussion section ends by exploring the challenges and questions for health care professionals, patients, and policy makers. 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].

Once again, answering these and many other questions concerning the backend of your software requires a certain level of expertise. Make sure you have access to professional healthcare chatbot development services and related IT outsourcing experts. In addition to answering the patient’s questions, prescriptive chatbots offer actual medical advice based on the information provided by the user.

Instant access to medical knowledge

Thus, instead of only re-organising work, we are talking about systemic change (e.g. Simondon 2017), that is, change that pervades all parts of a system, taking into account the interrelationships and interdependencies among these parts. Moreover, healthcare chatbots are being integrated with Electronic Health Records (EHRs), enabling seamless access to patient data across various healthcare systems. This integration fosters better patient care and engagement, as medical history and patient preferences are readily available to healthcare providers, ensuring more personalized and informed care. The growing demand for virtual healthcare, accelerated by the global pandemic, has further propelled the adoption of healthcare chatbots.

• A team of two researchers (PP, JR) used the relevant search terms in the “Title” and “Description” categories of the apps.
• Only six (8%) of apps included in the review had a theoretical/therapeutic underpinning for their approach.
• Shum et al. (2018, p. 16) defined CPS (conversation-turns per session) as ‘the average number of conversation-turns between the chatbot and the user in a conversational session’.
• Additionally, the article will highlight leading healthcare chatbots in the market and provide insights into building a healthcare chatbot using Yellow.ai’s platform.

Voice bots facilitate customers with a seamless experience on your online store website, on social media, and on messaging platforms. They engage customers with artificial intelligence communication and offer personalized solutions to shoppers’ requests. Oftentimes, your website visitors are interested in purchasing your products or services but need some assistance to make that final step. You can use bots to answer potential customers’ questions, give promotional codes to them, and show off your “free shipping” offer. Chatbots can be used to communicate with people, answer common questions, and perform specific tasks they were programmed for. They gather and process information while interacting with the user and increase the level of personalization.

Patient Triage

Tables 1 and ​and22 in Appendix 1 provide background information on each chatbot, its use cases, and design features. The process of filing insurance inquiries and claims is standardized and takes a lot of time to complete. The solution provides information about insurance coverage, benefits, and claims information, allowing users to track and handle their health insurance-related needs conveniently. Healthcare chatbots help patients avoid unnecessary tests and costly treatments, guiding them through the system more effectively.

Artificial intelligence (AI) is at the forefront of transforming numerous aspects of our lives by modifying the way we analyze information and improving decision-making through problem solving, reasoning, and learning. 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. The Oxford dictionary defines a chatbot as “a computer program that can hold a conversation with a person, usually over the internet.” They can also be physical entities designed to socially interact with humans or other robots. Predetermined responses are then generated by analyzing user input, on text or spoken ground, and accessing relevant knowledge [3].

Appointment scheduling

Embedding a chatbot within a high-traffic platform can enhance its visibility and discoverability and reduce the effort required to engage with it. As shown in Figure 3, the chatbots in our sample varied in their design along a number of attributes. Chatbots collect chatbot use cases in healthcare patient information, name, birthday, contact information, current doctor, last visit to the clinic, and prescription information. The chatbot submits a request to the patient’s doctor for a final decision and contacts the patient when a refill is available and due.

• It conducts basic activities like asking about the symptoms, recommending wellness programs, and tracking behavior or weight changes.
• Healthcare industry opens a range of valuable chatbot use cases, including personal medication reminders, symptom assessment, appointment scheduling, and health education.
• These data are not intended to quantify the penetration of healthbots globally, but are presented to highlight the broad global reach of such interventions.
• Though a minority, we highlight the importance of SMS-based and phone-call-based chatbots to bridge the digital divide and reach people who lack access to smartphones or reliable internet connections or lack the skills to use technology.
• This requires the same kind of plasticity from conversations as that between human beings.

Healthcare Chatbots: Role of AI, Benefits, Future, Use Cases, Development

This enabled swift response to potential cases and eased the burden on clinicians. Now, let’s explore the main applications of artificial intelligence chatbots in healthcare in more detail. This way, clinical chatbots help medical workers allocate more time to focus on patient care and more important tasks. Chatbots provide patients with a more personalized experience, making them feel more connected to their healthcare providers.

• There are things you can and cannot say, and there are regulations on how you can say things.
• Given that the introduction of chatbots to cancer care is relatively recent, rigorous evidence-based research is lacking.
• Thus, you need to be extra cautious when programming a bot and there should be an option of contacting a medical professional in the case of any concern.

By combining these two, conversational AI systems recognize various phrasings of the same intent, including spelling mistakes, slang and grammatical errors and provide accurate responses to user queries. Although the COVID-19 pandemic has driven the use of chatbots in public health, of concern is the degree to which governments have accessed information under the rubric of security in the fight against the disease. The sharing of health data gathered through symptom checking for COVID-19 by commercial entities and government agencies presents a further challenge for data privacy laws and jurisdictional boundaries [51].

User experience

In these ethical discussions, technology use is frequently ignored, technically automated mechanical functions are prioritised over human initiatives, or tools are treated as neutral partners in facilitating human cognitive efforts. So far, there has been scant discussion on how digitalisation, including chatbots, transform medical practices, especially in the context of human capabilities in exercising practical wisdom (Bontemps-Hommen et al. 2019). From the patient’s perspective, various chatbots have been designed for symptom screening and self-diagnosis.

A cross-sectional web-based survey of 100 practicing physicians gathered the perceptions of chatbots in health care [6]. Although a wide variety of beneficial aspects were reported (ie, management of health and administration), an equal number of concerns were present. Over 70% of physicians believe that chatbots cannot effectively care for all the patients’ needs, cannot display human emotion, cannot provide detailed treatment plans, and pose a risk if patients self-diagnose or do not fully comprehend their diagnosis. If the limitations of chatbots are better understood and mitigated, the fears of adopting this technology in health care may slowly subside. The Discussion section ends by exploring the challenges and questions for health care professionals, patients, and policy makers. There is no doubting the extent to which the use of AI, including chatbots, will continue to grow in public health.

Provide mental health assistance

A sentence (stimuli) is entered, and output (response) is created consistent with the user input [11]. Eliza and ALICE were the first chatbots developed using pattern recognition algorithms. The disadvantage of this approach is that the responses are entirely predictable, repetitive, and lack the human touch.

Thus, a chatbot may work great for assistance with less major issues like flu, while a real person can remain solely responsible for treating patients with long-term, serious conditions. In addition, there should always be an option to connect with a real person via a chatbot, if needed. Chatbots in healthcare industry are awesome – but as any other great technology, they come with several concerns and limitations.

Chatbots were found to have improved medical service provision by reducing screening times [17] and triaging people with COVID-19 symptoms to direct them toward testing if required. These studies clearly indicate that chatbots were an effective tool for coping with the large numbers of people in the early stages of the COVID-19 pandemic. Overall, this result suggests that although chatbots can achieve useful scalability properties (handling many cases), accuracy is of active concern, and their deployment needs to be evidence-based [23]. While chatbots can provide personalized support to patients, they cannot replace the human touch.

In addition, health chatbots have been deemed promising in terms of consulting patients in need of psychotherapy once COVID-19-related physical distancing measures have been lifted. For example, IBM’s Watson for Oncology examines data from records and medical notes to generate an evidence-based treatment plan for oncologists [34]. Studies have shown that Watson for Oncology still cannot replace experts at this moment, as quite a few cases are not consistent with experts (approximately 73% concordant) [67,68]. Nonetheless, this could be an effective decision-making tool for cancer therapy to standardize treatments. 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.

Our review suggests that healthbots, while potentially transformative in centering care around the user, are in a nascent state of development and require further research on development, automation, and adoption for a population-level health impact. Seventy-four (53%) apps targeted patients with specific illnesses or diseases, sixty (43%) targeted patients’ caregivers or healthy individuals, and six (4%) targeted healthcare providers. The total sample size exceeded seventy-eight as some apps had multiple target populations. We conducted iOS and Google Play application store searches in June and July 2020 using the 42Matters software. A team of two researchers (PP, JR) used the relevant search terms in the “Title” and “Description” categories of the apps. The language was restricted to “English” for the iOS store and “English” and “English (UK)” for the Google Play store.

Depending on their type (more on that below), chatbots can not only provide information but automate certain tasks, like review of insurance claims, evaluation of test results, or appointments scheduling and notifications. By having a smart bot perform these tedious tasks, medical professionals have more time to focus on more critical issues, which ultimately results in better patient care. 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.

It is open-source with available interfaces for Go, Java, JavaScript, Perl, and Python [31]. 2, we briefly present the history of chatbots and highlight the growing interest of the research community. 6, we present the underlying chatbot architecture and the leading platforms for their development. That happens with chatbots that strive to help on all fronts and lack access to consolidated, specialized databases.

Chatbots can help patients feel more comfortable and involved in their healthcare by conversationally engaging with them. 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. Undoubtedly, the accuracy of these chatbots will increase as well but successful adoption of healthcare chatbots will require a lot more than that. It will require a fine balance between human empathy and machine intelligence to develop chatbot solutions that can address healthcare challenges.

Minimum Viable Product (MVP) Development 101: The Main Do’s and Don’Ts

Added life expectancy poses new challenges for both patients and the health care team. For example, many patients now require extended at-home support and monitoring, whereas health care workers deal with an increased workload. Although clinicians’ knowledge base in the use of scientific evidence to guide decision-making has expanded, there are still many other facets to the quality of care that has yet to catch up. Key areas of focus are safety, effectiveness, timeliness, efficiency, equitability, and patient-centered care [20]. Although there are a variety of techniques for the development of chatbots, the general layout is relatively straightforward. As a computer application that uses ML to mimic human conversation, the underlying concept is similar for all types with 4 essential stages (input processing, input understanding, response generation, and response selection) [14].

• In practice, ‘chatbot expertise’ has to do with, for example, giving a correct answer (provision of accurate and relevant information).
• 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).
• We included experimental studies where chatbots were trialed and showed health impacts.
• Chatbots have already gained traction in retail, news media, social media, banking, and customer service.
• 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.

As well, virtual nurses can send daily reminders about the medicine intake, ask patients about their overall well-being, and add new information to the patient’s card. In this way, a patient does not need to directly contact a doctor for an advice and gains more control over their treatment and well-being. Most surprising to Dr. Lee, though, was a use he had not anticipated — doctors were asking ChatGPT to help them communicate with patients in a more compassionate way. They worried, though, that artificial intelligence also offered a perhaps too tempting shortcut to finding diagnoses and medical information that may be incorrect or even fabricated, a frightening prospect in a field like medicine.

This includes the triple aim of health care that encompasses improving the experience of care, improving the health of populations, and reducing per capita costs [21]. Chatbots can improve the quality or experience of care by providing efficient, equitable, and personalized medical services. We can think of them as intermediaries between physicians for facilitating the history taking of sensitive chatbot technology in healthcare and intimate information before consultations. They could also be thought of as decision aids that deliver regular feedback on disease progression and treatment reactions to help clinicians better understand individual conditions. Preventative measures of cancer have become a priority worldwide, as early detection and treatment alone have not been effective in eliminating this disease [22].

The Oxford dictionary defines a chatbot as “a computer program that can hold a conversation with a person, usually over the internet.” They can also be physical entities designed to socially interact with humans or other robots. Predetermined responses are then generated by analyzing user input, on text or spoken ground, and accessing relevant knowledge [3]. Problems arise when dealing with more complex situations in dynamic environments and managing social conversational practices according to specific contexts and unique communication strategies [4]. 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.