Chatbots in Healthcare: Top 6 Use Cases & Examples in 2023

It can provide symptom-based solutions, suggest remedies, and even connect patients to nearby specialists. Healthcare chatbots prove to be particularly beneficial for those individuals suffering from chronic health conditions, such as asthma, diabetes, and others. Chatbots gather user information by asking questions, which can be stored for future reference to personalize the patient’s experience. With this approach, chatbots not only provide helpful information but also build a relationship of trust with patients.

Use case for chatbots in oncology, with examples of current specific applications or proposed designs. Further research and interdisciplinary collaboration could advance this technology to dramatically improve the quality of care for patients, metadialog.com rebalance the workload for clinicians, and revolutionize the practice of medicine. 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.

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In Tess [6], CBT was clubbed with the theory of emotionally focused therapy and motivational interviewing to assist the behavioral counseling of adolescent patients. Similarly, in Woebot [31], CBT was clubbed with motivational interviewing and dialectical behavior therapy to provide emotional support and personalized psychoeducation to resist substance misuse. The theory of motivational interviewing was also used to devise interview questions addressed by NAO [5] (the social robot) and the motivation reinforcement messages provided by Bickmore et al’s [33] Chat1. In HCAI [28], CBT was clubbed with the Diabetes Prevention Program’s curriculum to develop content for conversations on weight loss. Out of the 15 studies, 7 (47%) reported acceptability and engagement of AI chatbots in terms of (1) satisfaction and (2) provision of a nonjudgmental safe space. Similarly, another study (7%) reported that the participants liked the chatbot’s advice one-third of the times [25].

• So, all in all, healthcare virtual assistant chatbots are there to make managing your healthcare as easy as possible.
• For instance, chatbot technology in healthcare can promptly give the doctor information on the patient’s history, illnesses, allergies, check-ups, and other conditions if the patient runs with an attack.
• And finally, patients may feel alienated from their primary care physician or self-diagnose once too often.
• For instance, cloud-based chatbots require less initial investment, they are more accessible and require less customization as compared to on premise based chatbots.
• A comprehensive search was conducted in June 2022 by 3 authors (CCT, SQ, and AA) in 7 bibliographic databases, namely PubMed, IEEE Xplore, ACM Digital Library, PsycINFO, Web of Science, Embase, and JMIR publications.
• 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.

AI chatbots have a low threshold for integration into these traditional services because they do not put a strain on existing resources such as experts, time, money, and effort. The chatbots can be freely deployed through daily use platforms and accessed at any time by the users. The use of chatbots can help integrate behavioral interventions into the daily clinical setting and avoid addition pressure faced by health care providers. For example, chatbots can independently offer low-intensity services such as information delivery to users. Furthermore, chatbots can offer provider-recommendation services, wherein, based on the analysis of real-time user data, the chatbots may offer suggestions to the health care providers to help them offer more effective services [27].

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A friendly AI chatbot that helps collect necessary patient data (e.g., vitals, medical images, symptoms, allergies, chronic diseases) and post-visit feedback. According to G2 Crowd, IDC, and Gartner, IBM’s Watson Assistant is one of the best chatbot builders in the space with leading natural language processing (NLP) and integration capabilities. Chat with a chatbot expert with questions regarding a chatbot for your healthcare business. Learn how SmartBot360 can be used for your needs and whether you need a HIPAA-compliant chatbot. Most chatbots are built by the creator setting up a flow for patients to follow. It typically is limited in the way that a patient can only select from options provided, but if they wanted to type in their question, chatbots that only use a flow system are not going to work well.

Similarly, InnerEye (Microsoft Corp) is a computer-assisted image diagnostic chatbot that recognizes cancers and diseases within the eye but does not directly interact with the user like a chatbot [42]. Even with the rapid advancements of AI in cancer imaging, a major issue is the lack of a gold standard [58]. Knowledge domain classification is based on accessible knowledge or the data used to train the chatbot. Under this category are the open domain for general topics and the closed domain focusing on more specific information. Service-provided classification is dependent on sentimental proximity to the user and the amount of intimate interaction dependent on the task performed. This can be further divided into interpersonal for providing services to transmit information, intrapersonal for companionship or personal support to humans, and interagent to communicate with other chatbots [14].

Getting started with a healthcare chatbot

There are a few things you can do to avoid getting inaccurate information from healthcare chatbots. Healthcare chatbots are still in their early stages, and as such, there is a lack of trust from patients and doctors alike. This can be done by providing a clear explanation of how the chatbot works and what it can do.

• Chatbots are designed to assist patients and avoid issues that may arise during normal business hours, such as waiting on hold for a long time or scheduling appointments that don’t fit into their busy schedules.
• Our team has developed an easy-to-use application with a wide range of functions, a web-based administrative panel, and a health and wellness application for Android and iOS platforms.
• Then, if it detects the patient is severely distressed, it can automatically alert their human therapist or prompt the patient to call their helpline.
• Healthcare chatbots can streamline the process of medical claims and save patients from the hassle of dealing with complex procedures.
• Still, the apparent facility with which the bot could handle medical concerns, in both style and substance, presages an actual, real-world use for these things.
• As there were no predefined or standard thresholds on the number of message exchanges that demonstrates feasibility, it was difficult to interpret whether the AI chatbots were feasible.

To develop an AI-powered healthcare chatbot, ScienceSoft’s software architects usually use the following core architecture and adjust it to the specifics of each project. Deliver your best self-service support experience across all patient engagement points and seamlessly integrate AI-powered agents with existing systems and processes. IBM offers a wide range of existing healthcare templates, including scheduling appointments and paying bills.

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Additionally, chatbots could also be used to automate simple tasks like scheduling appointments or ordering prescription refills, which would free up time for doctors and other staff members. The review found that AI chatbots reported mixed results in terms of feasibility, acceptability, and usability. In the case of feasibility, evidence on the safety of chatbots was quite less because only 7% (1/15) of studies reported safety [22]. As there were no predefined or standard thresholds on the number of message exchanges that demonstrates feasibility, it was difficult to interpret whether the AI chatbots were feasible.

Having 18 years of experience in healthcare IT, ScienceSoft can start your AI chatbot project within a week, plan the chatbot and develop its first version within 2-4 months. When aimed at disease management, AI chatbots can help monitor and assess symptoms and vitals (e.g., if connected to a wearable medical device or a smartwatch). A chatbot checks patients’ symptoms to identify if medical help is required. It also can connect a patient with a physician for a consultation and help medical staff monitor patients’ state. Watson Assistant is there for your patients, helping provide basic medical advice or helping track health goals and recovery.

Collecting Feedback and Claims

SmartBot360 integrates with your workflow and guides each patient according to triage guidelines. Keep logs of each patient neatly sorted and referenceable whether the patient needs digital or in-person help with our CRM integrations or through SmartBot360’s backend API. When a patient strikes up a conversation with a medical representative who may appear human but is an intelligent conversational machine. There are many areas where this technology has been used, such as payments, customer support, and marketing. Robotic process automation in healthcare is a rapidly growing AI technology with the potential to transform the healthcare industry.

First, the majority of the studies (9/15, 60%) used critically selected behavior change theories in the design and delivery of the AI chatbots. More interdisciplinary collaboration between behavioral health experts and computer scientists is required to develop theory-based AI chatbots for behavior change interventions. The chatbot intervention characteristics are summarized in Multimedia Appendix 5 [5,6,21-33]. In more than half of the studies (9/15, 60%), the AI chatbots’ content, features, and interface were designed based on a theory. Each study critically selected theories based on the intervention goals and target beneficiaries. The cognitive behavioral therapy (CBT) was used in Tess [6], Lark Health Coach (HCAI) [28], and Woebot [31] to devise strategies that enhance self-efficacy and sustain behavior change.

Impact of ChatGPT on medical chatbots as a disruptive technology

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. 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.

• Therefore, chatbots have the potential to be integrated into clinical practice by working alongside health practitioners to reduce costs, refine workflow efficiencies, and improve patient outcomes.
• Such technologies can understand clinical concepts (risk factors and symptoms) efficiently, and what is more important, can learn with more data to provide a more accurate preliminary diagnosis.
• For the best results in patient care, hospitals, clinics, and other organizations should integrate bots with medical professionals and psychologists.
• Health chatbots can quickly offer this information to patients, including information about nearby medical facilities, hours of operation, and nearby pharmacies where prescription drugs can be filled.
• Health care data are highly sensitive because of the risk of stigmatization and discrimination if the information is wrongfully disclosed.
• Moreover, training is essential for AI to succeed, which entails the collection of new information as new scenarios arise.

If you are interested in knowing how chatbots work, read our articles on voice recognition applications and natural language processing. This global experience will impact the healthcare industry’s dependence on chatbots, and might provide broad and new chatbot implementation opportunities in the future. Chatbots can extract patient information by asking simple questions such as their name, address, symptoms, current doctor, and insurance details. 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. Conversational chatbots with different intelligence levels can understand the questions of the user and provide answers based on pre-defined labels in the training data.