Chatbots in Healthcare: Six Use Cases

Benefits of Chatbots in Healthcare: 9 Use Cases of Healthcare Chatbots

chatbot healthcare use cases

Utilizing chatbots in healthcare can save time and money by helping with several tasks including processing insurance claims, handling appointment scheduling, dispensing prescriptions, and managing patient information. 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. A chatbot designed specifically for the needs of a medical center could allow patients to book their appointments in less than a minute without ever having to get in touch with a human agent or receptionist. 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.

For instance, a Level 1 maturity chatbot only provides pre-built responses to clearly-stated questions without the capacity to follow through with any deviations. If you are already trying to leverage Chatbot for your enterprise, feel free to connect with a leading chatbot development company in India for the project. The scalability of chatbots allows a single system to be used throughout a hospital or across an entire district. Wellness programs, or corporate fitness initiatives, are gaining popularity across organizations in all business sectors. Studies show companies with wellness programs have fewer employee illnesses and are less likely to be hit with massive health care costs.

Medical device regulation

Studies have shown that the interpretation of medical images for the diagnosis of tumors performs equally well or better with AI compared with experts [53-56]. In addition, automated diagnosis may be useful when there are not enough specialists to review the images. This was made possible through deep learning algorithms in combination with the increasing availability of databases for the tasks of detection, segmentation, and classification [57]. For example, Medical Sieve (IBM Corp) is a chatbot that examines radiological images to aid and communicate with cardiologists and radiologists to identify issues quickly and reliably [24]. 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].

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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].

Checking Symptoms

Both Conversa Health and Therachat have already put this use case well into practice, using the automated tech to keep constant contact between patients and their providers. Chatbots designed to not just actively capture but captivate the patients’ interest regarding their care calls into question if the tech can further engage patients to improve outcomes. If you are still looking for a healthcare bot development partner then DevTeam.Space can help you.

ChatGPT can use its language processing and machine learning algorithms to understand and interpret patient information, insurance information, and medical codes. It could then use this information to determine coverage and automatically submit claims to the patient’s insurance company. AI chatbots can be integrated into existing healthcare systems through APIs (Application Programming Interfaces), SDKs (Software Development Kits), or custom development. AI chatbots that have been upgraded with NLP can interpret your input and provide replies that are appropriate to your conversational style. Chatbots for mental health can help patients feel better by having a conversation with the person. Patients can talk about their stress, anxiety, or any other feelings they’re experiencing at the time.

Evidence for the Efficacy of Chatbot-Based Health Interventions

These include ethical considerations and concerns surrounding the use of Conversational AI without human intervention in sensitive healthcare settings. While Conversational AI holds immense potential to transform the healthcare industry, there are several drawbacks and challenges that must be considered. As with any technology, there are both ethical and practical considerations that need to be taken into account before widespread adoption. Healthily is an AI-enabled health-tech platform that offers patients personalized health information through a chatbot.


In the medical context, AI-powered chatbots can be used to triage patients and guide them to receive the appropriate help. Chatbots are considered a more reliable and accurate alternative to online searches patients carry out when they’re trying to understand the cause of their symptoms. Read this article to learn everything you need to know about the use of chatbots in healthcare and discover 5 insightful use cases that display their potential. 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.

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. Promising progress has also been made in using AI for radiotherapy to reduce the workload of radiation staff or identify at-risk patients by collecting outcomes before and after treatment [70].

chatbot healthcare use cases

Handling billings and claims in a medical institute is a very tedious and ongoing process. Therefore, the majority of the institutes keep healthcare AI bots that can help in checking the present coverage of the patient’s insurance, help to file claims, and track those claims’ status. AI-powered telehealth solutions can bridge the gap between patients and healthcare providers in remote or underserved areas by enabling virtual consultations, remote monitoring, and timely interventions. Many chatbots rely on scripted responses and rule-based programming, limiting their capabilities to providing simple answers to specific questions. In contrast, conversational AI delivers more advanced and natural interactions. Artificial intelligence platforms have the potential to be seamlessly integrated into your existing business systems, including legacy medical software upgrades, through APIs.

If you’re looking to get started with healthcare chatbots, be sure to check out our case study training data for chatbots. By providing patients with the ability to chat with a bot, healthcare chatbots can help to increase the accuracy of medical diagnoses. This is because bots can ask questions and gather information from patients in a more natural way than a human doctor can. Additionally, bots can also access medical records and databases to provide doctors with more accurate information.

chatbot healthcare use cases

This feedback concerning doctors, treatments, and patient experience has the potential to change the outlook of your healthcare institution, all via a simple automated conversation. By adding a healthcare chatbot to your customer support, you can combat the challenges effectively and give the scalability to handle conversations in real-time. 69% of customers prefer communicating with chatbots for simpler support queries. Real time chat is now the primary way businesses and customers want to connect.

This growth can be attributed to the fact that chatbot technology in healthcare is doing more than having conversations. AI chatbots in the healthcare sector can be leveraged to collect, store, and maintain patient data. This can be recalled whenever necessary to help healthcare practitioners keep track of patient health, and understand a patient’s medical history, prescriptions, tests ordered, and so much more. Undoubtedly, medical chatbots will become more accurate, but that alone won’t be enough to ensure their successful acceptance in the healthcare industry. As the healthcare industry is a mix of empathy and treatments, a similar balance will have to be created for chatbots to become more successful and accepted in the future.

  • This enables firms to significantly scale up their customer support capacity, be available to offer 24/7 assistance, and allow their human support staff to focus on more critical tasks.
  • This case study comes from a travel Agency Amtrak which deployed a bot that answered, on average, 5 million questions a year.
  • Still, it may not work for a doctor seeking information about drug dosages or adverse effects.
  • In turn, the system might give reminders for crucial acts and, if necessary, alert a physician.
  • Both of these use cases of chatbots can help you increase sales and conversion rates.
  • Whether it’s generating detailed invoices or resolving claims issues, AI does so by integrating with existing healthcare systems, ensuring accuracy and a unified patient experience.

Finally, there is the challenge of integrating Conversational AI with existing healthcare systems and workflows. This requires significant investment in resources and infrastructure, as well as buy-in from healthcare providers and administrators. Without proper planning and execution, the adoption of Conversational AI in healthcare could create more problems than it solves. While AI is transformative, human touch remains invaluable, especially in sensitive areas like healthcare. By analyzing patient language and sentiments during interactions, it can gauge a patient’s emotional state. With an increasing emphasis on patient-centric care, Conversational AI acts as a pivotal touchpoint between healthcare professionals and their patients.

  • Health care data are highly sensitive because of the risk of stigmatization and discrimination if the information is wrongfully disclosed.
  • However, the successful adoption of healthcare chatbots will require a fine balance between human understanding and machine intelligence to develop chatbot solutions that can address healthcare challenges.
  • Cem’s work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.
  • For example, a bot can answer questions such as which documents are necessary to receive treatment, what the payment tariffs are, how much is covered by the insurance, or what are the business hours.

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