Medical Chatbots Use Cases, Examples and Case Studies of Generative Conversational AI in Medicine and Health

An interesting use case—mHero33,34—involves facilitating coordination between distributed frontline healthcare workers and health organizations or the Ministry of Health in areas of poor technology infrastructure (1 case). The chatbot can gather real-time data from frontline workers to enable provision of essential support, answer their questions, and provide them with real-time information. Originally developed in response to the Ebola outbreak to reach frontline workers with basic text and audio messages,33 it can now also be implemented in WhatsApp and Facebook messenger. Acropolium provides healthcare bot development services for telemedicine, mental health support, or insurance processing. Skilled in mHealth app building, our engineers can utilize pre-designed building blocks or create custom medical chatbots from the ground up. Chatbot solution for healthcare industry is a program or application designed to interact with users, particularly patients, within the context of healthcare services.

After a person reports their symptoms, chatbots check them against a database of diseases for an appropriate course of action. Chatbots can take the collected data and keep your patients informed with relevant healthcare articles and other content. They can also have set push notifications for when a person’s condition changes. This way, bots can get more information about why the condition changes or book a visit with their doctor to check the symptoms. The COVID-19 pandemic has accelerated the digitization of healthcare services, making this technology more relevant than ever before.

What is the future scope of chatbots in healthcare?

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]. Using a combination of data-driven natural language processing with knowledge-driven diagnostics, this chatbot interviews the patient, understands their chief complaints, and submits reports to physicians for further analysis [43]. Similarly, Sense.ly (Sense.ly, Inc) acts as a web-based nurse to assist in monitoring appointments, managing patients’ conditions, and suggesting therapies.

While the app is overall highly popular, the symptom checker is only a small part of their focus, leaving room for some concern. Medical chatbots might pose concerns about the privacy and security of sensitive patient data. A use case is a specific AI chatbot usage scenario with defined input data, flow, and outcomes. An AI-driven chatbot can identify use cases by understanding users’ intent from their requests.

Collect patient data

This can help service providers better manage patient recovery and healthcare outcomes, as well as reduce healthcare costs by preventing potentially costly medical errors. 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 chatbot use cases in healthcare 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. The search was further limited using the Interactive Advertising Bureau (IAB) categories “Medical Health” and “Healthy Living”.

The most common categories to be combined were risk assessment (22 cases) and information dissemination (21 cases), with the most common multipurpose chatbot combination being these 2 categories (18 co-occurrences). Appendix 2 shows the chatbot use-case combinations for the 15 use cases we identified. A smaller group (3 cases) provides a report and explains the reasons behind their recommendation (Cases 15, 22, and 36).

Provide mental health support

However, more conversational bots, for example, those that strive to help with mental illnesses and conditions, cannot be constructed—at least not easily—using these thought models. This requires the same kind of plasticity from conversations as that between human beings. The division of task-oriented and social chatbots requires additional elements to show the relation among users, experts (professionals) and chatbots. Most chatbot cases—at least task-oriented chatbots—seem to be user facing, that is, they are like a ‘gateway’ between the patient and the HCP. The most famous chatbots currently in use are Siri, Alexa, Google Assistant, Cordana and XiaoIce. Two of the most popular chatbots used in health care are the mental health assistant Woebot and Omaolo, which is used in Finland.

Saba Clinics, Saudi Arabia’s largest multi-speciality skincare and wellness center used WhatsApp chatbot to collect feedback. But the unprecedented challenges in the past few years have shown how vulnerable the sector really is. With every significant disease outbreak and a growing population, providing equal care to every individual is becoming increasingly challenging. Improving human health through the combination of cutting-edge technologies and top medical expertise. This AI-powered chatbot is certainly growing under the supervision of Google’s Research team.

All authors contributed to the assessment of the apps, and to writing of the manuscript. For each app, data on the number of downloads were abstracted for five countries with the highest numbers of downloads over the previous 30 days. Chatbot apps were downloaded globally, including in several African and Asian countries with more limited smartphone penetration. The United States had the highest number of total downloads (~1.9 million downloads, 12 apps), followed by India (~1.4 million downloads, 13 apps) and the Philippines (~1.25 million downloads, 4 apps). Details on the number of downloads and app across the 33 countries are available in Appendix 2. Only ten apps (12%) stated that they were HIPAA compliant, and three (4%) were Child Online Privacy and Protection Act (COPPA)-compliant.

Also, make sure that you check customer feedback where shoppers tell you what they want from your bot. If the answer is yes, make changes to your bot to improve the customer satisfaction of the users. But if the bot recognizes that the symptoms could mean something serious, they can encourage the patient to see a doctor for some check-ups. The chatbot can also book an appointment for the patient straight from the chat. Bots can collect information, such as name, profession, contact details, and medical conditions to create full customer profiles. They can also learn with time the reoccurring symptoms, different preferences, and usual medication.