Chatbot use cases in the Covid-19 public health response PMC

The most common anthropomorphic feature was gender with 9 chatbots being female, 5 male, and 1 transgender. In addition, 1 chatbot had its gender randomly assigned for each interaction (Case 22) and 1 gave the user the option to choose (Case 28). Thirty chatbots were embedded within a specific organization’s platform (e.g., Case 1, Clara on the CDC’s website).

• The ability of patients to be directed to urgent referral pathways through early warning signs has been a promising market.
• Due to the small numbers of papers, percentages must be interpreted with caution and only indicate the presence of research in the area rather than an accurate distribution of research.
• For RCTs, the number of participants varied between 20 to 927, whereas user analytics studies considered data from between 129 and 36,070 users.
• In terms of cancer therapy, remote monitoring can support patients by enabling higher dose chemotherapy drug delivery, reducing secondary hospitalizations, and providing health benefits after surgery [73-75].
• In addition, automated diagnosis may be useful when there are not enough specialists to review the images.

Finance bots can effectively monitor and identify any warning signs of fraudulent activity, such as debit card fraud. And if an issue arises, the chatbot immediately alerts the bank as well as the customer. This is one of the chatbot use cases in banking that helps your bank be transparent, and your clients stay on top of their finances.

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Healthcare chatbots automate the information-gathering process while boosting patient engagement. Healthcare chatbots significantly cut unnecessary spending by allowing patients to perform minor treatments or procedures without visiting the doctor. Patients appreciate that using a healthcare chatbot saves time and money, as they don’t have to commute all the way to the doctor’s clinic or the hospital. Furthermore, if there was a long wait time to connect with an agent, 62% of consumers feel more at ease when a chatbot handles their queries, according to Tidio.

30% of patients left an appointment because of long wait times, and 20% of patients permanently changed providers for not being serviced fast enough. Chatbots will not replace doctors in medicine anytime soon, but they will likely become indispensable tools in patient care as AI continues to undergo major breakthroughs. The healthcare chatbot’s market size was valued at around $211 million as of 2022.

Chatbot Reduces Waiting Time

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. Another advantage is that the chatbot has already collected all required data and symptoms before the patient’s visit. Not only does this help health practitioners, but it also alerts patients in case of serious medical conditions.

Therefore, while utilizing official sources is a prudent practice, especially for off-the-shelf solutions and for non-healthcare organizations, more work is required to understand best practices. These mental health chatbots increase access to support and show promising results comparable to human-led treatment based on early studies. Chatbot algorithms are trained on massive healthcare data, including disease symptoms, diagnostics, markers, and available treatments.

Both practitioners as well as patients, can highly benefit from this implementation. Healthcare practices can equip their chatbots to take care of basic queries, collect patient information, and provide health-related chatbot healthcare use cases information whenever needed. As if the massive spike in patient intake and overworked health practitioners were not enough, healthcare professionals were battling with yet another critical aspect.

This highlights a potential tension between privacy and functionality, and balancing these could benefit use cases where follow-up or proactive contact may be useful. 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].

Chatbot History and Evolution

For instance, chatbots can engage patients in their treatment plans, provide educational content, and encourage lifestyle changes, leading to better health outcomes. This interactive model fosters a deeper connection between patients and healthcare services, making patients feel more involved and valued. In terms of cancer diagnostics, AI-based computer vision is a function often used in chatbots that can recognize subtle patterns from images. This would increase physicians’ confidence when identifying cancer types, as even highly trained individuals may not always agree on the diagnosis [52]. 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.

We identified 6 broad use-case categories and 15 use cases where chatbots were deployed in the Covid-19 public health response. Chatbots are scalable, enable social distancing, augment the capacity of healthcare and public health workers, broadly disseminate information, and gather real-time information from a broad audience to inform public health interventions. They can easily be deployed on different platforms and have easy-to-use conversational interfaces that enable broad reach and access to different demographics. Chatbots are most commonly used for information dissemination and risk assessment, which are critical to public health response. Scant attention has been devoted to chatbot deployment to support or gather data from frontline healthcare workers which is suggestive of future work. Finally, the vast majority of chatbots do not follow-up on users beyond an initial interaction or users need to initiate contact.

AI-Powered Health Platform

Create user interfaces for the chatbot if you plan to use it as a distinctive application. 47.5% of the healthcare companies in the US already use AI in their processes, saving 5-10% of spending. All you have to do is create intents and set training phrases to build an extensive question repository.

One of the most prominent AI-powered tools is ChatGPT, a natural language processing model developed by OpenAI. The chatbot inquires about the symptoms the user is experiencing as well as their lifestyle, offers trustworthy information, and then compiles a report on the most likely causes based on the information given. It has been lauded as highly accurate, with detailed explanations and recommendations to seek further health advice for cases that need medical treatment.

The Development and Use of Chatbots in Public Health: Scoping Review

One example of a task-oriented chatbot is a medical chatbot called Omaolo developed by the Finnish Institute for Health and Welfare (THL), which is an online symptom assessment tool (e-questionnaire) (Atique et al. 2020, p. 2464; THL 2020). The chatbot is available in Finnish, Swedish and English, and it currently administers 17 separate symptom assessments. 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).

Consequently, promoting a healthy lifestyle early on is imperative to maintain quality of life, reduce mortality, and decrease the risk of secondary cancers [87]. According to the analysis from the web directory, health promotion chatbots are the most commonly available; however, most of them are only available on a single platform. Thus, interoperability on multiple common platforms is essential for adoption by various types of users across different age groups. In addition, voice and image recognition should also be considered, as most chatbots are still text based. Cancer has become a major health crisis and is the second leading cause of death in the United States [18].

Unlike disease surveillance chatbots where the user initiates the interaction, these chatbots initiate contact with the users and ask questions about symptoms. According to research by Accenture, scaling healthcare chatbots could result in over $3 billion in annual cost savings for the US healthcare system alone by 2023. Another study found that 70% of healthcare organizations are currently piloting or planning to pilot chatbots. Collecting patient health data is crucial to provide proper medical care in the healthcare industry.