Chatbot for Health Care and Oncology Applications Using Artificial Intelligence and Machine Learning: Systematic Review PMC
Patients who require medical assistance on a regular basis can benefit from chatbots as well. For example, providers can use bots to create a link between their doctors and patients. Such a bot can provide a detailed record of the tracked health conditions and help assess the effects of prescribed management medication. According to a report from Accenture, over 40% of healthcare executives consider AI the technology that will have the greatest impact on their organizations within the next three years. Healthcare providers are already using various types of artificial intelligence, such as predictive analytics or machine learning, to address various issues.
AI-powered chatbots in healthcare can handle all your appointment bookings, cancellations, and rescheduling needs. Healthcare chatbots deliver information approved by doctors and help seniors schedule appointments if needed. The chatbots healthcare chatbot use cases relieve stress by answering specific health-related questions and creating strong patient engagement. Healthcare chatbots are the next frontier in virtual customer service as well as planning and management in healthcare businesses.
The Bottom Line
The American Medical Association has also adopted the Augmented Intelligence in Health Care policy for the appropriate integration of AI into health care by emphasizing the design approach and enhancement of human intelligence [109]. An area of concern is that chatbots are not covered under the Health Insurance Portability and Accountability Act; therefore, users’ data may be unknowingly sold, traded, and marketed by companies [110]. On the other hand, overregulation may diminish the value of chatbots and decrease the freedom for innovators. Consequently, balancing these opposing aspects is essential to promote benefits and reduce harm to the health care system and society. AI and ML have advanced at an impressive rate and have revealed the potential of chatbots in health care and clinical settings. AI technology outperforms humans in terms of image recognition, risk stratification, improved processing, and 24/7 assistance with data and analysis.
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). Today, advanced AI technologies and various kinds of platforms that house big data (e.g. blockchains) are able to map out and compute in real time most complex data structures. In addition, especially in health care, these systems have been based on theoretical and practical models and methods developed in the field. For example, in the field of psychology, so-called ‘script theory’ provided a formal framework for knowledge (Fischer and Lam 2016).
Chatbot use cases
However, the majority of these AI solutions (focusing on operational performance and clinical outcomes) are still in their infancy. Our data collection was supplemented by accessing these chatbots to gather more information about their design and use. For chatbots not conversing in English, we used Google Translate to understand the interaction. We could not access chatbots that required organizational credentials, customer or patient accounts, local phone numbers (except for the USA), or national identification numbers for access. Therefore, our analysis of design characteristics has an overrepresentation of publicly accessible chatbots.
Differences in language even within the same country, differences in local information and guidelines, and differences in popularity of different social media platforms across countries may limit the scope of such efforts. Nonetheless, economies of effort can occur (as we have observed) through off-the shelf solutions from vendors that organizations can customize to their needs. The 15 use cases that we have identified provide a basis for identifying functionality and customization options for different organizations or constituents.
Advantages of chatbots in healthcare
This way, you’ll know if your products and services match the clients’ expectations. An example of such a chatbot is Florence, a personal medical system designed for people who undergo long-term medical care. Users of the bot can get extra information about clinic locations and benefit from features such as health tracking, medication reminder, and statistics.
It not only improves patient access to immediate health advice but also helps streamline emergency room visits by filtering non-critical cases. Patients can easily book, reschedule, or cancel appointments through a simple, conversational interface. This convenience reduces the administrative load on healthcare staff and minimizes the likelihood of missed appointments, enhancing the efficiency of healthcare delivery. As they interact with patients, they collect valuable health data, which can be analyzed to identify trends, optimize treatment plans, and even predict health risks. This continuous collection and analysis of data ensure that healthcare providers stay informed and make evidence-based decisions, leading to better patient care and outcomes.
The accessibility and anonymity of these chatbots make them a valuable tool for individuals hesitant to seek traditional therapy. They ask patients about their symptoms, analyze responses using AI algorithms, and suggest whether immediate medical attention is required or if home care is sufficient. Healthcare chatbots revolutionize patient interaction by providing a platform for continuous and personalized communication.