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

The data can be saved further making patient admission, symptom tracking, doctor-patient contact, and medical record-keeping easier. The chatbot offers website visitors several options with clear guidelines on preparing for tests such as non-fasting and fasting health checkups, how to prepare for them, what to expect with results, and more. Conversational AI solutions help track body weight, what and which medications to take, health goals that people are on course to meet, and so on. Within the first 48 hours of its implementation, the MyGov Corona Helpdesk processed over five million conversations from users across the country. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.

Research on the use of chatbots in public health service provision is at an early stage. Although preliminary results do indicate positive effects in a number of application domains, reported findings are for the most part mixed. Studies on the use of chatbots for mental health, in particular anxiety and depression, also seem to show potential, with users reporting positive outcomes on at least some of the measurements taken [33,34,41]. Our inclusion criteria were for the studies that used or evaluated chatbots for the purpose of prevention or intervention and for which the evidence showed a demonstrable health impact. We included experimental studies where chatbots were trialed and showed health impacts. We chose not to distinguish between embodied conversational agents and text-based agents, including both these modalities, as well as chatbots with cartoon-based interfaces.

HIPAA Compliance for the Healthcare Industry

As the chatbot technology in healthcare continuously evolves, it is visible how it is reducing the burden of the already overburdened hospital workforce and improving the scalability of patient communication. Undoubtedly, the accuracy of these chatbots will increase as well but successful adoption of healthcare chatbots will require a lot more than that. It will require a fine balance between human empathy and machine intelligence to develop chatbot solutions that can address healthcare challenges. Leveraging chatbot for healthcare help to know what your patients think about your hospital, doctors, treatment, and overall experience through a simple, automated conversation flow.

In addition, our review explored a broad range of health care topics, and some areas could have been elaborated upon and explored more deeply. Furthermore, only a limited number of studies were included for each subtopic of chatbots for oncology apps because of the scarcity of studies addressing this topic. Future studies should consider refining the search strategy to identify other potentially relevant sources that may have been overlooked and assign multiple reviews to limit individual bias. Survivors of cancer, particularly those who underwent treatment during childhood, are more susceptible to adverse health risks and medical complications. Consequently, promoting a healthy lifestyle early on is imperative to maintain quality of life, reduce mortality, and decrease the risk of secondary cancers [87].

Number 1: Availing Medical Information for Diagnosis

Basically, it is a type of chatbot that comes with higher levels of intelligence that can provide some is because the medical chatbots consider the entire conversation as one and don’t read each line. In addition to this, conversational AI chatbot technology uses NLP and NLU to power the devices for understanding the human language. This is partly because Generative Conversational AI is still evolving and has a long way to go.

Both Marshall and Kalligas pointed out that chatbots could greatly expedite triaging patients and expect it to become a commonplace occurrence in healthcare. Kalligas believes that with AI-powered chatbots, providers will get to the root of a patient’s problem immediately by creating a more personalized, human experience. Whether it’s an urgent care setting or a part of prioritizing population health management practices, chatbots will serve an important function in this area.

Generative AI chatbots can process and convert unstructured medical data into a structured format. This transformation enables the healthcare industry to access comprehensive insights and meaningful information from diverse data sources. For example, Generative AI chatbot can extract relevant information from medical notes and categorize it into specific sections, such as patient history, symptoms, diagnosis, and treatment plans. Similarly, it can analyze medical images to identify abnormalities or assist in diagnosis by comparing them with a vast database of reference images.

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