Conversational AI is a solution that incorporates AI techniques such as Natural Language Processing (NLP) and Machine Learning (ML) to automate conversations with end users. They go above and beyond rule-based answering engines to understand the context, analyze the text and speech, the intent behind the questions and also consider the user’s preferences. Machine Learning enables the system to learn from the data it receives as and when it’s available and continuously improve its performance.
Conversational AI bridgesthe gap between humans and software even further, engaging in human like conversations and providing replies to users just like a human being would.
Conversational AI systems have been widely implemented in several industries including Banking, Retail, Marketing, E-commerce and others. But no other industry is riper and provides more impact creating opportunities for conversational AI than Healthcare.
If done right, such AI systems can unburden the maddeningly hectic lives of healthcare workers and have an extensive impact on human lives. Here are some interesting use cases for Conversational AI in healthcare and their important requirements.
One of the most basic implementations of a Conversational AI is that it understands the symptoms that are worded in the user’s query and provides tips, related articles and information about the probable cause, thereby helping patients to get their first directive without any delay.
Virtual Assistants designed and authorized by recognized medical institutions can also play a key role in dispersing critical medical information in a timely manner that can prove to be invaluable. Especially in times of a pandemic, when getting in touch with a physician is really difficult, the quick dispersal of information about the virus, its symptoms and preventive measures would be of the essence. A high performance IVA providing a seamless experience and would essentially cut down the waiting line from hospitals.
Such Conversational AI systems and their impact will be multifold in developing countries having a huge population, with a disproportionate number of physicians and patients.
Conversational AI, apart from disseminating the basic medical information, can also assist people in need of emergency medical assistance based on their symptoms.
This is achieved through a specifically designed diagnostic tool. For example, a simple case of nasal congestion can be addressed by the patient himself through the information provided by the IVA. But if the user describes sudden numbness or weakness in his face or arm, especially in one side of the body, then it could be the sign of a stroke which warrants a hospital visit. The IVA relays the information to the user and can also provide the nearest list of hospitals with their emergency hotline contact numbers based on the location of the user. In a pandemic situation such as this, triaging IVAs could make a huge difference to the already overwhelmed hospitals by performing effective first level screening of patients.
Booking appointments with a specific doctor at a hospital used to be through phone or an email to the hospital’s customer service team. This transitioned to online bookings through the hospital’s website.
Now, the same use case can be implemented through a conversational AI. Users can converse with the bot regarding their symptoms and based on the information, the bot suggests a list of doctors available in the user’s locality, thereby enabling the user to book their visit all through the IVA’s chat interface. The IVA can even list doctors based on specialty that relate to the symptoms being discussed and provide a link to the doctor’s profile so that the user can verify the doctor’s credentials and patient ratings/reviews, before booking an appointment. Hence, educating prospects about the various diseases, precautions and vaccinations that are required and subsequent lead generation can happen within the same conversation.
