Have you ever visited a website and used a chatbot, only to learn that it doesn’t have the answer for which you’re looking? You are given an assortment of choices, but none of them match what you want to know. 

Chatbots offer a lot of advantages for large companies, enabling them to provide a level of communication outside of emails and phone calls. Many, however, only give specific, scripted answers to a predetermined set of questions. If your question doesn’t match those responses, you’re out of luck. 

Advances in technology — especially machine learning and natural language processing — have broadened the capabilities of chatbots by putting artificial intelligence (AI) at the center. Instead of rules-based programming, which limits customer queries, businesses are employing conversational artificial intelligence. 

Just how big is conversational AI? AIM Research predicts that 40 percent of enterprise applications are expected to incorporate this technology in 2024, up from a mere five percent in 2020. 

Conversational AI is not only for large businesses, though. It is increasingly being utilized in healthcare organizations of all sizes, from appointment scheduling to post-appointment follow-up care. 

How Conversational AI Communicates 

Conversational artificial intelligence is used to deliver scalable and less costly medical support solutions that can help at any time via smartphone apps or online. It consists of computer systems that communicate with users through natural language user interfaces involving images, text and voice. It automates more natural, human-like interactions — or conversations — between computers and users. 

By combining advanced automation, artificial intelligence and natural language processing to enable comprehension of and response to human language, conversational AI can be used by healthcare providers to respond to common patient questions and streamline some administrative tasks. It achieves this by generating clear answers that mimic human interaction and asking follow-up questions if necessary. 

Conversational AI Vs. Rules-Based Chatbots: What is the Difference? 

Not all chatbots use artificial intelligence. Unlike conversational AI solutions, rules-based chatbots map out conversations based on user input and only answer queries that fit into pre-set questions and/or comments.  They follow a decision-tree matrix to guide users toward a specific action or answer and often provide robotic-like responses, which can result in a frustrating interaction and a negative patient experience. 

In addition to being equipped to provide a more flexible conversational flow, conversational AI technology learns from information gathered and is built to understand patterns of human behavior. The result is a variety of helpful responses to basic and complex patient questions. Plus, many conversational AI solutions understand multiple languages, allowing patients to interact using their native language without the need for coordinating translation services. 

When rules-based chatbots are used in healthcare, they are less likely to meet patient expectations. That means that along with lower patient satisfaction, physician practices and other healthcare providers experience decreased patient retention and added work for already understaffed patient-facing team members. 

The Benefits Conversational AI Brings to Healthcare 

Don’t just take our word for it — there is research on the perks of conversational AI for healthcare. Some studies have shown advantages of the use of conversational AI in different healthcare settings, such as enabling behavior change, coaching to support a healthy lifestyle, helping breast cancer patients and self-anamnesis for therapy patients. Other studies have shown some positive evidence for the usefulness and usability of conversational artificial intelligence to support the management of different chronic diseases. Users’ feedback shows helpfulness, satisfaction and ease of use in more than half of the included studies. 

Then there’s the cost savings. AI adoption within the next five years using today’s technologies could result in savings of 5 to 10 percent of national healthcare spending — $200 billion to $360 billion annually — without sacrificing quality and access. Based on AI-driven use cases, physician practices could save three to eight percent of costs, amounting to between $20 billion and $60 billion in savings. 

Conversational AI enables patients to procure quick and accurate information without having to speak to someone in their provider’s office. These tools provide 24/7 availability, meeting patients’ preferences for convenience that drive healthcare consumerism. They promote increased access to care and can be tailored toward a targeted patient population or for a specific medical group to provide more personalized interactions. 

Another merit of conversational AI is enhanced patient engagement. When patients have more convenient access to care through self-service, they are more likely to have a better overall experience with their healthcare provider, promoting increased engagement and better health outcomes. 

By streamlining and automating administrative tasks, conversational AI enables physician practice staff members to spend more time providing quality care to patients. Fewer phone calls and emails from patients also allow these team members to focus on other important tasks, resulting in increased productivity, improved staff satisfaction, lower costs and a higher patient retention rate. 

How Is Conversational AI Utilized in Healthcare? 

Employed by a growing number of medical groups, conversational AI is most commonly used for appointment scheduling — and rescheduling — along with clinical outreach. The technology offers reduced wait times for patients and fewer no-shows for providers. Physician practices can monitor utilization trends to schedule staff accordingly. 

Conversational AI can be used as a tool to help patients manage chronic conditions and increase rates of preventative screening. Through such solutions, patient outreach can be scaled to direct patients to the right level of care to close gaps in care — whether an in-office appointment or an at-home screening. Other uses of conversational artificial intelligence in healthcare include:

  • Communicating lab prep education
  • Providing guidance on self-care
  • Performing patient navigation to schedule and complete recommended care 
  • Conducting post-discharge follow-up
  • Retrieving basic billing information
  • Answering common patient questions about symptoms

Even healthcare payers can use conversational AI. Use cases consist of improving claims management (i.e., automating prior authorization), managing provider relationships and enhancing provider directory management.

Schedule a demo with us to learn how employing Providertech’s conversational AI solution can help you increase patient engagement while reducing the administrative burden on your staff.