AI and NLP have the potential to aid contact centres in the healthcare industry, and it couldn’t arrive at a better moment

According to a 2019 poll by 8×8, a unified communications company, 13% of calls in the healthcare business are terminated before the caller is routed to an agent, and 67% of callers hang up because they are dissatisfied at not being able to talk with a person. For most healthcare customers in 2021, call centre irritation endures.

“Inefficient and costly operations are the most typical challenges in healthcare contact centres,” said Joe Hagan, chief product officer of LumenVox, a voice recognition firm. “As a result of the early 2020 quick transition to remote labour, it became obvious that most contact centres have separate systems and incompatible software, making it impossible to handle growing call volumes and expectations on live agents.”

Being caught up in the COVID-19 epidemic hasn’t helped matters. When call volumes are high, healthcare contact centres must frequently change patient and employee passwords, and the tedium of doing so can slow down the process.

“In many healthcare institutions , healthcarecall centres have become a core aspect in customer service, and they play a major role in healthcare,” said Nick Kagal, vice president of marketing and business development at SpinSci, a customer engagement solutions provider. “Call management is essential for supporting patient demands like as scheduling, prescription refills, care queries, outbound communications, and key information management.”

Healthcare providers are looking to automation technologies like speech recognition to increase efficiency, performance, cost savings, and the patient experience to satisfy high customer service demands. Context artificial intelligence-based voice recognition is one of the technologies they’re using in their contact centres.

“AI can’t accomplish everything a human agent can,” Kagal added, “but it’s typically enough to provide a good reply for simple requests.” “By delegating ordinary, day-to-day queries (such as password resets) to AI, businesses may free up human agents to handle more difficult calls and provide additional operational savings.”

Every client encounter contains a plethora of data, and call centre AI is the tool that can automatically gather it. Simple conversation sentiment analysis may reveal how individuals feel about a business, service, or product. Healthcare call centre agents can record and transcribe service conversations using tools like natural language processing and voice recognition. Supervisors can easily analyse talks at a glance, pick up important details, and identify areas where agents can improve using transcriptions.

“One of the most important ways NLP helps contact centre operations is by assisting software programmes in understanding caller speech patterns and trains of thinking,” Hagan explained.

“This knowledge enables these programmes to provide more accurate patient care. It also aids contact centre technology teams in creating more natural-sounding automated chat and instant messaging exchanges.”

To use NLP in AI, IT departments must first train their voice apps to correctly understand and handle calls fast and accurately. This entails teaching the AI to accurately grasp the caller’s language and intent, as well as ensuring that the app provides a positive customer experience.

“The AI model is given a collection of training data and asked to make judgments based on that information in the initial training process,” Hagan explained. “As errors are discovered, IT staff make improvements to help the AI become more accurate. After the AI has finished its basic training, it is ready to proceed to validation. Using a new set of data, IT teams will test expectations about how effectively the AI will perform in this phase.”

“In the first training phase, the AI model is given a set of training data and instructed to make decisions based on that knowledge,” Hagan noted. “IT staff improves the AI when flaws are identified, allowing it to become more accurate. The AI is now ready to go on to validation after completing its basic training. IT teams will use a new set of data to evaluate expectations for how well the AI will function in this phase.”

Will artificial intelligence (AI) and natural language processing (NLP) improve the call centre experience in healthcare?

Yes, if the system’s request is straightforward, such as making or cancelling an appointment. Callers should still be sent to a qualified person for more difficult situations, such as discussing the findings of a lab test. The key to running a contact centre effectively is determining where this handoff point is and then designing procedures that function well for staff and patients. For healthcare organisations, this is still a work in progress, but the integration of AI technology undoubtedly helps.