Skip to main content Skip to footer Skip to menu

Using AI for More Patient-Centric Healthcare

A recent poll by the American Academy of Physician Associates (AAPA) found that U.S. adults spend the equivalent of an entire workday every month coordinating healthcare for themselves or their family.

The survey also found most patients understand the challenges that the industry faces; 47% of adults believe their healthcare providers are burned out and 71% feel the demands on providers are increasingly burdensome.

In order to improve the currently rocky status quo, many healthcare leaders are bringing a customer service mindset to patient experience – and technology is helping them do it. 

With AI, the healthcare sector is advancing faster toward a more patient-centric model where automation truly helps customers and doesn’t frustrate them. This transformation is redefining contact centers by streamlining operations, increasing access and personalizing patient care.

As providers navigate the automation landscape, it’s crucial to understand how AI enables more efficient and effective care. Here’s a look at some of the most impactful ways AI is changing the patient experience: 

Reducing complexity and eliminating friction 

Jeffery Sturman, SVP & Chief Digital Officer at Memorial Health Systems, is one of many leaders who feels the traditional patient experience model often creates obstacles that negatively impact patients and providers. He’s taken a focused approach to simplifying a complex healthcare system by placing an emphasis on the contact center.

“It’s not just building facilities and thinking that hospitals are the mecca… I think there’s an element of customer service that can be used to improve an environment that’s so hard to navigate,” he says. “I think if we can remove a lot of the friction you’re going to ultimately improve outcomes.”

For patients, AI is being used to remove the most common complexities they face by making tasks that were previously time-consuming seamless. Through intelligent routing, for example, AI can swiftly direct patient queries to the most appropriate care provider, reducing wait times and frustration.

Further up the automation scale, AI is being used to complete requests like scheduling, intake, account management, outbound reminders, and prescription management as effectively as human agents.

By resolving a higher volume of calls, AI helps free agents and clinicians and makes it easier for patients to get human support when they need it. Thus a smoother, simplified healthcare journey for every patient. 

Improving accessibility where patients need it most

Today’s AI solutions far outperform IVRs and first-generation chatbots in their ability to serve a wider patient base, actually resolve complex requests and reduce escalations.

AI gives patients the ability to speak naturally, as quickly or slowly as they want, and in any language while fully completing their requests at up to a 90% resolution rate. These accessibility improvements are especially critical in healthcare, where caller demographics are more varied than any other industry. 

In one case study, AI reduced both the average handle time and call escalation rate by 50% for a customer base that is almost entirely senior-age. That means their customers no longer have to deal with the typical burdens of automation like repeating themselves, waiting on hold or getting stuck in IVR menus. 

“Accessibility improves outcomes,” says Sturman. “If it’s easier to get to a doctor, if it’s easier to get a test, easier to get advice the first time you will have better outcomes.”

Of the eight hours that Americans spend each month coordinating healthcare, much of that time is spent on the phone. By optimizing the most common healthcare experience with AI, providers immediately take a massive step toward reducing patient frustration. 

No-wait support for patients’ most common requests

Far and away, one of the most AI-ready call types in healthcare is appointment management. As one of the highest volume requests, resolving appointment calls is traditionally an involved process for both agents and patients, with rescheduling, cancellations and no-shows often done over the phone.

With AI, automating even a single flow of the appointment scheduling process can lead to massive gains in both patient experience and contact center efficiency. In the case of Southwest Medical Imaging, implementing AI to automate exam confirmations and cancellations eliminated the need for agents to spend hours a week assisting customers with appointments and manually updating internal systems. 

This led agents’ average answer rate to increase from about 73% to over 90%, while caller abandonment rates dropped from around 25% to as low as 5% on average.

In addition, appointment availability became accurate in real-time, allowing more available slots to be filled and reducing unrealized revenue. Finally, with omnichannel features and always-on support, patients can get a consistent experience across every channel and resolve inquiries 24/7. 

Meet your SLAs and lower contact center costs

The primary cause of today’s status quo, where a majority of Americans get overwhelmed when managing their healthcare, is lack of resources. Agent attrition, nursing shortages, and budget restrictions have all led to declining metrics for SLAs like average speed to answer, customer satisfaction and first call resolution. 

AI has already proven to be instrumental in helping healthcare organizations meet their objectives with patients while also managing to lower operational costs. There are two reasons for this.

The first is that AI doesn’t aim to deflect patients to self-service options, which often leads to call-backs. It resolves their requests just as an agent would and, in cases where a handoff is needed, completes the initial steps of the request on behalf of agents before transferring. 

The second is that it offloads call volume from agents and clinicians, a substantial benefit in a world where staffing and retaining talent has never been harder. “It’s a win-win across the board,” says Sturman. “Not to mention the revenue side of things, because if I do all of that I can create more volume because things are getting done in a much quicker fashion.”

For many contact centers, AI-powered customer service has improved first call resolution rate for common requests with 50% lower costs, while opening up more agent capacity.

Starting and scaling customer service AI securely

Security and compliance are paramount in healthcare and leaders must have an airtight strategy to successfully implement AI into their patient experience. That’s why it’s equally important to partner with a trusted solution provider if you want to ensure AI systems are designed to be abundantly safe, enterprise-ready and compliant. 

Your solution provider should work with you every step of the way to design a solution that is not only efficient and accessible, but redacts sensitive information, prevents conversations from being used to train Large Language Models, and incorporates HIPAA-compliant authentication to safeguard patient data from the moment every interaction begins.

From a process standpoint, healthcare contact centers can customize, secure and deploy AI in as little as 10 weeks. A good place to start is with a call assessment, which determines which of your call drivers are most AI-ready by analyzing your data and costs.

Not only will this show your quickest path to scaling a solution, it will outline a business case of using AI for operational savings, smarter agent staffing, and most importantly a more patient-centric experience. 

design element
design element
Request a free
call assessment
Schedule a call with an expert