AI: A practical solution for patient hub services

Katie Wilson, managing principal, patient support services, at IQVIA, discussed how the company is leveraging AI within its patient relationship management (PRM) software to improve patient experience.

Kicking off her presentation at Access USA, “A Realistic Look at AI in Hub Services,” Wilson took a step back to reflect on the evolution of patient support services, noting the simple days of small molecule therapies and patient assistance programs to the current unique landscape of cell and gene therapies.

Patient support has had to transform to meet the challenges of increasingly complex therapies, payer hurdles, and patient needs.

“When you think about using AI in services, it’s obviously going to improve patient engagement. We can now look at behavioral information and predict what the patient might need,” she said, discussing IQVIA’s one-year-old PRM software.

“As we think about how we’re going to be able to utilize behavioral science insights, plus data, plus AI, we’re really going to be able to change the game over the next several years in patient services.”

One the most notable AI applications in IQVIA’s system is its real-time sentiment analysis, she pointed out.

“It’s essentially emojis. So it’s either a smiley face or a frowny face, and as the patient or the caller is talking to you, it changes as the conversation goes on,” she explained. This allows agents, such as nurse navigators or care managers, to gauge patient sentiment and adjust in real time accordingly.

Beyond emotional intelligence, Wilson explained how AI is also driving operational efficiencies at scale. That means transcriptions and summaries of complex case details and “listening” to consistently retrieve approved communication documents, she noted in her presentation deck.

“We can make edits to what we’re saying and how we’re saying it based on how it’s coming through,” she said. “We can pull information from different parts of the system to say, hey, you might need this knowledge or information to answer this question on this call. So it’s a kind of constantly listening in the background.”

What’s going to “change the game,” Wilson said, is redefining quality standards. With AI, IQVIA’s system can audit beyond sample sizes, search natural language, and report advanced analytics.

“Now we can audit almost everything. So [with] that advanced analytics and being able to apply AI on top of that and continue to ask questions, it’s pretty informative,” she said.

Wilson also added that AI had improved training and compliance. It’s enabling real-time call monitoring across all cases, instantly flagging cases that require agent retraining and other actions.

Although, IQVIA utilizes AI in the patient management system, Wilson made it clear it’s only used in the background. “It doesn’t interact with patients or providers or the callers that are calling in. It’s just for our agents.”

Early learnings

With IQVIA’s system only being one years old, Wilson provided the audience with lessons learned from implementation.

The first is change management. For example, some agents expressed skepticism toward the technology, and they continue manual notetaking despite available AI transcriptions.

“It just goes to show, you need to make sure they understand that. Give them time in the sandbox, to play around with it, and to test it. It is their words summarizing, but they do need to play with it to trust it,” she said.

Other early lessons Wilson noted are the evolution of metrics and speed and accuracy. Traditional metrics for agents, like average speed to answer, is becoming less relevant. “What we’ve seen, now that we have sentiment analysis, is it actually doesn't matter if our answer is 30 seconds or two minutes, the sentiment stays the same if you answer their question,” she said, adding that the focus has shifted to a one-call resolution and patient satisfaction.

Lastly, is saying goodbye to “swivel chair” approach, where agents juggled multiple systems and had to manually input data. In this case, patient support agents are logging into a CRM system to access patient information, then “swiveling” to another system to enter data or get result, then swiveling back to the CRM to update records.

“It’s not that efficient for our agents,” Wilson emphasized. “That has an impact on the patients and the people that we’re talking to on the phone because they can hear us pause, they can hear us doing different things … It’s got to be a very convoluted system to manage all these services over the last couple years.

“So really moving away from that is important as we as we think of AI.”

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