“Giving a voice” to Patients and Employees Through the Art of AI-enabled Listening

AI. The mere mention of the term can generate false expectations, create fear, and/or represent an opportunity to explore new horizons to benefit those we serve. At Inizio Engage, we are harnessing the power of AI to enable better listening on patient support calls in our Patient Solutions programs, resulting in more accurate and supported employees and an enriched understanding of the voices of the patients we serve.

Drawing upon our extensive experience with, and industry knowledge of contact centers and patient support, we have created a customized speech analytics solution on the CallMiner platform. This solution allows us to unpack the emotion and sentiments of the patient with tags created across a variety of different topics, touch points and behaviors, which are customized for the specific needs of our clients. The insights generated surface within hours, or a day of the call, providing the opportunity to make adjustments to a program in close to real-time.

By using this voice analytics tool, we are able to support the emotional well-being of our employees across their calls by tracking when the call(s) get tough and/or stressful for them within minutes to hours of it happening. We can then address these issues more quickly with the necessary empathy and/or coaching tips – all within a day of the call!

This practical application of AI supports our business, sets realistic expectations, and eliminates the fear that comes from not understanding the information source traditionally associated with AI-driven results. Because we drive and fine tune the results from CallMiner’s voice analysis with the tags and algorithms we create for the platform, there is no unknown “black box” to overcome.

How our AI-driven voice analytics platform works

For clients using our speech analytics tool, every recorded call our patient support team makes within our Five9 telephony platform is then exported into our voice analytics tool. Using the tags and algorithms we have established within the platform; every call is then processed near real time to deliver insights for our call team managers and our clients.

Our extensive experience in serving patients within a call center is crucial to this customization. The agent quality scorecard we establish within the customized CallMiner platform is set to look at such things as:

• Did the clinical educator open the call correctly? Take ownership?
• Was the clinical educator polite? Exhibit empathy?
• Did the clinical educator use the proper hold and transfer techniques?
• Did the patient express confusion or dissatisfaction? Was this confusion based on something another vendor in their healthcare chain may have created?
• And other client program-specific tags for targeted analysis.

The subsequent insights help us derive a 360° view of patients as they move through their support journey. A report on all calls made that day can then be provided to our clients in the same day or shortly thereafter. Clients leveraging our speech analytics tool have the distinct advantage of receiving immediate insights from day one. They no longer need to wait for a business review to understand the voice of the patient.

In a recent client program, we were tasked with identifying themes of confusion and dissatisfaction occurring during clinical educator calls. To meet this challenge, we identified a list of targeted sets of phrases in the “understandability” of language and “dissatisfaction” language.  The results led to insights that improved the overall experience for patient and clinical educator. [Click to read the complete Case Study.]

In addition, and perhaps just as importantly, this speech analysis tool allows us to provide our employees with the timely support they need to overcome any confusion or stressors they may experience in their day and reassure them they are not alone when tackling difficult situations. In essence, we are enhancing the overall clinical educator experience by providing them with a well-rounded view of their interactions that:

• Improves performance via automated quality scoring, near real-time coaching and self-coaching.
• Recognizes compliments and customer sentiment improvement leading to improved quality scores.
• Generates well-being through stressful call identification, near real-time support and personalized coaching.

This AI-driven speech analytics tool operates at scale for everyone. Instead of searching for a needle in a haystack, you have a magnet where you have the opportunity to go in and filter on calls that meet the criteria. Rather than hoping to come across certain things, you are doing it a full scale, which means you are getting a more complete perspective.

–Tom Mueller, VP, Digital Innovation & Product Management, Inizio Engage

How AI-driven voice analytics fits within Quality Monitoring

There is an aspect of quality monitoring that is invaluable when done by a person. Clients depend on this intensive review to pick up nuances, trends, product feedback and more.

However, the standard quality monitoring program, done by individual review of a recorded call, requires dedicated resources – supervisors, team leads, managers, and even the business unit director – everyone performing the quality monitoring for specific reasons. This represents a lot of time and expense that can be minimized with our AI tool.

AI-driven speech analytics evaluates the professionalism of quality monitoring and reports on whether or not clinical educators are hitting all the key points as defined by the tags and algorithms. In this respect, our voice analytics tool creates a lot of efficiency.  For example, under standard quality monitoring, a quality monitor can only listen to six-eight calls per day due to the length of the calls. As a result, we might monitor four-five calls per clinical educator, per month, essentially only listening to about 3% of the interactions.

Also, with clinical educators now working virtually, quality monitors no longer have the ability to walk into a call center and listen for tone and accuracy of response. Instead, our voice analysis platform provides the opportunity to monitor what is happening with all clinical educators in almost real time. By using the insights reported, our quality monitors can hone in on the key parts of the interaction to determine how the call is faring and where change might be necessary to address patient or clinical educator needs.

In a recent client engagement, we were tasked to drive operational excellence with our speech analytics tools. The client wished to establish program specific benchmarks for onboarding new team members and performance, monitor interactions at scale, and create a next-day feedback loop for their clinical educators. We used our speech analytics platform and customized scorecard to provide out-of-the-box scoring on core operational metrics including open and close, confidence, politeness and silence time. As a result, we:

• Achieved a 50x increase in the number of calls monitored.
• Identified benchmarks for speed of onboard as well as baselines for silence time on a call to help monitor performance across the team.
• With the start of next day coaching and self-coaching, the team saw rapid improvements in politeness and use of hold language.

In terms of quality monitoring, our customized voice analytics tool works to Improve overall patient support and creates efficiencies for clients in providing near to real-time insights and a reduction of the head count needed for quality monitors.  –Lou Romanoski, V.P., Global Head of Operational Excellence, Inizio Engage

Building an AI-driven Employee Health model

Clinical educators tend to view quality monitoring as a punitive exercise. Traditionally, they are told such things as “You didn’t do this,” “You didn’t open the call properly,” or “You could have done this better.”

With our customization of CallMiner, we are able to round out the quality monitoring process. We take what is often considered a negative situation and convert it to a positive.  Clinical educators get “pats on the back”, reminders and support when needed, all leading to better employee health. –Jim Halloran, Solutions Analyst Speech Analytics, Inizio Engage

Our programs using our customized CallMiner voice analytics platform work differently. In these, we support an Employee Health model in two key areas:

1. How clinical educators handle stress.
   CallMiner indicates when clinical educators are taking tough calls, experiencing a day or period of time where the sentiment, “Boy I hope I don’t get any more calls like this,” is more common than not. The patients on such calls might be experiencing stress as a result of financial strain in affording their medications, they may be belligerent, they may be confused. We work to identify those stressful components of the call, and report back to the manager the same day or next day. The manager is then able to check in on the mental health of the clinical educator shortly thereafter to see how they are feeling and then review if they handled the call correctly and give some coaching tips on how to avoid such stressful situations in the future. We provide empathy and support, reinforcing best practices at the same time.
2. “Kudos metrics.”
   Alternatively, in many instances, the patient on the call indicates that he or she has compliments for the clinical educator. We recognize these compliments, and managers make note to recognize the agents as the compliments occur. We call this kudos metrics. We are also now starting to measure and recognize clinical educators for an “improvement experience,” where the call starts out negatively and they are able to turn it around to positive.

Although this kind of positive reinforcement may come up in an evaluation score card, CallMiner gives us a hard set for measuring the sentiment, listening to key words and the patient’s satisfaction in near real-time, and recognizing the clinical educator shortly thereafter. That art of listening goes beyond what a Quality Monitor might be able to detect while listening to make sure that a call remains within compliance.

Feedback to the voice analysis experience from our clinical educators has been positive, and we are learning a great deal on the patient side as well. This customized voice analytics tool gives us the opportunity to examine key words and key trends in the call that most certainly help our client’s knowledge and gives them the ability to quickly adjust an FAQ or provide more resources to the agent to be more successful.

The next steps in improving our “art of listening”

The immediacy of the insights derived from our customized CallMiner voice analytics platform is very compelling both to Inizio Engage management and our clients. We recognize there is more we can provide with this AI-powered voice analytics tool, evolving beyond its current quality monitoring nature to one of a generative AI tool providing insights into the product and patient based on all calls.  That is the “art of listening” next generation.

Our extensive industry experience and continued significant investments in the most up-to-date technology, vendors, and AI and generative AI tools, combined with our commitment to enriching the health and lives of our employees, allows us to create a rich ecosystem to support our clients’ “listening” requirements today and well into the future.

Inizio Engage is driving transformative change in the health and life sciences industry through cutting-edge innovation and forward-thinking solutions. With CallMiner, Inizio Engage has gained near real-time insights and predictive analytics, providing its clinical educators with top-tier employment opportunities. They have taken an innovative and employee-centric approach to improving employee welfare as a key part of their overall organizational strategy, enhancing efficiency, fostering growth and exceeding client expectations. –Jonathan Ranger, Chief Customer Officer, CallMiner

Learn more about our 2024 LISTEN awards in our implementation of Call Miner.