Driving Value from Healthcare Customer Conversations: An Interview with Amy Brown, CEO of Authenticx

In an exclusive Q&A session with Amy Brown, the founder and CEO of Authenticx, we delve into the innovative approach of leveraging generative AI to unlock valuable insights from healthcare customer conversations. Amy shares insights into the inspiration behind Authenticx’s AI solution, its impact on the pharmaceutical industry, and the challenges faced by healthcare organizations in analyzing vast volumes of conversational data. Additionally, she discusses the platform’s role in improving patient experiences, ensuring data security, and the future advancements envisioned in healthcare customer experience data analysis.

1. Can you tell us more about the inspiration behind the development of Authenticx’s generative AI solution for healthcare customer experience data?

It’s essential for any type of AI adoption to start by identifying a real problem. One common problem is that organizations don’t realize where complex processes negatively impact the customer experience.

In my field, and at Authenticx in particular, we see the impact of listening to stories woven within conversational data daily. These exchanges — whether recorded contact center calls, chat conversations or even human-chatbot interactions — hold a wealth of information. And it’s too much information for any human or team to sift through and analyze. AI helps us structure and organize conversation data at scale to identify operational inefficiencies in customer experience. Generative AI specifically takes this structured data and summarizes takeaways and insights that allow you to contextualize and act on the information. This makes it easier to quickly gauge if patients are adequately supported and identify where they are not and what you can do about it.

2. How does Authenticx’s platform leverage its 7 billion parameter large language model to extract key insights from recorded customer conversations?

We have intentionally invested in healthcare-specific large language models by people with expertise in healthcare, social work, listening for data insights, and validating AI models.

Authenticx employs LLMs to summarize conversations, identify and monitor HIPAA-related interactions and topics, and locate instances of the Eddy Effect™ – the only commercially available customer friction model that identifies patient frustration, employee training opportunities, and barriers in continuing therapy. Other models are used to audit adverse events, identify and acknowledge safety events (such as product quality complaints), sentiment analysis, and agent quality.

3. In what ways do you see generative AI solutions like Authenticx’s impacting the pharmaceutical industry’s ability to derive value from customer interactions?

Access to conversation data empowers pharmaceutical companies to become more agile and responsive to the market. This real-time intel informs communication strategies, patient support and access barriers, and competitive insights.

The best approach to understanding current friction points is to listen to conversations where barriers are encountered. Generative AI in our platform allows users to unlock conversation data insights with reliable insights that analyze and summarize large volumes of data to drive informed decision-making and effective communication. Organizations will proactively be able to understand roadblocks at scale and remedy the real frustrations healthcare customers and agents experience.

4. Could you share some examples or case studies of how Authenticx’s platform has helped healthcare organizations uncover valuable insights from customer and clinical trial interactions?

Authenticx analyzed thousands of conversations around a newly launched infusion therapy for elderly patients. Within 30 days, they uncovered three key friction points: completing consent forms, accessing infusion sites, and understanding therapy costs/coverage. Their analysis revealed high rates of unresolved issues in these areas.

Armed with these insights, the manufacturer simplified the consent process, updated the infusion site locator tool, and clarified insurance coverage, resulting in drastic reductions in unresolved consent issues, patients struggling to find sites, and frontline staff better equipped to support patients through the diagnostic stage. Authenticx enabled the manufacturer to pinpoint tactical actions to streamline adoption and increase patient access.

5. What are the main challenges that healthcare organizations face when trying to analyze and derive insights from large volumes of customer conversations?

Healthcare data often resides in fragmented silos across different departments, systems and organizations. Organizing this disparate data into a unified platform for analysis is often complex and resource-intensive. Stringent regulations like HIPAA necessitate robust data security measures to protect sensitive, personally identifiable information (PII).

And, of course, there’s the human resources involved. Extracting meaningful insights from vast amounts of data requires time and capacity.

6. How does Authenticx ensure the security and privacy of sensitive customer data while extracting insights through its platform?

We have policies and procedures to ensure that information is kept safe, that communications are secure, and that we adhere to regulations like HIPAA  and GDPR. For example, we can anonymize data by removing or obfuscating PII before processing conversations. We limit data access to only the necessary personnel and grant minimum privileges needed to perform job functions to prevent unauthorized use.

7. With the rise of AI and data analytics in healthcare, how do you see Authenticx’s solution evolving to meet the changing needs of the industry?

Thinking of AI as a means to identify signals of disruption or opportunity can enormously impact healthcare business strategy. AI helps enhance listening so that your team can focus on taking action.

The Authenticx platform leverages gathered data to pinpoint causation and existing barriers patients face. We identify disruptions in conversations and then dive into the topics and themes that drove those obstacles in the first place. These insights are critical as the healthcare industry innovates and invests in digital transformation to help streamline complex processes.

8. Can you discuss the process of implementing Authenticx’s platform within a healthcare organization? What are the typical steps and considerations?

Authenticx offers various software bundles that can be customized to an organization’s needs and goals. Once determined, our onboarding team will work with the organization to integrate Authenticx with their existing data systems to intake conversations and provide data insights.

9. What are some of the key benefits that pharmaceutical organizations can expect to see from using Authenticx’s generative AI solution?

We collaborate closely with brand teams throughout the entire therapy lifecycle. By leveraging the Authenticx platform, brand teams gain valuable insights into the effectiveness of their launch plan and patient service support to identify areas for improvement, ultimately leading to better patient experiences.

10. Looking ahead, what future developments or advancements can we expect from Authenticx in the realm of healthcare customer experience data analysis?

We plan to continue to lean in on healthcare-specific AI models that reliably provide insights into existing barriers inside the healthcare system. Future developments include providing real-time agent coaching recommendations, proactively identifying conversation trends due to frequency or topic content, and enhanced reporting capabilities.

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