Conversation intelligence software, which uses artificial intelligence (AI) to analyze speech or text and extract unique and actionable insights for sales, customer experience, marketing and other teams, has become increasingly popular among B2B firms. Companies like Salesforce and Outreach have developed conversation intelligence technologies that analyze hundreds of thousands of text and voice exchanges to empower sales teams with real-time, data-driven insights into the optimal approach for success based on each prospect’s unique context and pain points.

The benefits of such technology may be obvious in the world of customer experience, where misunderstanding a user’s needs and challenges, bad timing, a few poor turns of phrase, or even the wrong tone can cause friction and lead to product abandonment or poor customer satisfaction.  But conversation intelligence has far-reaching applications beyond the B2B context, offering organizations of all stripes deeper insight into the behavior and challenges of both their clients and employees.

A new frontier in healthcare

Healthcare is a prime use case. In order to determine the effectiveness of a telehealth program, for example, healthcare organizations have traditionally needed to glean insights from patient portal usage, post-call surveys and Net Promoter Score questionnaires with low response rates, or wait for long-term clinical outcomes to take shape. While there are certainly valuable insights to be found by examining these metrics, none offer the clarity and immediacy of a live interaction. 

This is doubly true if an organization’s goal is assessing staff and operational efficiency, since live interactions make up a significant portion of care management teams’ daily duties and – given the limited amount of time each patient spends with a care team member – can have an outsized impact on patient health, engagement and satisfaction.

The trouble has been analyzing those conversations at scale. While they can take notes and create reports on their interactions, care team members are typically the only ones who have any sense of how these conversations unfolded. They also have no easy way to share insights or get feedback from team members and managers to ensures they’re operating effectively and efficiently. Post-COVID-19, this sort of close examination of individual interactions is effectively impossible without AI assistance. Indeed, a recent study by McKinsey found that virtual visits have stabilized at levels 38 times higher than before the start of the pandemic.

By combining real-time and historical analysis of patient-provider interactions with health records, encounter notes, historical behavioral data and previous clinical interventions and outcomes, conversation intelligence can give healthcare organizations unprecedented visibility into the words, strategies and workflows of their top performers. These insights can also be shared in real time and used to help other care team members unlock their full potential and drive positive health outcomes, engagement and patient satisfaction. 

Conversation intelligence can also offer relief from the demands virtual care places on care teams already stretched thin. By analyzing patient-provider interactions and offering personalized insights on the best approach and follow-up, conversation intelligence can help care teams streamline workflows and support larger case loads without risking burnout. 

This is especially true in the context of chronic care management, which sees care management teams maintaining long-term relationships with patients in order to educate and motivate them to adhere to necessary care plans and enjoy a better quality of life. 

With the help of conversation intelligence, care teams can get a comprehensive, contextual understanding of these patients and their unique long-term goals and challenges, without drowning in a sea of previous encounter notes, medical records and remote monitoring data. This could not only lead to deeper patient-provider relationships, but also higher patient and staff satisfaction with each encounter.

Untapped potential

By taking advantage of conversation intelligence technologies, healthcare providers can: 

  • Evaluate care team performance with hard data. Conversation intelligence can analyze patient-provider interactions and subsequent clinical and operational outcomes to surface insights on an individual care team member’s successes and areas of opportunity, allowing for truly personalized and evidence-based coaching and performance evaluation.
  • Offer personalized coaching in real-time. As a virtual coaching tool, conversation intelligence can draw on the work of an organization’s top performers to offer real-time assessment, guidance and nudging that helps underperforming or inexperienced care team members refine their approach and be more effective and efficient at the point of care.
  • Save time with workflow automation. It’s often said every hour with a patient meant two hours of admin work. Conversation intelligence can combine an analysis of historical patient-provider interactions and clinician workflows to automate administrative activities and anticipate the needs of clinicians by surfacing the right information at the right time, improving the efficiency of interactions both in real time and long term.

As you can see, drawing on the unique insights offered by conversation intelligence, care teams not only can zero-in on the key behaviors, coaching styles and workflows that drive engagement and satisfaction among both patients and staff, but also uncover new metrics by which to measure organizational success and develop internal training.

Waleed Mohsen

Author Waleed Mohsen

Waleed Mohsen is the co-founder and CEO of mynurse.ai. He has been named a UCSF Rosenman Innovator and has over 10 years of experience working with leaders of hospitals and medical institutions in his business development roles at Siemens and Cisco.

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