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How artificial intelligence improves healthcare customer satisfaction scores



by Brooke Phillips


The healthcare industry is under tremendous pressure to meet the high standards of customer service that consumers have come to expect from online retailers. Healthcare executives have made it a strategic priority post-pandemic to actively measure and improve customer satisfaction (CSAT), as they have witnessed the many ways poor customer service experience can affect the business, the bottom line, and even the well-being of the patient.

A recent survey of CSAT rates within the industry highlights the many opportunities for improvement, with health insurance companies ranked 36th and hospitals ranked 44th out of the 47 benchmarked industries. The 2022 J.D. Power U.S. Commercial Member Health Plan Study found that health plan customer satisfaction has been flat over the past five years and identified several key drivers of dissatisfaction, including contact center support and digital tools. The study found that customers not only want immediate, accurate answers on whatever platform might feel best to them (phone, online, chat, etc.), but they also want the agent to provide those answers with empathy and care.

While the pandemic response and recovery has resulted in delays in digital optimization and adoption, healthcare reform targeted at the integration of disparate technology systems and increasing transparency around the cost of care is starting to prompt change. Both reforms require intensive efforts to integrate patient and member data from a variety of third-party sources, which can be difficult to do in an industry that has generally resisted the use of advanced technologies.

Measuring the behaviors that impact patient satisfaction Healthcare companies want to deliver the best customer experience that they can. Many of them, especially those working with legacy technology systems, have tried to achieve this by hiring workers to listen to hundreds of hours of random customer interactions—an expensive, time-consuming undertaking that can be subjective and inconsistent. Without an objective way to evaluate interactions across agents, the practice can lead to agent job dissatisfaction, a high number of quality score disputes, and insufficient insight into CSAT trends.

This is where artificial intelligence (AI) comes in. To be truly successful in today’s marketplace, healthcare organizations must be able to objectively measure and score the specific agent behaviors that have the greatest impact on patient and provider satisfaction levels. To do so, many healthcare companies are incorporating AI solutions into the organization’s larger analytics and quality program, which can help them:

  • Score agent soft-skill behaviors, like demonstrating empathy, actively listening, or acknowledging loyalty.

  • Assist agents navigating complex member issues in real time with prompts on which behaviors are needed or the next-best action to take.

  • Provide agents with the opportunity to positively impact their CSAT outcomes by highlighting the behaviors needed to achieve their goal.

  • Monitor and manage the rates of member patient satisfaction, which could impact a provider’s Medicare gold star rating and reimbursement rate for the care provided.

Consider, for example, one leading Fortune 100 healthcare provider that wanted better insight into its agent-patient interactions. The organization recognized how complex the healthcare system had become for every patient, provider, and participant and had seen the stagnation in company CSAT scores. Its leaders wanted to better understand their agent behaviors at scale, ensure compliance, and gain a deeper understanding of patient intent and satisfaction. They decided AI-driven software was the way to achieve their goals. Now armed with the AI-driven ability to monitor and capture insights from every single agent interaction, the business has been able to easily categorize the reasons and outcomes for every call.

In the highly complex and quickly changing healthcare industry, customer satisfaction has never been more important. Agent behaviors have a direct influence on member satisfaction levels, and companies need to understand how their agent’s behaviors are influencing the bottom line if they want to succeed in a very competitive marketplace. Learn more about the new ways technology like AI is transforming the healthcare industry from the call center out.

Common challenges for healthcare organizations Most contact center interactions in a healthcare organization are initiated to address something that has gone wrong. These factors place a lot of emotional and performance pressure on the contact center agent, making soft skills like empathy, active listening, setting expectations, and effective questioning incredibly important. Some of the challenges to providing improved customer experiences and CSAT for members can include:

  • Siloed (member) data: Vast volumes of patient data are available, but data is siloed across different types of providers and types of insurance, etc.

  • Multiple stakeholders: Agents are tasked with serving various stakeholders, including the member, the care provider, and even the employer.

  • Fragmented (member) journeys: Each insurance member journey is unique, resulting in fragmented journeys.

  • Multiple channels: Members expect to be able to use multiple channels to communicate and seek information from their healthcare providers.

  • Generational differences: All age groups need healthcare but have different preferences about how they want to interact with the healthcare organization.

  • Wide range of member issues: Contact center agents are tasked with handling a wide range of patients. Just about every interaction is likely a highly personal one requiring skilled agents who can provide timely, personalized, and empathetic service.


Brooke Phillips Brooke is a senior product marketing manager with over 15 years of marketing communications experience in b2b technology, having worked for large enterprises as well as several start-ups. Her industry marketing experience includes media, intelligent transportation services, and business consulting. At NICE, she is focused on product messaging and positioning for customer engagement analytics and Enlighten AI.

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