How Artificial Intelligence Improves Healthcare Customer Satisfaction Scores

The healthcare industry is under enormous pressure to meet the high standards of customer service that users expect. 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 a poor customer service experience client can affect the business, the bottom line and even the well-being of the patient.

A recent ACSI survey of CSAT rates within industry highlights the many opportunities for improvement, with health insurance companies ranked 36th and hospitals 44th out of 47 industries compared. This survey found that customer satisfaction has been flat for the past five years and identified several key drivers of dissatisfaction, including contact centre support and digital tools. The study found that customers not only want immediate and accurate answers on the digital channels of their choice (phone, chat, WhatsApp, SMS, etc.), but they also want the agent to offer those answers with empathy and attention.

Measurement of Behaviours That Impact Patient Satisfaction

Healthcare companies want to offer the best possible patient experience (PX). 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 and time-consuming task that can be subjective and inconsistent. Without an objective way to assess interactions between agents, the practice can lead to their job dissatisfaction and insufficient understanding of CSAT trends.

This is where Artificial Intelligence (AI) comes in. To be truly successful in today’s marketplace, healthcare organisations need to be able to objectively measure and qualify the specific agent behaviours that have the greatest impact on patient and provider satisfaction levels. To do so, many healthcare companies are incorporating AI solutions into the organisation’s quality and analytics program.

How Artificial Intelligence Improves Healthcare Customer Satisfaction Scores

• Rating the agent’s soft skills behaviours, such as demonstrating empathy, active listening, or acknowledging loyalty.
• Helping agents navigate complex patient issues in real time with prompts for what behaviours are needed or the next best action to take.
• Providing agents the opportunity to positively impact their CSAT scores by highlighting the behaviours necessary to achieve their goal.
• Monitoring and managing patient satisfaction rates.

Enreach Omnichannel Contact Center Artificial Intelligence Module can help healthcare companies. How? Keep reading!

1) Putting your Chatbot and Voicebot at the Service of your Customers

Optimise your communications and increase the effectiveness of your call centre by evaluating the customer’s intention and offering the expected response 24/7. Answer all calls and messages received. Automatically solve the most frequent queries and allow your agents to focus on more important tasks.

2) Technology that Understands, Responds and Analyses

Through Enreach’s Artificial Intelligence engine, you can train your bot to understand the needs of your customers and resolve their queries. Connect our bots with external systems and complete their responses with information from your customers. In addition, you can configure the bot with more than 120 languages, collect information from each interaction, analyse why they contact you and improve responses.

In the highly complex and rapidly changing healthcare industry, customer satisfaction has never been more important. Agent behaviours have a direct influence on patient satisfaction levels, and companies need to understand how these behaviours influence the bottom line if they want to succeed in a highly competitive marketplace.

Common Challenges for Healthcare Organisations

Most call centre interactions in a healthcare organisation are initiated to address something that has gone wrong. These factors put a lot of emotional and performance pressure on the contact centre agent, making soft skills like empathy, active listening, setting expectations, and effective questioning incredibly important. Some of the challenges in delivering better CSAT and customer experiences may include:

• Siloed data: There are large volumes of patient data available, but the data is siled between different types of providers and types of insurance, etc.
• Multi-stakeholders: Agents are tasked with serving multiple stakeholders, including the patient and the care provider.
• Multiple channels: Patients expect to be able to use multiple channels to communicate and find information from their health care providers.
• Generational differences: All age groups need health care but have different preferences for how they want to interact with the health care organisation.
• Resolution of complex queries: Call centre agents have the task of managing a wide range of patients. Almost all interactions are likely to be highly personal and require trained agents who can provide timely, personalised, and empathetic service.