Smart Follow-Ups with GenAI for Patient Retention

Modern healthcare is progressing rapidly, and so are patients, creating a situation where many providers lose patient engagement and, as a result, lose those patients. With digitalization, most patients require digital engagement, and when you fail to provide that, they choose another provider.

A report by Accenture states that digital engagement is a strong predictor of loyalty and retention. Nearly 80% of the younger generation and tech-savvy people are likely to continue with the same provider. This means if you keep your patients engaged enough, you will be less likely to lose them and the revenue generated through them.

One more issue that makes retaining patients a tough task is the lack of response to follow-ups, especially if they lack creativity. However, generating engaging content is not that easy and requires resources and time that many providers do not have.

This is where healthcare GenAI patient follow-up comes in, making it easier to create engaging follow-up messages that won’t get buried. Moreover, it personalizes messages to suit each patient, eliminating the equation that generic messages are equal to instant tune-out and bringing personalized patient outreach into the practice. 

But these are not the only benefits that a healthcare GenAI patient follow-up brings, and this blog will explore the core benefits of generative AI in patient retention. So, let’s get down to it without any further ado!

The Patient Retention Crisis: Why Traditional Follow-Ups Fail

You may have faced a situation where you sent a message to a patient about their upcoming appointment, but got no response from them. This is the first sign that your patient is losing engagement, and there is a chance that you may lose the patient. However, have you ever wondered why this happens frequently? Let me tell you, the problem here is your approach to connecting with them.

Today, we live in a world of constant alerts and notifications, and if you do not personalize them, then your messages get buried. This is why generic messages like “You have an appointment tomorrow” do not work. Along with avoiding generic messages, you also need to get your timing right; if you send a follow-up too early or too late, it loses value. 

Being specific about the content of your message is important because when patients do not understand the relevance, they tend to ignore the messages. You also need to use message channels that patients prefer and use, as using different channels can result in patients overlooking or not receiving them at all.

So, patients want personalization, timely contact, and especially clear, actionable information. When you give them this, lowering your healthcare patient drop-off becomes easier. Moreover, implementing AI-like appointment follow-up AI reduces revenue loss due to missed appointments and delayed treatments.

GenAI Revolution: Personalized Messaging That Connects

Personalization has become a need of this era, as patients are drowning in generic reminders and impersonal notifications. GenAI-powered messaging is finally bringing the much-needed personalized patient outreach to make you heard by patients and keep them engaged.

With generative AI in healthcare messaging, we can finally leave the one-for-all messaging approach behind. Now, you can provide patients with messages that are tailored to their patient records and preferences, like language and style, with multilingual GenAI models.

But what makes GenAI health updates or messages unique from other healthcare AI messaging platforms is its ability to understand the context. It knows patient conditions and for what type of appointment they are coming, along with the right time to send a follow-up. This helps tremendously and lets patients know that you care for and value them.

One more advantage of generative healthcare AI messaging is its emotionally intelligent patient communication. In healthcare, people are anxious, confused, and overwhelmed. GenAI helps bridge the empathy gap by adapting tone, style, and word choice based on each patient’s emotional context. 

Here’s where it gets interesting, as GenAI doesn’t just push a single message and hope for the best. It adapts in real-time based on how a patient engages with a particular message. For instance, if a patient does not respond to a message, then it changes the phrasing next time. 

Multi-Channel Mastery: Text, Email, & Voice Workflows

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