How to Use Healthcare Analytics to Provide a Smoother Patient Journey

As technology and data became integral to healthcare, the need for analytics has skyrocketed. Working on data strategies was a top priority for two-thirds of chief data officers in one Deloitte survey. In healthcare, analytics can help you understand your patients, create better experiences and strengthen your revenue cycle. Still, analytics comes in many forms, so you’ll need to find the right tools, data sources and strategies for your practice or facility.

How Healthcare Analytics Can Support Your Patients and Revenue Cycle

Before we explore how to use analytics tools, let’s establish why we use them. Healthcare data analysis offers an array of opportunities, such as:

• Improving decision-making: Data insights help you find areas for improvement and opportunities for growth. Make more informed decisions backed by cold, hard data so you know your resources go to the most effective places. The right tools can also turn those insights into actionable suggestions or automate tasks like outreach.
• Focusing on patients who need extra support: Analytics can investigate many data points, like demographic information and payment histories, to flag patients who may be less likely to pay their bills. You can intervene to ensure timely payments and maintain a positive relationship with the patient.
• Boosting patient engagement: Targeted healthcare analytics allow you to learn more about your patients and reach them in more engaging, enjoyable ways. You can see what they like and what supports your goals. Better engagement can lead to higher satisfaction and more revenue.
• Evaluating initiatives: Analytics is also crucial for evaluating the success of your efforts. Tracking metrics shows whether your strategies achieve the impact you want or if you need to adjust them.
• Making predictions: Predictive analytics in healthcare can help you gauge a customer’s expected behavior based on prior activity. For instance, if they never open your emails but always open your texts, you can predict that a text-based reminder will likely get read.

4 Ways to Use Healthcare Engagement Intelligence to Improve the Patient Journey 

Understanding how your patients engage with you is crucial to improving their experience and, ultimately, your revenue stream. That’s why engagement intelligence is a core component of Millennia’s solution, which helps providers maximize their data and streamline the patient payment experience. It collects data on patient engagement and analyzes it for actionable improvements throughout your revenue cycle and the patient experience.

Here are a few ways you can use analytics and healthcare engagement intelligence to personalize and improve the patient journey.

1. Use Machine Learning Propensity to Pay to Boost Payments and Retention

Machine learning systems learn from data to improve performance over time. With machine learning propensity to pay, you can engage with patients in their preferred ways. For example, the system can analyze various data points, such as:

• Patient demographics.
• Patient preferences.
• Previously used payment methods.
• The time of day patients usually make payments.
• Communication channels used for payment reminders, alerts, etc.

By finding connections between these data points, machine learning propensity to pay can identify engagement methods most likely to lead to payments. For example, one patient might be more likely to make payments after work hours or when they receive a reminder text. Another patient could prefer emails and likes to pay bills during work.

Machine learning calculates the best solutions in the background to help you strengthen your revenue cycle. As out-of-pocket spending continues to rise, a steady cash flow depends on strong payment engagement. More on-time payments can also help patients maintain good standing and a good relationship with your facility.

2. Engage Patients With Targeted, Data-Driven Methods

You can use the same capability to focus on patient engagement and provide your patients’ preferred options. After collecting data on communication preferences — such as receiving statements or reminders via text, email or QR code — you can offer tailored solutions for each person.

Many patients think it’s important for providers to offer customized experiences. Targeted engagement modeling, for instance, builds off the machine learning propensity-to-pay engine to assess each patient’s behaviors and organizational trends. Through its healthcare predictive analytics, it chooses and initiates engagement solutions to reach the patients most effectively.

While boosting payments, targeted engagement provides a more enjoyable experience for each person. For instance, it might not send a reminder to someone who doesn’t need it. This system zeroes in on the patients who need engagement the most while supporting higher satisfaction.

3. Make Big-Picture Decisions

With healthcare engagement intelligence, you can collect information on almost any aspect of the patient experience, such as how satisfied they are with their care and what changes they might want to see. Feed that data into an analytics tool to explore trends and find opportunities. Monitoring satisfaction rates, surveys and other metrics provide better visibility into the patient experience so you can make more informed decisions.

Say your satisfaction rates have dipped. You investigate and find that wait times increased as your business grew — the check-in process got too slow. You explore the options and send out surveys to see if people want to submit intake forms at home and check in from their phones. With positive results and implementation, your satisfaction rates improve. In this example, healthcare analytics successfully identified a problem, confirmed the viability of a solution and measured its success.

Incorporate analytics into your workflow and regularly review the results to learn more about your operations and find new opportunities.

4. Let AI Find Insights From Phone Calls

Every interaction with your patients is an opportunity to learn from them. Unfortunately, phone calls are often a blind spot since they aren’t collected in your system. With the help of AI, you can extract more data from phone calls.

A speech AI tool listens to phone calls and analyzes the contents for information about trends and engagement. It might look for a trigger word like “missing payment” or provide reports for automating quality assurance. Keep recordings and transcriptions on hand to easily review the interactions and dive deeper.

Explore Your Healthcare Analytics With Millennia Patient Payment Solution

Analytics are necessary in any modern healthcare facility, allowing you to understand your patients better and make data-driven changes. For the nonclinical elements of the patient journey, there’s Millennia Patient Payment Solution. Our platform integrates with your electronic health record (EHR) to make healthcare engagement intelligence tools simple and easy to use. Offer your patients a better experience at every stage, from making an appointment to paying a bill.

 Request a Millennia consultation today to learn more about how we can help.