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Machine learning may sound like science fiction, but it’s simply software that can analyze data and adjust accordingly without additional input from human operators. By adding machine learning (ML) capabilities to your patient billing department, you can benefit from more efficient processes and workflows. Explore these key advantages of ML implementation in a cloud-based digital patient billing service. 

Delivering an enhanced customer experience and improved service

If your practice still relies on paper billing, machine learning can support the shift to a digital environment. You can quickly and accurately scan and upload paper patient charts with electronic health records software that has ML capabilities, including handwritten records and notes.

This step supports the patient preference to pay bills online, which can increase collection rates and speed up the revenue cycle. According to a July 2021 study published by Insider Intelligence, more than half of patients prefer digital payments. In addition, 32% want to pay by mobile app, and 37% prefer payments through an online portal.

Machine learning in digital patient billing can also improve transparency by delivering accurate patient estimates, one factor that helps establish a trusting provider relationship. Forbes reports that using ML dramatically reduces the time and errors associated with creating these estimates, resulting in a 60% to 100% increase in collections that occur at the point of service.

If your staff spends a lot of time connecting with patients by phone or email about billing, you can take advantage of machine learning and artificial intelligence within a chatbot feature that addresses frequently asked questions for your practice. Examples include “How can I pay my bill?” “What portion of my treatment will insurance cover?” and “How much will I owe on the day of my appointment?”

Increasing patient engagement and payment rates

As patient financial responsibility for their healthcare increases, providing an outstanding customer service experience can encourage retention of your client base;  building strong relationships while simultaneously accelerating the ability to collect payments promptly.

Secure billing software programs with machine learning capabilities can adapt your messages to patients’ preferred methods of contact. Factors such as gender, age, and responses to previous attempts to communicate influence how each person receives bills for healthcare services, appointment reminders, and other messages. In fact, these systems can even determine the ideal day and time to send texts and emails based on open and response rate data. According to MedCityNews, this approach results in an impressive response rate of 76%.

Final Thoughts

Machine learning in digital patient billing may be an entirely new world, but you don’t have to explore it alone. Whether you’re new to high-tech patient financial engagement solutions or have been researching this type of tech for some time, MailMyStatements can help you with smart software and services that drive better billing and higher revenue. Connect with our team today to see if our winning solutions may be a good fit for your practice.