Executive Summary:

With patients taking on greater financial responsibility for their healthcare costs, more Health Systems are relying on digital communication and payment tools. However, shifting to digital is still tough: 77.5% of all healthcare emails are never opened, according to one survey.

While many patients express a desire for paperless statements and self-service payment options, the reality for most health systems is that patient financial engagement has lots of room for improvement. What if there were a way to know the best way to engage patients in order to significantly boost payments and deliver a better patient experience? What if it didn’t involve any more work from already overworked revenue cycle teams?

These are questions the Patientco team asked when testing a new breed of patient communication and payment tools powered by Artificial Intelligence (AI) to support proprietary machine learning models — and in doing so, challenged what “smart” means in an ever-evolving, consumer-driven world.

Impact of Smart Technology:

The Patientco team learned (and the technology continues to learn) that health systems can recognize statistically significant improvements by leveraging smart technology that: 1) analyzes both expressed and implied preferences, and 2) automatically adapts to patients’ engagement to accelerate payments, reduce costs, and increase patient satisfaction.

Redefining Smart Technology:

The definition of smart technology has evolved and today encompasses a much broader range of capabilities and solutions. It’s not unheard of for a company to call its solution “smart” simply because it is intuitive, user friendly, or perhaps has some abilities to give patients choice through self-selected preferences.

Patientco defines smart technology differently. It is a solution that maximizes engagement by dynamically adjusting to continuous analysis of patient payment data (both historical and real time) combined with consumer preferences (both expressed and implied) as well as health system-specific business rules. Smart Technology

The Approach:

Smart technology is only as good as the data it analyzes to find new insights and optimization opportunities. While health systems generate large datasets, few are able to leverage these datasets to influence patient behavior. One healthcare leader remarked to the Patientco team, “We may have a data lake, but I only have puddles of usable information.”

To address this challenge, Patientco developed smart billing and payment technology. This technology leverages machine learning capabilities to determine the best ways to influence patient engagement and payment behavior. Using capabilities such as A/B testing and multi-armed bandit testing, Patientco smart technology analyzes hundreds of data features including:

  • Patient Engagement (opens, clicks, payments initiated)
  • Bill balance
  • Demographics
  • Census data
  • Payment history
  • Patient preferences (expressed and implied)
  • Health System specific business rules
  • Send times/days
  • Offer Sequence
  • Patientco proprietary dataset from +12 million patient interactions

Data Smart Technology

Results:

Consider one recent testing scenario, in which the Patientco team sought to improve the open rate of eBills and increase engagement by experimenting with the ideal day and time to send. This is an ongoing challenge, as standard open rates for healthcare emails hover around 20% according to a leading email provider study.

By analyzing open rates for a series of eBills across an array of days and times using a multi-armed bandit testing methodology, the team learned that emailing patients a bill at noon on any business day (except Friday) increased the engagement rate significantly. Furthermore, one specific day outperformed all the others. The insights generated from this experiment combined with insights from experiments on subject line, eBill design, call to action, and others ultimately boosted open rates to over 50%.

This is just one example: In reality, there are far too many opportunities to test and optimize for at scale without automated technology and data scientists mining the insights. Every adjustment over time has the potential to make small, but cumulatively material improvements in an organization’s revenue cycle outcomes.

The Bottom Line:

Given advances in machine learning, some of the technologies revenue cycle managers call “smart” will quickly become dated. Therefore, healthcare organizations should take advantage of truly smart technology that maximizes payments by creating a better patient experience.

Moving forward, revenue cycle leaders should do the following:

1. Move AWAY from technology requiring manual analysis and adjustment of patient financial engagement tactics. Administrative staff do not have time to analyze every interaction with the billing office. They also do not have time to comb through data to isolate trends and make continuous adjustments.

2. Move AWAY from static technology and toward dynamic solutions that adjust to payment preferences and engagement over time. Patients’ preferences and behaviors are fluid; technology should also continuously adapt, optimizing automatically.

3. Move TOWARD solutions that are always improving through artificial intelligence and machine-learning models to create a smarter payments experience. Smart technology continuously analyzes hundreds of data points to ensure the best possible patient billing experience.

Don’t risk the lifetime value of the patient by simply switching to any modern billing and payments technology. Instead, take a smart approach that is centered on continuously improving the patient experience. Switch to a technology partner that shares your long-term vision. Prompt payments and happier patients will follow.

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