Why AI? Transforming patient account resolution

Ryan Hartman, Alex Boone
| 1/23/2024
Kodiak Solutions

Machine learning, AI, and automation can drive efficiency and value for today’s overstretched account resolution teams.

Artificial intelligence (AI), machine learning, data science. Today’s account resolution teams most likely have heard these terms. But are they using technology effectively to tackle their growing account volumes?

AI is transforming healthcare, other industries, and everyday life, and many opportunities exist for healthcare account resolution teams to harness these technologies. In fact, doing so can drive efficiencies, address challenges, and enhance account resolution, all while helping to secure cash flows amid dwindling resources and staff shortages.

So, why AI?

First, some clarification. The following terms are seemingly ubiquitous but might not be fully understood:

  • AI is a field that combines computer science and robust data sets to enable problem-solving.
  • Machine learning is a set of algorithms that analyze and learn from data. In account resolution, it is useful for identifying patterns, such as those in a set of patient accounts (for example, duplicate payments).
  • Data science is a discipline that combines aspects of math and statistics, AI, and other fields to analyze large data sets and generate meaning from data.

Combined with automation, these tools can aid account resolution teams in addressing organizational challenges, such as inefficiencies in workflows, and industry issues, such as pervasive workforce shortages. For example, manually reviewing accounts takes an incredible amount of time and resources. And many of the accounts have little or no cash value. Applying automation and machine learning to resolving lower-value accounts allows organizations to remove low- or no-value accounts from the account resolution team’s work queue. This in turn redirects staff efforts toward more value-added tasks such as improving collections and reducing costs.

Examples of accounts that are ideal for automation include credit and low-value debit balances. These accounts yield little value but require a great deal of staff time and effort.

If an organization is new to automation, machine learning, and AI, starting with lower-value accounts can help the organization and account resolution staff become more comfortable with these technologies. After successfully implementing the technology on low-value accounts – and as the staff’s comfort level increases – organizations can consider moving to more complex data science tasks that can further optimize their business processes. In general, the focus with using these technologies should be on creating more efficiencies throughout the account resolution team and the organization overall.

Optimize account resolution

While many organizations are trying to use automation, it still can be a difficult undertaking. In fact, nearly half the attendees of a recent Kodiak Solutions webinar replied “True” to the polling statement, “My organization would struggle to implement machine learning and automation.”

Organizations that have made the transition to automating some of their account resolution work processes have some success factors in common. Some keys to success include:

  • Leadership support. As with all important business undertakings, support from the top is crucial. Leaders who embrace AI, machine learning, and automation recognize that dedicated resources and staff are required to back these technologies and act accordingly.
  • A focus on data. Data is essential to successfully incorporating automation into account resolution processes. But organizations need to understand their limitations. For example, do they have visibility into and access to their data? Do they have staff members who can pull the required data? Or do the teams need to work with external vendors to manage their data sets? Leadership should have a good understanding of the organizations’ data capabilities and be willing to adapt their account resolution models based on the available information. Flexibility is key.
  • An open mind. Change is difficult, but it is ever present, especially in a fast-moving industry like healthcare. Lack of engagement, however, can be detrimental to any benefits achieved from the move toward these technologies. With many workers wary about the changes that automation and machine learning will bring to their jobs and organizations, it’s important for leaders to acknowledge the uncertainty that results from change. And then, leadership should embrace the changes and stress the organizational – and individual – benefits these technologies will bring.

As healthcare organizations work to enhance their patient account resolution processes, AI, machine learning, and automation will no doubt be at the forefront. To find out more about how this technology, backed by deep industry knowledge and experience, can optimize your organization’s account resolution, contact Kodiak Solutions’ specialists today.


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Ryan Hartman
Ryan Hartman
Director, Revenue Cycle, Kodiak Solutions 
Alex Boone
Kodiak Solutions