Preparing for the No Surprises Act: How Automation Can Help Solve the Supplier Directory Problem


The No Surprises Act (NSA) comes into effect on January 1, 2022. We know what that means for patients: a welcome respite from unexpected medical bills resulting from circumstances beyond their control. But what about other stakeholders, like insurance companies? One of the provisions of the No Surprises Act requires health plans to update their supplier directories more frequently. This goes to the root cause of surprise billing, which is the ability of patients to easily identify providers who are part of the network. If payers can update their directories in just 48 hours, as required by law, patients will have a much better chance of finding care that is actually covered by their plans.

Sounds reasonable, right?

Except for the fact that health plans deal with an avalanche of vendor data at any given time. And data doesn’t flow seamlessly through a shared platform between payers and providers. Payors literally receive Excel spreadsheets from hundreds of different vendor groups, each with their own unique and ever-changing models. The data is so messy that all plans have dedicated staff whose job it is to assess, interpret, clean up, and then enter it into the plan’s system. It’s no surprise – pun intended – that these updates can take weeks, cost millions of dollars a year, and still have accuracy rates as low as 60%. This is extremely problematic, as plans rely on this information not only to update their supplier directories, but also to determine which suppliers should be paid at contract rates, for specialty and license updates, and for changes to billing information that are necessary to properly pay claims.

While historically it has been difficult for payers to solve all of these issues, recent advances in machine learning and artificial intelligence are now making it possible to automate the millions of human hours spent on cleaning and typing. of these data each year, as well as to improve their accuracy. . Think of it this way: landscapers have machines that help them shovel, so they can focus on the beauty of a garden. And to give an example of another industry where human lives are at stake, pilots make all flight decisions, not planes.

These are two examples of technologies that help humans easily and safely perform large amounts of work. If plans use these technologies, not only will they comply with the No Surprises Act, but they will also be empowered to bring employees back to their core business: keeping members healthy.

How payers should think about automation

There are three main things to keep in mind over the next few months as health insurers consider leveraging automation to help them comply with the No Surprise Act.

  1. Find out what automation can and can’t do. Automation cannot completely solve the problem of global interoperability. However, some of the more sophisticated platforms can sit between disparate systems and act like a translator. If plans start with coding the knowledge that resides in the staff who cleaned and entered that data, and then feed it to an algorithm, that algorithm can take on the work associated with understanding the data. In simpler terms, if an automation tool has all the information about how humans made decisions about handling that data, then it can apply that same decision framework, but in a much more efficient way. and consistent.
  2. Assess the situation and set realistic goals for yourself. Under current manual processes, how long does it take on average for the payer to complete vendor updates? What percentage of updates are correct? What types of issues does the plan have most often with the data it receives (is it missing column headers and / or has empty fields in Excel files, from listed vendors? at the wrong practice locations, or something)? The answers to these questions will vary from one payer to another, as will the improvement goals. National plans obviously receive larger volumes of supplier data than those dedicated to individual markets. Some plans have already started documenting their data processing decision trees, while others have not even identified the need for this documentation. Health plans that are more advanced may want to set goals beyond what is required by the No Surprises law, aiming for a turnaround time of less than 24 hours for supplier updates (as opposed to 48 hours). that will be needed) and accuracy levels of 95% or better. These are reasonable goals, given the power of automation tools available to solve this problem today.
  3. Understand the range of automation solutions available. Not all automation solutions are created equal. Some require a “rip and replace” approach that payers may find disruptive to existing IT infrastructure, but other solutions may actually coexist with current systems. Solutions also vary in terms of the type of data they are able to automate: insurers should seek out those that are sophisticated enough to cope with the mess inherent in human-generated data. Finally, payers should look for an automation partner who provides human support in addition to the technology. You don’t need to have an in-house team of data scientists to take advantage of automation. The right partner can help assess needs and set goals, provide advice on how to document current manual processes, set expectations for when the automation rolls out and, of course, speed up the schedule. .

January 1, 2022 may still seem a long way off, but given the upcoming vacations and free time people typically take in the fourth quarter of the year, the deadline for the No Surprises Act is practically near. Payers who want to be in compliance with its provision on the supplier directory must act now.

Photo: fizkes, Getty Images


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