Industry Voices—Making provider directories accurate is hard. Finding a solution could solve a lot of problems

Directory errors can lead to accidental visits to out-of-network providers. This often results in surprise bills for out-of-network charges, which are often much higher than in-network allowed amounts. (Getty/AndreyPopov)

Much has been said about California Senate Bill 137 (SB 137) since it was passed in late 2015. In short, SB 137 requires “a health plan or insurer to make available a directory of contracting providers, with specified requirements for completeness and accuracy." This sent provider directory stakeholders in California scurrying to comply.

Perhaps the most compelling part of the bill is something that is not found in the bill at all.

When California Senator Ed Hernandez introduced the bill in January 2015, it specified that “the insurer shall ensure that the accuracy of the provider directory meets or exceeds 97%.” The version of the bill as signed by Governor Jerry Brown makes no reference to an accuracy standard or anything approaching 97%.

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What happened? Is accuracy not important? That can’t be: Regulators—and the plaintiffs’ bar—are of the mind that inaccurate directories pose a barrier to care for health plan enrollees.

RELATED: Study: Inaccurate provider directories disrupt care access

Legislators may have omitted the standard because they came to the same conclusion that industry had: Accuracy is hard. 

Just how (in)accurate are provider directories? The Centers for Medicare & Medicaid Services (CMS) recently released the results of its third round of annual review of the Medicare Advantage Organizations (MAOs) provider directories; the results were better than the second round, but the bar was low. Close to 49% of provider locations had at least one error in them, and “inaccuracies with the highest likelihood of preventing access to care were found in 41.75% of all locations.” 

Starting in 2017, Qualified Health Plans were required to make their directories available in machine-readable format, dubbed “public use files”—or PUF—by CMS. These files were thought to “increase transparency by allowing … software developers to access provider data and create innovative and informative tools to assist customers in understanding plans’ provider networks.” A noble intent, to be sure; however, when one considers the results of a recent poll of PUF accuracy conducted by Ribbon Health, these directories are even less accurate than those for MAOs.

Although the two studies contained methodological differences, the takeaway is that provider directory accuracy leaves much to be desired. How did directories become so inaccurate? This problem didn’t happen overnight.

To answer this question, one has to consider the data that are contained—or intended to be contained—in a health plan’s provider directory. In short, these data are complex in that they need to incorporate myriad data elements such as contracting relationships, network tiers, and multiple provider locations. The data are dynamic and constantly changing. One example of this is the requirement for directories to indicate which providers are accepting new patients. Setting aside for a moment the nuance in how the value of this data field is determined, one can imagine the difficulty a health plan would have in ensuring that this field is current and up to date.

Further, these data are highly variable across the various and disparate data sources in which they are found, often even within the four walls of a health plan. Finally, CMS holds plans responsible for not only keeping provider directories up to date but also meeting stringent medical loss ratio requirements in doing so. This means that plans are asked to do more with less.

The potential ripple effects of directory errors are easy to imagine: a patient relies on a directory to choose a provider and attempts to contact the provider but can’t due to an inaccurate phone number; or the patient goes to visit the provider to receive healthcare services and relies on an inaccurate address in the directory. The directory is intended, indeed required, to include in-network providers; however, inaccuracies can lead to an accidental visit to an out-of-network provider.

This often results in a surprise bill for out-of-network charges, which are often much higher than in-network allowed amounts. This has garnered the serious attention of state —and perhaps soon, federal—legislators.

CMS doesn’t miss an opportunity to remind health plans of its authority to issue civil monetary penalties and enrollment sanctions due to provider directory deficiencies. To date, CMS has not issued either in response to its aforementioned reviews of MAO online provider directories. However, this does not mean that CMS has let MAOs off the hook; to wit, it issued compliance actions to all but two of the MAOs included in the third round of review.

RELATED: Medicare Advantage provider directories are riddled with errors. They're not the only ones

Further, when announcing an unanticipated fourth round of review, CMS reiterated its position that a “centralized repository for provider data is a key component missing from the accurate provider directory equation.” CMS cedes that such a database “will take time and does not obviate the short-term, immediate need … to improve directories.”

So what is to be done to fill the immediate need? An increasing number of stakeholders—each with their own tech and approach—are putting their best thinking toward this issue. For example, the recently rebranded California Symphony Provider Directory proposes to “design a platform that makes it easier to meet SB 137, Medicare and Medi-Cal requirements.”

This model leverages a cloud-based platform on which plans and providers share information, which leans heavily on provider engagement to address the accuracy issue. The Synaptic Health Alliance—originally comprised of Humana, Multiplan, Optum, Quest Diagnostics, and UnitedHealthcare—proposes to “explore how blockchain technology can be used to help ensure that provider directories contain the most current and accurate information possible.” It was recently announced that Aetna (and presumably by extension, CVS) and Ascension have joined in this effort.

The aforementioned Ribbon Health espouses to use predictive analytics and algorithms to “find truth in messy and noisy physician information.”

Astute observers of this space maintain that the problem will not be solved by one solution in isolation. However, if Voltaire was right when he said that “no problem can survive the assault of sustained thinking,” it will be an interesting journey to find a solution.

Brian Hoyt is a managing director at Berkeley Research Group, where he advises clients including Fortune 20 companies and Am Law 100 law firms in implementing a data-driven approach to identify and analyze critical business issues.

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