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thinking inside the box with a provider decision quadrant: identifying FWA and taking action on high-risk providers

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August 24, 2017

So far in our blog series on the provider decision quadrant, we’ve explained how this tool helps health plans fine-tune how they identify and prioritize potential fraud, waste, and abuse (FWA) in their provider networks, and also performed a close examination of providers who reside in the low-risk quadrants. In this blog post, we’ll zero in on the high-risk quadrants, where payers already focus most of their efforts, to determine how the provider decision quadrant influences plan anti-FWA activities for providers in these categories. 

 

provider_decision_quadrant_blog (revised).png 

low dollars versus high dollars

Providers who fall in the upper two quadrants are a higher risk to the health plan because of their fraud likelihood scores, which are derived from variables such as billing history, past fraud behavior, claim edit history, geographic risk, and specialty risk. Based on historical patterns, these providers are more likely to have a higher percentage of claims with “modifier 59,” for example, or a higher percentage of allowed dollars from edit-flagged lines than the geographic average over a set period. Leading indicators such as these allow plans to better target providers for special investigative unit (SIU) attention.

 

Verscend has found that when providers are plotted in the provider decision quadrant, most fall in the low-risk/low-dollar quadrant. The second largest group lands in the high-risk/low-dollar quadrant. Although providers in this second group tend to exhibit fraudulent or abusive behavior, the financial implications to the health plan are relatively insubstantial—a fact that should influence health plan interventions. 

a closer look

To understand the nuances between these two high-risk quadrants, we’ll once again compare them using a set of critical metrics: 

  • Average visits per patient
  • Percentage of edited claims
  • Percentage of providers with recent fraud triggers
  • Percentage of providers with one or more recent claim edits
  • Average claim edit appeal rate

Download our Perspective for our full analysis of non-facility provider data, which yields some expected and unexpected results. First, high-dollar providers have twice the number of average visits per patient and generate fraud triggers at nearly five times the rate of their low-dollar counterparts. Both findings are not only consistent with the high-risk behaviors of providers in this quadrant but likely also contributors to their more significant financial impact on the health plan. Couple that with the fact that these providers are less likely to appeal a claim edit, suggesting an awareness of their behavior, and SIUs have clear direction when it comes to prioritizing providers for an open case.

 

A closer look at the metrics for high-risk/low-dollar providers, however, starts to reveal how all risk is not created equal. These providers are generating a higher percentage of claim edits, but relatively few have recent fraud triggers. In addition, the average claim edit appeal rate is significantly higher. Taken together, these metrics suggest that the behavior of some providers may be less intentional at the same time it has less financial impact.

 

We’ll bring it all together by looking at migration patterns between all four quadrants in our next blog post of this series.

 

Download our latest Perspective for a deeper analysis of the key metrics discussed in this blog and actionable advice for how payers should handle providers that reside in the two high-risk quadrants.

get our perspective 

As chief analytics officer, David Costello works closely with the product, consulting, data operations, and client services teams to ensure that Verscend’s proprietary analytics help our clients meet their business objectives and remain relevant in the industry. Prior to Verscend, David was the chief analytic officer at Press Ganey, where he was responsible for building a set of analytic products that allowed hospitals and provider groups to enhance patient experience, solidify their reimbursements, and identify areas for process improvement and revenue enhancements. David also previously served as SVP of consumer segmentation and engagement strategies at Health Dialog. He holds a BA in Business Administration and Sociology from Northern Michigan University and a MA/PhD in Sociology from the University of Delaware. He also served for four years in the United States Air Force.

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