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thinking inside the box with a provider decision quadrant: monitoring provider network stability

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September 06, 2017

As we’ve explored in earlier blog posts, the provider decision quadrant uses two dimensions—fraud likelihood score and 12 months of paid claim exposure—to classify providers into four groups based on whether they are high or low risk and high or low cost. This framework allows health plans to better understand often subtle differences in provider risk profiles and tailor their fraud, waste, and abuse (FWA) prevention tactics with greater precision. In this final blog post of our series, we’ll examine the movement of providers between quadrants.

 

By examining some simple but critical metrics within the context of the provider decision quadrant, health plans gain an additional level of insight to inform their FWA initiatives and regain some network stability. Identifying and going after high-risk/high-dollar providers are necessary, but catching a provider who is on an upward trajectory of risk is easier and more effective, particularly because it limits long-term exposure. 

negative migration patterns

The health plan’s goal for its provider network is to keep as many providers as possible in the low-risk category, particularly those with significant billings. Providers should be plotted on the provider decision quadrant at least every quarter, if not monthly, so that plans can be alerted to detrimental migration patterns.

 

provider_decision_quadrant_migration.png

Provider migration to either of the high-risk quadrants serves as an early warning sign of providers potentially growing emboldened in their FWA activities. When providers move from the low-risk/low-dollar quadrant to the high-risk/low-dollar quadrant, a plan may see an increase in a provider’s claim edit scoring and claims suspected for FWA. The increased fraud risk score, coupled with the continuation of low exposure, could suggest that the provider is “testing the waters” by spreading out the exposure with more low-dollar treatments that are outside of policy, yet not outright fraudulent.

 

The plan should look at the provider’s billing patterns over an extended period versus simply comparing the provider’s more recent patterns to that of his or her peers. A sustained length of time in the quadrant means it may be time the plan move from monitoring to action. The SIU team may choose to pend payment of all future claims related to the suspicious billing behavior, for example, while clinical analysts review the behavior. 

a smarter approach to FWA mitigation

The U.S. Government Accountability Office estimates that $1 out of every $7 spent on Medicare is lost to fraud and abuse, and commercial payers feel a similar sting. While a good portion of that loss certainly happens in the high-risk/high-dollar quadrant, health plans can cover more ground, better match outreach to risk, and nip many behaviors in the bud if they use the provider decision quadrant approach.

 

Download our Perspective for a deeper look at how health plans can prevent providers from migrating from the low-risk quadrants to the high-risk quadrants.

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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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