Data-driven analytics uncover hidden drains on revenue

Payer organizations, while looking outside for causes of waste, also are finding that scrutinizing their own processes can uncover revenue drains.

Return on investment for fraud programs alone generally run in the range of 10-to-1 to 20-to-1, and when you add on the savings from closing the multitude of waste and abuse gaps, payers are looking at a significant percent of their revenue. What kinds of gaps are being found? Recent experience points to specific areas where hard-to-uncover waste and abuse may be embedded inadvertently in routine processes. Once discovered, some have relatively easy fixes. Savings are magnified when you consider unintended payments that occur over and over again at high volume.

Examples include:

There have been some great results by combining a data-driven approach with the best of the rules-based systems more traditionally used in healthcare. On the data side, analytic tools have been successful in reducing fraud and abuse in the credit card industry. These predictive analytics anticipate new patterns as they are emerging, but before they are widespread.

To this, add a clinically-rich rules-based system. Clinically-rich rules play a crucial role in seeking out pre-specified problems. Common situations can be anticipated with rules that can be built into the aberrancy finder.

For example, a modifier that tends to be abused, or two codes together that represent an inappropriate unbundling, can be flagged. Alerts are created that are triggered when data exceeds the expected rule threshold. The result is a comprehensive dragnet for irregularities. Whether certain aberrancies are caused by a policy gap or inappropriate billing may require human interpretation, but the process can be automated up to that point.

A sophisticated rules-based solution, on its own, cannot keep pace with the dynamic nature of healthcare where billing methods constantly evolve, for better and worse. And a data-driven solution alone, without an infusion of clinically-based rules, can drive many false leads.

Early experience with these powerful new tools has pointed to common and inadvertent gaps that reduce payment optimization. Every plan has different gaps, and examining one area often reveals an unexpected problem elsewhere. Even plans that aren't yet using data-driven analytics can optimize their existing systems.

This includes:

As solutions are sought that can diminish waste and abuse, all indicators point to the importance of paying consistently and accurately in accordance with contracts, and doing so transparently. This means full disclosure of payment-and the more accessible the disclosure, the better. An online portal can show a payer as well as a provider what code edits a claim encountered, plus the clinical rationale for those edits.

Such tools are important toward finding and eliminating the processes that lead to waste and abuse. As important as it is for a provider to file claims that are in line with a payer's policies, it also is incumbent on the payer to ensure that its automated systems and processes are up-to-date with current policies.

Tune Ups Needed

Ongoing attention to the potential for waste is crucial. Plans too often start looking for the cause of a problem after an alarming signal appears in a mid-year report. By then, it may not be worth the time and resources for payment recovery, despite substantial losses. A reasonable impulse is to institute periodic checks.

By using current data, we can flag aberrancies before money is paid out. Older-generation systems seek out abuse and waste in data that is at least 30 days old. However, chasing money costs more than preventing it from going out the door in the first place.

Finding the source of waste provides an opportunity to correct it-sometimes before payment (If outliers are flagged, claims for the relevant codes can be pended for review, for example). The plan can address the root cause by changing an internal process, writing a rule to plug a policy gap, or embarking on an outreach and education program with providers. Once the problem is addressed, the analytics can recalibrate because the gap has been systematically closed.

An occasional check under the hood cannot keep up with a rapidly changing environment however. We must be checking the oil, the battery and multiple other dashboard indicators at all times. A plan must be constantly closing gaps and tightening up payment policy and processes, as well as extending constant vigilance for potential abuse.

Opportunities exist to stem the loss from excessive payments. Powerful new data-driven technologies, proven to curtail losses in other industries, are now armed with clinical intelligence to address waste and abuse in healthcare. These tools, used properly and consistently, make it possible for organizations to perform continuous payment optimization that is in sync with the dynamic nature of healthcare.

Jim Evans is vice president, claims performance for McKesson Health Solutions.