How Predictive Analytics Solutions Can Reinvent Payment Integrity

Oct 12, 2016

How Predictive Analytics Solutions Can Reinvent Payment Integrity

Few industries suffer from the wasteful spending patterns afflicting the healthcare industry today. Up to 30% or more of the 5 trillion collected yearly for healthcare payments is squandered, often through avoidable mistakes or redundant billing.

For healthcare payers, all the necessary data to avoid wasteful spending exists. However, data mining alone only provides extraction and a cursory glance at corresponding patterns. Deep insight and actionable strategies remain untouched. Taking the payment integrity process one step further by implementing predictive analytics solutions completes the larger forecasting picture.

Here’s how better predictions contribute to an improved and cost-effective claims management process:

Increase Cost Recovery

Without a universal database tracking every point of coverage Americans have, there are bound to be instances of claims payment overlap and duplicate remittance. The lack of incentive for members to report multiple instances of healthcare coverage complicates the payment integrity process with hidden risk of erroneous payment. In fact, 33% of claims expenses are caused by members having multiple policies. Unfortunately, revealing payer overpayment is not as simple as connecting the dots.

Though data mining spots some data that correlates with duplicate coverage, it is the predictive analysis that transforms those findings into a larger net to cast. By itself, data mining presents what is happening without addressing why and which subsequent actions need to be taken.

Here’s an example. Let’s say data mining identifies members who demonstrate fluctuation in coverage periods from one record to the next. Spotting a correlation between inconsistencies in MSP periods or other coverage is possible with data mining. However, the limits of measuring one variable against the control data group keeps growth of cost recovery relatively static.

The three dimensional data modeling available through predictive analytics solutions increases the frequency with which cost recovery actions turn up results. MSP periods measured against the control group (known instances of duplicate coverage) and additional factors elicit greater returns from payment integrity. Being able to determine the probability of a member having a change of coverage or a need to coordinate benefits can make for an extraordinary improvement in payment recoveries.

Improve Labor Force Productivity

Before healthcare payers began the recent trend of strategic mergers and acquisitions to survive market competition, the volume of member data was prodigious. Now, it is almost unmanageable to mine through traditional methods. Without predictive analytics solutions, recovery activities are scattershot and the productivity of a specific investigation is less assured.

In data mining, the lack of multilayered modeling means that trends are less visible from the start. Claims analysts see correlation in the data but often lack the full insight to make cost-effective investigations. Predictive analytics solutions, on the other hand, maximize the time claims analysts are using on useful actions.

For example, claims analysts using our Payment Accuracy Module make the most of their claims investigations. The complexity of predictive modeling notifies analysts of the probability of pre-payment concerns in preventing the need for future payment recovery. Red flags are more obvious and make for a higher percentage of accurate remittance by healthcare providers.

With claims analysts increasing the results of their case investigations, healthcare payers expend less on administrative costs. Fewer analysts are needed to return equal or greater reimbursements with less effort. That diminishes the drain on labor dollars in a tough market.

Putting Predictive Analytics Solutions into Practice

That is just the tip of the iceberg for payment integrity insight. The potential of predictive analytics solutions over traditional data mining opens up insights that would otherwise have remained hidden longer. Inaccurate payments are caught earlier in the process and cost avoidance is three times more successful. However, a large component of successful payment integrity is having experienced professionals guiding the process.

At w3r, we have a team of data specialists who know how to use sophisticated analytics programs, decode insight from large datasets, and create strategies that help healthcare payers attain greater results. Explore our Payment Integrity Assurance solution to determine how we can help you recover claims that are owed to your business.

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