Overpayment Solutions Require Multipayer Data, Payer/Provider Collaboration

For health care providers and payers, investigating and resolving overpayment issues is costly. Solving health care claims overpayments takes leveraging technology across multiple payers and the collaborative effort of payors and providers, according to Terry Cameron, Senior Vice President of Payment Integrity Services at Emdeon. Focusing on prepayment solutions and educating providers to prevent overpayments from occurring in the first place is much more effective than following the current pay and chase method, Cameron said. “Providers need to know how to bill, when to bill, and what is appropriate billing from health care plan to health care plan.” Working for a vendor that moves claims from providers to payers, Cameron has had first hand experience monitoring claims, accurately identifying aberrant claims by using more effective data models across multiple payers, communicating problems, and educating payers and providers. Cameron presented approaches for solving claim overpayments based on his knowledge at a webinar sponsored by the Health Care Compliance Association (HCCA) on Monday, November 18, 2013.

Problems with Current Processes for Overpayment Identification

“Overpayments are a cause of significant lost and delayed revenue,” Cameron explained. Between $68 and $226 billion is lost annually to fraud, waste, and abuse in the health care industry, with abuse accounting for about 10 percent of health care spending.  Although the pay and chase postpayment recovery model will continue to be implemented because an HHS ruling states that only fraud program recovery costs can apply to medical loss ratio rates, and the Recovery Audit Contractor program identifies and corrects improper payments that have been made on claims, these processes do not serve the overall problem well, Cameron stated.  Payers are applying payer-centric models to a provider-centric problem and are not leveraging technology on prepayment claims or using multiple payer data.  The current processes do not identify provider aberrancies accurately, missing some and identifying others that might not constitute fraud or abuse when seen in the bigger picture of multiple payers. Rather than applying to the 20 percent of providers whose practices may be considered fraudulent or abusive, all providers have the potential of being impacted in some way under the current methods. Simplifying the process and use of similar payment rules by multiple payers would result in faster processing of claims and improvement in the revenue cycle.

Approaches to Solving Claims Overpayments

Cameron recommends that providers integrate fraud, waste, and abuse analytics into their workflow and monitor claims submissions. In addition, providers should score risks identified in their networks and proactively reduce risks through appropriate interventions.  Although health plans are investing money in technology to identify and prevent overpayments, the investments “have not produced the returns promised or expected,” Cameron said. He stressed that health plans should leverage technology to prevent overpayments in the first place with prepayment review and augment postpayment recovery approaches with prepayment solutions. “A strategy that includes claims scoring predictive analytics and rules-based detection technologies is vital for today’s health plans,” he added. Moreover, payers must have an adequate and trained staff to manage the solutions.

Cameron suggested a multi-payer data approach to identifying overpayments and outlier claims, explaining that more value is offered when health plans can trace a doctor’s billing patterns across multiple payers. By looking at multipayer databases and across providers, it is easier to identify providers with aberrant patterns and score them on the level of risk of fraud, Cameron added.  Not all outliers are fraud; there might be a good reason for the aberrant pattern. If the pattern is aberrant but not fraud, the payer can educate the provider and provide an opportunity for the provider to make changes, Cameron explained. Health plans also can implement analytic technologies that combine predictive, data-driven, integrated code edits, and clinical aberrancy rules to identify claim outliers at the time a claim is adjudication, Cameron said. “These data-driven analytical solutions examine hundreds of variables and can detect unknown and emerging patterns and can rank each claim to determine the measure of risk it represents.”