Upcoding. Overpayment. Out-and-out fraud. By some estimates, such vulnerability adds up to hundreds of billions of dollars of unnecessary healthcare spending each year. Yet healthcare still struggles to get at the root of fraud, waste and abuse (FWA). Why has this consistently been the case, when we all understand the imperative to find a solution?
Although waste from miscoding or upcoding has mostly been addressed, and fraud efforts continue to build at the federal and state levels, the middle ground of complex wasteful or abusive billing remains largely elusive, such as:
• Claims that are against payment policy where the policy has no associated adjudication rules in place
• Claims that meet payment policy by themselves but are associated with a procedure not covered by plan medical policy
• New treatment areas that have less-established policies
• Outdated provider contract terms
To make matters worse, these vulnerabilities only stand to increase with the adoption of more complex reimbursement models and the transition to ICD-10. Each change brings with it a degree of new-adopter confusion that can create inefficiencies and opportunities for exploitation.
To be fair, many factors stand in the way of fast, accurate payment. Payment systems function in an environment of ever-changing rules, coding practices and billing patterns, and they often respond sluggishly with outdated tools. Coordination among various departments such as claims operations, provider audit, and special investigations can be difficult, with each having different practices and short-term goals. In addition, expected transparency about payment rules effectively hands abusive providers the playbook on how to get claims through adjudication. For example, a health plan's medical policies on the Web describe what services are covered for specific diagnoses. Or claims editing systems necessarily detail why a claim is denied and what is required for it to be paid.
So what can payers do to address this middle ground of waste and abuse -- in a time of increasing payment complexity -- for quicker savings involving less pay-and-chase and payer-provider conflict?
The first step is to look at your claims editing system rules and ensure that you are maximizing the use of your current tools to automatically stop all of the known areas of wasteful or abusive billing -- fixing rules or creating new ones that stop claims that clearly show over-utilization or misuse of established coding and payment guidelines. Claim analytics will help you. This entails engaging the services of experts in claims behavior and your claims system to analyze and optimize the behavior of your system based on how claims are processed through the full set of rules available to you. Ask your claims editing vendor if your agreement includes these services.
Next, focus on new and emerging schemes and patterns that rules-based systems can't catch until the claims operations team knows about them. Manual audits are a slow and resource intensive way to identify unknown issues. In addition, they address only part of the problem -- large-dollar claims -- part of the time. Meanwhile, the less attention-getting smaller issues add up. For example, a health plan could be paying unnecessarily for an investigative procedure based on a specific lab code that usually raises no alarm bells in claims systems. By itself, the abuse is small, but by the time the payer discovers this abuse a year later by serendipity, it's spread to many providers across the United States, and the medical cost paid out is in the millions of dollars.
To overcome the problems of random, manual auditing, apply sophisticated neural analytics as a second layer of defense to the claims editing process. Neural analytics are data-driven, mathematical algorithms that run across large groups of claims to first identify peer-based norms, then the claims, providers or members who deviate from those norms. The goal is to uncover potential gaps and inconsistencies. Unlike rules, analytics have no "preconceived notions" -- they simply look at patterns. Also unlike rules, neural analytic models automatically and continuously adjust or "learn" as more claims come in. In the example above, the specific laboratory code would have triggered a procedure repetition analytic alert in the neural models as well as an excessive procedure dollars alert based on historical payouts for the same laboratory code across the plan's book of business. And it would have been found within days or maybe weeks of onset rather than months or years later.
The final step is to apply the findings of the sophisticated neural analytics to your rules-based system to proactively and automatically stop more waste and abuse before claims are inappropriately paid. Aberrant billing patterns identified long before a scheduled audit require smart reporting tools that quickly get at the specific leak in your rules system that can be addressed by integrating new rules, which creates a feedback loop of continuously improving ROI. Using the lab code example once again, the investigative procedure issue raised by the mathematical models of the analytics could be addressed to stop all similar future occurrences by adding a claims editing rule that pends for further review all claims with that lab code.
This interplay of pre-pay rules and pre- and post-pay analytics and the resulting boost in efficiency has powerful effects on the entire payment environment:
• Paying only for medically necessary care becomes a more attainable goal.
• Advanced detection stops waste and abuse in its tracks.
• An enhanced process of claims investigation sends the message that payers are watching.
• More issues are prevented pre-pay, reducing the costs associated with pay-and-chase.
• Gains in administrative efficiency save both time and money.
A changed climate of deterrence plus decisive response not only benefits payers now -- it will also change healthcare over the long haul, so that the industry reaps benefits already experienced by others that have successfully blended rules and analytics.
Payers have long had a visceral understanding of the need to reduce FWA, and the issue is gaining traction outside the industry as awareness grows across our society. With payment policy optimization, we now have an important new weapon in the fight against runaway healthcare spending.
Jim Evans is vice president of financial management at McKesson Health Solutions.