Trim Expenses and Improve Healthcare: Subrogation Settlement Ratios Predictive Modeling Fuels a New Breed of Post-Adjudication, Pre-Payment Solution
by Timothy E. Cahill and Blaise J. Guzewicz, J.D., Socrates, Inc.Subrogator Spring/Summer 2009
Subrogation strategies have never been more important for health plans and plan sponsors. Economic uncertainty, intense competition and potential regulatory changes are sure to exert downward pressure on income for months, even years, to come. Healthcare payers need the right tools and techniques in place to preserve revenue in this difficult operating environment.
While important, the effectiveness of traditional subrogation tactics may be limited by associated expenses and recovery times. However, there is a new approach that complements tried-and-true models to not only help control costs, but to also improve post-payment settlement ratios up to 7 percent. Further, it promises to inject a new level of efficiency into subrogation tactics in order to ensure that organizations remain economically viable over the long term.
The Historical Approach
Subrogation traditionally has been characterized by “pay-and-pursue” or “pursue-and-pay” methodologies. With a responsibility to settle claims on a timely basis, health plans and plan sponsors have long met their reimbursement obligations even with the knowledge that they may not be financially liable for many of these claims. So begins the tactical and legal dance to identify Other Party Liability (OPL) claims and recover inappropriately disbursed funds: Health plans review paid claims retrospectively and then undertake the often convoluted process of convincing other insurers to cut repayment checks. Seeking to squeeze as much money as possible from their subrogation efforts, many health plans employ aggressive collection tactics; however, in doing so, they ultimately reduce recouped claim amounts because of limited fund sources or, because they must share the funds with other parties, such as personal injury attorneys. In addition, being exposed to the “court of public opinion” in a reimbursement action is always an internal consideration.
Although not perfect, this post-payment model has significant value and will undoubtedly continue to be the linchpin of successful subrogation programs. Health plans and plan sponsors routinely recover 1 to 2 percent of total annual paid-claims value. For a 100,000-member health plan, this can translate into approximately $1.5 million annually.
These results, however, do not tell the whole story. While investments in OPL identification solutions are worthwhile, the costs associated with post-payment claim recovery may be uncomfortably high. In addition to legal and vendor fees, health plans can expect to receive a settlement ratio that is 40 to 45 percent less than the original amount of the claim.
An Innovative Way to Subrogate
Going forward, the industry needs to decide how to augment current subrogation models, utilizing methods to identify and recoup OPL claims that are less costly, while improving settlement ratios and overall financial outcomes. Those that can accomplish this will establish themselves as differentiators in the dynamic healthcare industry.
Fortunately, new processes and innovative technologies are emerging and can help forward-thinking health plans achieve this objective. The most promising are designed to move much of the legacy subrogation processes upstream – after adjudication, but before the claim has been paid. This new supplemental prepayment model enables payers to extract claims, filter them through identification software and then suspend payment on any transaction that the system verifies as a viable subrogation case – potential worker’s compensation or motor vehicle accident (MVA) claims, for example. Not intended to replace traditional subrogation efforts, prepayment subrogation complements a health plan’s established pay-and-pursue tactics and helps to ensure that the organization is maximizing its revenue potential.
Best-of-breed prepayment subrogation systems and highly focused, targeting a subset of about 25 to 30 percent of the claims that much broader post-payment models typically uncover – about 2 percent of all paid claims, in other words. Software available on the market today accept adjudicated claims from the payer and filter them through a proprietary customer-specific rules engine and predictive modeling formulas based on CPT and ICD-9 codes that are most often associated with OPL claims.
Agility and speed in claims investigation is paramount; there is a very small window of time for the technology to analyze the adjudicated claim and indicate its potential for subrogation. Advanced systems will quickly suspend, tag and deny payment on claims that are verified as viable subrogation or OPL cases. Once identified, advanced solutions can trigger an investigative process via efficient member outreach processes to determine the payer’s true liability.
Meanwhile, the remaining claims deemed ready for payment undergo standard batch processing, and reimbursement is issued as normal. Regardless of a claim’s ultimate fate, emerging systems provide the health plan with a report, indicating the claim’s status, whether it’s clean and OK to be paid, or confirmed as OPL (thereby halting payment). Due to claim payment constraints in the certain cases, there simply isn’t enough information for the software to determine OPL. As such, the claim would be forwarded to the health plan for traditional post-payment subrogation activities.
Predictive Modeling is Key
Best-of-breed post-adjudication, pre-payment systems incorporate predictive modeling to determine which cases are potentially viable for OPL and subrogation. This advanced technique, for instance, can flag claims with specific diagnosis codes that most likely indicate injuries related to work-related events or motor vehicle accidents.
Consider this example: A payer receives two claims that are nearly identical. One reports a patient suffering fractures of the left wrist and right leg. Built-in logic exhibited by these new solutions will indentify the first as likely caused by a fall but, the second, as a possible MVA.
Prepayment solutions may even help reduce liability in states that prohibit subrogation. Let’s say that a claim in New Jersey, an anti-subrogation state, suggests the beneficiary was treated for fractures that were a result from a car accident in the capital city, Trenton. The filtering software recognizes that the claim cannot be subrogated and it is forwarded for payment.
But perhaps the same beneficiary from New Jersey is involved in a MVA in Texas and a claim for medical care is submitted to the health plan. Unlike New Jersey, Texas allows subrogation. Therefore, although the insured’s home is in an anti-subrogation state, a well-designed, intuitive system will make the distinction and indicate that the plan should investigate this for potential subrogation.
These emerging solutions offer yet another benefit: Many incorporate features to indentify OPL prescription claims that previously went undetected. Because they often are regarded as insignificant, OPL prescription claims are rarely isolated for subrogation. New software, however, is built on logic that considers Rx as well as Dx data. As a result, these solutions pick up those previously lost dollars. Even if they catch only 5% of OPL claims, revenue can add up when spread across all beneficiaries participating in all plans.
Benefits to Prepayment Subrogation
Identifying, verifying and suspending (or denying) payment of OPL claims after adjudication but, before disbursement, clearly boosts the efficiency of a health plan’s overarching subrogation strategy and has tremendous fiscal potential for health plans. Given the typical recovery time of 9 to 12 months on a disputed claim, health plans that prevent paying claims for which they are not liable will improve their overall cash flow. And they save between 30 to 40 percent per case by avoiding recovery compromises, plan member attorney fees and contingent vendor expenses associated with traditional post-payment processes.
Further, health plans can increase their post-payment settlement ratios by 5 to 7 percent by adding these innovative tactics to their subrogation program. When comparing total lien to gross recovery calculations, emerging technologies indentify subrogation cases 60 to 75 days faster then conventional post-payment processes. This enables internal post-payment departments or external vendors to access and recover available fund sources more quickly and with less outside involvement of other lien holders.
Conclusion
Health plans and plan sponsors face trying economic times. Compounding the problem, payment complexities are on the rise and an evolving regulatory environment offers little assurance that payers will be able to subrogate claims with the same leverage in which they currently enjoy.
It has become increasingly clear that post-payment subrogation techniques commonly used to recoup OPL payments are not sufficient on their own. More and more, payers are supporting their traditional subrogation efforts with leading-edge, predictive modeling technologies designed to catch as many subrogatable claims as possible, prior to disbursement – before revenue is lost to the erosion of legal fees and settlement ratios.
