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Major Risk Adjustment Changes Will Require Plans to Develop New Strategies to Improve Revenue

One of the fast-emerging parts of the value-based purchasing realm is government regulators’ move toward apportioning revenue in our health system to plans based on the acuity of their overall population. With a race-to-the-bottom rate structure emerging in most lines of business, it will be critical for plans to accurately assess and document all the disease states of a member to gain additional revenue.

This Risk Adjustment strategy is a mainstay now in the Medicare Advantage world. While the Medicare Advantage (MA) and the Part D programs use the Hierarchical Condition Category (HCC) system (Part D scores are set using ICD diagnoses, not drug data), about 30 states use various risk adjustment models to pay for their Medicaid populations. And now, the Exchange line of business has adopted a variant of HCC for the Affordable Care Act insurance expansion.

The Centers for Medicare and Medicaid Services’ (CMS) approach to assessing risk adjustment in Medicare is undergoing a major change. Since risk adjustment’s introduction in the MA program, CMS has calculated risk scores using diagnoses submitted by MA plans in the Risk Adjustment Processing System (RAPS) format. This relatively easy-to-compile format allowed plans to submit frequently from claims systems as well as put in supplemental submission for diagnoses that may not have been submitted through standard claims.

However, CMS has long been frustrated with the current system of validating diagnoses for risk adjustment. One concern is CMS’ perception that the RAPS process distorts risk scores in MA plans compared to those in the Fee for Service (FFS) system, which submits full claims data. Therefore, in an effort to develop a more accurate payment model, in 2012 CMS began mandating the collection of encounter data — detailed information on the services and items furnished to members — from MA plans in parallel with RAPS data. This information, referred to as encounter data or 837 data, is more comprehensive than the beneficiary diagnosis data provided in the RAPS. While the intention was to move to a system of setting risk scores based on encounter data, technological obstacles and negative pressure from plans delayed this migration. Until now.

This year, CMS added encounter data as an additional source to calculate risk scores for MA beneficiaries. This in and of itself did not negatively impact risk scores as plan 837 data is additive this year. However, for 2016, CMS will blend encounter data-based risk scores with RAPS-based risk scores in an effort to begin the conversion to full encounter data reliance. In 2016, the calculation will be weighted as 90% RAPS and 10% encounter data; in the future, the percentage of encounter data will increase and eventually completely replace RAPS data.

Where CMS sees the move as a modest step, some plans see major issues, including a potential negative revenue impact. It is now a business imperative for plans to have a robust encounter submission strategy in place to preserve revenue in 2016 and improve revenue in the future. These strategies must be all encompassing as the RAPS retroactive filing process that garners a great deal of revenue for plans will ultimately disappear. The strategies must involve capitated providers as well as downstream at-risk entities, who often place a low priority on submitting encounters, much less all of the diagnoses that might garner added revenue.

Additionally, plans will need to ensure that all claims and encounters move seamlessly, cleanly, and swiftly through the claims system, and that compliant 837 data is created for submission to CMS. Currently, MA plans have 13 months for EDI submissions. Practically speaking, MA plans will need to build aggressive timeframes to submit and then resubmit encounters as necessary to ensure all diagnoses are properly credited. This can be a huge financial, operational, and technological undertaking for many plans – regardless of size. Experience in the Medicaid world seems to underscore this.

The risk adjustment change comes at the same time that CMS is fully adopting the redesigned version 22 HCC risk adjustment coefficient model. For the past two years, CMS has blended the version 22 model with the original version 12 model. CMS states that this model will reflect more recent utilization and costs, be more clinically accurate, and be able to accommodate ICD-10 codes. CMS has already estimated a net revenue loss of 1.7 percent to plans next year due to the total conversion to model 22, in part because of the change in the treatment of Chronic Kidney Disease. The risk-adjustment change will only compound a plan’s potential revenue impact.

Revenue reconciliation, prediction, and enhancement will be additional obstacles for plans because the encounter data process would now put CMS, not the plans, in the driver’s seat when it comes to determining acceptable claim lines and diagnoses. Therefore, MA plans that develop a strong strategy for improving revenue using encounter data will be in a more competitive position in the shift to a value-based healthcare model.

Marc Ryan

Marc S. Ryan serves as MedHOK’s Chief Strategy and Compliance Officer. During his career, Marc has served a number of health plans in executive-level regulatory, compliance, business development, and operations roles. He has launched and operated plans with Medicare, Medicaid, Commercial and Exchange lines of business. Marc was the Secretary of Policy and Management and State Budget Director of Connecticut, where he oversaw all aspects of state budgeting and management. In this role, Marc created the state’s Medicaid and SCHIP managed care programs and oversaw its state employee and retiree health plans. He also created the state’s long-term care continuum program. Marc was nominated by then HHS Secretary Tommy Thompson to serve on a panel of state program experts to advise CMS on aspects of Medicare Part D implementation. He also was nominated by Florida’s Medicaid Secretary to serve on the state’s Medicaid Reform advisory panel.

Marc graduated cum laude from the Edmund A. Walsh School of Foreign Service at Georgetown University with a Bachelor of Science in Foreign Service. He received a Master of Public Administration, specializing in local government management and managed healthcare, from the University of New Haven. He was inducted into Sigma Beta Delta, a national honor society for business, management, and administration.

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