In its Final Call Letter, the Centers for Medicare and Medicaid Services (CMS) announced the schedule for transitioning its sol methodology from the Risk Adjustment Process System (RAPS) to the Encounter Data Processing System (EDPS). CMS is making this transition so risk-adjustment payments to Medicare Advantage Organizations (MAOs) will be based on a higher level of detail than previously. That poses a pressing challenge to MAO information professionals, who will require new analytics capabilities to protect their organizations from data inequities and resulting revenue loss.
While health plans have been making EDPS submissions to CMS for years, encounter data is only now beginning to be used in CMS’s scoring methodology. Scoring will consist of a 90/10 percentage mix of RAPS/EDPS in payment year 2016, and the mix will shift incrementally toward EDPS each year until RAPS is completely phased out in payment year 2020. If a health plan’s algorithms, which calculate risk factors for the RAPS portion of blended submissions, are not aligned with the CMS algorithms for EDPS, a health plan can receive significantly less revenue than it anticipates. The associated shortfall will increase over time with the rising prominence of EDPS in scoring.
To protect against revenue loss, health plans must work to close all the gaps they can currently existing between RAPS and EDPS. This will require analyzing an organization’s RAPS scoring relative to EDPS, adjusting its RAPS business logic if needed for alignment and assuring 100% complete and accurate EDPS submissions.
How RAPS and EDPS Become Misaligned
RAPS-EDPS gaps can occur because of variations in how health plans can structure their RAPS business rules. Some plans have historically taken a very narrow and conservative approach to preparing their submissions, while others have taken a lighter approach. CMS has also made changes to the RAPS logic based on the published EDPS logic that health plans may not have mirrored in their own RAPS logic.
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The quality of EDPS data submissions can also contribute to RAPS and EDPS score variances. Since EDPS scoring for payment is new, many health plans have not closely managed EDPS submissions, assuring that all data is submitted and all data errors for risk adjusting data elements have been corrected. Complete and accurate EDPS submission is necessary to eliminate EDPS data as a cause for RAPS-EDPS score variances and repercussions for MAOs.
Impact of Misalignment to Revenue
According to a study conducted by Altegra Health, forward-looking plans that have begun analyzing RAPS-EDPS gaps reveal they are experiencing reduced risk scores in payment year 2016 from -02 to -2.5%, for an average revenue decrease of -1.2%. If not addressed by the health plans included in these figures, revenue decreases would more than double in payment year 2017. By payment year 2020, with 100% EDPS, these score decreases would range from -1.8 to -27.6%, resulting in average revenue decrease of -11.9%. In other words, current score variances are set to cause health plan losses in the millions of dollars today, and multiples of today’s losses in four more years. Clearly, closing those gaps should be among a health plan’s highest financial priorities.
Doing so requires analytics that health plan information professionals are not accustomed to and has been made more challenging because of visibility issues. Because plans were in control of RAPS, they had full visibility into the payment impact. But as the percentage of revenue cycle shifts to EDPS, that visibility diminishes as CMS makes the EDPS calculation. That means analyzing RAPS-EDPS gaps requires best efforts to create algorithms that simulate EDPS calculations. That in turn will enable the comparison of EDPS results to RAPS to understand the magnitude of the differences and the reasons they exist.
Health Plans Control
Most RAPS-EDPS gaps exist because of misalignment in RAPS and EDPS logic, as well as EDPS data errors. Because health plans are in control of RAPS logic and EDPS data submission, they are also in control of implementing the solution. They can and should take immediate steps to identify differences between RAPS and EDPS submission logic and modify RAPS logic so that alignment is as close as possible.
In other cases, RAPS-EDPS gaps may result from issues with the EDPS data submitted to CMS. Health plans should assure that all data is fully submitted to CMS and that resulting errors are corrected and rejections are tracked. If not all risk adjusting errors are corrected, CMS won’t get all of the data to generate risk scores. Accuracy and error-correction are now more important than ever, and are also in the health plan’s control.
Gaps may also exist if CMS has an issue with EDPS scoring calculations. There has been some industry chatter regarding known errors in the MAO 004 reports that make the impact look bigger than it is, and these concerns may be valid. However, even with an error-free MAO 004 report, there would certainly be gaps from issues with alignment or data flow between the health plan and CMS. Rather than wait for CMS action and correct the MAO 004 reports, it’s time for health plans to do all they can to smooth the transition.
Three steps to smooth the transition from RAPS to EDPS
To support internal customers effectively and efficiently, health plan information professionals should follow these three steps in closing RAPS-EDPS gaps.
- Prioritize and correct errors with risk adjustment impact first, starting with the claims that have the largest risk adjustment error mix. A claim with errors may contain multiple mistakes, and it’s important to identify claims with the most errors that contribute to risk adjustment. This will typically require a new set of analytics. Once those analytics are in hand, efficiency can be increased by having the plan’s financial professionals prioritize and correct errors with the largest financial impact.
- To narrow the effort, identify contracts with the largest score variances and the members who are causing the majority of the gap. Once financial reporting needs have been prioritized, information professionals must accordingly prioritize their efforts. Start with a detailed analysis of score variance between RAPS and EDPS scores and determine the members with the largest score gaps. Then, analyze these members’ data to identify which HCC’s and diagnosis codes are missing from each score. This will enable efforts to be directed where they will generate the most positive financial impact.
- Use MAO-002s and RAPS data to determine the specific variance (RAPS submission, EDPS errors or CMS scoring), take action and adjust revenue accruals accordingly. Using MAO 002 reports, simulate the EDPS score using CMS methodology. Compare that score to the RAPS score and, when corrected, the MAO 004 score. By comparing all three scores and analyzing the details, health plans can pinpoint the underlying cause of RAPS-EDPS gaps — whether issues of alignment, data flow or perhaps CMS issues.
Thorough analysis can identify where actions need to be taken at the health plan level, at the contract level and at the member level. By working together, information professionals, plan executives, finance and risk adjustment managers can prioritize and direct efforts accordingly to minimize the impact to the bottom line in the RAPS to EDPS transition.
Lisa DiSalvo is senior vice president of product strategy & development at Altegra Health, Inc.