Tag Archives: encounter data

How will the pandemic impact Medicare Advantage revenue and risk scores in 2021?

While there is a great deal of focus on resource availability and handling a potential influx of severe inpatient cases resulting from COVID-19 infections, the majority of the United States saw a dramatic reduction in healthcare services around March and April 2020 and measurable reductions continue with great variation across the nation. 

As with many prospective risk adjustment models, Medicare Advantage (MA) and Part D (PD) risk scores are based on medical claims, more specifically diagnoses from face-to-face visits from the year prior to the year in which the risk score drives revenue. For 2021 MA payments, 2020 diagnoses are the basis of the final risk scores. To the extent that beneficiaries delay or avoid care, there may be fewer face-to-face encounters with providers where diagnoses can be recorded and applied toward 2021 risk scores.  

While the Centers for Medicare and Medicaid Services has announced additional flexibilities in including telehealth-based diagnoses in risk score calculations, a significant reduction in overall services is likely to result in a material reduction in both MA and PD risk scores. In this article, Milliman’s Rob PipichKarin Cross, and Deana Bell discuss the results of an analysis they performed to support 2021 MA and PD bids. They present nine scenarios intended to illustrate a range of potential outcomes on 2021 MA and PD risk scores. 

Survey analyzes differences between Medicare Advantage RAPS and EDS risk scores

As the Centers for Medicare and Medicaid Services (CMS) continues to phase out the Risk Adjustment Payment System (RAPS) as a source for risk adjustment diagnoses, it is important that Medicare Advantage organizations (MAOs) understand the expected impact of the Encounter Data Processing System (EDS) as the single source of diagnoses for calculating risk scores and the impact this transition may have on revenue.

Milliman professionals have periodically conducted surveys that identified the average difference between RAPS-based and EDS-based risk scores. The most recent survey results show that EDS scores have now caught up to or exceeded RAPS scores in many cases, whereas surveys from prior years showed that EDS were generally lower than RAPS scores.

Milliman actuaries David Koenig, Emily Vandermause, and Rebecca Gergen discuss the results in their paper entitled “Have we reached parity between Medicare Advantage RAPS and EDS risk scores?

Medicare Advantage’s transition from RAPS to EDS risk scores

In 2017, there were many changes to Medicare Advantage (MA) risk adjustment as the transition continued from Risk Adjustment Processing System (RAPS) data to Encounter Data System (EDS) data. MA organizations will also experience complexity and challenges in payment year (PY) 2019.

This article by Milliman’s Deana Bell, David Koenig, and Charlie Mills compares EDS and RAPS risk scores and details some of the program highlights from the past 12 months:

• A 25% EDS weight for PY 2017
• EDS file layout updates
• PY 2016 EDS deadline extension and change to payment timing
• PY 2017 RAPS and EDS deadline extensions
• Including inpatient RAPS diagnoses in EDS risk scores for PY 2019




Webinar: Medicare Advantage risk scores

Payment year 2017 is a key year for Medicare Advantage (MA) plans, as encounter data is weighted 25% and has been shown to result in lower risk scores and revenue. An upcoming Milliman webinar hosted by Charlie Mills and Deana Bell will explore how MA plans have prepared for the transition to encounter data, and highlight best practices for monitoring financial results and encounter data submissions. The webinar entitled “Medicare Advantage risk scores: Best practices in financial monitoring and encounter data submissions” is scheduled for October 19 from 11 a.m. – 12 p.m. PT (2 p.m. – 3 p.m. ET).

For more information or to register, click here.




Transition from RAPS to EDS data decreases Medicare Advantage risk scores

Milliman consultants Deana Bell, David Koenig, and Charlie Mills performed a study of how the transition from Risk Adjustment Processing System (RAPS) data to Encounter Data System (EDS) data is affecting payment year (PY) 2016 risk scores and revenue for Medicare Advantage organizations (MAOs). Fifteen MAOs participated in the study, reflecting a cross section of small- and medium-sized organizations and representing over 900,000 members in 154 plans. The consultants offer perspective in their article “Impact of the transition from RAPS to EDS on Medicare Advantage risk scores.”

Overall, the study found that the median percentage difference between PY 2016 risk scores based on RAPS and the EDS-based risk scores is 4.0%. The percentage difference is larger for special needs plans (SNPs) and smaller for general enrollment plans as shown in Figure 1. The prior year’s diagnoses make up a larger component of SNP members’ risk scores, compared to general enrollment plans, so the risk score impact for SNP plans is larger.

[The authors] have not attempted to quantify what portion of the difference between RAPS and EDS is due to incompleteness of the EDS submissions, issues with CMS’s return files (revised MAO-004 files), changes to filtering logic, and the effect of claims coding errors.

As an illustration, the potential Part C PY 2016 revenue using the median difference of -4% between RAPS and EDS results in a reduction of approximately $40 per member per year, assuming approximately $800 in Part C risk-adjusted revenue and a 1.0 RAPS-only risk score. To the extent that this -4% gap persists in future years, the revenue impact will grow because the EDS-based risk score will make up an increasing portion of the final risk score (e.g., with the 25% EDS weight in PY 2017, the per member reduction would be about $100 per year).

This article is the second in a series of articles on the transition to EDS. For more information about the EDS and RAPS data used in MA risk scores, read “Medicare Advantage and the Encounter Data Processing System: Be prepared.”




Medicaid encounter data: The next national data set

Quality encounter data is necessary for successful Medicaid managed care programs. States and managed care organizations have partnered to work toward solutions for developing and transmitting complete and accurate encounter data. In this article, Milliman’s Jennifer Gerstorff and WellCare Health Plans’ Sabrina Gibson discuss the need for, and challenges of, collecting Medicaid encounter data as well as the future of Medicaid encounter data.

Copyright © 2016. The Society of Actuaries, Schaumburg, Illinois.
 Reproduced by permission.