Modest slowdown in premium growth distinguishes second-quarter financial results for MPL specialty insurers
We look at the financial results for medical professional liability (MPL) insurers for the second quarter of 2022.
Milliman completed a study of how the transition from Risk Adjustment Processing System (RAPS) data to Encounter Data System (EDS) data is affecting the payment year (PY) 2016 risk scores and revenue for Medicare Advantage (MA), also known as Medicare Part C. Fifteen Medicare Advantage organizations (MAOs) participated in the study, reflecting a cross-section of small and medium size organizations and representing over 900,000 members in 154 plans. The study relied on the revised EDS MAO-004 files that the Centers for Medicare and Medicaid Services (CMS) released late in October 2016. This article is the second in a series of articles on the transition to EDS. Read the first paper for more details about the EDS and RAPS data used in MA 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.
Figure 1: Part C risk score difference percentiles (EDS vs. RAPS)
Note: Members included are non-end-stage renal disease (ESRD)/non-hospice members who were enrolled during the entire calendar year 2015.
We 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).
Figure 2 presents the distribution of differences between the Part C RAPS and EDS risk scores, showing that 87% of the members in the study had the same Part C risk score under RAPS and EDS, 12% of members had lower EDS risk scores, and 1% had higher EDS risk scores. The distribution is based on the estimated final PY 2016 risk scores for members enrolled in 2015. We saw more differences in the Medicare Part D risk score than in the Part C risk scores—only 80% of the Part D risk scores were the same. Additionally, about 1% of Part C members’ EDS risk scores were a full unit (1.0 risk score unit) lower than their RAPS risk scores.
Figure 2: Member-level comparison of EDS and RAPS Part C risk scores
Since our last paper on the topic, CMS has released a new memo regarding risk adjustment data deadlines. The December 29, 2016, memo1 from CMS announced two changes to the data submission and risk score calculation schedules that were previously released:
MAOs have more time to review their EDS diagnosis submissions between now and May 1, 2017, in order to improve any deficiencies in their EDS submission processes. As we outlined in our first paper, MAOs should consider the following steps on their diagnosis submissions:
1) Calculate risk scores from each source: EDS return files (MAO-004s), RAPS return files, and detailed source data.
2) Compare risk scores resulting from each source.
3) Identify submission gaps and coding gaps, and quantify the effect.
4) Prioritize and resolve process gaps.
The delay in providing early information to MAOs on PY 2017 risk scores also underscores the necessity of MAOs performing their own calculations of risk scores from the two sources in order to monitor earned revenue and identify any diagnosis submission issues.
Working with the survey participants and other MAOs shed light on several problems which MAOs are still struggling with:
The transition to EDS-based risk scores will have a significant effect on MAOs in PY 2016 and future years. The participants in our study saw a median decrease in risk scores of 4% when comparing EDS scores with RAPS scores. In addition to the reduced risk scores and revenue that are expected to result from this transition, MAOs have been challenged with difficult problems related to EDS data submission and receiving information in a timely manner. Despite revisions from CMS, these issues are not fully resolved. It is important that MAOs implement their own processes of calculating, reviewing, and monitoring their EDS and RAPS risk scores in order to identify problems early and resolve them before submission deadlines in order to avoid unnecessary revenue reductions.