Background
On September 14, 2020 CMS released The Advance Notice of Methodological Changes for Calendar Year (CY) 2022 for Medicare Advantage (MA) Capitation Rates and Part C and Part D Payment Policies – Part I, CMS-HCC Risk Adjustment Model. In this Notice, CMS proposes implementing the long promised 100% use of encounter data for risk scores starting in 2022. This is in accordance with the 21st Century Cures Act and sections 1853(a)(1)(I)(iii) and 1853(b)(2) of the Act, as amended by section 17006 of the 21st Century Cures Act.
Currently, for the 2020 Plan Year, Encounter Data and RAPS are evenly divided 50/50. Under the proposal, in 2021 Encounter data would represent 75% of the risk score calculation and in 2022 risk scores will be solely based on encounter data.
CMS began capturing encounter data for this purpose in 2016 from plans. The long- term intent of using this data was for risk adjusted payment purposes, as well as to be able to evaluate services rendered for frequency, by zip code, demographics and providers.
CMS has been monitoring the data provided and is required to phase in over a three year approach moving to use of 100% encounter data reporting informing federal payment to plans. CMS has historically been met with significant push back from plans due to the challenges associated with complete encounter data.
Plans are paid on a per enrollee risk adjusted score. If those risk scores are artificially lower due to poor encounter data, this will lead to lower federal payments to plans.
CMS Compliance Requirements and Common Challenges
CMS has limited requirements regarding encounter data submissions beyond the 837-format requirement. Currently, the frequency of encounter data submission is required with a “not-less-than” metric by the plan’s membership. However, given data size limitations, plans are encouraged to submit more frequently than required.
CMS expects plans to conduct self-assessments to validate the completeness of their encounter data, as well as perform a comparison between the volume of encounters with fee- for-service (FFS) payments. Plans should be using the report cards from CMS to compare to their own findings.
Despite the limited compliance requirements around encounter data, there are still many challenges. One challenge plans face is the sheer magnitude of file size; the RAPS file requires minimal fields to submit, while the encounter file is a full 837 format. Another factor is populating that file from fields in the plan core system. Additional mapping of system fields may be required to ensure all required data is populated.
Plans also face a challenge with provider education. There is a disconnect between provider billing and providers understanding the encounters are being used for more than just their claims payment. For example, billing departments submit the diagnosis to get the claim paid or capitated providers not submitting complete encounter data, because they feel it is not relevant, since the plan is not processing the claims. Plans will need to aggressively conduct provider education to ensure encounter data is complete and accurate.
What Does that Mean for Plans?
As CMS moves to a sole reliance on encounters for payment purposes, it’s important to ensure those are complete and accurate.
Get started now! The move to utilize Encounter data for risk adjustment payment is just around the corner, so getting a start on implementing the right policies, procedures and processes is critical for readiness. Utilizing industry expert resources to assist is a great option to help you understand gaps, provide staff and provider education and help implement processes so you are prepared for the transition.
BluePeak Can Help
BluePeak has extensive experience evaluating Plan encounter processes, policies and procedures and reports, to ensure that they have an efficient and compliant process. In addition, BluePeak has the ability and expertise to load all your Part D PDE data and to identify possible situations where the beneficiary’s encounter data is not consistent with the submitted PDE data. The PDE analysis would identify possible situations of Fraud, Waste, and Abuse where the encounter data may be over-reported, as well as, more likely situations where the encounter data is not being captured for beneficiaries.
