Predictive Qualifying APM Participants
The Centers for Medicare & Medicaid Services (CMS) announced predictive Qualifying APM Participant (QP) status for 2017 Advanced APMs. By looking at historical Part B claims data, CMS predicts that nearly 100% of eligible clinicians in Advanced APMs with data currently available will be QPs in performance year 2017.
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What is the Predictive QP status analysis?
One of the Quality Payment Program’s goals is to be clear about your Qualifying APM Participant (QP) or Partial QP status.
For the 2017 Predictive QP analysis, this is how CMS determined if you, from your participation in one of the following Advanced APMs, are predicted to be a QP for the 2017 performance year and are likely to be eligible for the 5% APM Incentive Payment in the 2019 payment year. These calculations are predictive in nature, meaning they are a prediction of your QP status in performance year 2017, if you participate in at least one of these Advanced APMs in performance year 2017:
- Comprehensive ESRD Care (CEC) -Two-Sided Risk
- Comprehensive Primary Care Plus (CPC+)
- Next Generation Accountable Care Organization (ACO) Model
- Medicare Shared Savings Program -Track 2
- Medicare Shared Savings Program -Track 3
For this analysis, CMS used administrative claims with dates of service between 1/1/16 and 8/31/16 that were processed between 1/1/16 and 11/30/16. Actual QP determinations will use claims data from the relevant performance year as of three points in time, or “snapshot” dates: March 31, June 30, and August 31.
If you are a participant in the Comprehensive Care for Joint Replacement Model (CJR)—CEHRT Track, CMS did not make predictions about your QP status for performance year 2017. The CJR-CEHRT Track did not begin until 2017 so there are no historical claims data available.
In addition, CMS did not make predictions for the Oncology Care Model (OCM)—Two-Sided Risk Arrangement as there are no OCM practices currently participating in this arrangement.
What were the Predictive QP & Partial QP determination steps?
CMS took the following steps to estimate QPs and Partial QPs in our 2017 predictive analysis.
- Identified eligible clinicians participating in Advanced APMs using the APM Entity participation lists.
- Identified attribution-eligible beneficiaries from Medicare Parts A and B administrative claims data and Medicare beneficiary enrollment information.
- Identified beneficiaries attributed to Advanced APM Entities.
- Calculated payment amount Threshold Scores.
- Calculated patient count Threshold Score.
- Determined predictive QP or Partial QP status for an APM Entity group based on the payment amount or patient count. We applied the more advantageous QP Status to the eligible clinicians participating in the APM Entity.
How did CMS identify attribution-eligible beneficiaries?
CMS found beneficiaries to be attribution-eligible to an APM Entity if during the historical assessment period they:
- Weren't enrolled in Medicare Advantage or a Medicare Cost Plan.
- Didn't have Medicare as a second payer.
- Were enrolled in both parts A and B for the entire QP performance period.
- Were at least 18 years of age on January 1.
- Were a United States resident.
- Had at least one claim for E/M services furnished by one or a group of eligible clinicians used in assignment in an APM Entity during the historical assessment period.
To match the attribution eligibility criteria with each APM’s attribution methodology, we may apply exceptions to the evaluation and management requirement for attribution-eligible beneficiaries. Such an exception will be applied in 2017 to the CEC model, including the predictive QP analysis.
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CMS Is Accepting Future Measures and Activities for Three MIPS Performance Categories
CMS' Annual Call for Measures and Activities for the Merit-based Incentive Payment System (MIPS) track of the Quality Payment Program (QPP) is accepting Quality and Advancing Care Information measure proposals through June 30, 2017 for the 2018 program year; measures submitted beginning July 1, 2017 will be considered for the 2019 program year.
CMS encourages clinicians, measure stewards, organizations, and other stakeholders to identify and submit measures and activities to be considered for the Quality, Advancing Care Information, and Improvement Activities performance categories of MIPS in future years.
Submission Details
- Quality: Measures proposed for inclusion should be submitted through JIRA. Submissions should include the JIRA Measures under Consideration (MUC) template and other associated documents CMS deems necessary for the submission process.
- Advancing Care Information: Measures proposed for inclusion should be sent using the Advancing Care Information Submission Form to CMSCallforMeasuresACI@ketchum.com.
- Improvement Activities: Activities proposed for inclusion should be sent using the Improvement Activities Submission Form to CMSCallforActivitiesIA@ketchum.com.
Measures and activities should be relevant, reliable, and valid at the individual clinician level. To be considered, proposals must include measure specifications, related research, and background.
A final list of measures and activities for MIPS clinicians will be published in the Federal Register no later than November 1 of the year prior to the first day of the performance period. Please note that some Advancing Care Information measures finalized in the 2018 final rule may not take effect until 2020, depending on the functionalities and workflow changes needed for implementation.
For More Information
Remember to review the Annual Call for Measures and Activities fact sheet to learn more and understand the process for submitting measures for the MIPS performance categories. Please direct any questions on measure and activity submissions to the QPP Service Center at QPP@cms.hhs.gov.
Remember to review the Annual Call for Measures and Activities fact sheet to learn more and understand the process for submitting measures for the MIPS performance categories. Please direct any questions on measure and activity submissions to the QPP Service Center at QPP@cms.hhs.gov.