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Considerations for Choosing MIPS Quality Measures

Considerations for Choosing MIPS Quality Measures. Updated January 2019. Overview of Contents. Updated Quality Category Information for 2019 First know yourself Finding measures Understanding scoring Special Considerations – about registries Special Considerations – ESRD patients

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Considerations for Choosing MIPS Quality Measures

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  1. Considerations for Choosing MIPS Quality Measures Updated January 2019

  2. Overview of Contents • Updated Quality Category Information for 2019 • First know yourself • Finding measures • Understanding scoring • Special Considerations – about registries • Special Considerations – ESRD patients • Understanding the data that feeds measures – numerators, denominators, and excluders – OH MY! • Data capture in the typical workflow • Data quality and integrity • Notes and considerations on reporting • 2018 proposed CMS updates RPA Guide to QPP Participation

  3. 2019 Updates to the Quality Category • The quality category is now 45% of the total QPP score (down from 50%). • Measures reporting can now be “mixed and matched” across multiple submission methods (claims, EHR, QCDR, etc.) • Data submitted for measures that do not meet completeness criteria will now receive 1 point (as opposed to 3) for practices of >15 providers. • Scoring - 3 points for measures without a benchmark or which do not have the minimum # of cases reported.  Measures that do not meet data completeness requirements will get 1 point instead of 3 points (small practices will continue to get 3 points). • Measures have been added and dropped from the CMS quality measure library (see slide 5) • Measures with an averag mean performance between the 98th to 100th percentile range may be removed in the next rule-making lifecycle. RPA Guide to QPP Participation

  4. First Know Yourself - Successful quality measurement is dependent on choosing measures that: • Capture the most typical care you or your practice provide • Use data that you have access to – “discrete” data in fields that your electronic health record system can export for reports and/or use to calculate measure performance • Have a reasonable distributions of performance (decile range benchmarks) so you can achieve high scores, even if you don’t have 100% performance RPA Guide to QPP Participation

  5. Identifying and Choosing Measures • Library of Measures at qpp.cms.gov • There are 257 approved measures for 2019, but more than 1000, when specialty-specific QCDR measures are included • Measures are benchmarked differently depending on the submission method • Therefore, your score is dependent on decile of performance AND the submission method. • Decile of performance equals point score; e.g. 9th decile = 9 points • For 2019, you can submit data from a combination of submission methods (EHR, QCDR, claims, etc.) *Small practices will still have 3-point floor All tables adapted from http://healthcareblog.pyapc.com/2017/01/articles/pay-for-performance/optimizing-your-mips-score-quality-measure-benchmarks-and-reporting-mechanisms/ Data from https://qpp-cm-prod-content.s3.amazonaws.com/uploads/342/2019%20MIPS%20Quality%20Benchmarks.zip

  6. Scoring for QPP – MIPS Quality Category • Quality portion of MIPS composite score = 45 (out of 100) points for 2019 • Your MIPS Quality score is based how well you perform on 6 chosen quality measures, where each measure is worth a maximum of 10 points. • Groups of ≥16 clinicians will also be held accountable for a 7th measure – the AHRQ all cause hospital readmission measure. No reporting is required – data is aggregated and reported for you by CMS from claims data. • There are bonus points achievable for choosing certain measures* or using certified EHR technology (CEHRT) to submit your data (“end-to-end” reporting). • Clinicians can also earn up to 10 additional percentage points based on the rate of improvement in the Quality performance category from the previous year. • The 45 points of the MIPS composite score (MCS) is the % of points out of 60 (or 70 for groups >16) quality category points earned. *2 or more outcome or high priority quality measures, including opioid-relate measures RPA Guide to QPP Participation

  7. MIPS – Quality Measure Score Card Example • Group ≥16 clinicians, therefore 70 maximum possible quality category points (All Cause Readmission measure calculated and applied by CMS) • Used a CMS identified topped-out measure for #2, therefore 7 is maximal score(-2.3, but +1 bonus point for CEHRT use) • Did not meet the minimum reported cases (20) for measure #6, there for score reduced to 3 (-6.7) • Earned bonus points for reporting via CEHRT (end to end reporting) and choosing high priority measures (#1,2,3, and 5) • Earned 74% of total possible quality points; 33.3/45 points towards MIPS composite score (MCS) Example updated from MACRA final rule TABLE 19: Quality Performance Category Example with High Priority and CEHRT Bonus Points https://www.federalregister.gov/documents/2016/11/04/2016-25240/medicare-program-merit-based-incentive-payment-system-and-alternative-payment-model-incentive-under

  8. Further Notes on Scoring of Measures • Score is based on the performance decile achieved according to published, benchmarked distribution. • CMS publishes benchmarks for all measures on QPP.CMS.GOV • Some measures are topped-out, meaning there are very small performance differences separating the highest deciles. • The same measure may have different benchmarks that vary by the submission method • EHR submission measures tend to have the lowest percentage of topped out measures, but this may change since CMS is removing topped out measures. • 2019 Measure Scoring Adjustments of Note • 3-point floor for measures scored against a benchmark (i.e. those CMS publishes) • 3-point floor for measures that don’t have a benchmark (new QCDR custom measures) • 3-point floor for measures that don’t meet case minimum requirement (<20 cases).  • 1-point floor for measures that do not meet data completeness requirements (60% of Part B patients who meet denominator - except that small practices will continue to get 3 points. • 6-point ceiling for *some* topped out measures (list published by CMS) All tables adapted from http://healthcareblog.pyapc.com/2017/01/articles/pay-for-performance/optimizing-your-mips-score-quality-measure-benchmarks-and-reporting-mechanisms/ Data from https://qpp-cm-prod-content.s3.amazonaws.com/uploads/342/2019%20MIPS%20Quality%20Benchmarks.zip

  9. Notes on Registries • Qualified Registries (QRs) are approved vendors that aggregate and report quality data on behalf of subscribing clinicians and practices. MIPSwizard is an example. • QCDRs (Qualified Clinical Data Registry) are databases that allow the collection and submission of the data needed to report on quality measures. • QCDRs differ from Qualified Registries (QRs) in that QCDRs will offer both standard quality measures as well as custom, CMS-approved quality measures that are not available in standard MIPS library of measures published by CMS. These custom measures may be specific to a disease or specialty of medicine. RPA’s Kidney Quality Improvement Registry (a QCDR) is an example. • Both QRs and QCDRs typically charge subscription fees and may offer various data analysis tools, beyond simple data aggregation and reporting. RPA Guide to QPP Participation

  10. Notes about ESRD Patients and Quality Measures There is a lot of confusion about the ”requirements” for reporting across MIPS categories on ESRD patients. • At a minimum (and depending on how a clinician or group reports data), CMS requires reporting on 60% of Part B patients who fall in the denominator of a chosen measure. • When choosing measures, the types of encounters (based on CPT code) and/or disease state based on (ICD-10) will determine which patients are included in the denominator. • There are very few measures that use the dialysis CPT codes (909XX) or the ICD-10 N18.6 as a denominator inclusion criterion. • However, if a measure does include ESRD patients, how to capture the numerator and denominator data for the measure will have to be considered. Robust data capture in the dialysis setting is often not straight forward. RPA Guide to QPP Participation

  11. Understanding the data that feeds measures –numerators, denominators, excluders, OH MY! • For each selected measure, it is important to ensure that the following is known about each required data element: • Where is the data captured in the practice workflow? • Who is responsible for capturing the data? • In which EHR field must the specific data be entered? • What is the acceptable range of data for each element needed? • Who and how will the integrity and completeness of the data be monitored? RPA Guide to QPP Participation

  12. These are CPT II codes For reporting quality measures Measure #226 Data Workflowand CPT for each potential outcome Report CPT 4004F Report CPT 1036F Report CPT 4004F-1P Report CPT 4004F-8P From https://pqrs.cms.gov/dataset/2016-PQRS-Measure-226-11-17-2015/s8gr-6b6i/data

  13. Breaking Down a MeasureSmoking Cessation – CMS #226 Preventative Care and Screening: Tobacco Use Measure: Percentage of patients aged 18 years and older who were screened for tobacco use one or more times within 24 months AND who received cessation counseling intervention if identified as a tobacco user RPA Guide to QPP Participation

  14. Matching Data Requirements to Workflow:Data Needed for Measure #226

  15. Matching Workflow to Data Requirements:Where in the patient encounter data can be gathered for measure #226

  16. Considerations on Data Capture • What practice-level incentives are in place to ensure staff and clinicians are capturing the right data, in the right place, and at the right time? • What and how often are reports reviewing the quality and completeness of the data captured being run? Who reviews these reports? How is feedback offered to correct or acknowledge data capture behavior? • What mechanisms, policies, and/or procedures are in place to amend the medical record if problems of missing or inaccurate data are discovered? • For your EHR and other data tools, what is the time lag between when data is recorded/entered in the EHR to when scorecards or quality measure reports are updated for review? RPA Guide to QPP Participation

  17. Considerations on Reporting Data to CMS… Before allowing your registry vendor (QR, QCDR, or your EHR) to submit data, consider the following: • Have you confirmed what measures will be reported to CMS? • Have you reviewed the data to be submitted for each clinician and checked it against internal reports? • Will you have confirmation of transmission to CMS AND a copy of the exact data file(s) sent? • Are you aware of when and how CMS will report their calculated MIPS score for your practice and/or clinicians? • Are you aware of the deadlines and steps CMS offers to appeal/amend scoring on submitted quality (and other) data? RPA Guide to QPP Participation

  18. 2019 Nephrology-Specific Quality Measure Bundle Table B.19 in the 2019 final rule https://www.federalregister.gov/documents/2018/11/23/2018-24170/medicare-program-revisions-to-payment-policies-under-the-physician-fee-schedule-and-other-revisions RPA Guide to QPP Participation

  19. For additional resources, including a list of MIPS measures relevant to nephrology, visit www.renalmd.org/physiciandevelopment RPA Guide to QPP Participation

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