Type Purpose CharacteristicsFormative Local improvement, rapidtesting, inform nexttest, shape outcomesSmaller scale, small...
••
Was thechange animprovement?What can welearn?Should wespread thechange?ChangeResultsfrom 10Sites
Data Tool From IOM WebsiteGoal: explore current distribution of FFS spend surfacing ideas re how to impact costs.
UCL 10414.15CL 7994.21LCL 5574.274487.155487.156487.157487.158487.159487.1510487.1511487.15AK AR CA CT DE GA IA IL KS LA M...
Data Tool From IOM WebsiteDrill Down3000350040004500500055006000650070007500800085002007 2008 2009 2010Standardized Risk-A...
But, at some point as youincrease the amount ofinformation you actuallybegin to increase the levelof confusion again.Confu...
ProgrammanagementSharedlearningEvaluation
•••••••–––
Pioneer ACO Driver DiagramJune 2012100% of the originalPioneer ACOsgenerate sufficientcost savings andqualityimprovements ...
The distributions of sixutilization measures (out of20) are shown. The top 5% ofthe non-annualizedexpenditure (upperleft, ...
700450200700450200700450200700450200Q1 Q2 Q3 Q1 Q2 Q3 Q1 Q2 Q3 Q1 Q2 Q3 Q1 Q2 Q3 Q1 Q2 Q3 Q1 Q2 Q3 Q1 Q2 Q329 813 14 19 7 ...
8410412414416418420422424416 25 15 1 23 24 12 32 3 30 18 28 22 26 9 2 20 6 27 31 17 21 4 10 13 14 19 7 11 5 29 8All Condit...
19 Pioneers increased provider participationbetween PY1 and PY25 Pioneers had little change (-15 and +15)8 Pioneers decrea...
0%10%20%30%40%50%60%70%80%90%100%25 4 27* 15 18* 10 31* 6* 5 1 9 3* 13* 14* 30* 2 24 16 28 19 22 11 23 12 26 7 17 8 29 20 ...
0.00.51.01.52.02.53.03.54.011 22 8 25 5 2 16 10 26 23 28 32 31 20 13 3 27 6 12 18 17 14 21* 19 9 15 1 29 7 30 4 24Care Coo...
ProgrammanagementSharedlearningEvaluation
Health Datapalooza 2013: Uses of CMS Data in Rapid-Cycle Innovation - Rocco Perla & Hoangmai Pham
Health Datapalooza 2013: Uses of CMS Data in Rapid-Cycle Innovation - Rocco Perla & Hoangmai Pham
Health Datapalooza 2013: Uses of CMS Data in Rapid-Cycle Innovation - Rocco Perla & Hoangmai Pham
Health Datapalooza 2013: Uses of CMS Data in Rapid-Cycle Innovation - Rocco Perla & Hoangmai Pham
Health Datapalooza 2013: Uses of CMS Data in Rapid-Cycle Innovation - Rocco Perla & Hoangmai Pham
Health Datapalooza 2013: Uses of CMS Data in Rapid-Cycle Innovation - Rocco Perla & Hoangmai Pham
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Health Datapalooza 2013: Uses of CMS Data in Rapid-Cycle Innovation - Rocco Perla & Hoangmai Pham

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Health Datapalooza IV: June 3rd-4th, 2013
Uses of CMS Data in Rapid-Cycle Innovation
Moderator:
Kavita Patel, Managing Director for Clinical Transformation and Delivery, Brookings Institution
Speakers:
Rocco Perla, Director, Learning and Diffusion Group, Centers for Medicare & Medicaid Services
Hoangmai Pham, Director, Division of Accountable Care Organization Populations, Centers for Medicare & Medicaid Services
Will Shrank, Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women’s Hospital, Harvard Medical School
Farzad Mostashari, National Coordinator for Health Information Technology (ONC), US Department of Health and Human Services

The rapid proliferation of health data and improved usability has led to a sea change in how new health programs are designed, implemented and evaluated and in the speed in which innovation can occur. In this session, officials from the Centers for Medicare & Medicaid Services and the Office of the National Coordinator for Health Information Technology will describe specific government programs or functions that rely on rapid use of data to support patient targeting, feedback and learning, and highlight developments in data use that will promote innovation to deliver higher quality care at lower costs to patients.

This session is eligible for continuing education credit.

Published in: Health & Medicine, Business
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  • Of the models that we are supporting, there are No “Turnkey” Solutions – providers cannot simply flip a switch and optimally implement an ACO model, transform primary care practices, or coordinate all services in a hospitalThe models we will require fundamental changes in the structure of healthcare delivery, as we realign incentives for health systems, primary care, hospitals and other health servicesIn each of these cases, Substantial learning and adaptation will be necessary before achieving the greatest efficienciesHealthcare delivery in these models will be maturing once implemented – they wll not be staticIt is important to note that while we all agree that RCTs offer the most incontrovertible evidence about the effect of an intervention, they will not be feasible in most cases for the Innovation Center. Practically, we must identify providers who are willing and eager to participate in the models we plan to test. This practicality, along with our need to move quickly, require that we implement “natural experiments” and use quasi-experimental designs to evaluate effectiveness.
  • Health Datapalooza 2013: Uses of CMS Data in Rapid-Cycle Innovation - Rocco Perla & Hoangmai Pham

    1. 1. Type Purpose CharacteristicsFormative Local improvement, rapidtesting, inform nexttest, shape outcomesSmaller scale, smalln’s, messy, unadjusted, targeted samples, timeseriesSummative Large scalebenefit, determine neteffects, summarizeoutcomesLarger scale, largen’s, power, adjusted, onelarge test, p-values
    2. 2. ••
    3. 3. Was thechange animprovement?What can welearn?Should wespread thechange?ChangeResultsfrom 10Sites
    4. 4. Data Tool From IOM WebsiteGoal: explore current distribution of FFS spend surfacing ideas re how to impact costs.
    5. 5. UCL 10414.15CL 7994.21LCL 5574.274487.155487.156487.157487.158487.159487.1510487.1511487.15AK AR CA CT DE GA IA IL KS LA MD MI MO MT ND NH NM NY OK PA RI SD TX VA WA WVStandardizedRisk-AdjustedPerCapitaCosts^StateX Chart (Standardized Risk-Adjusted Per Capita Costs - 2010)BA
    6. 6. Data Tool From IOM WebsiteDrill Down3000350040004500500055006000650070007500800085002007 2008 2009 2010Standardized Risk-Adjusted Per Capita Costs – Over TimeNational Per Capita Costs State A Per Capita Cost State B Per Capita Cost
    7. 7. But, at some point as youincrease the amount ofinformation you actuallybegin to increase the levelof confusion again.ConfusionInformationLow HighHighThere is a point at whichincreasing informationreduces confusion.
    8. 8. ProgrammanagementSharedlearningEvaluation
    9. 9. •••••••–––
    10. 10. Pioneer ACO Driver DiagramJune 2012100% of the originalPioneer ACOsgenerate sufficientcost savings andqualityimprovements toqualify forpopulation-basedpayments in yearthree of the ModelACOdemonstratessignificant costsavings andqualityimprovementsCMMIdemonstratesan effective ACOmodel that canscaleAim• Peer based learning• Strong data systems• Staff and resources for continuous improvement• Capacity to test new ideas at point of care• Population-based measurement• New payment models for clinicians• Clinician involvement in changes• Involvement of patients/consumer advocates inchange• New and innovative communication strategies• Engagement with private payers and Medicaidagencies• ACO models understood by state insurancecommissioners and other regulatory bodies• R&D, innovation, and breakthrough ideas• Adaptation of the ACO framework at a regional andlocal level• Adaptation at a national and regulatory levelContinuous careimprovement driven by dataUtilization patterns for valuebased careOrganizational structurecapable of achieving resultsProductive relationships withprovidersBeneficiary engagementContinuous evolution of theACO modelTrustworthy partnershipand unconditional teamworkwith CMSPrimary Drivers Secondary DriversPayment reform(with risk for gains or losses)• Recognition of Pioneers as national leaders• Effective communication• Effective and collaborative problem-solving• CMS facilitation of and technical assistance forpeer-based learning• CMS and Pioneers honor the Pioneer Agreement• Coordinated care transitions• Care management of high risk patients• Utilization of primary care services• Appropriate use of hospital and ancillary services• Others - TBD by Pioneers• Effective leadership and governance• Improvements in overhead and waste(i.e., non-value added activities)
    11. 11. The distributions of sixutilization measures (out of20) are shown. The top 5% ofthe non-annualizedexpenditure (upperleft, Q3, median 40.2%)demonstrate higher than theReference Population(RP)(median 39.8%); whilehospitalizationevents(lower, right, Q3, median 370.2) are fewer than theRP(Q3, median 382.3). Thechanges over the threequarters vary amongmeasures, but most changesare less than one percent andthey are also not statisticallysignificant.
    12. 12. 700450200700450200700450200700450200Q1 Q2 Q3 Q1 Q2 Q3 Q1 Q2 Q3 Q1 Q2 Q3 Q1 Q2 Q3 Q1 Q2 Q3 Q1 Q2 Q3 Q1 Q2 Q329 813 14 19 7 11 54 1020 6 27 31 17 219 23 30 18 28 22 2616 25 15 1 23 24 12 32
    13. 13. 8410412414416418420422424416 25 15 1 23 24 12 32 3 30 18 28 22 26 9 2 20 6 27 31 17 21 4 10 13 14 19 7 11 5 29 8All Condition Readmission RateQ1 Q2 Q3 Q3 All Pioneer ACOs(160) Q3 National Reference Population (157)
    14. 14. 19 Pioneers increased provider participationbetween PY1 and PY25 Pioneers had little change (-15 and +15)8 Pioneers decreased Provider Participation
    15. 15. 0%10%20%30%40%50%60%70%80%90%100%25 4 27* 15 18* 10 31* 6* 5 1 9 3* 13* 14* 30* 2 24 16 28 19 22 11 23 12 26 7 17 8 29 20 21 32PCPs in an ACO Receiving Individual Performance Reports (%)Q3 Mean Q4 Mean Q3 Q4
    16. 16. 0.00.51.01.52.02.53.03.54.011 22 8 25 5 2 16 10 26 23 28 32 31 20 13 3 27 6 12 18 17 14 21* 19 9 15 1 29 7 30 4 24Care Coordinators per 1000 Pioneer BeneficiariesQ1 Q2 Q3 median of 3 quarters0.01.02.03.04.0Q1 Q2 Q3Ratio0.47 0.690.97
    17. 17. ProgrammanagementSharedlearningEvaluation

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