IDEAS home Printed from https://ideas.repec.org/p/mpr/mprres/d4649f0778804c4eb0adcf2dbdfdcf36.html
   My bibliography  Save this paper

Evaluation of the Million Hearts® Cardiovascular Disease Risk Reduction Model: Third Annual Report

Author

Listed:
  • Laura Blue
  • Gregory Peterson
  • Keith Kranker
  • Tessa Huffman
  • Alli Steiner
  • Amanda Markovitz
  • Malcolm Williams
  • Kate Stewart
  • Julia Rollison
  • Jia Pu
  • Thomas Concannon
  • Liisa Hiatt
  • Nabeel Qureshi
  • Precious Ogbuefi
  • David Magid
  • Leslie Conwell
  • Nancy McCall
  • Michael Barna
  • Linda Barterian
  • Elizabeth Holland
  • Dan Kinber
  • Sandi Nelson
  • Lei Rao
  • Carol Razafindrakoto
  • Danielle Whicher

Abstract

In its first three years, the Million Hearts Model improved cardiovascular preventive care, but did not yet reduce observed heart attacks and strokes or lower Medicare spending.

Suggested Citation

  • Laura Blue & Gregory Peterson & Keith Kranker & Tessa Huffman & Alli Steiner & Amanda Markovitz & Malcolm Williams & Kate Stewart & Julia Rollison & Jia Pu & Thomas Concannon & Liisa Hiatt & Nabeel Qu, "undated". "Evaluation of the Million Hearts® Cardiovascular Disease Risk Reduction Model: Third Annual Report," Mathematica Policy Research Reports d4649f0778804c4eb0adcf2db, Mathematica Policy Research.
  • Handle: RePEc:mpr:mprres:d4649f0778804c4eb0adcf2dbdfdcf36
    as

    Download full text from publisher

    File URL: https://innovation.cms.gov/data-and-reports/2021/mhcvdrrm-thirdannevalrpt
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Greg Peterson & Linda Barterian & Keith Kranker & Amanda Markovitz & Adam Rose & Rumin Sarwar & Allison Steiner & Leslie Conwell & Jia Pu & Michael Barna & David Magid & Kate Steward & Laura Blue & Da, "undated". "Evaluation of the Million Hearts® Cardiovascular Disease Risk Reduction Model: Second Annual Report," Mathematica Policy Research Reports 632a9404b1ce4f8996f890018, Mathematica Policy Research.
    2. repec:mpr:mprres:6573 is not listed on IDEAS
    3. Peter Z. Schochet, "undated". "Is Regression Adjustment Supported by the Neyman Model for Causal Inference? (Presentation)," Mathematica Policy Research Reports abfc39d59c714499b2fe42f68, Mathematica Policy Research.
    4. Peter Z. Schochet, "undated". "Is Regression Adjustment Supported By the Neyman Model for Causal Inference?," Mathematica Policy Research Reports 782da2242fba458eb61752f96, Mathematica Policy Research.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. repec:mpr:mprres:7638 is not listed on IDEAS
    2. repec:mpr:mprres:6965 is not listed on IDEAS
    3. repec:mpr:mprres:6286 is not listed on IDEAS
    4. repec:mpr:mprres:7273 is not listed on IDEAS
    5. Kenneth Fortson & Natalya Verbitsky-Savitz & Emma Kopa & Philip Gleason, 2012. "Using an Experimental Evaluation of Charter Schools to Test Whether Nonexperimental Comparison Group Methods Can Replicate Experimental Impact Estimates," Mathematica Policy Research Reports 27f871b5b7b94f3a80278a593, Mathematica Policy Research.
    6. Peter Z. Schochet, 2018. "Design-Based Estimators for Average Treatment Effects for Multi-Armed RCTs," Journal of Educational and Behavioral Statistics, , vol. 43(5), pages 568-593, October.
    7. Lu, Jiannan, 2016. "On randomization-based and regression-based inferences for 2K factorial designs," Statistics & Probability Letters, Elsevier, vol. 112(C), pages 72-78.
    8. repec:mpr:mprres:6094 is not listed on IDEAS
    9. John Deke, 2016. "Design and Analysis Considerations for Cluster Randomized Controlled Trials That Have a Small Number of Clusters," Evaluation Review, , vol. 40(5), pages 444-486, October.
    10. Peter Z. Schochet & Hanley Chiang, "undated". "Technical Methods Report: Estimation and Identification of the Complier Average Causal Effect Parameter in Education RCTs," Mathematica Policy Research Reports 947d1823e3ff42208532a763d, Mathematica Policy Research.
    11. Peter Z. Schochet, 2020. "Analyzing Grouped Administrative Data for RCTs Using Design-Based Methods," Journal of Educational and Behavioral Statistics, , vol. 45(1), pages 32-57, February.
    12. Joel A. Middleton, 2021. "Unifying Design-based Inference: On Bounding and Estimating the Variance of any Linear Estimator in any Experimental Design," Papers 2109.09220, arXiv.org.
    13. Melissa A. Clark & Philip Gleason & Christina Clark Tuttle & Marsha K. Silverberg, 2011. "Do Charter Schools Improve Student Achievement? Evidence from a National Randomized Study," Mathematica Policy Research Reports af41392138504f369930e6f2b, Mathematica Policy Research.
    14. Peter Z. Schochet, 2010. "The Late Pretest Problem in Randomized Control Trials of Education Interventions," Journal of Educational and Behavioral Statistics, , vol. 35(4), pages 379-406, August.
    15. repec:mpr:mprres:7443 is not listed on IDEAS
    16. Peter Z. Schochet, "undated". "The Late Pretest Problem in Randomized Control Trials of Education Interventions," Mathematica Policy Research Reports fb514df5dbb84a5dbea79865c, Mathematica Policy Research.
    17. Peter Z. Schochet, "undated". "Technical Methods Report: Statistical Power for Regression Discontinuity Designs in Education Evaluations," Mathematica Policy Research Reports 61fb6c057561451a8a6074508, Mathematica Policy Research.
    18. repec:mpr:mprres:8128 is not listed on IDEAS
    19. Peter Z. Schochet, 2013. "Estimators for Clustered Education RCTs Using the Neyman Model for Causal Inference," Journal of Educational and Behavioral Statistics, , vol. 38(3), pages 219-238, June.
    20. repec:mpr:mprres:6372 is not listed on IDEAS
    21. Susan Athey & Guido Imbens, 2016. "The Econometrics of Randomized Experiments," Papers 1607.00698, arXiv.org.
    22. Thomas Fraker & Peter Baird & Alison Black & Arif Mamun & Michelle Manno & John Martinez & Anu Rangarajan & Debbie Reed, "undated". "The Social Security Administration's Youth Transition Demonstration Projects: Interim Report on Colorado Youth WINS," Mathematica Policy Research Reports f57994086f8a436ca69e24800, Mathematica Policy Research.
    23. Peter Z. Schochet, 2021. "Statistical Power for Estimating Treatment Effects Using Difference-in-Differences and Comparative Interrupted Time Series Designs with Variation in Treatment Timing," Papers 2102.06770, arXiv.org, revised Oct 2021.
    24. Alberto Abadie & Susan Athey & Guido W. Imbens & Jeffrey M. Wooldridge, 2014. "Finite Population Causal Standard Errors," NBER Working Papers 20325, National Bureau of Economic Research, Inc.
    25. Peter Z. Schochet, "undated". "Statistical Theory for the RCT-YES Software: Design-Based Causal Inference for RCTs," Mathematica Policy Research Reports a0c005c003c242308a92c02dc, Mathematica Policy Research.
    26. Thomas Fraker & Todd Honeycutt & Arif Mamun & Michelle Manno & John Martinez & Bonnie O'Day & Debbie Reed & Allison Thompkins, "undated". "The Social Security Administration's Youth Transition Demonstration Projects: Interim Report on Broadened Horizons, Brighter Futures," Mathematica Policy Research Reports 7698c1fc1bde4b0a8a50f042b, Mathematica Policy Research.
    27. Thomas Fraker & Peter Baird & Arif Mamun & Michelle Manno & John Martinez & Debbie Reed & Allison Thompkins, "undated". "The Social Security Administration's Youth Transition Demonstration Projects: Interim Report on the Career Transition Program," Mathematica Policy Research Reports 8b90037b73b64e07a8c762e83, Mathematica Policy Research.
    28. Słoczyński, Tymon, 2012. "New Evidence on Linear Regression and Treatment Effect Heterogeneity," MPRA Paper 39524, University Library of Munich, Germany.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:mpr:mprres:d4649f0778804c4eb0adcf2dbdfdcf36. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joanne Pfleiderer or Cindy George (email available below). General contact details of provider: https://edirc.repec.org/data/mathius.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.