Evidence map›Paper›PMID 35272505›Full record

Observational studyCirculation. Cardiovascular quality and outcomes2022

Reducing Cardiovascular Risk in the Medicare Million Hearts Risk Reduction Model: Insights From the National Cardiovascular Data Registry PINNACLE Registry.

William B Borden, Jingyan Wang, Philip Jones, Yuanyuan Tang, Johanna Contreras, Stacie L Daugherty, Nihar R Desai, Salim S Virani, Jason H Wasfy, Thomas M Maddox

Open access · bronzeAbstract readObservational Study
In one paragraph

Observational study in Circulation. Cardiovascular quality and outcomes, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.7field-weighted citation impact, top 31% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
  3. Assessment of Atherosclerotic Cardiovascular Disease Risk in Primary Prevention.Journal of cardiopulmonary rehabilitation and prevention · 2022
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 10 institutions in 1 country.

William B BordenGeorge Washington University, Washington, DC (W.B.B.).ORCID 0000-0002-8246-5957
Jingyan WangUniversity of Texas Health Science Center, Houston (J.W.).ORCID 0000-0002-8000-2174
Philip JonesSaint Luke's Mid America Heart Institute and University of Missouri-Kansas City School of Medicine, Kansas City (P.J.).ORCID 0000-0002-7136-4464
Yuanyuan TangEli Lilly and Company, Indianapolis, IN (Y.T.).
Johanna ContrerasMount Sinai, New York, NY (J.C.).
Stacie L DaughertyUniversity of Colorado School of Medicine, Aurora (S.L.D.).ORCID 0000-0001-8969-566X
Nihar R DesaiYale University, New Haven, CT (N.R.D.).ORCID 0000-0003-2384-2545
Salim S ViraniMichael E. DeBakey Veterans Affairs Medical Center & Baylor College of Medicine, Houston, TX (S.S.V.).ORCID 0000-0001-9541-6954
Jason H WasfyHarvard University, Boston, MA (J.H.W.).ORCID 0000-0002-0871-5970
Thomas M MaddoxWashington University School of Medicine, St. Louis, MO (T.M.M.).ORCID 0000-0003-1426-9433
Eli Lilly (United States) · USGeorge Washington University · USHarvard University · USMichael E. DeBakey VA Medical Center · USMount Sinai Hospital · USSaint Luke's Health System · USThe University of Texas Health Science Center · USUniversity of Colorado Denver · USWashington University in St. Louis · USYale University · US

Funding

CD2H - The National COVID Cohort Collaborative (N3C) IDeA CTR CollaborationU24TR002306 · NCATS · UNIVERSITY OF COLORADO DENVER · PI CHUTE, CHRISTOPHER G, EICHMANN, DAVID A. · 2017 to 2021
$28.9M
COVID-19 and Acute Medical Care: Impact on Dementia PatientsR01AG062282 · NIA · MASSACHUSETTS GENERAL HOSPITAL · PI HSU, JOHN · 2018 to 2022
$4.5M
Using values affirmation to reduce the effects of perceived discrimination on hypertension disparitiesR01HL133343 · NHLBI · UNIVERSITY OF COLORADO DENVER · PI DAUGHERTY, STACIE LUTHER · 2016 to 2019
$3.0M
NCATS NIH HHS U24 TR002306NHLBI NIH HHS R01 HL133343NIA NIH HHS R01 AG062282
6 · The paper itself

Abstract

backgroundThe Million Hearts Cardiovascular Disease Risk Reduction Model provides financial incentives for practices to lower 10-year atherosclerotic cardiovascular disease (ASCVD) risk for high-risk (ASCVD ≥30%) Medicare patients. To estimate average practice-level ASCVD risk reduction, we applied optimal trial outcomes to a real-world population with high ASCVD risk.

methodsThis study uses observational registry data from the National Cardiovascular Data Registry Practice Innovation and Clinical Excellence Registry from January 2013 to June 2016. We modeled ASCVD risk reductions using historical clinical trial data (reducing cholesterol by 26.5%, reducing systolic blood pressure by 10.9%, reducing smoking rates by 21.8%) the average reduction in ASCVD risk associated with individual and combined risk factor modifications, and then percentage of practices achieving the various incentive thresholds for the Million Hearts Model.

resultsThe final study population included 135 166 patients, with 16 248 (12.0%) with 10-year ASCVD risk of ≥30%, but without existing ASCVD. The mean 10-year ASCVD risk was 41.9% (±1 SD of 11.6). Using risk factor reductions from clinical trials, lowering cholesterol, blood pressure, and smoking rates reduced 10-year ASCVD risk by 3.3% (±3.1), 6.3% (±1.1) and 0.5% (±1.3), respectively. Combining all 3 reductions resulted in a 9.7% (±3.6) reduction, with 67 (27.0%) of practices achieving a patient-level average 10-year ASCVD risk reduction of ≥10%, 181 (73.0%) achieving a 2 to 10% reduction, and no practice achieving <2% reduction.

conclusionsIn cardiology practices, about 1 out of 8 patients have a 10-year ASCVD risk ≥30% and qualify as high risk in the Million Hearts Model. If practices target the three main modifiable risk factors and achieve reductions similar to clinical trial results, ASCVD risk could be substantially lowered and all practices could receive incentive payments. These findings support the potential benefit of the Million Hearts Model and provide guidance to participating practices.

Indexed as

AtherosclerosisCardiovascular DiseasesAgedCholesterolHeart Disease Risk FactorsHumansMedicareRegistriesRisk FactorsRisk Reduction BehaviorUnited StatesCholesterolatherosclerosis ◼ blood pressure ◼ cardiovasculardiseases ◼ myocardial infarction ◼ risk

Identifiers

PMID35272505
PMCPMC9187962
OpenAlexW4220746988

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.