Model cuts 5-year CVD event risk for Medicare patients

Results from a new study in JAMA found that the Million Hearts Model, which paid participating health care organizations to assess and reduce patients’ CVD risk, decreased myocardial infarction and stroke rates for Medicare fee-for-service beneficiaries aged 40 to 79 years at high or medium risk for these events.

The Million Hearts Model, part of the broader Million Hearts initiative, is co-led by CDC and CMS and aims to prevent one million heart attacks and strokes over 5 years.

According to the study findings, the Million Hearts Cardiovascular Disease Risk Reduction Model reduced the probability of a first-time myocardial infarction or stroke over 5 years by 0.3 percentage points, and the probability of a first-time CVD event or CVD death by 0.4 percentage points for study participants when compared with the general population.

Researchers said the results support guideline recommendations for cardiovascular risk assessment.

In the trial, which ran from 2017 to 2021, patients with no previous myocardial infarctions or stroke and with high or medium CVD risk were enrolled from U.S.-based primary care and specialty practices, health centers, and hospital-based outpatient clinics. Organizations were assigned to a model intervention group or standard care control group. Of 516 organizations, 342 entered patients into the study population.

CVD-related Medicare spending in the intervention and control groups was similar, suggesting that paying for the intervention did not result in higher costs overall.

Using a novel, longitudinal risk calculator, researchers noted that the model was unique in paying for overall CVD risk reduction, rather than tying performance-based payments to control of individual risk factors.

The researchers said that the findings have implications for value-based payment policy.

“Systematic reviews show that value-based payment initiatives, both overall and for CVD care, have improved care processes, but few improved long-term outcomes. This randomized pragmatic trial suggests that paying for risk assessment and reduction could improve outcomes of public health importance. However, high rates of model nonparticipation demonstrate the importance of calibrating payments to effort and reducing burden of data sharing,” researchers wrote.