Effects of the Million Hearts Model on Myocardial Infarctions, Strokes, and Medicare Spending: A Randomized Clinical Trial.

Importance: The Million Hearts Model paid health care organizations to assess and reduce cardiovascular disease (CVD) risk. Model effects on long-term outcomes are unknown. Objective: To estimate model effects on first-time myocardial infarctions (MIs) and strokes and Medicare spending over a period up to 5 years. Design, Setting, and Participants: This pragmatic cluster-randomized trial ran from 2017 to 2021, with organizations assigned to a model intervention group or standard care control group. Randomized organizations included 516 US-based primary care and specialty practices, health centers, and hospital-based outpatient clinics participating voluntarily. Of these organizations, 342 entered patients into the study population, which included Medicare fee-for-service beneficiaries aged 40 to 79 years with no previous MI or stroke and with high or medium CVD risk (a 10-year predicted probability of MI or stroke [ie, CVD risk score] ≥15%) in 2017-2018. Intervention: Organizations agreed to perform guideline-concordant care, including routine CVD risk assessment and cardiovascular care management for high-risk patients. The Centers for Medicare & Medicaid Services paid organizations to calculate CVD risk scores for Medicare fee-for-service beneficiaries. CMS further rewarded organizations for reducing risk among high-risk beneficiaries (CVD risk score ≥30%). Main Outcomes and Measures: Outcomes included first-time CVD events (MIs, strokes, and transient ischemic attacks) identified in Medicare claims, combined first-time CVD events from claims and CVD deaths (coronary heart disease or cerebrovascular disease deaths) identified using the National Death Index, and Medicare Parts A and B spending for CVD events and overall. Outcomes were measured through 2021. Results: High- and medium-risk model intervention beneficiaries (n = 130 578) and standard care control beneficiaries (n = 88 286) were similar in age (median age, 72-73 y), sex (58%-59% men), race (7%-8% Black), and baseline CVD risk score (median, 24%). The probability of a first-time CVD event within 5 years was 0.3 percentage points lower for intervention beneficiaries than control beneficiaries (3.3% relative effect; adjusted hazard ratio [HR], 0.97 [90% CI, 0.93-1.00]; P = .09). The 5-year probability of combined first-time CVD events and CVD deaths was 0.4 percentage points lower in the intervention group (4.2% relative effect; HR, 0.96 [90% CI, 0.93-0.99]; P = .02). Medicare spending for CVD events was similar between the groups (effect estimate, -$1.83 per beneficiary per month [90% CI, -$3.97 to -$0.30]; P = .16), as was overall Medicare spending including model payments (effect estimate, $2.11 per beneficiary per month [90% CI, -$16.66 to $20.89]; P = .85). Conclusions and Relevance: The Million Hearts Model, which encouraged and paid for CVD risk assessment and reduction, reduced first-time MIs and strokes. Results support guidelines to use risk scores for CVD primary prevention. Trial Registration: ClinicalTrials.gov Identifier: NCT04047147.

Effect of the Million Hearts Cardiovascular Disease Risk Reduction Model on Initiating and Intensifying Medications: A Prespecified Secondary Analysis of a Randomized Clinical Trial.

Importance: The Million Hearts Cardiovascular Disease (CVD) Risk Reduction Model pays provider organizations for measuring and reducing Medicare patients' cardiovascular risk. Objective: To assess whether the model increases the initiation or intensification of antihypertensive medications or statins among patients with blood pressure or low-density lipoprotein (LDL) cholesterol levels above guideline thresholds for treatment intensification. Design, Setting, and Participants: This prespecified secondary analysis of a cluster-randomized, pragmatic trial included primary care and cardiology practices, health care centers, and hospital-based outpatient departments across the US. Participants included Medicare patients who were enrolled into the model in 2017 by participating organizations and who were at high risk and at medium risk of a myocardial infarction or stroke in 10 years. Patient outcomes were analyzed for 1 year postenrollment (through December 2018) using an intent-to-treat design. Analysis began November 2019. Interventions: US Centers for Medicare & Medicaid Services paid organizations for risk stratifying Medicare patients and reducing CVD risk among high-risk patients through discussing risk scores, developing individualized risk reduction plans, and following up with patients twice yearly. Main Outcomes and Measures: Initiating or intensifying statin or antihypertensive therapy within 1 year of enrollment, measured in Medicare Part D claims, and LDL cholesterol and systolic blood pressure levels approximately 1 year after enrollment, measured in usual care and reported to Centers for Medicare & Medicaid Services via a data registry (data complete for 51% of high-risk enrollees). The study's primary outcome (incidence of first-time myocardial infarction and stroke) is not reported because the trial is ongoing. Results: A total of 330 primary care and cardiology practices, health care centers, and hospital-based outpatient departments and 125 436 Medicare patients were included in this analysis. High-risk patients in the intervention group had a mean (SD) age of 74 (4.1), 15 213 (63%) were male, 21 657 (90%) were receiving antihypertensive medication at baseline, and 16 558 (69%) were receiving statins. Almost all (21 791 [91%]) high-risk intervention group patients had above-threshold systolic blood pressure level (>130 mm Hg), LDL cholesterol level (>70 mg/dL), or both. Patients in the intervention group with these risk factors were more likely than control patients (8127 [37.3%] vs 4753 [32.4%]; adjusted difference in percentage points, 4.8; 95% CI, 2.9-6.7; P < .001) to initiate or intensify statins or antihypertensive medication. Centers for Medicare & Medicaid Services did not pay for CVD risk reduction for medium-risk enrollees, but initiation or intensification rates for these enrollees were also higher in the intervention vs control groups (12 668 [27.9%] vs 7544 [24.8%]; adjusted difference in percentage points, 3.1; 95% CI, 1.9-4.3; P < .001). Among high-risk enrollees with clinical data approximately 1 year after enrollment, LDL cholesterol level was slightly lower in the intervention vs control groups (mean [SD], 89 [31.8] vs 91 [32.1] mg/dL; adjusted difference in percentage points, -1.8; 95% CI, -2.9 to -0.6; P = .002), as was systolic blood pressure (mean [SD], 133 [15.7] vs 135 [16.4] mm Hg; adjusted difference in percentage points, -1.7; 95% CI, -2.8 to -0.6; P = .003). Conclusions and Relevance: In this study, a pay-for-performance model led to modest increases in the use of CVD medications in a range of organizations, despite high medication use at baseline.

Testing the Replicability of a Successful Care Management Program: Results from a Randomized Trial and Likely Explanations for Why Impacts Did Not Replicate.

OBJECTIVES: To test whether a care management program could replicate its success in an earlier trial and determine likely explanations for why it did not. DATA SOURCES/SETTING: Medicare claims and nurse contact data for Medicare fee-for-service beneficiaries with chronic illnesses enrolled in the trial in eastern Pennsylvania (N = 483). STUDY DESIGN: A randomized trial with half of enrollees receiving intensive care management services and half receiving usual care. We developed and tested hypotheses for why impacts declined. DATA EXTRACTION: All outcomes and covariates were derived from claims and the nurse contact data. PRINCIPAL FINDINGS: From 2010 to 2014, the program did not reduce hospitalizations or generate Medicare savings to offset program fees that averaged $260 per beneficiary per month. These estimates are statistically different (p < .05) from the large reductions in hospitalizations and spending in the first trial (2002-2010). The treatment-control differences in the second trial disappeared because the control group's risk-adjusted hospitalization rate improved, not because the treatment group's outcomes worsened. CONCLUSION: Even if demonstrated in a randomized trial, successful results from one test may not replicate in other settings or time periods. Assessing whether gaps in care that the original program filled exist in other settings can help identify where earlier success is likely to replicate.