Comparing 3 evidence-based strategies to reduce cardiovascular disease burden

Abstract

BACKGROUND: Understanding the real-world impact of clinical trials that change risk factors is important for health policy. We developed a microsimulation that estimates the population-level benefits in each US state of cardiometabolic interventions.

METHODS: We designed a state-specific agent-based simulation model with 51 million in silico individuals and estimated results for 2023 to 2040. Input data reflected current cardiometabolic health and the effects of interventions and risk factors. We constructed 3 health policy intervention scenarios based on randomized controlled trials proven to improve cardiometabolic population health: improved access to fixed-dose combination antihypertensive medication, a pharmacist-led intervention with phone-based reminders to increase adherence to statin and antihypertensive medications at the time they are initiated, and a community-based lifestyle and behavior intervention designed to prevent diabetes. Outcomes included CVD events, deaths, and disability-adjusted life years (DALYs).

RESULTS: Our simulation included a representative population of the United States, accurate at the age, sex, and state level. By 2040, the fixed-dose combination intervention was estimated to have prevented 776 000 (95% uncertainty interval, 578 000-956 000) CVD DALYs and 44 600 (95% uncertainty interval, 32 700-55 600) deaths annually. The pharmacist-led intervention prevented 170 000 (95% uncertainty interval, 129 000-208 000) CVD DALYs, and the community-based intervention prevented 152 000 (95% uncertainty interval, 128 000-173 000) CVD DALYs.

CONCLUSIONS: A fixed-dose combination of antihypertensives could prevent 1.2% of total CVD DALYs, with smaller benefits from adherence and lifestyle-focused programs. Impact of interventions varied by state. Providing accurate population-level estimates can help local health policy decision-makers implement the most impactful interventions.