Value-based care is an established framework in the healthcare industry that focuses on keeping patients healthy through proactive care and coordinated treatment while eliminating unnecessary services. As more providers and healthcare organizations adopt value-based care principles to manage costs and improve patient experiences, technology will serve an increasingly prominent role. When integrated into a value-based care model, technology serves as a key mechanism to advance care models and strengthen care delivery without overburdening staff or compromising care quality.
But what is value-based care in practice? How can it be paired with advanced technologies and artificial intelligence (AI) to transform healthcare models at scale? We answer these questions and more in our article through the lens of one of the costliest diseases in healthcare to treat: heart disease.
Value-based care is a healthcare model designed to improve patient outcomes and reduce costs by aligning healthcare organizations and provider incentives with quality and cost-effectiveness of care. With value-based care, providers and healthcare organizations are rewarded based on meeting quality targets such as patient safety, efficiency of treatment, or improving health equity.1 The result is a win-win for providers and patients: providers are encouraged to focus on preventive care and coordinate care across health care professionals, and patients stay healthier longer and avoid unnecessary treatments, reducing out-of-pocket expenses.2
Value-based care has gained traction in recent years as a way to address the inefficiencies and skyrocketing costs associated with traditional fee-for-service healthcare models. This approach promotes better health outcomes and controls costs by incentivizing providers and healthcare organizations to deliver high-quality, cost-effective care.
Several factors have contributed to the growing popularity of value-based care in healthcare:
Increasing healthcare costs: The escalating costs of healthcare have put pressure on providers, payers, and patients to find more cost-effective ways to deliver and pay for care.
Growing focus on patient outcomes: There is an increasing emphasis on improving patient outcomes and ensuring that care is tailored to the specific needs of each individual.
Technological advancements: The development and adoption of advanced technologies, such as AI and data analytics, have enabled providers to deliver more personalized and effective care.
AI has the potential to revolutionize value-based care for heart disease by enabling more personalized, efficient, and effective treatment strategies. AI technologies, such as machine learning and natural language processing, can analyze vast amounts of data to identify patterns and trends that can inform clinical decision-making and care delivery. AI can play a critical role in the diagnosis and treatment of heart disease through:
One of the key ways that AI can contribute to value-based care in heart disease is by facilitating more accurate risk stratification and prevention efforts. For example, AI algorithms can analyze electronic health records, molecular data, and lifestyle patterns to predict an individual’s risk of developing heart disease. This information can then be used to guide preventive interventions and lifestyle modifications that can help reduce the likelihood of heart disease onset.
AI algorithms can analyze medical imaging data, such as echocardiograms and MRIs, to detect signs of heart disease with greater accuracy than traditional methods. These algorithms can potentially detect signs of heart disease that may be too subtle to observe manually.
Machine learning techniques can harness vast datasets and complex patient characteristics that consider individual variations in genetic predispositions, medical histories, and therapeutic responses.3 This can help providers predict particular treatment outcomes with greater precision for patients with heart disease.
AI technologies can be used to track patient progress and adjust treatment plans as needed, ensuring that patients receive the most effective and appropriate care for their specific needs. AI can also support value-based care in heart disease by facilitating more effective post-treatment care and rehabilitation. For instance, AI-powered remote monitoring devices can collect real-time patient vital signs and physical activity data, allowing providers to monitor patients closely and intervene promptly if any complications or setbacks occur. This can help reduce hospital readmissions and improve long-term outcomes for patients with heart disease.
Heart disease is the leading cause of death worldwide and one of the most expensive conditions to treat.4,5 Treatment of heart disease can benefit significantly from implementing value-based care strategies that can improve patient outcomes and control costs, especially when paired with cutting-edge technologies like AI.
In the U.S., more than 61% of people are expected to have some type of cardiovascular disease (CVD) by 2050, with total costs expected to triple over the next three decades to $1.8 trillion.5 The economic burden of heart disease extends beyond direct medical costs, with substantial indirect costs such as lost productivity and reduced quality of life for patients and their families.
By shifting the focus from volume to value, value-based care has the potential to transform the way heart disease is treated, ultimately leading to better outcomes for patients and more efficient use of healthcare resources.
Some of the benefits of applying value-based care principles to heart disease treatment include:
Improved patient outcomes: Value-based care encourages providers to prioritize preventive care and early intervention, which can lead to better disease management and reduced complications for patients with heart disease.
Reduced healthcare costs: By incentivizing providers to deliver high-quality, cost-effective care, value-based care can help curb the rising costs associated with heart disease treatment.
Enhanced patient satisfaction: Value-based care models often emphasize patient-centered care, which can lead to higher levels of satisfaction and engagement among individuals with heart disease.
A key pillar of value-based care is not only keeping individual patients healthy but improving overall population health. Value-based care analytics such as measuring and tracking population health data over time can help drive this pillar. With population health data, healthcare organizations can quantify the disease burden across their population, strengthen risk-based contracting, and make data-driven enhancements to care program design.
Once you’ve established value-based care principles in your organization, it may seem like your work is done. But to realize the benefits of a value-based care model, you need to be able to quantify its impact on your return on investment. A population health data platform, such as HeartRisk™, that aggregates the presence of disease across your organization can help you achieve this. HeartRisk tracks heart attack risk, coronary heart disease prevalence and disease drivers in your population so that you can measure the success of strategies such as earlier interventions or targeted care programs focused on value-based care goals.
Risk-based contracting is an arrangement that links provider compensation to achieving certain quality benchmarks. In these arrangements, providers typically take on certain financial risk for the cost and quality of care but wield greater flexibility in the way that they deliver care.6 Population health data helps you identify high-cost, high-risk individuals in real-time so that you can establish tailored care interventions and proactively manage the financial risk in value-based arrangements.
How do you know if your value-based care program is working? If numbers aren’t informing the direction of your care program design, it could be costing your organization. With population health analytics, you can understand where your budget can have a meaningful impact and which patient segments need it the most. Platforms like HeartRisk also can benchmark disease prevalence against regional or national data so that you can identify strengths and areas for improvement specific to your population, which could inform more optimized resource allocation.
Advanced technology and AI play a pivotal role in shaping the future of value-based care. Heart disease, in particular, stands to benefit from this approach, given its high prevalence and associated treatment costs. But healthcare systems need to have the capacity to support it. According to a survey of payers and providers by Reveler, value-based contracting is growing, with 95% of providers reporting contract growth.7 Yet, while 98% of providers report having the right infrastructure, 94% say manual processes still dominate value-based care workflows, revealing a significant gap between perceived and actual technology readiness for value-based care.5
Integrating AI technologies can further enhance value-based care for heart disease by enabling more personalized, efficient, and effective treatment and management strategies. By overcoming the challenges associated with AI implementation, healthcare organizations, providers, patients, and payers can reap the benefits of this powerful combination, ultimately leading to improved outcomes and cost savings in heart disease care.
Clinically reviewed by: Robert Philibert, MD, PhD
Smith TM. What is value-based care? These are the key elements. American Medical Association. Published August 8, 2024. https://www.ama-assn.org/practice-management/payment-delivery-models/what-value-based-care-these-are-key-elements
Feldheim B. Outcomes over volume: how prevention powers value-based care. American Medical Association. Published May 22, 2025. https://www.ama-assn.org/practice-management/payment-delivery-models/outcomes-over-volume-how-prevention-powers-value-based
Gala D, Behl H, Shah M, Makaryus AN. The role of artificial intelligence in improving patient outcomes and future of healthcare delivery in cardiology: a narrative review of the literature. Healthcare (Basel). 2024;12(4):481. doi:10.3390/healthcare12040481
World Health Organization. Cardiovascular diseases. https://www.who.int/health-topics/cardiovascular-diseases
American Heart Association. Population shifts, risk factors may triple U.S. cardiovascular disease costs by 2050. American Heart Association Newsroom. Published June 4, 2024. https://newsroom.heart.org/news/population-shifts-risk-factors-may-triple-u-s-cardiovascular-disease-costs-by-2050
PricewaterhouseCoopers. Risk contracting overview. In: Health Care Entities guide. Viewpoint. https://viewpoint.pwc.com/dt/us/en/pwc/accounting_guides/health-care/health_care_guide/chapter_4_risk_contracting_by/4_1_risk_contracting_overview.html
Reveleer, Inc. The State of Technology in Value-Based Care 2026: AI Adoption Without Readiness. Reveleer; 2026. https://go.reveleer.com/hubfs/260707--VBC%20Report/State_Of_Technology_in_Value_Based_Care_Report_2026_Reveleer.pdf
