Cardiovascular disease (CVD) remains the leading cause of death in the United States, impacting nearly half of American adults, yet only one in three adults received care for cardiovascular conditions or risk factors in 2020. The American Heart Association forecasts that the economic burden of cardiovascular conditions will nearly quadruple–from $393 billion to $1.49 trillion–between 2020 and 2050. With a growing prevalence of risk factors like obesity, diabetes, and hypertension, the burden of CVD continues to grow. Improving the efficiency and effectiveness of cardiovascular care and disease prevention is critical to addressing the increasing costs of CVD.
A key challenge in cardiovascular care is navigating complex and often chronic conditions. Fragmented coordination among primary care physicians, cardiologists, and other specialists can lead to delays in care, unnecessary and/or excessive testing, and poor adherence to long-term care plans. Health plans, in turn, also struggle to balance costs and benefits due to limited clinical data across multiple providers, making it difficult to manage chronic conditions effectively. Traditional prior authorization processes add to these inefficiencies, creating administrative bottlenecks that delay care and frustrate providers and patients. However, advancements in intelligent prior authorization and cardiology care offer a path to overcoming these obstacles.
The impact of fragmentation in cardiovascular care
Managing cardiovascular conditions like diabetes, hypertension, and CVD often requires input and coordination from multiple providers across specialties. Unfortunately, such care is frequently disjointed. Disparate departments try to piece together the data from misaligned communication and inconsistent use of evidence-based guidelines. These inefficiencies can lead to the selection of inappropriate diagnostic services and delays, which can worsen patients’ outcomes. For example, a patient experiencing early symptoms of coronary artery disease might encounter delays in receiving stress tests or angiography due to unclear approval pathways.
AI-driven prior authorization solutions address these challenges by automating approvals, streamlining traditionally burdensome processes, and ensuring care is aligned with current evidence-based guidelines. AI and clinical intelligence facilitate real-time decision-making, enabling providers to identify the appropriate diagnostic service and setting, collaborate more effectively, and focus on delivering timely care. This approach helps ensure patients receive the most appropriate, effective, and high-quality care, improving their overall care journey and outcomes.
Reducing unnecessary testing and avoidable costs
The financial burden of unnecessary testing in cardiovascular care is significant. The economic burden of CVD is projected to reach $1.490 trillion annually by 2050. Inconsistent approval processes and redundant diagnostics inflate costs and lead to patient frustration and disengagement. Optimizing care for this population presents an important opportunity to reduce costs. AI-driven prior authorization solutions can preempt these issues by identifying and suggesting to providers high-value care (e.g., appropriate sites of service) that can improve outcomes based on individual patients’ characteristics.
For example, research conducted by cardiology societies like the American Association of Cardiology indicates that myocardial perfusion imaging (MPI-SPECT) works best for patients with symptoms who have a moderate risk of significant coronary artery disease (CAD). However, the overuse of this expensive procedure increases healthcare spending and can expose patients to unnecessary radiation without clear benefits. Intelligent prior authorization helps optimize the use of MPI-SPECT by suggesting it for appropriate cases while guiding providers toward safer, more cost-effective testing options. This approach allows health plans to reduce spending and maintain safe, high-quality care for patients with CAD.
Overcoming barriers to long-term adherence
Cardiovascular conditions require ongoing management involving medication adherence, lifestyle modifications, and routine follow-ups. However, long-term care plans are frequently affected by a lack of patient engagement and compliance, as well as insufficient provider oversight and transparency. Intelligent prior authorization can address these gaps by aligning health plans and providers throughout the episode of care; care coordination insights enable providers to proactively manage patient adherence and reduce the likelihood of readmissions.
A roadmap to better cardiovascular care
AI-driven prior authorization solutions serve as a springboard for transforming how we treat and manage cardiovascular care. By speeding up patients’ access to care, promoting appropriate testing, and supporting long-term disease management, these tools pave the way for more cost-effective, high-quality care and improved outcomes. For health plans and their provider networks, adopting these solutions means less time spent navigating administrative hurdles and more time to focus on delivering quality care.
American Heart Month serves as an important reminder of how critical both prevention and innovation are in tackling the increasing costs and challenges associated with CVD. Harnessing an intelligent prior authorization platform powered by AI and rooted in clinical evidence can significantly improve care delivery, while reducing providers’ administrative burden. Leveraging technology and data-driven insights within prior authorization processes can unlock new opportunities for innovation in cardiovascular care, enhancing care quality, value, and, ultimately, patient outcomes.
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Susan Bennett
Dr. Susan Bennett, Medical Director of Cardiology at Cohere Health, is a non-invasive consulting cardiologist practicing in both metropolitan and rural areas for over 25 years, specializing in echocardiography and preventive cardiology. She created and established the George Washington University Women’s Heart Program, one of the first in the country. Dr. Bennett trained in Internal Medicine at Barnes Hospital, Washington University of St. Louis, then in Cardiology at Hospital University of Pennsylvania and University of Maryland in Baltimore.
