Utilization management strategies, including prior authorization, are commonly used to facilitate safe and guideline-adherent provision of new, individualized, and potentially costly cardiovascular therapies. However, as currently deployed, these approaches encumber multiple stakeholders. Patients are discouraged by barriers to appropriate access; clinicians are frustrated by the time, money, and resources required for prior authorizations, the frequent rejections, and the perception of being excluded from the decision-making process; and payers are weary of the intensive effort to design and administer increasingly complex prior authorization systems to balance value and appropriate use of these treatments. These issues highlight an opportunity to collectively reimagine utilization management as a transparent and collaborative system. This would benefit the entire healthcare ecosystem, especially in light of the shift to value-based payment. This article describes the efforts and vision of the multistakeholder Prior Authorization Learning Collaborative of the Value in Healthcare Initiative, a partnership between the American Heart Association and the Robert J. Margolis, MD, Center for Health Policy at Duke University. We outline how healthcare organizations can take greater utilization management responsibility under value-based contracting, especially under different state policies and local contexts. Even with reduced payer-mandated prior authorization in these arrangements, payers and healthcare organizations will have a continued shared need for utilization management. We present options for streamlining these programs, such as gold carding and electronic and automated prior authorization processes. Throughout the article, we weave in examples from cardiovascular care when possible. Although reimagining prior authorization requires collective action by all stakeholders, it may significantly reduce administrative burden for clinicians and payers while improving outcomes for patients.

Stroke is one of the leading causes of morbidity and mortality in the United States. While age-adjusted stroke mortality was falling, it has leveled off in recent years due in part to advances in medical technology, health care options, and population health interventions. In addition to adverse trends in stroke-related morbidity and mortality across the broader population, there are sociodemographic inequities in stroke risk. These challenges can be addressed by focusing on predicting and preventing modifiable upstream risk factors associated with stroke, but there is a need to develop a practical framework that health care organizations can use to accomplish this task across diverse settings. Accordingly, this article describes the efforts and vision of the multi-stakeholder Predict & Prevent Learning Collaborative of the Value in Healthcare Initiative, a collaboration of the American Heart Association and the Robert J. Margolis, MD, Center for Health Policy at Duke University. This article presents a framework of a potential upstream stroke prevention program with evidence-based implementation strategies for predicting, preventing, and managing stroke risk factors. It is meant to complement existing primary stroke prevention guidelines by identifying frontier strategies that can address gaps in knowledge or implementation. After considering a variety of upstream medical or behavioral risk factors, the group identified 2 risk factors with substantial direct links to stroke for focusing the framework: hypertension and atrial fibrillation. This article also highlights barriers to implementing program components into clinical practice and presents implementation strategies to overcome those barriers. A particular focus was identifying those strategies that could be implemented across many settings, especially lower-resource practices and community-based enterprises representing broad social, economic, and geographic diversity. The practical framework is designed to provide clinicians and health systems with effective upstream stroke prevention strategies that encourage scalability while allowing customization for their local context.

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