How Technology Will Drive Value-Based Models For Cardiovascular Care

How Technology Will Drive Value-Based Models For Cardiovascular Care Ami Bhatt, Forbes Councils Member

Ami B. Bhatt, MD, Chief Innovation Officer, American College of Cardiology, Associate Professor, Harvard Medical School. Opinions my own.

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Modern cardiovascular care involves human acumen, complex data and collaborative intelligence between the two. Payment models are based on well-defined tests and procedures and are baffled by the accelerating complexity and technological disruption of the field. Architecting payment models in technology-driven care demands novel financial incentives and performance measures.

Evolving payment reform supports scalable digital health, creates primary care/cardiology fiscal partnerships to improve access and timely treatment and encourages participation in quality and process improvement programs to create modern, fiscally responsible and equitable care.

The Current Cardiovascular Payment Reform Landscape

Current payment reforms include the Hospital Readmissions Reduction Program, which fiscally penalizes excess cardiovascular readmission; the Hospital Value-Based Purchasing Program, a pay-for-performance model for Medicare; and the Bundled Payments for Care Improvement Initiative, providing fixed payments for high-quality care after a cardiovascular event.

The fixed costs associated with these models do not easily support technology-enabled care. There are two new promising evolutions of payment models that address the intersection of technology and clinical care delivery.

First, a comprehensive condition-based value model, measuring an episode of care from treatment to stabilization, has gained traction by accounting for episodic revenue-generating care while promoting value. These models have evolved from episode-based bundled care, which provides fiscal reimbursement for all of the care associated with an episode of illness until a patient is back at their baseline.

This could involve, for example, a heart attack from ER presentation to discharge home with cardiac rehabilitation or a new atrial fibrillation diagnosis from its capture on remote monitoring to medical treatment, cardiac ablation or clinical resolution. The incorporation of digitally-enabled metrics ensures fiscal responsibility by supporting documentation and treatment effect. It can also direct capital infusion to create the greatest clinical impact.

Second, a continuous care value-based model fiscally marries primary care and chronic cardiovascular management. Early identification of cardiovascular disease allows treatment or escalation of care in an equitable, scalable and sustainable way. Remote screening and virtual care can be strategically used to meet access metrics and optimize resource allocation.

By pairing cardiovascular and primary care fiscal models, we can reduce redundancy and optimize access as patients are managed locally and receive timely referrals to subspecialty care for specific pre-agreed-upon diagnoses. Widespread adoption of these models relies on positive incentives for clinical acumen, technology and team-based care.

Team-Based Care And Non-Performance Metrics

Team-based value measurements (i.e., patient-reported outcomes, practice efficiency, appropriate use criteria or clinical goals) incentivize clinicians to rely on one another for care delivery and address all of the components that must align to contribute to clinical outcomes. With the increasing complexity and interplay of medical and social determinants of health, there is no longer only a one-to-one relationship between a clinician's care and the patient's success in achieving medical milestones.

Dismantling the models that fiscally encourage higher cost procedures and differentially pay for procedural time is likely the next key step in payment reform (for example, performing a procedure is currently incentivized over spending time talking with a patient). Non-production metrics (i.e., payments for achievement of target blood pressure, cholesterol, health literacy, days out of the hospital or appropriate use of procedures) trade contradictory incentives for purposeful achievement.

Utilizing Quality Metric Programs To Ease The Transition

Program accreditation allows for quality assurance, accountability and transparency with a clear infrastructure for health equity and optimization of resource utilization. This approach allows hospitals to build system-wide processes to streamline and benchmark care and optimize patient outcomes and financial performance while decreasing unnecessary variations in care. This standardization allows systems to measure the aforementioned non-production metrics and eases the move to value-based payment models.

Cardiovascular data registries create structured opportunities for systems to promote data collection for quality, cost, patient-reported outcomes and drivers of health. This shared infrastructure aligns with the culture shift from fee-for-service to value-based care and highlights the benefits of technology and innovation to support specialty integration for chronic disease management. Data abstraction, using artificial intelligence to auto-fill fields, eases the administrative demand of participating in a quality review or reporting and registry involvement.

Data analytics also allow clinicians to focus on patient care while offering clinical insights at the individual and practice levels, increasing operational efficiency and right-sizing resource utilization. Some of these metrics can be used to create prospective payments for bundled care or document retrospective performance reconciliation to aid the transition to value measurement models.

Value-Based Models With Adequate Infrastructure

Addressing drivers of health is essential for successful payment models. Financial support for local disease screening, social services, community partnerships and digital navigation ensures patients can access quality care. Embedding drivers of health, like social vulnerability indices into payment models, will enable the creation of risk adjustment for social determinants of health similar to medical risk-adjusted models.

For example, successful management of diabetes as a co-morbid condition with heart disease results in increased payments; in the future, being unhoused will carry higher fiscal value when the system achieves improved access to care and medications in these individuals. Equitable adoption of new payment models must recognize the inherent structural inequities in healthcare and be paired with a willingness to iterate when bias is observed.

Summary

Successful value-based models will address four challenges in today's technology-enabled healthcare. Accelerating complexity is addressed by scalable, reimbursable population screening to capture early disease progression and supporting a primary care/cardiology fiscal and clinical infrastructure to optimize access and utilization.

Exponential information overload can be managed with remote patient monitoring with a payment structure that compensates for an overarching continuous care model rather than individual measurements. Rapid technological disruption offers efficient care solutions; however, payment models need to support innovation in clinical practice to allow technology to be iterated upon such that its impact is meaningful.

Drivers of health demand strong financial support and inclusion in value-based payment models to ensure equitable access in a value-based system.

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