The future of accountable care: How AI is redefining value-based health care

Jay Ackerman: ©Reveleer

Last year, CMS set an ambitious goal: to have 100% of Traditional Medicare beneficiaries and the vast majority of Medicaid beneficiaries in accountable care relationships, a type of value-based care model, by 2030. Considering more than 66 million people are enrolled in Medicare and 80 million are enrolled in Medicaid, that’s nearly half of the entire U.S. population.

It’s an admirable goal, but the reality is value-based care is difficult to execute for both health plans and providers. Significant roadblocks, including- financial obstacles, lack of organizational readiness, and poor data integration, exist that unintentionally deter health care professionals from delivering value-based care as consistently as they may want to. For example, take medical records, which are complex and contain vast amounts of structured and unstructured data. In the context of value-based care, precise coding of this complicated data, which has historically been time consuming to analyze, is essential for delivering quality patient care, to achieve accurate rating scores like HEDIS, and secure fair reimbursements. The shift from CMS-HCC Model V24 to V28 will require even greater specificity in documentation and code assignment to ensure the accurate level of Medicare Advantage patients’ illness severity is captured.

These types of challenges have long felt insurmountable. But now, AI-powered technology offers a new, incredibly efficient way to overcome these obstacles, and simplifies the complexities of value-based care by turning vast amounts of data into actionable insights and, most importantly, enabling better patient care.

How AI-powered solutions can deliver on the promise of value-based care

AI is revolutionizing health care, particularly in the realm of value-based care. It addresses long-standing issues like fragmented data and inefficient workflows, driving improvements that include:

• Increased Efficiency: AI can significantly streamline operations by automating time-consuming tasks, such as clinical documentation, data entry, and coding, as well as routine tasks like appointment scheduling, claims processing, and regulatory compliance checks.
• Enhanced Accuracy: Human error, particularly in tasks like documentation and data analysis, can lead to misdiagnoses, incorrect treatment plans, or billing issues. AI can quickly sift through vast amounts of patient data to identify patterns, predict potential risks, and flag inconsistencies in clinical records or diagnoses, reducing errors and saving time.
• Actionable Insights: AI can transform raw patient data into actionable insights that guide clinical decision-making. By pulling data from various sources, AI can identify key trends, early signs of deterioration, or opportunities for intervention.
• Scalability: As health systems continue to embrace value-based care, the volume of data they need to process is exploding. AI is purpose-built to manage large amounts of data quickly and efficiently, helping organizations scale up without sacrificing quality or efficiency.
• Continuous Improvement: Thanks to machine learning, AI systems are constantly evolving. As they process more data and receive feedback from clinical outcomes, they become smarter and more accurate, refining their capabilities over time to improve overall performance.

By implementing AI-driven solutions, health care organizations can navigate the complexities of value-based care with confidence, optimizing both clinical and financial outcomes. That said, hesitancy in embracing this technology still exists.

Physicians indicate both optimism and apprehension towards AI

According to arecent Physician Sentiment Survey conducted by The Harris Poll, 60% of physicians are concerned that AI could lead to a loss of human touch in patient care. Additionally, 42% believe AI will just be one more thing that will complicate health care, while 40% believe AI is overhyped and won’t meet expectations.

At the same time, many physicians indicated they are open to embracing AI. The same Physician Sentiment Survey found that 83% of physicians believe that AI has the potential to ease some of the biggest challenges in health care, particularly by cutting down on administrative burdens and boosting efficiency. For many, the "silver lining" in AI advancements is the hope that it will ultimately allow them to spend more time with patients and improve care outcomes.

How AI will improve patient outcomes

AI has the potential to fully achieve the goals of value-based care by enabling proactive, personalized, and predictive patient care. To turn this vision into reality, collaboration among health care providers, technologists, and policymakers will be the key to unlocking AI’s full capabilities. Health care providers, and the industry, should embrace AI-driven solutions to optimize data utilization, improve health predictions, streamline administrative tasks, and foster collaboration across care teams. By exploring the right AI partners and strategies, providers can stay ahead in this evolving landscape and drive better patient outcomes, lower costs, and improve care coordination.

Jay Ackerman is CEO and president of Reveleer.