Overcoming Challenges in Value-Based Care and Population Health Management

Learn about the benefits, challenges, and measurement of effective value-based care programs, emphasizing the role of artificial intelligence in driving improved patient outcomes and cost reduction in this interview with John Fryer, CRO at Lumeris. 

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Please share your full title and a brief overview of your professional history. 

I’m John Fryer, chief revenue officer for Lumeris. We partner with health care providers to enable value-based care success for all populations via risk-sharing and total-cost-of-care models.  We work daily to empower physicians, care team members, and health systems to fulfill the promise of value-based care by developing and executing strategy and operationalizing clinical programs to improve population health and reduce care costs by leveraging our proprietary technology and deep expertise.  
Before joining Lumeris nearly 7 years ago, I was a management consultant working for health systems nationwide. As private capital investment picked up in health care and various value-based care models became more broadly adopted—including Medicare Advantage—I joined Lumeris to help accelerate and expand the adoption of these progressive community and population-based models across the health care provider community. 

At Lumeris, we seek to partner with health care organizations to accelerate value-based care adoption across their entire enterprise. In doing so, we’ve aligned with our partners not just operationally but also financially. We develop long-term relationships with providers through a financially aligned model that ensures all parties have skin in the game. Today, our value-based care relationships with health systems and provider organizations impact nearly 2 million people across more than 12 markets.

Please share your definition of value-based care and why the adoption of value-based care continues to increase across the country. 

We define value-based care as creating a system of care every doctor would want for their own family. We believe value-based care transformation best occurs when health care providers and organizations adopt evidence-based models for driving clinical care improvement to lower total cost of care while delivering superior clinical outcomes across all populations and communities our partners serve. We accomplish this through co-creating a system of care with our health system and provider partners that are enabled by AI-powered technology, people, and processes to drive meaningful action from the data insights we can surface at the point of care.

Value-based care success for health care organizations will ultimately come down to their ability to drive improvements in the health of populations while reducing the overall growth of health expenditures. Not only are health care costs rising—with the Medicare program facing potential insolvency soon—but we’ve also seen the health of vulnerable populations decline. People struggle to gain access to needed care, medications, and support which is the first defense against complex disease. Ultimately this raises health care costs by prompting people to delay care or seek care in the most expensive care settings, such as emergency departments (EDs). With chronic disease now the leading cost of death and disability and the leading driver of rising health care expenditures (6 in 10 of all adults and 95% of adults over 60 are currently managing at least one chronic disease), our nation needs a model that seeks to manage health and wellbeing at the whole-person level versus approaching care episodically. 

Scenarios like these have created a sense of urgency around the need to adopt value-based care models among health care providers, payers, and employers for the betterment of those populations these stakeholders exist to serve. Health care organizations must not only accelerate the move toward these models but also accelerate their ability to measure and deliver impact if they are to succeed in today’s health care landscape. Maintaining the broken status quo risks being left behind as competitors new and old drive change via value-based care, and as employers and health plans demand better outcomes at lower costs for their members.

What are the primary benefits and challenges of adopting value-based care? 

The benefits of a value-based approach to care run deep, ranging from better access to care to more effective management of complex and life-changing conditions, reduced hospital admissions and ED visits, and better coordination of care, including post-acute care. Each of these benefits contributes to improved health and well-being, strengthening communities while decreasing the cost of obtaining vital care services.

The challenges of adopting value-based care are often tied to understanding the populations that a provider organization serves at a local level. This requires access to diverse data, including social determinants of health (SDOH), patient-reported information, and the conditions where people work, live, play, and age. These factors have a massive impact on an individual’s health, and the Centers for Medicare & Medicaid Services (CMS) now requires that health care providers begin to track these measures to strengthen the health of our communities. But for providers, one of the biggest challenges surrounding SDOH data lies in the application of this data: “Now that we have access to this data, what do we do with it?” 

Since much of this data is unstructured, it isn’t readily viewable within a patient’s electronic medical record. It also requires analysis to determine where health challenges or disparities in care and health outcomes exist and how to address them. Getting to the point where providers can leverage this data for better health requires huge analytic capabilities, now increasingly organized and actioned by AI, and the resources to apply this information to engage those whose health is most at risk.

How do you measure and evaluate the effectiveness of value-based care programs?

Effective value-based care programs impact the aggregate system at the patient level by driving improvements in experience, quality of care, and cost. We believe central to value-based care is the delivery of accountable primary care. Accountable primary care is a team effort, incorporating the physicians, their care teams, and wrap-around services and technology to streamline and enhance the patient’s ability to participate in their health journey. Increasing annual wellness visits, preventative screenings, and other activities to drive improved health outcomes are critical to the success of any value-based care program. All our provider organizations have a balanced set of measures within their contracts that incorporate experience, quality, and cost. The patient-first clinical model drives the programs and aligns the incentives we're putting in place which is key to our success. We measure our impact based on clearly defined outcome metrics including changes in overall health status (population level measures), consumer satisfaction (eg, CAPHS), utilization of key services, and measures that are leading indicators to how care is being accessed (eg, reduction of inpatient and ED visits). Ultimately, effective value-based care programs benefit all stakeholders while lowering the aggregate cost of care. 

How is artificial intelligence relevant to the growth of effective value-based care? What are the challenges of using AI in managing population health data? 

Artificial Intelligence (AI) is increasingly becoming a pivotal tool in the health care sector, particularly in advancing the paradigm of value-based care. AI plays a crucial role in the value-based care transformation by enhancing patient outcomes, optimizing health care delivery, and reducing costs. 

Near Term Uses of AI in Value-Based Care:

• Predictive Analytics: AI can analyze vast amounts of data to predict health trends within populations. This can identify patients at high risk of developing chronic conditions or those who may benefit from preventative care, allowing for interventions that can prevent hospital readmissions and reduce costly treatments. 
• Personalized Care Plans: By analyzing patient data, AI can help in crafting personalized care plans that consider the unique health needs and conditions of each patient. This individualized approach is at the heart of value-based care, aiming to provide the right treatment for the right patient at the right time. 
• Efficiency and Cost Reduction: AI can streamline operational processes, reduce redundancies, and automate administrative tasks, allowing health care providers to focus more on patient care. This operational efficiency can lead to significant cost savings, aligning with the cost-effectiveness goals of value-based care. 
• Enhanced Decision Making: AI tools can support clinicians in making better-informed decisions by providing them with comprehensive, data-driven insights. This can improve diagnosis accuracy, treatment effectiveness, and patient outcomes. 
• Patient Engagement and Monitoring: Through wearable devices and mobile health apps integrated with AI, health care providers can monitor patients' health in real-time. This continuous monitoring supports proactive management of chronic conditions and engages patients in their health, leading to better outcomes.

Challenges of Using AI in Managing Population Health Data:

• Data Privacy and Security: The use of AI in health care involves handling sensitive patient data. Ensuring the privacy and security of this data is paramount. 
• Data Quality and Integration: AI systems require high-quality, comprehensive data to generate accurate predictions and insights. However, health care data is often siloed, incomplete, or inconsistent, posing challenges to effective AI implementation. 
• Bias and Equity: AI models can perpetuate or even exacerbate biases if they're trained on non-representative datasets. This can lead to disparities in care and outcomes, undermining the equity goals of value-based care.
• Professional Skepticism and Adoption: Health care professionals may be skeptical of AI tools, questioning their reliability and fearing the potential for job displacement. Overcoming these barriers requires significant efforts in education, training, and demonstrating the value of AI in enhancing clinical practice.

How can health care disparities for underserved communities be addressed through accountable care organization (ACO) models? 

ACO models hold strong potential to deliver superior care, improve patient experiences and drive down avoidable costs for underserved communities. The implications of SDOH on health equity are significant since underserved communities have long experienced wide gaps in household income and household wealth. There is so much to address in the SDOH space—access to quality education, employment, housing, transportation, and nutrition all can influence the well-being of a community more than the delivery of health care services in and of itself.  However, sustained success demands that administrators know which individuals are most in need of help so they may direct attention and resources to these groups in ways that make a significant impact. This allows providers to prioritize proactive outreach to these patients so primary care and SDOH interventions can be delivered as early as possible. It’s an approach that reduces disparities in care and care access and builds relationships that improve health, reduce costs of care, and increase trust among those in underserved communities.

For example, when you take on risk for a large Medicare population, a percentage of patients will not have access to a qualified primary care physician. Such a relationship is critical for ensuring high-risk and underserved populations receive care coordination services that enable them to access the health care system when and where they need it.

How can health care providers and organizations effectively transition from fee-for-service to value-based care models?

Value-based care models stand as the unequivocal blueprint for steering our trajectory towards a future marked by enhanced population health and viable financial frameworks for health systems and the broader American health care sector. The next 5 years in health care promise a surge in both scale and efficacy, propelled by intensified economic, regulatory, and societal forces that underscore the urgent need to pivot from a structurally deficient fee-for-service model. The paradigm shift from fee-for-service is pivotal for delivering high-quality care across all populations, aligning the industry with the evolving needs of our communities. Successfully navigating the transition from transactional fee-for-service revenue to prospective payment and risk-based models of care necessitates a profound cultural shift within organizations. Business transformation will need to unfold against this backdrop of shifting paradigms and evolving health care delivery models, underscoring the urgency for change while acknowledging the formidable challenges inherent in navigating this monumental shift. It mandates a departure from traditional approaches, fostering collaboration, innovation, and a patient-centric mindset throughout every facet of health care delivery.

Enabling partnerships plays a pivotal role in accelerating this transformation journey. Health systems and physician practices need to form collaborative (and often risk-sharing) relationships with partnering influencers who can provide invaluable insights, resources, support, and infrastructure as they navigate uncharted waters. These partnerships can offer access to best practices, advanced technologies, and strategic guidance, empowering organizations to overcome obstacles and drive meaningful change more effectively. Harnessing the cutting-edge potential of AI models and advanced analytics capabilities will be paramount in driving transformative changes to enhance population health outcomes to ensure long-term sustainability in a rapidly evolving health care landscape.

How do you ensure that value-based care models are sustainable and financially viable for health care organizations and providers? 

While the risk-sharing component of value-based care models can be flexible, to create models that are sustainable and financially viable for health care organizations and providers as well as their partners, there must be skin in the game. That means all parties must work together to define where the provider or health care organization is in its value journey and develop a value approach that best suits the organization’s capabilities and the needs of the populations it serves. From there, all parties must be committed to developing a long-term relationship for value transformation, with built-in execution, financial, and operational risks that drive alignment.

There’s no cookie-cutter approach to value-based care model development or implementation—or to risk sharing, for that matter. There are sophisticated organizations that have been managing value-based populations for the past decade, and there are organizations that are very nascent in their efforts. The problems each of these organizations are trying to solve can look very different. It’s important to customize the model according to the organization’s capabilities and resources, and the objectives it is trying to achieve.

Is there anything else you would like to share? 

I’m excited by the advancements we’re seeing, both in the application of AI to advance population health management and the gains organizations are making in the move toward—and impact of—value-based care transformation. AI is going to increasingly unlock data insights deployed in a comprehensive model and supported by comprehensive information that can assist providers and health plans to make the right connections for whole-person care. It empowers clinicians and community health workers to strengthen primary care engagement and specialty care referrals. It also gives community health workers the capacity to make connections to community service agencies or physicians that could meet patients’ whole health needs. 

By leaning into advanced analytics and technology to drive value-based care improvement—and by ensuring all parties have financial skin in the game—we can make a significant and sustainable difference in improving health for all.