The transformative potential of generative AI in healthcare is undeniable—from reducing administrative costs to enabling proactive patient care. Yet, as adoption accelerates, organizations must navigate critical challenges like data security, accuracy, and transparency. In this piece, David Morris explores how healthcare leaders can responsibly implement AI to enhance clinical and financial outcomes, improve interoperability, and meet evolving industry demands, all while maintaining trust and delivering value across the healthcare ecosystem.
Generative AI in Healthcare: Generative AI (gen AI) is poised to transform healthcare by reducing administrative costs, improving financial stability, and enabling earlier, proactive care interventions. The promise is clear, but thoughtful implementation is essential.
Right now, many organizations are investigating how to leverage AI. According to a recent McKinsey & Company survey, 89% of payers, providers, and technology vendors are planning to use or already using gen AI, often with third-party vendors. However, this surge comes with notable concerns: 60% of respondents cite risks—such as data security, privacy, and AI output accuracy—as their top challenge.
“The delivery of healthcare is complex and is demanding an increasing amount of information to drive meaningful insights on individual and population health” said Greg Mansur, CEO of EHE Health, a national healthcare provider specializing in preventive health and primary care services. “Many of our partners have serious and valid concerns about the hasty implementation of AI technology. As a result, we’re being cautious, employing a responsible approach to our AI roadmap that addresses the security and privacy concerns of our partners while we continue to drive population health insights through the blending of disparate data.”
AI technology in healthcare cannot be rushed. With potential impacts on health outcomes, responsible study and implementation are key. To mitigate these challenges, healthcare delivery organizations need to take a responsible approach to the development and implementation of gen AI technology. This includes:
- Balancing AI advancements with transparency, patient safety, and trust.
- Eliminating model bias with large datasets that boost accuracy.
- Refining models over time to ensure the accuracy and efficacy of AI outputs.
- Building trust with providers by making the source data of AI outputs accessible and interpretable.
Real-Time Data, Real Impact: Near-instant data access is revolutionizing AI-driven insight and decision-making, empowering providers to streamline operations and cut costs.
Clinician productivity is among the areas believed to benefit most from gen AI. But for providers to efficiently achieve better clinical and financial performance, timely data is a prerequisite. The ability to blend multiple data sources—claims, clinical data, and more—can lead to a more accurate understanding of utilization patterns and preventive quality measures.
“Being able to blend data from multiple fronts, including claims and clinical data, is a vital competency for providers seeking to lay a foundation for future real-time gen AI capabilities,” said Greg Mansur, CEO of EHE Health. “With help from our technology partner, Cedar Gate Technologies, we are able to access and use these different data sources—including blended clinical and claims data—to help us more accurately understand utilization patterns and the impact of preventive quality measures, allowing us to demonstrate greater participation in our prevention program which then helps steer patients to available and relevant employer point solutions to address specific clinical needs.”
System interoperability remains the main barrier, as reliably accessing data is critical for producing actionable gen AI insights. Providers must ensure real-time access to admissions, discharges, and transfers, as well as EHR and HIE data.
As interoperability improves and providers adopt advanced data-sharing standards, gen AI’s real-time insights will elevate clinical and financial outcomes to new heights. Faster data exchange will empower providers to pivot more quickly, respond to population health trends proactively, and realize greater cost savings.
Employers Taking Charge in VBC: With the growth of direct-to-employer contracts and new AI-powered health improvement solutions, employers require more precise ways to track the ROI of their benefits and care management programs and continue driving care quality and affordability.
“EHE Health finds immense value in being able to measure the impact of prevention programs for specific cohorts. With Cedar Gate, we can compare performance between users and non-users of our program as well as how our program increases adoption of other employer point solutions. We also can incorporate commercial benchmarks, which many employer customers find valuable for understanding how their overall experience compares to companies in major industry categories,” said Greg Mansur, CEO of EHE Health.
Employers are seeking more detailed visibility into the performance and ROI of their health improvement programs. This includes the effectiveness of care management programs, as well as the value of targeted “point solutions” that focus on a specific condition, like diabetes.
CMS Mandates and Bundled Payment Models: With CMS accelerating bundled payments, 2025 is the time for hospitals and healthcare delivery organizations to prepare for an entirely new way of being reimbursed.
“EHE Health is not a TEAM participant, but we see significant opportunity with bundled payments in our lines of business,” said Greg Mansur, CEO of EHE Health. “This is why we’ve partnered with a technology company with deep experience in value-based care and payment models. It’s a strategic move that gives us the flexibility to quickly add capabilities, effectively being able to compose our own technology solutions that support where we are today and where we’ll be in the future.”
Many hospitals selected for participation in the new CMS TEAM program do not have bundled payment experience. For some, a service-enabled approach will be the best path forward. Others might seek technology to manage bundles themselves. For both approaches, expertise, and purpose-built technology are vital for precision and accuracy. Common barriers to participating in bundled payments include:
- Data limitations – the ability to bring together disparate data from multiple sources is a challenge for many hospitals.
- Unpredictable costs and outcomes – unable to confidently forecast the potential impact of financial and clinical performance.
- Trust and transparency – providers must be willing to share information and best practices.
- Risk aversion – TEAM is a mandate, so there is no choice.
- Administrative complexity – bundles administration and payment require time, purpose-built technology, and human resources.
Keys for bundles success include:
- A partner with a track record of bundled payment success.
- Software designed for bundled payment, including analytics, reporting, and bundles administration.
- A plan to educate provider partners.
David L. Morris
David Morris is Executive Vice President & Chief Commercial Officer at Cedar Gate Technologies. He has over 30 years of operational and executive leadership experience at blue chip companies throughout the healthcare ecosystem, driving client success in value-based care by addressing technology and service needs for payers, providers, and self-funded employers.
