The AI Revolution Series – How AI and Value-Based Payments Can Increase Quality of Care

The transition to an AI-enhanced healthcare system will not happen overnight and it will require a significant investment in technological infrastructure. The development and integration of AI capabilities requires advanced hardware, software, and data management and security systems. This is in addition to the expertise to operate and maintain them, as well as the training to ensure everyone is up to speed. The technological leap requires considerable investment, which can pose a substantial challenge, particularly for smaller providers.

For providers, securing funding to build the necessary technology infrastructure to implement AI is essential. Without the financial support to adopt AI technologies, smaller providers risk falling behind, which can widen the gap in quality of care between large and small-scale operations. This disparity could have big consequences for consumer care, especially in underserved or rural areas where smaller providers are sometimes the only option.

This is where VBP comes into the picture because these models offer a strategic avenue to fund investments in technological infrastructure, including AI systems. A goal of value-based payments has always been innovation in healthcare and the same holds true when it comes to AI. Investment in AI technology can be directly justified under value-based payments models because it can enhance patient outcomes and reduce costs, which meet the core objectives of value-based care. When health outcomes are tied to reimbursement, health plans have an incentive to invest in AI systems for their providers. In theory it’s a win for everyone because providers get the technology they need, consumers see better health outcomes, and health plans increase their chance of obtaining maximum reimbursement under VBP models.

Through AI, providers can predict patient complications early, personalize treatments, and manage chronic diseases more effectively. In doing so, they can improve patient outcomes, which are financially rewarded in VBP models, and reduce costs. The alignment between the investment in technology and payment structure creates a financial incentive for plans and providers to upgrade their technological capabilities, as the initial costs can be offset by the improved outcomes and associated reimbursements. 

These investments are not only financially sound but are also crucial for maintaining competitive advantage in a rapidly evolving healthcare landscape. We know that AI is essential for the healthcare industry, because even policymakers and government organizations are getting behind it. In fact, HHS just announced new funding opportunities for AI, highlighting the importance of making the integration of AI happen. 

Through predictive analytics, personalized care plans, and automated administrative tasks, AI technologies can help providers meet the requirements of these models to obtain maximum reimbursements. As we’ve covered in past blogs, AI technology can reduce hospital readmissions, help providers manage chronic conditions effectively, and enhance consumer engagement. With AI’s data-driven insights, providers have more informed decision-making, leading to better health outcomes and, ultimately, higher reimbursements under VBP arrangements. It also allows plans and providers to reduce unnecessary services, which lower their costs and boost their bottom line. In theory, AI is a win for plans, providers, and consumers!

However, integrating AI into home health care services presents financial and logistical challenges. Building out the necessary AI infrastructure requires significant investment in technology, training, and data management capabilities. While the long-term benefits of this investment can be substantial, the upfront costs can be a barrier for many providers. The good news is that VBP can also help with that.