AI on FHIR

AI-Driven Interoperability: Transforming Value-Based Care with Microsoft

It has been 2,052 days since I last posted here. This pause has given me time to think. I will be sharing a series of posts about some of the things that I have been considering. Of course, my passion is still healthcare, technology, and open government and my posts will highlight advances in emerging technology reaching for solutions to our most pressing problems. 

The healthcare industry is undergoing a transformative shift, driven by the rapid advancement of artificial intelligence (AI). Over the past several years, AI has ignited the healthcare ecosystem's imagination, offering real-world solutions that impact clinicians, patients, and health systems alike. From enhancing diagnostic accuracy to streamlining clinical workflows, AI's potential to reshape healthcare is increasingly apparent. Real-world examples like the collaboration between Nuance and Microsoft, which utilizes AI-driven speech recognition technology to automate clinical documentation, or Mayo Clinic's use of AI to detect atrial fibrillation from electrocardiogram (ECG) data, underscore AI's ability to deliver immediate, tangible improvements in healthcare outcomes.

At the core of this transformation is the HL7® Fast Healthcare Interoperability Resources (FHIR®) standard, which plays a critical role in enabling seamless data exchange across healthcare systems. FHIR provides a standardized framework for sharing healthcare information electronically, addressing one of the most significant challenges in healthcare: interoperability. Interoperability, or the ability to exchange and use information across different healthcare systems, is essential for improving patient outcomes, reducing inefficiencies, and enabling innovations like AI.

To underscore the importance of AI-driven solutions in healthcare, our work at AI MINDSystems is making strides through the National HERO Initiative. This initiative focuses on leveraging AI to support military members, veterans, first responders, and their families by improving access to healthcare services and enhancing care coordination. By integrating AI with interoperable data systems, such as those enabled by the FHIR standard, the HERO Initiative aims to optimize clinical outcomes and reduce the administrative burden on healthcare providers serving this critical population. Through efforts like these, AI MINDSystems is committed to creating AI solutions that not only improve healthcare delivery but also ensure that the benefits of AI reach those who need them most. 

When combined with AI, the FHIR standard takes interoperability to the next level. FHIR's standardized data formats allow AI algorithms to easily access and analyze patient data, whether from electronic health records (EHRs), wearable devices, or imaging systems. This enables healthcare providers to make better-informed decisions based on real-time data. For instance, AI models built on FHIR can provide predictive analytics for population health management, identify early warning signs of diseases, and even automate administrative tasks such as prior authorization, all while ensuring data is exchanged securely and efficiently.

In this context, Microsoft is helping to lead the charge in harnessing AI-driven interoperability through tools like the FHIRlink Power Platform connector. By simplifying the integration of healthcare data across systems, FHIRlink empowers organizations to build low-code applications that automate workflows, streamline operations, and enable smarter, faster decision-making. The EHR giant Epic has supported these tools to help ignite interoperability of health data. These advancements not only improve the efficiency of healthcare delivery but also lay the groundwork for the broader adoption of value-based care, where outcomes, rather than services, drive the financial model of healthcare.

The United States federal government has been helping to push interoperability into this new frontier with policies that promote the development and use of FHIR. The Assistant Secretary for Technology Policy (ASTP) at HHS has released the Draft Federal FHIR® Action Plan to help guide investment in and adoption of the FHIR® standard. This effort is part of the broader goal of advancing healthcare interoperability to improve the accessibility, quality, and efficiency of care across the nation. As the federal government invests in advancing healthcare technology, ASTP's role in promoting FHIR adoption ensures that federal health agencies can leverage modern data standards to improve care delivery and interoperability across the healthcare ecosystem. 

The shift from a fee-for-service model to value-based care has become a central focus in healthcare transformation, driven by the need to improve patient outcomes while controlling costs. In value-based care, healthcare providers are reimbursed based on the quality of care they deliver rather than the quantity of services rendered. This transition necessitates data-driven insights that can predict outcomes, streamline care delivery, and provide personalized treatment plans, and this is where AI comes in. 

AI can analyze large, diverse datasets in real-time to identify patterns and trends that inform clinical decision-making. For example, predictive analytics models powered by AI can help healthcare organizations identify at-risk populations, track disease progression, and implement preventative measures tailored to individual patients. AI-driven tools are also critical in optimizing care coordination, ensuring that treatments are both efficient and effective. Microsoft’s AI-driven platforms, such as the FHIRlink Power Platform connector, enable the seamless integration of clinical data across disparate systems, helping healthcare providers maintain an accurate, up-to-date understanding of a patient’s health across their care continuum. 

AI also supports the operational aspects of value-based care by automating administrative tasks such as claims processing, patient scheduling, and regulatory compliance checks. These efficiencies reduce costs and free up healthcare providers to focus on patient care. By leveraging AI, healthcare organizations can deliver care that not only meets the clinical needs of individual patients but also aligns with the broader goals of improving population health and managing healthcare resources more effectively. This seamless integration of AI and data interoperability is essential for realizing the full potential of value-based care. 

It is critical that AI use in healthcare is trustworthy and responsible. A very helpful document is the AI Outcomes Framework (you will need to provide your email to download). Ensuring that AI systems are reliable, ethical, and transparent is critical to building clinician and patient trust, particularly when these systems are involved in clinical decision-making or data handling. The Trustworthy and Responsible AI Network (TRAIN) announced at HIMSS this year, emphasizes the importance of creating AI models that are safe, secure, and free from bias. In healthcare, where patient safety and data privacy are paramount, these principles are not just technical requirements but ethical imperatives. AI systems must be transparent in their decision-making processes, explainable to clinicians, and compliant with regulatory frameworks such as HIPAA and GDPR. By embedding trust into the very architecture of AI tools, Microsoft ensures that healthcare providers can rely on these technologies to improve patient outcomes while safeguarding the integrity and confidentiality of sensitive health data. 

As healthcare organizations prioritize privacy and security in AI implementations, they are simultaneously tasked with harnessing the full potential of health data to drive better clinical outcomes. Ensuring data privacy is foundational, but it is equally important to enable the integration of data from diverse sources—such as electronic health records (EHRs), wearable devices, and social determinants of health—to improve population health management. We must be about, as Amy D. Berk, MSN, RN, Director, Population Health, Microsoft says, “bridging data for optimal clinical outcomes, and the broader framework of optimizing care delivery and clinical transformation.” Bridging these data silos allows healthcare providers to gain a more comprehensive view of patient populations, identify at-risk groups, and implement tailored interventions before conditions worsen. Care delivery’s shift is demanding interoperability. 

There is no doubt that generative AI will continue to have a profound impact on healthcare. There are warning flags around responsible and ethical use, but also operational concerns. Last year the Gartner Hype Cycle for Emerging Technologies positioned generative AI on the Peak of Inflated Expectations, meaning the technology has garnered significant attention and investment, but many organizations are still grappling with the practical challenges of implementation.

The transition from inflated expectations skimming through disillusionment to tangible value requires focused efforts on areas like trustworthy AI, interoperability (through standards like FHIR), and ensuring that AI-driven solutions deliver on the promise of improving outcomes, reducing costs, and enhancing care. As the healthcare industry moves forward, organizations that can navigate this challenging phase by focusing on responsible, ethical, and secure AI implementations will ultimately succeed in realizing the true potential of AI. 

The transformative potential of AI in healthcare is clear, but the path to fully realizing its value is complex. AI’s ability to streamline clinical workflows, enhance diagnostic accuracy, and support population health initiatives places it at the forefront of healthcare innovation. However, the successful integration of AI hinges on the principles of trustworthy and responsible implementation. By leveraging standards like FHIR to ensure data interoperability and embedding ethical safeguards into AI systems, healthcare organizations can overcome the initial challenges of AI adoption. 

But it is essential that organizations maintain a commitment to transparency, security, and the ethical use of data. Microsoft’s initiatives, including the FHIRlink Power Platform connector and the Trustworthy and Responsible AI Network (TRAIN), provide a robust foundation for navigating this evolving landscape. By focusing on AI-driven interoperability, value-based care, and population health, healthcare providers can embrace AI not just as a tool for operational efficiency, but as a transformative force for improving patient outcomes and advancing care delivery. In this critical phase, those who prioritize responsible AI implementation will be positioned to lead the way, delivering on the promise of AI to transform healthcare for the better.