As the capstone to our 10-part series on health technology trends in 2025, this article examines the evolving landscape of health data interoperability and integration. Seamless data exchange is foundational for innovation in medical devices, biopharma, digital health, and diagnostics. Yet, as adoption accelerates, persistent barriers impact the delivery of comprehensive, patient-centered care. In this final installment, we examine the latest trends, challenges, and opportunities that are shaping the future of healthcare data exchange—a topic of critical importance to executives across the health technology sector.
The State of Interoperability: 2025 Snapshot
Industry adoption of health data standards is reaching an inflection point in 2025, driven by regulatory imperatives, rapid technological advancements, and surging demand for connected care solutions. Globally, the use of FHIR (Fast Healthcare Interoperability Resources) APIs or FHIR-compliant platforms continues to grow, reflecting a shift toward the real-time, secure exchange of both clinical and administrative data. This surge is fueled by mandates such as the 21st Century Cures Act, pushing vendors and providers toward open, patient-accessible data while over 90% of EHR vendors now support FHIR as their interoperability baseline.1,2
The Trump administration’s Making Health Tech Great Again initiative furthered industry consolidation around new US CMS interoperability guidelines. CMS’s Interoperability Framework, now a core reference point for cross-entity data standards and access policies, has aligned over 60 market leaders on voluntary APIs and data-sharing protocols to unlock innovation in patient-centric care.3
Current Trends in Data Exchange and Integration
- Widespread FHIR Adoption: Health systems worldwide are increasing the implementation of FHIR-enabled APIs. Real-time exchange capabilities enable patient data to flow securely between different providers and patient-facing apps, reducing manual work and errors.1, 2
- Multi-Stakeholder Partnerships: Large EHR vendors, AI leaders, diagnostics platforms, and public-sector agencies are now engaged in public-private alliances defining technical and policy standards for secure, actionable data sharing (e.g., TEFCA, CMS Frameworks).3,4
- Expanded Use Cases: Use extends across administrative optimization (e.g., automated prior authorizations), digital patient engagement, telehealth data integration, population health analytics, and deployment of AI decision-support, all powered by interoperable, standardized data flows.2,4,5
Persistent Challenges in Health Data Interoperability
Despite measurable progress, persistent hurdles remain:
- Legacy System Fragmentation & Silos: Many provider groups, especially those using closed or older EHR solutions, face vendor lock-in and isolated data silos. Complexities multiply when integrating data across disparate, proprietary systems or merging structured and unstructured data.2
- Semantic Consistency and Data Quality: Even where FHIR, HL7, or SNOMED CT are implemented, real-world deployments often lack true semantic interoperability—meaning codes, units, and terms may differ between organizations, complicating data aggregation, analytics, and AI deployment.6,7
- Usability and Workflow Problems: AMA research highlights clinician frustration with information inaccessibility, inadequate interoperability between care settings, alert fatigue, and visual display issues in EHRs—causing inefficiencies and potentially impacting patient safety.8
- Security & Regulatory Risk: The move to open APIs and cross-network sharing introduces new exposures to privacy breaches and regulatory challenges. Complying with HIPAA, GDPR, and fast-changing local and global regulations is a high-stakes, ongoing endeavor.3,4
- Organizational Gaps: Skilled HIT workforce shortages, change management barriers, and IT resource limitations slow the adoption and operationalization of modern interoperability standards.4,8
- Patient-Level Complexity: Empowering patients to manage and share their health records at scale brings challenges around consent, authentication, and data literacy, particularly as mobile health, consumer apps, and third-party analytics proliferate.3,4,5
Regulatory and Policy Landscape
Major national and international initiatives define the contours of data integration:
- CMS Interoperability and TEFCA: The US Centers for Medicare & Medicaid Services has established mandatory interoperability rules and the Trusted Exchange Framework and Common Agreement (TEFCA). These establish baseline technical and legal guardrails for secure and scalable data sharing.3
- Global Policy Leadership: Major economies in the EU, Asia, and the UK are adopting and enforcing FHIR-based standards, with international coordination increasingly vital for global biopharma and cross-border clinical studies.1,2
- Addressing Information Blocking: Enforcement actions and reporting mechanisms are evolving to eliminate practices that unduly restrict data exchange, aiming to ensure patients and authorized clinicians have timely access to the full patient record.3
Opportunities for Life Sciences Executives
- AI and Advanced Analytics: Reliable, machine-readable data is the foundation for deploying AI at scale in clinical trial optimization, diagnostics, and precision medicine—all high-value opportunities for life sciences innovation.4,7
- Patient-Centric Models: Seamless integration across medical devices, digital therapies, and diagnostics enables true longitudinal care records and drives adoption of precision medicine and proactive patient management.5,9
- Operational Efficiency: Robust interoperability reduces duplication, accelerates regulatory reporting, and improves data-driven decision-making—delivering clear cost advantages.4,8
- Collaborative Ecosystem Development: Leading organizations are forging cross-industry alliances to drive standards harmonization, de-risk technical investments, and scale best practices company-wide, supporting innovation and market growth.3,5
Outlook: Building Trust and Value
Sustained leadership attention is required in three areas:
- Data Governance: Strict policies and oversight are essential as new data sources and AI models enter the healthcare ecosystem. Quality, accuracy, provenance, and transparency must be prioritized throughout the data 4,6,7
- Workforce Development: Regular, targeted training on evolving digital standards and data ethics enables teams to stay ahead of technical and compliance challenges.4,8
- Enhanced Safeguards: Expanding encryption, secure authentication, and robust privacy management are critical as cross-boundary data pipelines become the norm.3,4,9
Conclusion
For life sciences executives, real opportunities await those who can advance beyond today’s data silos, quality obstacles, and security risks. Interoperability is quickly becoming a baseline expectation, not just a competitive differentiator. Winning organizations will treat interoperability as a strategic, ongoing capability, built on informed, collaborative, and ethical leadership.
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Sources:
- FHIR Adoption Statistics in 2025: A Global Overview
- Twenty-Five Years of Evolution and Hurdles in Electronic Health Records and Interoperability
- Charting the Way Forward: New Efforts to Advance Electronic Health Information Sharing
- Emerging Healthcare Regulatory Trends in 2025 and Beyond
- EHR Interoperability Solutions in 2025: What Actually Works?
- Semantics-driven improvements in electronic health records data: A systematic review
- Standards in sync: five principles to achieve semantic interoperability for TRUE research for healthcare
- When Health Data Plays Nice Together (Finally!)
- Clinical data integration and processing challenges in healthcare caused by contemporary software design
About the Author
Paula Norbom is the Founder and CEO of Talencio, an executive search and staffing firm serving health technology companies. She has worked in the health technology industry for over 30 years.