A new survey highlights that healthcare organizations are still struggling to fully realize the benefits of interoperability, even as they invest heavily in connecting systems. Despite 76% of leaders citing interoperability as a top strategic goal, many face ongoing hurdles that slow progress and impede AI readiness. Fragmented systems, staffing shortages, and reliance on vendors remain key obstacles that limit the ability to scale and operate efficiently.

Interoperability Still a Work in Progress

The survey, which included responses from over 200 hospital executives and IT decision-makers, shows that many organizations are caught in a cycle of troubleshooting and patching their systems. Nearly one in four spend more than 20 hours each week resolving integration issues, demonstrating how resource constraints and complex legacy systems continue to hinder seamless data exchange. While organizations recognize the importance of interoperability, translating that recognition into effective action remains a challenge.

Staffing shortages and vendor dependency are identified as the main barriers. These issues slow down efforts to achieve a mature interoperability infrastructure. Despite these challenges, there’s a clear momentum toward improving connectivity, with 61% planning to link more external systems in the coming year. Additionally, 44% are focusing on APIs and interfaces to support standards like FHIR and HL7v2, as well as migrating to cloud-based systems. This signals a shift toward more scalable and flexible infrastructure models.

Moving Toward AI-Ready Healthcare Systems

Experts emphasize that interoperability is now a leadership imperative rather than just an IT project. The ability to adopt AI solutions depends heavily on trusted, high-quality data and a robust infrastructure. Sagnik Bhattacharya, CEO of Rhapsody, notes that organizations that remove friction and invest in reliable connectivity are better positioned to scale AI initiatives safely across clinical and operational workflows.

To help organizations assess their current maturity, Rhapsody introduces the ‘Digital Infrastructure Maturity Model,’ a four-stage framework. This model aims to guide healthcare providers in understanding where they stand in their interoperability journey and what steps are needed to reach AI readiness. Asnaani highlights that achieving AI-readiness is about more than technology — it requires leadership alignment, trusted data, and scalable systems. The goal is to transform interoperability from a technical milestone into a comprehensive maturity goal.

The report underscores that true progress involves not just investing money but removing barriers that slow down data sharing. Organizations that streamline their systems and eliminate friction will be better equipped to harness AI’s full potential in improving patient care and operational efficiency. The full State of Interoperability Report is now available for organizations seeking guidance on their path forward.

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• https://ai-techpark.com/interoperability-isnt-ai-ready-yet-despite-heavy-investment-rhapsody-finds/