Spring 2025 Issue

Balancing Privacy and Access
By Bart Howe
For The Record
Vol. 37 No. 2 P. 24

Overcoming Barriers to Data Exchange

HIM has come a long way since the days of paper medical records stowed away in filing cabinets. Rather than drowning in a sea of hand-written documents, health care leaders of today are making leaps and strides to improve data accessibility through interconnected digital systems.

As clinical information exchange advances, health care moves closer to a future where patients can access all their health data in one easy, secure location. But despite advancements in technology, regulation, and processes in recent years, health care data remains incredibly fragmented. Breaking down all these barriers is critical to achieving three core health care goals:

• improving care coordination by eliminating data siloes;
• empowering patients by improving access to their own health information; and
• reducing administrative strain for health care professionals.

Though we continue to make progress in expanding interoperability, many challenges persist today—and one of the most enduring of these challenges is balancing the need to make health data more accessible while also keeping it secure.

In this article, we will explore the evolution of clinical information exchange, its transformative impact, and its future potential.

The Early Days
The term “interoperability” evokes a sense of modernity, but its roots run deep, beginning with early efforts to digitize health care in the late 20th century. The journey began with electronic data interchange (EDI) in the 1980s and steadily evolved through the introduction of EHRs and early regional health information exchanges (HIEs) in the late 1990s.

These efforts laid the groundwork for a series of federal laws and regulations that elevated clinical information exchange from a mere concept to an achievable standard in the future of health care.

EDI Begins
In the 1980s, long before EHR adoption became widespread, health care organizations turned to EDI to streamline administrative processes such as billing and claims management. EDI introduced structured formats that made it possible to transmit information electronically between providers, payers, and vendors, marking one of the earliest steps toward interoperability.

While initially limited to administrative functions, EDI had a lasting influence on modern clinical information exchange by:

• standardizing communication across the health care ecosystem;
• paving the way for digital transformation; and
• supporting cross-organizational data sharing.

These early standards helped set the stage for future regulatory actions, which were breathed into life with HIPAA in 1996. Along with many of the privacy and security protections for health care data that still exist today, HIPAA also introduced mandated EDI transaction standards and signaled the need for consistent data exchange rules.

These developments paved the way for what would come next: the digitization of medical records.

Early HIEs and EHRs
Immediately following the boom of EDIs in the 1980s, the 1990s ushered in the earliest era of EHRs. While still in their infancy, these systems offered a glimpse into what digitized health care could look like in the future. But it wasn’t until the 2010s—driven by federal initiatives such as Meaningful Use—that EHR adoption truly took off. Spearheaded by the Office of the National Coordinator for Health Information Technology (ONC), Meaningful Use incentivized providers to implement certified EHR systems and laid the groundwork for interoperable data sharing.

During this time, the Federal Health IT Strategic Plan (2011–2015) further solidified national goals for interoperability, prompting the creation of state and regional HIEs. Early HIEs were designed to connect providers to the right health data at the right time, thereby improving care continuity and reducing operational redundancies.

However, first-generation HIEs were highly regional and lacked any federal efforts to connect nationally. This kept clinical health data siloed and limited in scope. As a result, early HIEs struggled with widespread scalability, long-term sustainability, and inconsistent EHR standards across different states.

Laying the Groundwork
Despite their region-locked challenges and scalability limitations, early HIEs gave us a clear picture of what interoperability initiatives could be capable of at a national scale and encouraged digitizing and modernizing the health care industry.
Research from the National Library of Medicine found that while regional networks improved localized data access, they were hindered by fragmentation and uneven participation. Still, they proved that real-time, cross-provider communication was not only possible but also beneficial—especially for patient care.

Over the years, the federal government has introduced multiple incentive programs to drive adoption of modern clinical information exchange at scale, including the following:

• the Medicare Access and CHIP Reauthorization Act, which introduced value-based care models and rewarded providers who used technology to coordinate care, share data, and engage patients; and

• the Quality Payment Program, which tied interoperability directly to provider reimbursement, pushing organizations to prioritize more connected, efficient systems.

More recently, the 21st Century Cures Act and its Final Rule established mandates for standardized, patient-centered data exchange. Famously, it set the standard to discourage information blocking and required EHRs to support seamless communication across systems. The 21st Century Cures Act also fueled the widespread adoption of FHIR, an application programming interface (API)–driven standard that enables scalable, real-time exchange of health information.

Looking at the history of clinical information exchange from a bird’s-eye view lets us see how we have adapted from past oversights and transformed trial and error into progress. From EDI to EHRs to FHIR, each advancement has played a valuable role in shaping today’s interoperability landscape.

Understanding the Current Landscape
Before we can chart the future of where clinical information exchange can continue to grow, we need to understand what the landscape looks like today.

APIs: A Firm Foundation
APIs are central to modern interoperability initiatives across all industries, with their ability to facilitate real-time data access. APIs are used to connect disparate systems, automate data sharing, and support a growing ecosystem of digital health tools.

APIs are used in a variety of ways in health care, such as the following:

• Treatment: APIs support better treatment outcomes by improving care coordination and continuity of care across provider teams.

• Pharma and clinical research: Pharmaceutical companies and clinical trial sponsors use APIs to connect to registries and other clinical data sources for real-world evidence and to identify eligible patients for studies.

• Payer-provider collaboration: APIs support smoother prior authorizations, eligibility checks, and claims adjudication by allowing real-time data exchange between provider systems and payer platforms.

• Mobile health and patient apps: APIs power consumer-facing apps that capture health data from multiple sources, offering patients a more unified or insightful view of their care, improving data transparency and patient engagement.

It goes without saying that APIs are powerful, but they’re not a silver bullet. The rise of APIs introduces new complexities for the current and future state of interoperability, especially in areas like data governance, standardization, and compliance.

As their use expands, the industry must explore complementary approaches—including more intelligent access filters, dynamic consent models, and identity verification tools—to mitigate risk while supporting innovation.

Modern Interoperability Efforts
When assessing where modern initiatives stand, we have to discuss the Trusted Exchange Framework and Common Agreement (TEFCA) and Carequality, two separate frameworks that are representative of national interoperability efforts today.

Carequality is a private-sector initiative that enables data sharing between participating EHR vendors and providers through a consensus-based trust framework already in wide use. It is one of the most widely adopted interoperability initiatives in the country, supporting billions of clinical document exchanges each year.

TEFCA, on the other hand, is a federally backed framework developed by the ONC. TEFCA’s mission is ambitious but clear: to break down silos, improve care coordination, and empower patients with easier access to their own health records. By setting technical, policy, and governance standards, TEFCA aims to ensure that different interoperability efforts can work together under a common set of rules.

However, recent developments have put the future of these frameworks into question. Epic’s highly publicized spat with Particle Health and Carequality in 2024 over data privacy concerns caused an avalanche in the health care industry. Epic stands firm on the principle that we need stronger data use protections and more control over who can access patient data, highlighting the friction always at the core of health care conversations: How do we accomplish this while balancing privacy and access? And at the same time, TEFCA’s fate is currently uncertain given the restructuring underway at Health and Human Services.

National data sharing frameworks like these may have a utopian, one-stop-shop appeal in theory, but in practice, resolving tensions around balancing privacy and access across a broad set of use cases and ecosystem actors is not only incredibly challenging; it’s also becoming more complex with competing regulatory frameworks and ever-evolving data demands.

Many industry experts contend that frameworks such as TEFCA and Carequality have a place in the future of interoperable health care; but in order for patient data to flow securely and seamlessly across the growing list of use cases and data-fueled applications, purpose-built clinical information exchange networks and solutions tailored to specific clientele will need to exist at scale. If successful, the innovation driven by a competitive ecosystem of networks and solutions could enable a more seamless, secure, and efficient health care experience for us all.

Many Barriers Still Persist
Health care has made huge strides in achieving wider-spread support for interconnectivity, but there are still many barriers that continue to impede progress, including the following:

• Regulatory complexity: Striking the right balance between privacy and access remains a challenge, as evidenced by the Epic and Particle Health dispute that led Epic to shift its attention from Carequality to TEFCA.

• Standardization gaps: While FHIR adoption is growing, inconsistencies in implementation create bottlenecks that prevent seamless communication between disparate systems.

• Technology integration challenges: Many health care organizations still struggle with legacy systems that are not built for modern interoperability standards, requiring costly updates and integrations.

Open Issues Remain
Despite the progress we have made over the last four decades, true clinical information exchange remains an open issue. Fragmented systems, complex laws, and inconsistent data still create barriers to seamless data exchange. To move forward, we must tackle these challenges head-on, breaking down silos and building a secure data-sharing foundation that puts patients first and empowers providers with optionality to select the right interoperability solutions for their practice.

Patient Health Record
Picture a world where every patient has instant access to their complete medical history—no missing records, no frustrating delays, and no data fragmentation. Every diagnosis, treatment, and test result from every provider, all in one seamless, real-time view. This isn’t just a vision for the future; it’s the next frontier in health care. The goal of a unified, lifelong health record is within reach, but it demands a collective push toward a competitive interoperability ecosystem, continuous innovation, and patient-first data sharing strategies.

AI-Fueled Predictive Analytics
AI and predictive analytics are nothing new, but their prominence has never been more present and relevant today. Using AI to drive predictive analytics for health care has immense potential to make a meaningful impact on patient outcomes. When paired with interoperable data systems, AI can surface insights in real time, flagging potential diagnoses, predicting adverse events, and identifying care gaps before they lead to an event. Even today, predictive algorithms can analyze patterns across vast datasets, enabling more personalized care plans, proactive interventions, and strategies that are tailored to individual risk profiles. For this vision to become a reality, we need to keep breaking down information silos—ensuring success hinges on access to structured, harmonized, and complete patient data, not just certain pieces.

Final Thoughts
As interoperability improves, the quality and diversity of data fueling these models will improve along with it, unlocking even greater potential for human and AI-powered intelligent decision-making, as well as streamlined administrative tasks like coding and documentation. But to realize these benefits, the data must be accurate, accessible, and standardized. As long as we work together to fully understand and harness the power of the technology at our fingertips, the question isn’t if we’ll get there; it’s how soon we can make it happen.

— Bart Howe is the CEO of HealthMark Group, a digital HIM company. He also serves as the president of the Alliance for Health Information Operations and Standards, an organization comprising HIM service companies with the mission to promote compliance and excellence in the management of confidential, patient-identifiable information.