Why a Data Exchange Platform Is Vital to Healthcare Interoperability

Today’s healthcare system touts high levels of EHR adoption among hospitals and physician practices thanks to billions of dollars in incentives made available by the Centers for Medicare & Medicaid Services (CMS). As of 2021, 96 percent of acute care hospitals and 78 percent of office-based physicians have adopted certified EHR technology, a marked improvement over 2011 when those figures sat at 28 percent and 34 percent, respectively.

Such high adoption statistics empowered a former CMS administrator in 2018 to call for the end of fax-based information sharing in healthcare by the decade’s close. But that vision failed to come to fruition, and fax remains a dominant mode of health data exchange, accounting for 75 percent of all medical communication.

The federal government is still pursuing standards-based exchange in developing final rules for healthcare attachments and prior authorization. Both received pushback during the comment periods following notification of proposed rulemaking. The former proposes adopting the HL7 CDA standard, an XML-based markup standard for the encoding, structure, and semantics of clinical documents for transmitting attachments. The latter would impose new requirements for qualified health plans and providers to improve the digital exchange of healthcare data and processes around prior authorizations.

Taken together, a clear disconnect is apparent. Not all parts of the care continuum qualified for incentives to adopt certified EHR technology, meaning the health IT playing field is not level. Advancing interoperability depends on the capabilities of the sender and the recipient, and any solution to strengthen health data-exchange processes must consider the numerous ways healthcare organizations send and receive sensitive information. Fortunately, technology exists to securely route patient information in the right way to the right provider at the right time.

Value of a data exchange platform

The ability of two or more systems to access, exchange, integrate, and use health information depends on various processes and technology. Historically, enabling this kind of exchange required the development of HL7 interfaces — a way for two systems to speak the same language. Over the years, the emergence of application programming interfaces (APIs) has allowed healthcare organizations to access and modify data and functionality through agreed-upon protocols, commands, and other functions.

Within healthcare, Fast Healthcare Interoperability Resources (FHIR) has emerged as the most popular API among regulators and developers. FHIR enjoys the backing and support of the developer community, federal regulators, and leading healthcare institutions. It is a standard and API designed specifically for the web and provides resources and foundations based on XML, JSON, HTTP, AToM, and OAuth (Open Authorization) structures. Using FHIR, providers can exchange information and create, manage, and send referrals. Moreover, it is compatible with other health data standards, improving health data exchange, clinical decision support, population health management, and patient engagement.

While FHIR is proving impactful in the healthcare industry, it doesn’t solve all the challenges facing interoperability and health data exchange across the continuum of care. For many organizations supporting a FHIR standard when they are still using fax machines is a big hurdle. They don’t have the technology skills or the budget for these deployments. As mentioned before, they were left out of the original technology incentives. These types of organizations are care settings that are critical for information sharing so that the continuity of care is not disrupted. Many of these organizations still rely on unstructured data (e.g., open text, images, PDFs) to send and receive information vital for care coordination and delivery.

Enter the data exchange platform, a technology solution that is the central hub for seamless data exchange between EHRs, medical billing, lab information, and other applications using standards and protocols from the unstructured PDF image to an HL7 and FHIR message or even an X12 message standard and translates and normalizes that data between different formats and systems. In place of one-off interfaces, a data exchange integration streamlines the movement of clinical, financial, and operational data between healthcare IT systems in real time, streamlining workflows and reducing errors.

Under the hood, a data exchange platform performs several processes critical to moving information from point A to point B.

Data conversion changes the structure of information while maintaining its content. In healthcare, this process is crucial for converting unstructured data (e.g., notes, faxes, scanned images, etc.) into a structured format such as JSON (JavaScript Object Notation), an open standard file and data interchange format using human-readable text. Using natural language processing (NLP) and artificial intelligence (AI), developers can speed up data identification and extraction while streamlining data normalization. This process enables intelligent data mapping to the desired structure within disparate systems.

Data mapping converts data from one format or structure to another to allow its use by different systems and applications, such as EHR technology to care management platforms. Successful data mapping requires analyzing source and target data structures, matching data fields, transforming the data, and ensuring the process meets the specified requirements. Data extraction, which is the beginning of data mapping, needs to support standards of clinical content (e.g., C-CDA, USCDI) for the data to have a corresponding field to map to. HL7 and FHIR are leading transport standards for data sharing in healthcare.

Data normalization converts extracted data into a standardized format (HL7, FHIR) to be easily integrated into other healthcare systems and applications, which promotes data sharing and analytics across the care continuum. Data must be collected, cleaned, transformed, validated, and integrated to make the information suitable for clinical decision-making for individuals and populations.

Data integration enables information to be combined from multiple sources into a consolidated view. By successfully aggregating, filtering, or transforming information, data integration is typically an ongoing process that is performed to support information reporting, analytics, and other tasks based on timely and accurate data.

Data transformation changes the data’s structure, format, or content to meet an organization’s specific requirements or to support data processing tasks. It often involves more complex data mapping and interventions (e.g., changing data types, formatting dates, or normalizing data) to achieve a successful result.

Intelligent data extraction has further accelerated the process of identifying and extracting relevant information from unstructured data sources (e.g., PDFs, images) using optical character recognition (OCR), NLP, and AI. In healthcare, relevant data can be pulled from unstructured documents — digital faxes, scanned images, TIFFs, etc. — to determine patient demographics, diagnoses, and treatments and plans to support clinical decision-making continuity of care, building a longitudinal record and improving health outcomes.

Combined with recognized methods for data transport, a modern data integration platform can move sensitive information across the enterprise and between institutions in a manner that suits both the sender and receiver. In a digitally fragmented healthcare system, this is extremely important. The ability to do so can equate to the difference between patients receiving accurate and inadequate care.

In the next two installments of this series, we will profile two use cases that demonstrate the power of an integration engine to support providers and patients during and between encounters.

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See the other articles in this series:

Enabling Healthcare Interoperability with Fax to FHIR Solution

Overcoming Interoperability Challenges with Digital Fax and FHIR