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What Are the Four Levels of Health Data Interoperability?

According to the Healthcare Information and Management Systems Society (HIMSS), health data interoperability has four levels: foundational, structural, semantic, and organizational.

While health data interoperability has arguably become an industry buzzword over the past decade, the concept's importance for digital health transformation cannot be understated.

According to the Healthcare Information and Management Systems Society (HIMSS), health data interoperability is "the ability of different information systems, devices and applications (systems) to access, exchange, integrate, and cooperatively use data in a coordinated manner, within and across organizational, regional and national boundaries, to provide timely and seamless portability of information and optimize the health of individuals and populations globally."

Benefits of healthcare interoperability include improved care coordination for patients and reduced administrative burden for healthcare payers and providers. Interoperability can also support public health surveillance and population health initiatives.

Healthcare organizations can achieve interoperability to various degrees. HIMSS breaks down interoperability into four stages: foundational, structural, semantic, and organizational.

Foundational Interoperability

Foundational interoperability "establishes the interconnectivity requirements needed for one system or application to securely communicate data to and receive data from another," according to HIMSS.

In this form of interoperability, the receiving IT system does not need to be able to interpret the exchanged data -- it must simply be able to acknowledge receipt of the data payload.

An example of foundational interoperability is sharing a PDF document that contains a summary of the patient's hospital stay and discharge medication list with another system. The receiving system can store the PDF and the clinician can read the document to inform care delivery. However, the receiving system cannot further process the data in the document without manual effort.

The health IT system cannot analyze the individual items on the discharge medication list to update the patient's current medication list, for instance. Instead, the provider must manually input this data into the patient's EHR.

While foundational interoperability is an essential HIE building block, it is not enough because it does not allow providers to meaningfully use health data.

Structural Interoperability

Structural interoperability builds on foundational interoperability by "defining the format, syntax, and organization of data exchange, including at the data field level for interpretation," as defined by HIMSS.

This intermediate form of interoperability depends upon message format standards to support the exchange of health data from one system to another while maintaining the meaning of the data. Sending and receiving systems must use the same data standards to achieve structural interoperability.

An example of structural interoperability is ePrescribing. The provider's health IT system must leverage the same data standards for common prescription elements as the pharmacy's system to ensure accurate prescribing.

HL7 Fast Healthcare Interoperability Resources (FHIR) has quickly grown into one of the most popular standards for structural interoperability. Most major EHR vendors have implemented FHIR, which has helped enforce the internet-based data standard as a leading health information exchange (HIE) method.

The standard enables health data exchange from one health IT system to another in a way that maintains the clinical or operational meaning of the data. FHIR achieves this by assigning each discrete data element a standardized, shareable identifier that operates like a webpage URL. Resources can include metadata, text, or data elements, enabling discrete data sharing.

Semantic Interoperability

Semantic interoperability "provides for common underlying models and codification of the data including the use of data elements with standardized definitions from publicly available value sets and coding vocabularies, providing shared understanding and meaning to the user," according to HIMSS.

In other words, semantic interoperability means that two or more systems can exchange data accurately with a common format and meaning.

Semantic interoperability involves clinical terminologies such as SNOMED CT, ICD, and LOINC. These languages provide standardized meanings of concepts to ensure that data is not only transferred accurately and interpreted meaningfully but also used in a clinically relevant manner, according to AHIMA.

Through this level of interoperability, providers can exchange patient summary information with caregivers and other authorized parties using different EHR systems. This can enhance care delivery through a common understanding of medical terminology.

Semantic interoperability can allow providers to share patient data to reduce duplicative testing, enable clinical decision support, and avoid adverse health events. Effective data sharing can also help improve care coordination, reduce hospital readmissions, and ultimately save hospitals money.

Organizational Interoperability

According to HIMSS, organizational interoperability includes "governance, policy, social, legal, and organizational considerations to facilitate the secure, seamless, and timely communication and use of data both within and between organizations, entities, and individuals."

Since various organizations with different aims, regulations, and requirements are involved in this form of interoperability, stakeholders must address additional non-technical aspects of HIE, such as policy, legal, social, and organizational considerations.

Some HIE organizations are pursuing organizational interoperability through a health data utility (HDU) model. According to Civitas Networks for Health, HDUs are statewide entities that combine, enhance, and exchange electronic health data for treatment, care coordination, quality improvement, and public and community health purposes.

HDUs emphasize multi-stakeholder organizational and data governance and are usually designated non-profit organizations or independent state agencies. HDUs often leverage existing infrastructure for data exchange, such as regional and statewide HIE networks.

According to Civitas, the necessary conditions for HDUs include:

  • Broad stakeholder participation, connectivity, exchange, and community-level engagement
  • State policy levers, including incentives and/or mandates
  • Mature Medicaid and public health use cases
  • Multistakeholder corporate and data/network governance
  • High standards for data privacy and security

While organizational interoperability is the aim, most healthcare organizations are still working to establish foundational and structural interoperability. However, adopting health data standards to achieve lower levels of interoperability can help set healthcare organizations up for future advancements in health data exchange as the digital health transformation progresses.

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