Achieving seamless health data exchange is difficult due to its paradoxical nature: the data includes sensitive personal information that should be properly protected from leaks, but it also requires a simplified access mechanism to ensure better patient outcomes. Moreover, it is important to maintain the precise meaning of the information shared between systems, which is called semantic interoperability.
Healthcare includes various data types that need to be transferred between systems based on different frameworks, standards, and protocols. There are two ways to establish data exchange between systems. The first one implies the transfer of coded information, which requires providing a system receiver with decoding rules. Another way is to move from the traditional coding approach to simpler textual formats.
Industry professionals try to balance the need to keep data secure and provide seamless data access to the participants of the healthcare process for the sake of the patient’s well-being.
Today, we want to discuss how to solve one of the main problems with semantic interoperability in healthcare and make more systems/receivers understand the content of transferred data, regardless of its format.
INTEROPERABILITY LEVELS: A LOGICAL APPROACH TO SEMANTIC INTEROPERABILITY IN HEALTHCARE
Semantic interoperability is the highest level of interoperability built on foundational and structural interoperability to provide the necessary infrastructure for smooth data exchange.
Why is foundational and structural interoperability important?
Foundational interoperability refers to raw data exchange, achieved by employing security protocols and data transmission standards. Interpretation of data on the systems level is not required for foundational interoperability.
Structural interoperability refers to the exchange of structural formats of data and requires the interpretation of a data field. Message format standards help achieve the intermediate level of interoperability and allow you to start working on semantic interoperability.
Standards for foundational and structural interoperability have been around for a long time. However, the niche still required standards for exchanging, using, and re-using health data to help stakeholders realize semantic interoperability.
In late 2005, Health Level 7 (HL7) came up with the HL7 V3 standard. HL7 is a standard development organization primarily focused on clinical and administrative domains. In the V3 standard, HL7 introduced the healthcare world to the RIM (reference information model) concept, which was supposed to become a tool for achieving FHIR semantic interoperability.
Read Also: HL7 Integration: Key Benefits & Case Studies
HL7 V3 AND RIM
The Reference Information Model is a foundational abstract model that expresses all things healthcare. RIM is used to derive all V3 messages. It is the first standard for semantic interoperability in healthcare that allows sharing of health data via all HL7 messages regardless of the message structure.
HL7 V3 has structured messages in XML format. You will find more details about HL7 V3 messages in our FHIR vs. HL7 article.
Fundamental HL7 components for semantic interoperability in healthcare:
- standard information model (RIM) that covers all healthcare aspects (clinical, administrative, and financial);
- clearly defined messaging process for retrieving data from RIM;
- a robust base for RIM with a formal Data Type Specification;
- defined mechanism of the RIM attributes to terminology binding.
The RIM defines backbone classes as core building blocks for health information representation.
RIM backbone classes:
Entity class – represents everything or anything involved in a healthcare event (person, animal, organization, thing).
Role class – defines responsibilities of the Entity elements (patient, employee, etc.).
Role link – connects two roles in the Role class and expresses their dependency.
Act – represents actions/events that occur in the context of healthcare (patient encounters, observations, procedures, and more).
ActRelationship – represents relationships between two Acts.
Participation – connects the Entity and the Act and specifies the Role of the Entity in the Act.
Apart from backbone classes, the RIM structure includes codes drawn from expressive terminologies, such as Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) or Logical Observation Identifiers Names and Codes (LOINC). LOINC is used for identifying health measurements, observations, and documents. The SNOMED CT is considered the most extensive, multilingual clinical healthcare terminology in the world.
How can terminology systems improve semantic interoperability for healthcare?
Clinical terminologies were developed to ensure semantic interoperability of clinical information and support clinicians that provide care. Terminologies provide a common vocabulary and standardized data representation that improve the consistency and accuracy of exchanged information. Here are some other benefits of terminologies:
Simple data integration – it is easier to integrate data from different systems and other sources due to standardized data representation provided by terminology systems.
Clinical decision support – terminologies reduce the risk of errors by analyzing patient history/symptoms and suggesting diagnoses and proper treatments.
Healthcare data analysis – terminologies allow the analysis of vast amounts of health data and tracking trends to respond to the needs of humanity in time.
Overall, terminology systems help achieve semantic interoperability in health information systems and healthcare in general. They improve the accuracy and consistency of health data. Also, they target the major challenge of semantic interoperability in healthcare: the difficulty of health data interpretation.
RIM’s backbone classes are standardized representations of common healthcare concepts and data elements. The backbone classes allow modeling relationships between different healthcare elements, such as patients, procedures, observations, etc. HL7 promoted the general adoption of the HL7 V3 standard as the next step to bring healthcare closer to achieving semantic interoperability.
However, the V3 standard has not been widely adopted in the industry for several reasons:
Complexity – the standard accommodates a wide range of health data and all healthcare use cases, which makes it bulky.
Lack of backward compatibility – the V3 standard isn’t backward compatible with previous HL7 standards, at least in a direct way. As a result, it would take much work for organizations to upgrade their existing systems, which became one of the significant barriers to adopting the standard.
Cost – the previously mentioned point resulted in a need to build systems based on HL7 V3 from scratch. It required massive investments in new hardware, software, and personnel to support the standard, which only large enterprises could afford.
The question of semantic interoperability remained open until HL7 introduced the world to the new healthcare standard — FHIR. You can also learn more about FHIR terminology module in one of our recent articles.
FHIR FOR SEMANTIC INTEROPERABILITY
For details of FHIR standard development and its history, we invite you to read our Ultimate Guide to FHIR. This material will enlighten various administrative and technical aspects of Fast Healthcare Interoperability Resources (FHIR).
Today, we would like to focus on the impact of FHIR on semantic interoperability in healthcare. FHIR semantic interoperability creates a solid interoperability base and ensures the complete achievement of foundational and structural interoperability by providing:
FHIR resources: just like RIM classes, FHIR resources serve as a standardized way to represent data. The main difference is that a resource-based model allows breaking complex, voluminous healthcare data into small units that simplify the data exchange process.
FHIR profiles: a profile is a set of resources adapted for a specific healthcare context, which allows for extensions and restrictions of elements and terminologies of FHIR resources. Profiles ensure accurate data exchange between systems by providing consistent structure.
FHIR API: FHIR APIs are based on REST architecture, which uses HTTP protocol. RESTful APIs help retrieve, create, update, and delete resources seamlessly.
Code systems: code systems defined in FHIR standards allow for representing diagnoses, procedures, laboratory tests, and other healthcare concepts in standardized ways.
Value sets: a collection of codes from different code systems to represent various aspects of clinical and administrative domains.
Concept maps: one of the most important instruments for semantic interoperability, which defines a healthcare data mapping between terminologies. It enables systems to translate terminologies and represent the correct interpretation of information transferred between different systems.
Terminology services: an interface for accessing and resolving terminologies. It supports multiple value sets and code systems, enabling systems to access terminologies regardless of basic code systems and value sets underlying a system.
FHIR provides a standardized yet flexible framework for healthcare data exchange and representation. It allows effective communication between multiple systems/stakeholders, ensures accurate interpretation of shared data, and improves the speed and efficiency of healthcare.
USE CASES OF SEMANTIC INTEROPERABILITY IN HEALTHCARE
One of the prime examples of semantic interoperability is the automated data exchange between two systems that can recognize medical symbols and terminology without requiring human input.
For instance, imagine a scenario where Hospital A must share a patient’s electronic health record (EHR) with Hospital B. Through semantic interoperability, the two systems can effortlessly exchange and comprehend medical information, including diagnoses, medications, procedures, and other relevant data, without manual intervention.
Semantic interoperability eliminates language barriers and enables effective communication and collaboration across healthcare organizations. In addition, semantic interoperability enhances the accuracy, efficiency, and safety of healthcare delivery by establishing a common understanding of medical terminology and concepts.
Embracing and expanding the scope of semantic interoperability is a critical step toward acknowledging the full potential of digital healthcare.
DISCOVER TOP-NOTCH ENTERPRISE-LEVEL TOOLS FOR SEMANTIC INTEROPERABILITY MADE BY EDENLAB
Edenlab’s experts have deep knowledge of the FHIR standard and have proven experience in the development of national-level healthcare systems. Our Kodjin Interoperability Suite includes an event-driven Kodjin FHIR Server. Our specialists will help you define concrete and consistent steps toward achieving semantic interoperability.
Where can I find examples of semantic interoperability in healthcare?
The best example of semantic interoperability is the automated data exchange between two systems that recognize medical symbols and terminology without human input.
What is the meaning of semantic interoperability in health records standards?
It allows different systems and technologies to exchange health data efficiently. Moreover, it ensures correct and consistent interpretation of electronic health information.
How do you achieve semantic interoperability with EHR systems?
Semantic interoperability in EMR/EHR requires establishing basic interoperability levels and flexible mechanisms for accessing and translating terminologies.
Is SMART on FHIR the new healthcare interoperability standard?
SMART on FHIR is a set of open standards developed to achieve a smooth and secure clinical data exchange between systems by standardizing how the data is stored and accessed. Learn more about modern healthcare data access solutions from our SMART on FHIR article.