SNOMED CT, LOINC, and ICD-10 – The Foundations of Semantic Interoperability


Conducting large-scale medical research or clinical trials requires streamlining all data processes to the most comfortable extent. This is not an easy task, considering that the operational software needs to relate medical terminology across medical fields and databases simultaneously. The solution – implementing semantic interoperability in operating systems software.

Semantic interoperability implies the mapping of terminology across various valuable medical thesauruses. Cutting-edge systems use the resources deposited in such medical vocabularies to accurately relate one specific term to another.

In other words, by integrating various medical vocabularies on code-level, interoperable software breaches the terminology gaps between medical fields. These vocabularies are immensely populated databases that need to be synchronized in semanticity and syntax to provide a more accurate clinical data assessment.

The core information needed for operating large-scale clinical trials and research is the one that concerns patient-care data, diagnostic codes, and clinical laboratory results.

For a multi-centred clinical trial to be appropriately developed and run, the operating software needs to relate to the essential medical resources, such as SNOMED CT, LOINC, and ICD-10.

Here, we offer a quick insight on those medical vocabularies and discuss their true potential as foundations of semantic interoperability.


SNOMED CT (Systematized Nomenclature of Medicine – Clinical Terms) is a multilingual dictionary of standardized clinical terms that facilitates the exchange of relevant information between healthcare professionals. It is considered the most comprehensive glossary of clinical terminology in the world.

SNOMED CT encodes the meanings of terms often used in healthcare settings, such as symptoms, signs, diagnoses, procedures, clinical findings, and body structures. Its database is also able to distinguish between etiologies, pharmaceuticals, specimens, and medical devices.

Today, this system is the core of information systems used for keeping electronic healthcare records and is fundamental for interoperable health-related software.

History of SNOMED CT

Throughout its long history, the system has been meticulously perfected through practice and updated multiple times.

The system originated in 1965 from Systematized Nomenclature of Pathology (SNOP), which was used to describe morphology and pathology. To satisfy the growing need for medical research, SNOP was expanded to SNOMED in 1975. Later on, in 2002, after the merger with other clinical terminology standards, such as CTV3, the final version of SNOMED CT was created.

Today, SNOMED CT is developed, maintained, and distributed by the International Health Terminology Standards Development Organization (IHTSDO), established in 2007.

Since 2013, SNOMED has been a standard mandatory in the US for keeping EHRs.

How Does SNOMED CT Work?

SNOMED is used for indexing, storing, and retrieving medical data. Furthermore, it groups information and facilitates sharing between distant healthcare specialists and through various healthcare settings.

Within the system, data can be stored in various healthcare settings simultaneously, and at the same time, organized, queried, and analyzed.

Three criteria define each term in the base:

  • Concepts – Each one is a unique clinical meaning,
  • Descriptions – Every concept relates to two descriptive categories:
    • Fully Specified Name (FSN), and
    • Synonym,
  • Relationships – Series of cross-functions that define how concepts relate to each other.

Concepts are defined within a nine-system hierarchy, and these are:

  • Clinical finding concepts,
  • Procedure concepts,
  • Evaluation procedure concepts,
  • Specimen concepts,
  • Body structure concepts,
  • Pharmaceutical/biologic product concepts,
  • The situation with explicit context concepts,
  • Event concepts,
  • Physical object concepts.

Each concept is numerically represented, and as of January 31st, 2020, there were officially 352,567 different concepts within SNOMED CT.

Who Uses SNOMED and Why?

Healthcare professionals use SNOMED to capture data and researchers to link relevant information across settings.

SNOMED CT can be cross-mapped to other international standards, such as ICD-10, which helps facilitate semantic interoperability. For clinicians, it is an essential resource with extensive medical content.

The numerical reference system helps exchange clinical information between disparate health care providers and electronic medical records systems. This streamlined data exchange reassures for evidence-based patient care across different healthcare contexts.

What Is LOINC?

LOINC (Logical Observation Identifiers Names and Codes) is a unified database that assists in exchanging and gathering clinical results, such as laboratory tests, clinical observations, and measurement-related patient outcomes. It is also used for laboratory testing devices and healthcare management.

LOINC facilitates both laboratory expertise and research by providing a unified terminology for different results. The LOINC database and its operating software are created and maintained by the Regenstrief Institute, Inc.

History of LOINC

LOINC was introduced in 1994 to assist the exchange of results obtained by different laboratories. Before that, no universal standard for laboratory tests existed, which presented a problem for cooperating laboratories.

Even today, LOINC is not considered as a necessity for performing laboratory and observational operations.

Many other systems use different computable coding systems, such as IHE or HL7. However, LOINC is regarded as a more interoperable system and is generally preferred.

How Does LOINC Work?

LOINC database uses more than 71,000 terms to describe observations.

LOINC terminology has two main parts:

  • Laboratory LOINC, which covers lab tests and microbiology values;
  • Clinical LOINC, which describes non-laboratory observational values, such as obstetric ultrasound, ECG values, etc.

Each six-figured term in the database represents a single test, observation, or measurement. Every figure represents a distinctive value of the test or measurement:

  • Component
  • Kind of property
  • Time aspect
  • Specimen type
  • Type of scale
  • Type of method

Furthermore, the database has other descriptive fields, such as synonyms, status, translations, and substance information.

Other standards, such as ASTM, E1238, IHE, HL7, or CEN/TC251, use LOINC to electronically transfer results from different reporting settings to a single network.

How Is LOINC Used in Clinical Trials?

LOINC is used with RELMA (Regenstrief LOINC Mapping Assistant) – a program designed for searching through LOINC databases and mapping local files to it.

New versions of LOINC and RELMA are released twice every year, in June and December.

LOINC codes allow a researcher to merge clinical results from multiple trials into a single database. Using corresponding universal codes is considered as a time-valuable investment.

The downside of LOINC is the interpretation of its hierarchy. The computable hierarchy exists; however, it is not exposed in a semantic format, that would be easy for a terminology server to interpret.

What is ICD-10?

ICD-10 is the global reference base for morbidity and mortality statistics used by many healthcare systems and researchers worldwide. Officially, its full name is the International Statistical Classification of Diseases and Related Health Problems, and it has been promoted and monitored by WHO since 1948.

Today, it is considered a global information standard for clinical care and research. Its use provides better disease monitoring and data transparency and facilitates financial management. It is widely used in epidemiology, clinical research, and everyday healthcare practice.

ICD-10 is primarily used to define diseases, study disease patterns and subgroups, manage healthcare, monitor outcomes, and even allocate resources. ICD-10 facilitates international comparability in collecting, processing, classification, and presentation of disease-related data.

Brief History of ICD-10

This system was initially introduced as the International list of Causes of Death by the International Statistics Institute of London in 1893. The WHO was entrusted with the maintenance of this classification system in 1948, when the 6th version of the system was released. The WHO insists that its member states use the most current version of ICD in their health practices.

ICD-10 is the tenth version. Over the years, the system has been improved, and its developmental timeline reflects developing healthcare advances. ICD-10 has about ten times as many codes for medical conditions compared to its predecessor, and it has been in official use since 1992.

The eleventh edition, ICD-11, was officially accepted by the World Health Assembly in 2018, and it is considered as a significant step forward because it will comprehensively enhance the standardization of digital health. It will be active as of January 1st, 2022.

How Does ICD-10 work?

ICD-10 is the technological platform created and maintained to share health-related information by using a unified language.

Technically, ICD-10 is a comprehensive system of diagnostic codes used for disease classification. Each code defines the primary disease, and has broadening criteria for every nuance class, including symptoms, signs, unordinary findings, circumstances, complaints, and even therapy adverse effects. The designated code for each condition is up to six figures long, and it relates to appropriate genetic categories.

In other words, every disease, injury, or other health condition is defined and grouped as an individual entity, which has both descriptive and statistical values.

Who uses ICD-10?

There are more than 100 countries that use this standard worldwide. It has been translated into 43 languages, and It has been cited in more than 20,000 scientific articles.

ICD-10 is used by physicians, nurses, health workers, clinical researchers, health information managers, and policymakers.

It is also used as a referencing standard for managing resources, for as 70% of global healthcare expenditures, such as reimbursements and resource allocations are calculated using ICD-10.

The Benefits of ICD-10 in Clinical Trials

It facilitates evidence-based decisions by providing quick retrieval and analysis of health information. ICD-10 also helps in sharing related information between healthcare settings, regions, and hospitals.

The coding system leads to more extensive information on comorbidities and (serious) adverse events. Additionally, it allows the interpretation of a patient’s medical history in a more detailed and comprehensive way, thus aiding patient selection and providing better outcomes.

It allows researchers to set up a trial and maintain clarity through its available statistical information, such as prevalence, incidence, and financial burdens of disease.