Featured Case Studies
EMEA
Advancing Procedure Concept Modeling in SNOMED CT: Standards, Best Practices and Evolution.
As a key component of the Quality Improvement project, the SI Content Team is engaged in the ongoing evaluation and refinement of the 71388002 |Procedure (procedure)| hierarchy. This process aims to standardize and normalize content, ensuring strict compliance with established Editorial Guidance and Policy to uphold terminology structural quality, consistency, accuracy and usability. Furthermore, user feedback is systematically analyzed to optimize modeling patterns, resulting in the creation and dissemination of updated Model Patterns, Editorial Guidance and Templates designed to support SCT authors and implementers.
EMEA
A Semantic Strategy is a key element of interoperability in electronic healthcare: A proposal for an approach in Germany
Data interoperability is a crucial element for the success of a digitalization strategy. Achieving data interoperability requires clear semantic and syntactic rules. Therefore, digitalization in healthcare should be accompanied by a semantic strategy to outline a foundation of agreed reference coding systems and valuesets for specific domains and segments of the electronic health record. The electronic healthcare system in Germany is evolving. With legal agreement for a European Health Data Space in 2025 also a harmonization in Europe will be pursued. The BfArM as the National Competence Center for medical terminologies has issued a position paper, which is currently discussed with stakeholders. The paper proposes a gradual convergence of standardized documentation in healthcare towards a binding set of basic coding systems and valuesets. Requirements should be identified and semantic reference sources agreed by the domain expert community. A consented semantic framework will support users and software providers in their decision-making and aims to reduce the diversity of individual solutions. A long-term strategy will give decision-makers certainty in their planning and will support a gradual alignment of electronic data towards a mandatory set of basic coding systems. A central asset in this strategy is a central terminology server for the healthcare domain. It will act as a single “source of truth” and reliable platform for semantic references. A central platform will serve as “on-stop-shop” for automatic technical distribution and consumption and also as reliable long-time versioning archive during the live-cycle of electronic healthcare record items.
Asia Pacific
An approach to monitor obstetric clinical indicators using SNOMED CT encoded clinical notes
This use case describes the automation of monitoring obstetric clinical indicators using SNOMED CT encoded clinical notes. The semi-structured clinical notes were extracted and encoded with SNOMED CT using a natural language processing system called MyHarmony. A tri-partite arrangement was established, which involved the informaticians at the Health Informatics Centre (Pusat Informatik Kesihatan, PIK) in the Ministry of Health Malaysia, the clinicians headed by the head of Malaysia’s obstetric speciality, and the Information Technology (IT) engineers of the hospitals involved. Each party has specific roles and responsibilities. There were four benefits identified with using this approach: (1) No data entry required. (2) Saved time and resources due to the automation process for data submission, codification, and reporting. Hence, there is no effect on clinical workflow or requires additional workload. (3) Richer analysis due to the granularity of the data written in free text. (4) Timely result which enables clinicians to monitor and intervene faster. However, there were several expected challenges during this project. First is the incompleteness of the documentation by the doctors which need can be improved with continuous awareness. the documentation and the resulting reports. Secondly, the team must standardize the semi-structured clinical notes from different hospitals. Therefore, it is important that the informatician understand the clinical requirement to ensure the right data are extracted by the IT engineers. This approach will be introduced to other clinical specialities so they can experience the same benefit when using SNOMED CT.
APAC
Automatic Standardization of Chinese Clinical Terms to SNOMED CT Based on Large Language Model Technology
This study presents a method for the automatic standardization of Chinese clinical terms to SNOMED CT using large language model (LLM) technology. To address the challenges of mapping Chinese medical terminology to standardized international vocabularies, the research constructs a dataset covering diverse clinical terms and fine-tunes a pretrained large model (DeepSeek-V3) to improve the accuracy and efficiency of term mapping. Experimental results demonstrate that the LLM-based approach significantly outperforms traditional rule-based or dictionary-based methods. It effectively handles complex cases such as polysemy and term variations, while also supporting contextual understanding to ensure precise term alignment. This technology has the potential to enhance clinical data integration and interoperability, providing standardized terminology support for intelligent healthcare systems and medical research applications.
EMEA
Digital metrology in laboratory medicine: a call for bringing order to chaos to facilitate precision diagnostics
Laboratory medicine is faced with rapid developments in data exchange, secondary use of data and AI. Safe exchange of laboratory data requires a suitable terminology standard. NPU, LOINC and SNOMED CT are increasingly used for this purpose, but none of these terminology standards can currently accommodate safe exchange across the full spectrum of conventional laboratory data. Furthermore, rapid technological advances in, amongst others, the ‘omics’ area will enforce a shift towards precision diagnostics. These emerging technologies demand an appropriate and future-proof terminology standard.
Given the current and future challenges in laboratory terminologies, we here present a concept for digital metrology in laboratory medicine. Terminology standards used in laboratory medicine should be adjusted to the current state of science to allow safe data exchange and interpretation. Essential test information for safe data exchange and secondary use of data now and in the future entails the full spectrum of pre-pre-analysis to post-post-analysis. Major improvements needed include sufficient coding detail for the molecular form of the measurand and information on metrological traceability. Furthermore, it will become essential to indicate interrelationships between measurands. Herefore, integration with established taxonomies like UniprotKB would allow improved identification of interrelationships between measurands and linkage with scientific information for multidisciplinary data science. Hence, laboratory data can further gain in specificity and value.
The time has come to lay the basis for safe data exchange in the era of precision diagnostics. A consensus for digital metrology in laboratory medicine will be essential to move forward with health data exchange.
APAC
Mapping Clinical Terms to Standard Terminology for Multi-institutional Research Platform: Mapping Principles
This project focuses on the principles of mapping clinical terms to standard terminology for a multi-institutional research platform. A hybrid mapping approach, combining automated and manual methods, ensures accurate and consistent terminology alignment. Strict mapping guidelines and 1:1 mapping principles are implemented to address terminology variations and data format differences.
This study highlights the critical importance of precise terminology mapping for reliable multi-institutional research.
EMEA
The EU QUANTUM Data Holder's Maturity Model and its application in health data management
The EU QUANTUM Data Holder’s Maturity Model represents a significant advancement in the assessment and enhancement of health data quality and management maturity across Europe. Developed as part of the QUANTUM initiative, this model provides a structured approach to evaluating data holders’ capabilities in managing health data, ensuring alignment with the European Health Data Space (EHDS) regulations. This presentation will explore the development, methodology, and key findings of the model, highlighting its relevance for standardisation, interoperability and governance within health data ecosystems. Attendees will gain insight into the model’s application and its role in fostering a more integrated and reliable data-sharing environment.
EMEA
Using Graph Databases to Harmonize Multi-Center Data with SNOMED CT
Effective data sharing across institutions is crucial in low prevalence disease research to achieve statistical power and improve clinical outcomes. However, independently created clinical databases often lack semantic interoperability due to non-standardized terminologies. This project takes advantage of an implementation of SNOMED CT within a Neo4j graph database (https://github.com/IHTSDO/snomed-database-loader/), utilizing graph-based algorithms to calculate semantic distances between clinical concepts. By applying the shortest-path algorithm, we significantly reduce manual review efforts required for data harmonization. This implementation facilitates efficient and accurate identification of equivalent or closely related clinical variables across diverse research databases, thus enhancing multi-center collaboration and interoperability in low prevalence disease studies.
EMEA
Using SNOMED CT to build a reference data catalogue for hospital resource management
In the wake of the Covid crisis, vendors have been rolling out hospital resource management software to help French hospitals improve the use of their medical resources (beds, staff, imaging equipment, ...). The core principle of which is to link health conditions to hospital resources, so that each new patient registration results in appropriate booking of resources. Currently, hospitals are required to define their own list of health conditions, a process that has many shortcomings ranging from costly delays to lack of interoperability. PHAST's goal is to create a national list, TIO, that vendors can integrate quickly and securely, and that hospitals can easily customise and maintain.
