IHTSDO Adopts Trading Name of SNOMED International Back 31 Dec 2016 Back Subscribe to SNOMED International news Stay up to date on SNOMED news, features, developments and newsletters by subscribing to our news service. Subscribe

Kakao Healthcare developed the Healthcare data Research Suite (HRS) platform to support multi-institutional research by enabling semantic interoperability through terminology standardization using SNOMED CT. However, manual mapping of local terms to SNOMED CT is labor-intensive and prone to inconsistency. To overcome these challenges, we developed and evaluated "Chipmunk‚Äù, a large language model (LLM)-based tool that automates SNOMED CT mapping and supports the authoring of new concepts through post-coordination. The automated mapping process involved preprocessing local terms, applying syntactic matching, conducting vector similarity searches with an embedding model, and continuously enriching the reference terms through iterative incorporation of verified mapping results. New concepts were authored via a structured post-coordination process. Performance was evaluated using diagnostic and surgical procedural terms from four hospitals in South Korea with usability feedback from expert clinical terminologists. After adding reference terms, accuracy in the diagnostic domain ranged from 89.69% to 98.67%, while in the surgical procedural domain, it ranged from 82.62% to 99.19%. The tool also reduced mapping time by 47% and human resource usage by 70%. Users reported reduced effort, decreased errors, and improved usability. Chipmunk demonstrated strong accuracy and efficiency in real-world SNOMED CT mapping by integrating pre- and post-coordination into a unified workflow. However, challenges remain with complex surgical procedures, ambiguous terms, and abbreviations, highlighting the need for ongoing expert review. Future directions include integrating knowledge graph-based retrieval and enhanced validation features. Despite advances in automation, human expertise remains essential for ensuring precise and contextually accurate terminology mapping. Back View Map Kakao Healthcare (2 of 5) Improving Clinical Data Interoperability: An LLM-Based Approach to Mapping Local Terms to SNOMED CT Read More Country / Region APAC Tags Artificial intelligence, Implementation, Innovation, Mapping, Pre/postcoordination, Tooling Kakao Healthcare developed the Healthcare data Research Suite (HRS) platform to support multi-institutional research by enabling semantic interoperability through terminology standardization using SNOMED CT. However, manual mapping of local terms to SNOMED CT is labor-intensive and prone to inconsistency. To overcome these challenges, we developed and evaluated "Chipmunk‚Äù, a large language model (LLM)-based tool that automates SNOMED CT mapping and supports the authoring of new concepts through post-coordination. The automated mapping process involved preprocessing local terms, applying syntactic matching, conducting vector similarity searches with an embedding model, and continuously enriching the reference terms through iterative incorporation of verified mapping results. New concepts were authored via a structured post-coordination process. Performance was evaluated using diagnostic and surgical procedural terms from four hospitals in South Korea with usability feedback from expert clinical terminologists. After adding reference terms, accuracy in the diagnostic domain ranged from 89.69% to 98.67%, while in the surgical procedural domain, it ranged from 82.62% to 99.19%. The tool also reduced mapping time by 47% and human resource usage by 70%. Users reported reduced effort, decreased errors, and improved usability. Chipmunk demonstrated strong accuracy and efficiency in real-world SNOMED CT mapping by integrating pre- and post-coordination into a unified workflow. However, challenges remain with complex surgical procedures, ambiguous terms, and abbreviations, highlighting the need for ongoing expert review. Future directions include integrating knowledge graph-based retrieval and enhanced validation features. Despite advances in automation, human expertise remains essential for ensuring precise and contextually accurate terminology mapping. Description Research Aim and Scope This research aims to develop and evaluate Chipmunk, a LLM-based SNOMED CT automatic mapping tool designed for multi-institutional research. The scope encompasses the methodology for developing the tool, its implementation in a real-world environment, and a comprehensive evaluation‚Äîincluding both performance (accuracy) and usability assessments. The evaluation was conducted using diagnostic and surgical procedural terms collected from four South Korean hospitals. In addition, special attention is paid to the challenges of automatic mapping when standardizing clinical terminologies in multi-center settings. Anticipated Impact The system offers several key improvements: (1) it enhances resource and time efficiency through advanced preprocessing‚Äîsuch as Korean-to-English translation of local terms, abbreviation handling‚Äîand by applying curation rules, thereby significantly reducing repetitive manual tasks; (2) it improves the quality and accuracy of mapping by leveraging automated mapping results, reducing human errors and increasing precision; (3) it increases consistency by minimizing variability between different mappers that often occurs with manual mapping; (4) it supports an efficient workflow by enabling both pre-coordinated and post-coordinated mapping within a single process; and (5) it further advances usability with an intuitive, user-friendly interface‚Äîsimilar to Excel‚Äîcompared to traditional methods. Ultimately, by using Chipmunk, large-scale mapping projects such as multi-institution terminology standardization can be performed more easily, quickly, accurately, and efficiently, thereby ensuring semantic interoperability and facilitating the meaningful use of clinical data. Scope 1. Global Standard Terminology System: SNOMED CT is globally adopted, ensuring international standardization and interoperability. 2. Comprehensive Reference Terminology: It covers various medical domains, ensuring broad consistency in healthcare data. 3. Support for Post-Coordination: It enables creating new concepts by combining existing terms, providing flexibility. 4. Rich Attribute Relationships and Hierarchical Structure: Its detailed structure allows for sophisticated and precise data querying. 5. Standard Terminology System for HRS: It is the chosen standard for multi-institutional data standardization within Kakao Healthcare's HRS platform. How SNOMED CT will be used SNOMED CT serves as the standard terminology system for multi-institutional data standardization in the Healthcare data Research Suite (HRS) developed by Kakao Healthcare. Here are the key ways SNOMED CT is utilized: 1. System Architecture and Implementation The automatic mapping process begins with setting up a mapping project and includes two main steps: auto-mapping and new concept authoring. Final mappings are integrated into a database as the local term-SNOMED CT mapping table. Both mapping results and new SNOMED CT concepts are added to the reference term database, which holds previous mapping data and extensions. A terminology review committee, along with the mapping team, reviews and cross-validates these results 1.1 Auto-mapping Method The overall automated mapping process, as illustrated in Figure 2. Key steps include: * Preprocessing: Refine local terms by removing unnecessary symbols, expanding abbreviations, and translating non-English terms into English using tools like Google Cloud and OpenAI API. * Syntactic Mapping: Local terms are mapped to exact text matches in SNOMED CT and reference databases, with search results restricted by semantic tags to ensure precision and efficiency. Consistency is maintained by applying mappings across duplicate terms while taking into consideration any domain differences. * Vector Similarity Mapping: Vector similarity search is used with reference terms generated from SNOMED CT descriptions and mapped terms, embedding these terms with the text-embedding-3-small model and storing the results in the FAISS Vector DB for fast retrieval. * Reference Term Integration and Improvement: Figure 3 illustrates the process of generating reference terms. Finalized mappings are added to the reference term set for ongoing refinement, with duplicate terms removed and unique ones undergoing vector embedding. This process uses an iterative approach, continuously enhancing tool performance across multiple institutions. 1.2 Authoring New Concepts Chipmunk facilitates the authoring of new SNOMED CT concepts through a structured post-coordination process * Focus Concept Selection: Begin with choosing a focus concept, aided by proximal primitive concept retrieval to ensure accurate supertype inference and minimize errors. * Concept Modeling with MRCM: Model the concept following MRCM rules, utilizing guided naming to prevent errors. Chipmunk restricts attribute selection based on domain, ensuring only relevant ones are available, and narrows permissible values using ECL queries. * Classification and Validation: These are performed to maintain precision and consistency, using tools like the SNOMED Release Validation Framework and the OWL Toolkit. * Integration: Newly authored concepts are integrated into a mapping table, structured to include the source terminology and corresponding SNOMED CT identifiers. 2. System Evaluation * Dataset: Data from four South Korean medical centers provided a diverse set of diagnostic and surgical procedural codes, ensuring comprehensive evaluation aligned with SNOMED CT semantic tags. * Accuracy Evaluation: Accuracy was tested by comparing automated results to verified manual mappings, using top-1‚ and top-5 metrics. Performance was assessed both within individual hospitals and with added reference terms from others. * Efficiency Evaluation: Baseline manual processes were timed and then compared to the tool-enabled processes to measure time savings and resource optimization. Why SNOMED CT will be used Contact More information Learn more Get SNOMED CT Information about our license and fee structure Learn more Learn more Explore the wide range of resources available to our community of practice Subscribe to SNOMED International news Stay up to date on SNOMED news, features, developments and newsletters by subscribing to our news service. Subscribe

Welsh case study demonstrates SNOMED CT's proven clinical benefits Back 9 Jun 2017 Back Within NHS Wales, an electronic patient record system has been developed since 2009 with a focus on a core generic clinical information model built using SNOMED CT. Mark Wardle, Consultant Neurologist, at Cardiff and Vale University Health Board, and Andy Spencer, Chair of the Informatics for Quality Committee, have recently produced a case study of the implementation of SNOMED CT in an online clinical database in Wales. The case study outlines how SNOMED CT has proven clinical benefits, including supporting: Direct patient care by making information available immediately to staff at the point of care Clinical governance and service provision by making aggregated data immediately available in live reporting Clinical research with a focus on generic and disease-specific patient outcomes. Read the linked case study to learn more. Subscribe to SNOMED International news Stay up to date on SNOMED news, features, developments and newsletters by subscribing to our news service. Subscribe

Surfacing Rare Diseases Earlier: Smarter Signals from Health System Clinical Data Back 11 Dec 2025 Back By Tudor Groza (Bioinformatics Institute, A*STAR & Maternal and Child Health Research Institute, KK Women’s and Children’s Hospital, Singapore) and Ian Green (SNOMED International) Rare diseases affect up to 300 million people worldwide – yet for most patients, the journey to a diagnosis is long, fragmented, and frustrating. It often takes 5–6 years and dozens of healthcare encounters before a rare condition is identified, during which patients navigate uncertainty, delayed care, unnecessary referrals, and emotional burden. For health systems, this delay represents not only clinical risk but also an opportunity cost: patients with rare disorders frequently cycle through services without coordinated recognition or intervention. As nations build digital health infrastructure at population scale, new tools are needed to proactively identify individuals likely to have a rare disease and connect them to specialist pathways sooner. In a recent study published in npj Digital Medicine , Tudor Groza et al introduced a novel screening approach grounded in information content (IC) – a measure of how "unusual" or specific a patient's clinical profile appears in electronic health records. Applied across a nationwide cohort of 1.27 million patients in Singapore, this method demonstrated that rare disease patients exhibit distinct, higher Information Content (IC) patterns from their earliest clinical encounters. Using SNOMED CT – the clinical terminology embedded in Singapore's electronic health records – the authors showed that IC can reliably stratify patients and help surface candidates who may benefit from rare disease assessment or genetic evaluation. At the health-system level, this approach achieved ~95% sensitivity using simple IC thresholds, while keeping follow-up burdens manageable. Beyond identifying known rare disease patients, their work also revealed 71 potential underdiagnosed rare conditions within the population – the majority likely genetic. This highlights a powerful secondary benefit of this methodology: enabling health systems not just to detect individual patients earlier, but also to uncover hidden clinical patterns and unmet needs across their population. Importantly, the approach does not require complex machine learning infrastructure. IC can be embedded as a lightweight screening layer on top of existing electronic health records, making it implementable even in early-stage digital health environments. "Rare disease patients often spend years navigating the healthcare system before receiving a diagnosis, even though many of the clues are already present in their medical records,” says Associate Professor Saumya Jamuar, Senior Consultant in the Genetics Service at KK Women's and Children's Hospital, Director of the SingHealth Duke-NUS Institute of Precision Medicine and Lead Principal Investigator of the Singapore Childhood Undiagnosed Disease Programme. “By harnessing information content from routinely collected clinical data, this work shows how we can surface patients earlier and more systematically – not by adding burden to clinicians, but by letting the health system itself flag individuals who may benefit from specialist review. Our vision is to shorten the diagnostic odyssey and ensure that every patient with a rare condition has a fair chance to be identified, assessed, and supported as early as possible." A key enabler of this work is the growing alignment between terminologies used in clinical care and rare disease research. SNOMED CT offers significantly richer representation for rare conditions than previous standards like ICD-10, and its official mappings to Orphanet – the global authority for rare disease classification – made it possible to systematically identify rare disease patients and evaluate IC-driven screening performance. This collaboration underscores the value of modern, semantically rich terminologies in accelerating precision medicine at scale. "SNOMED CT's rich clinical vocabulary and its alignment with Orphanet provide a powerful foundation for understanding rare diseases within health systems,” says Ian Green, Global Clinical Engagement Lead at SNOMED International. “ This study demonstrates how standardized terminology and high-quality mappings can unlock new analytical approaches that were previously out of reach. We are proud to support research that turns structured clinical data into meaningful insights – and helps health systems proactively identify and care for patients with rare conditions." Looking ahead, Groza et al. envision this as a foundation for a broader ecosystem of rare disease early-detection tools. Integrating information-theoretic screening with genomics, machine learning, and clinical workflows could further shorten the diagnostic journey, enabling faster specialist referral and earlier therapeutic intervention. The authors encourage health systems, clinicians, and patient advocacy groups to explore the adoption of proactive rare disease screening – because every year shaved off the diagnostic odyssey has the potential to change a life. The study is available here: https://doi.org/10.1038/s41746-025-02096-x Subscribe to SNOMED International news Stay up to date on SNOMED news, features, developments and newsletters by subscribing to our news service. Subscribe

Termlex Ltd Back Termlex Ltd Vendor Overview Termlex aims to change the way software is used for healthcare. We specialise in supporting organisations with their terminology & coding needs. Our expertise in terminology & interoperability standards like SNOMED CT & FHIR allow doctors and patients to share their health information seamlessly, so they can avoid unwanted investigations/tests, reduce prescribing errors and access relevant information at the right place. Our expertise is based on international experience of implementing healthcare standards and using them in clinical information systems. We work with clients in NHS and across the UK to create software that solves clinical problems. Subscribe to SNOMED International news Stay up to date on SNOMED news, features, developments and newsletters by subscribing to our news service. Subscribe SNOMED CT-enabled solutions Termlex employs world class terminologists and informaticians who are grounded in clinical work and combine many years of experience in curating SNOMED and supporting deployment. We have worked closely with lead clinicians and laboratory information managers to support national catalogues of laboratory test requests and results. We can offer terminology requirements analysis, digital maturity assessments and as part of the Termlex team provide tailored solutions to meet national informatics mandates. We specialise in supporting the implementation of SNOMED CT in clinical information systems and its maintenance in enterprise settings. Our services and products enable our clients to adopt SNOMED CT easily and realise its benefits. Scope of services Analytics, Clinical coding, EHR, Lab, Oncology Downloadable documents Office Spaces - The Porter Building Slough Berkshire SL1 1FQ UnitedKingdom https://termlex.com/ Contact details Jay Kola Director 02032907080 info@termlex.com Regions where operational Europe

Access SNOMED CT, the world’s most comprehensive clinical terminology, through a variety of flexible membership, licensing and fee exemption options. Get SNOMED CT Access the world’s most comprehensive clinical terminology through a variety of flexible membership, licensing and fee exemption options. As a Member or licensee, you join an international community with shared assets, common needs, and a commitment to collaboratively improving the health of people worldwide. Membership Licensing Fee exemptions Contact us Membership SNOMED International is a strong Member-owned and driven organization, having demonstrated growth in Membership each year since inception. Members of SNOMED International can be an agency of a national government, or another body (such as a corporation or regional government agency) endorsed by an appropriate national government authority within the territory it represents. If you are deploying SNOMED CT in a Member country , please register your use with the National Release Center (NRC) of that country (unless your country has MLDS access, when this service should instead be used). SNOMED International does not charge for Affiliate Licensing or for use of SNOMED CT in Member countries. Learn more Licensing SNOMED International does not charge for use of SNOMED CT in SNOMED International Member countries or territories. Charges may apply for affiliate use of SNOMED CT in non-Member territories and are calculated based on use as well as the territory as determined by the World Bank. If you are using and/or deploying SNOMED CT in a non-Member country/territory, you are required to apply for a license through the Member Licensing & Distribution Service (MLDS) on an annual basis. All license holders in non-Member countries or territories are required to submit a Statement of Usage via MLDS on an annual basis. Invoices are issued once annually. Learn more Download the Affiliate License Agreement Fee exemptions Fee exemptions may be applied for SNOMED CT deployments in non-Member territories. Learn more Contact us Do you have questions about SNOMED International membership, licensing or fee exemptions? For a fee calculation or estimate, please contact info@snomed.org with information about your intended use. Other modes of deployment e.g. web applications and browsers, will require special permission and fees applied. Learn more Events Annual Business Meetings, Expo, and SNOMED CT Web Series Learn more Learn more Explore the wide range of resources available to our community of practice Subscribe to SNOMED International news Stay up to date on SNOMED news, features, developments and newsletters by subscribing to our news service. Subscribe

BT Clinical Computing (Global) Back BT Clinical Computing (Global) Vendor Overview BT Clinical Computing aims at structuring the existing data of medical and hospital information systems into a SNOMED CT repository from where the data can be reused for secondary coding (ICD10), data extraction for Patient Summary, Personal Health Record and clinical research. The intelligent SNOMED CT-repository can feed decision support systems and business intelligence. Eighty percent of medical data are in free text…Natural Language Parsing of existing medical reports to SNOMED CT discloses a gold mine of clinical data for further use. Subscribe to SNOMED International news Stay up to date on SNOMED news, features, developments and newsletters by subscribing to our news service. Subscribe SNOMED CT-enabled solutions NLP (Natural Language Processing) from texts to terms SNOMED CT-guided text interface Terminology management system SNOMED CT Big data Repository Code convertor Patient Summary Scope of services Clinical coding, Clinical documentation, EHR, EMR, Middleware Downloadable documents BT Clinical Computing - Brochure BT Clinical Computing - Executive Summary Office BT Clinical Computing SA Av. Paul Pastur 361 Mont-Sur-Marchienne Hainaut 6032 Belgium http://www.btclinicalcomputing.com/ Contact details Thierry Klein CEO +32473944312 thierry.klein@btclinicalcomputing.com Regions where operational Global

SNOMED International and INSERM sign third consecutive collaboration agreement Back 16 Dec 2024 Back SNOMED International and INSERM, the French National Institute of Health and Medical Research , have renewed a collaboration agreement initially established in 2015. The focus of the agreement continues to be on ensuring that rare diseases can be identified and recorded in a standard way globally and this is supported by the inclusion of rare disorders nomenclature content from Orphanet in SNOMED CT. Orphanet, the INSERM unit dedicated to knowledge on rare diseases, maintains the Orphanet nomenclature of rare diseases (ORPHAcodes) and provides a multilingual database of information related to rare diseases and orphan drugs. Orphanet is a network of 40 countries, committed to improving the recognition, information and knowledge to improve rare diseases patients’ lives. The Orphanet nomenclature of rare diseases is a key resource facilitating primary and secondary use of rare disease data supporting care, research and public health. It is the only rare disease specific medical terminology, constantly evolving as knowledge evolves, with the contribution of rare disease experts from around the world. Orphanet operates under the joint authority of the French Ministry of Health and the National Institute of Health and Medical Research. INSERM is a public scientific and technological institute dedicated to biomedical research and human health, including rare diseases, and is involved in the entire range of activities from the laboratory to the patient's bedside and to public health. SNOMED CT is the most comprehensive, multilingual clinical healthcare terminology in the world. It is used in 80 countries, representing a third of the global population. SNOMED International is committed to supporting interoperability across the healthcare sector globally, facilitating terminology integration and improving safe patient care. Effective October 2024, the agreement builds on prior collaboration agreements (2015 and 2020) intended to raise the visibility of rare diseases in terminologies and promote interoperability between organizations and countries using different coding systems. The collaboration has already delivered Orphanet rare disease content into the SNOMED CT International release and a linkage between SNOMED CT and Orphanet. The new collaboration agreement continues the work to maintain and update the alignment between SNOMED CT and Orphanet. In addition, both organisations are committed to supporting those requiring and using rare disease content to facilitate better patient care, precision medicine and research. Implementation is key to enable a global picture of rare diseases to provide understanding and allow improved patient management. “The ongoing renewal of our collaboration with INSERM demonstrates that we are building on a foundation of trust and achievement that has successfully delivered SNOMED CT content and product improvement,” said SNOMED International CEO Don Sweete. “We look forward to another five years of successfully working together to achieve our mutual goals to globally improve and transform healthcare delivery for patients and clinicians in the rare diseases domain.” Katrien Scheerlinck, Senior Expert Health Standards at the Belgium National Release Centre, said, “The integration of rare diseases concepts from Orphanet offers a significant administrative simplification in our case. What currently requires additional administrative resources can now automatically flow into our scientific registers and statistics. Academic hospitals and research centres are extremely enthusiastic about this forward-looking solution and simplification." Theresa Barry, Clinical Terminology Architecture Lead, (Téarmaíocht Chliniciúil Ceannaire Ailtireachta), Ireland said, “Having the Orphanet codes in SNOMED made available with a mapping file is going to be transformational for the collection of data for rare diseases, allowing registries and statistics to seamlessly flow data that will benefit patients and researchers. This approach is widely acknowledged as being progressive and beneficial, to all stakeholders.” “This renewed collaboration with SNOMED International aligns with Orphanet’s strategy of contributing to the creation of an interoperable rare disease data ecosystem. ORPHAcodes are the common language between countries and between sectors, for a better recognition of rare diseases, data production and knowledge generation, bringing health data to registries and data spaces. This cannot be achieved without the sustained collaboration with SNOMED since 2015, a collaboration of which we are proud,” said Dr Ana Rath, Orphanet Director. Media Inquiries Inserm, US14 - Orphanet Charlotte Rodwell Email: media.orphanet@inserm.fr SNOMED International Kelly Kuru Email: comms@snomed.org Subscribe to SNOMED International news Stay up to date on SNOMED news, features, developments and newsletters by subscribing to our news service. Subscribe

SNOMED CT and Covid-19 SNOMED CT and COVID-19 Our actions to support our Community of Practice during the global Coronavirus (COVID-19) pandemic. Read about the challenge COVID-19 content in SNOMED CT In cases where a global emergency persists and warrants action, SNOMED International has taken steps to issue an interim release of the SNOMED CT International Edition to serve a public good. Here you can review the current SNOMED CT content applicable to COVID-19, including an updated SNOMED CT to ICD-10 map. Please refer to your local National Release Center (NRC) for updates to local extensions. SNOMED CT COVID-19 & Related Content The SNOMED CT International Edition contains all relevant COVID-19 concepts including any applicable changes to descriptions. Access SNOMED CT COVID -19 content SNOMED CT and COVID-19 news updates Review recent news items about how SNOMED International is equipping our Members, affiliates and users globally to manage the current pandemic with SNOMED CT terminology. See latest news Support Our help desk team is located across several time zones. We respond to each inquiry quickly and efficiently, passing them to specialists as required. You will receive a notification that your question has been logged. This will be followed by a reply, made at the earliest opportunity. Submit inquiry Learn more Learn more Explore the wide range of resources available to our community of practice Learn more COVID-19 and the GPS Coronavirus content added to the Global Patient Set Learn more COVID-19 Interoperability Alliance SNOMED CT joins the Alliance Learn more Coronavirus descriptions Changes to concept descriptions related to COVID-19 (Feb 2020) Subscribe to SNOMED International news Stay up to date on SNOMED news, features, developments and newsletters by subscribing to our news service. Subscribe

AMA and SNOMED International announce the validation of new SNOMED CT and CPT cross maps Back 28 Mar 2022 Back Since the date of issue, this information is now out of date and has been archived. It has been made available for reference. The American Medical Association (AMA) and SNOMED International announce the validation of the AMA’s Current Procedural Terminology (CPT ®) to SNOMED CT® cross maps. This validation exercise is the latest in a series of steps to enhance the bi-directional, rules-based cross maps that deliver better data transparency to enable heath systems to pinpoint efficiencies along care pathways and optimize resource utilization management to achieve better health outcomes. Tighter integration of the AMA’s CPT ® to SNOMED CT brings the power of two global medical terminologies to health systems seeking to gain resource utilization insights, administration analytics and physician compensation data linkage to their clinical documentation. Health systems deploying SNOMED CT will be able to leverage these connections to CPT content and unlock answers from their onslaught of complex clinical data more easily. The collaboration between AMA and SNOMED International aims to improve integration between the CPT and SNOMED CT terminologies by producing solutions for governments, hospitals, clinical practices, researchers and other stakeholders to help organize and utilize healthcare data better. As both terminologies continue to evolve to keep pace with modern medicine, they agree that an increasingly common medical language elevates the potential for even more medical innovation around the globe. The AMA and SNOMED International plan is to continue make health data enhancements to support medical innovation and use-case changes. Both organizations encourage health care stakeholders to join our conversation to share the new ideas, to explore new data paths and to evaluate how the combined terminologies can be used best to drive more value to their health care systems. “Health systems as a whole, require health-related data standards that are credible, comprehensive, and developed using collaborative, rigorous, and evidence-based processes,” said the AMA’s Lori Prestesater, Vice President of Health Solutions. “The AMA’s collaboration with SNOMED supports the shift to digitization and will help the healthcare industry optimize resources and increase efficiencies as it works towards achieving better patient outcomes, and improved patient and clinician experiences, all at a lower cost.” “As we continue to observe, there are many moving parts to achieving optimal information flow, data quality, and user satisfaction across regional, national and international healthcare systems,” offers Don Sweete, SNOMED International CEO. “Fulfilling a strategic objective to facilitate and integrate terminology standards and classifications, our ongoing mapping and validation activities with AMA is a prime example of two organizations working together to enhance and streamline the health and care ecosystem for the benefit of users and care recipients.” Both organizations are dedicated to the pursuit of unambiguous exchange of clinical information. Together, they seek to address the health system’s emerging need for greater integration in support of interoperability as well as health and resource data analytics. Subscribe to SNOMED International news Stay up to date on SNOMED news, features, developments and newsletters by subscribing to our news service. Subscribe

Accessing pathology cancer data within and across healthcare institutions is problematic. Manual curation of large quantities can take years. Factors including lack of normalization of grading and staging systems and non-standard narrative reporting formats hinder easy access to the data. However, these data could become readily available for research using newly published SNOMED CT content developed specifically for use in structured pathology reporting using data elements from the College of American Pathologists (CAP) Cancer Protocols and the International Collaboration on Cancer Reporting (ICCR) datasets . As a demonstration of the power of using SNOMED CT to create an interoperable data repository across multiple institutions, encoded cancer pathology reports and ancillary data for resections of invasive cancer of the breast following administration of neoadjuvant therapy were combined from two large academic medical centers[ME1] for 2021- present. Extracted data included histologic type, biomarker profile, grade, and pathologic assessment of the response to therapy for the tumors. These data were stored in a repository structured on the Observational Medical Outcomes Partnership (OMOP) model for further analysis. This presentation establishes a reproduceable methodology that can be used to extract, combine and represent pathology data from two separate EHR systems for subsequent analysis. Back View Map College of American Pathologists SNOMED CT encoded pathology breast cancer data to determine pathological response to neoadjuvant therapy Read More Country / Region Americas Tags Clinical Practice, Data analytics, Implementation, Research Accessing pathology cancer data within and across healthcare institutions is problematic. Manual curation of large quantities can take years. Factors including lack of normalization of grading and staging systems and non-standard narrative reporting formats hinder easy access to the data. However, these data could become readily available for research using newly published SNOMED CT content developed specifically for use in structured pathology reporting using data elements from the College of American Pathologists (CAP) Cancer Protocols and the International Collaboration on Cancer Reporting (ICCR) datasets . As a demonstration of the power of using SNOMED CT to create an interoperable data repository across multiple institutions, encoded cancer pathology reports and ancillary data for resections of invasive cancer of the breast following administration of neoadjuvant therapy were combined from two large academic medical centers[ME1] for 2021- present. Extracted data included histologic type, biomarker profile, grade, and pathologic assessment of the response to therapy for the tumors. These data were stored in a repository structured on the Observational Medical Outcomes Partnership (OMOP) model for further analysis. This presentation establishes a reproduceable methodology that can be used to extract, combine and represent pathology data from two separate EHR systems for subsequent analysis. Description The project addresses the value of electronic SNOMED CT encoding of histopathology in the medical record (EHR) to support cancer research within an institutional agnostic paradigm. Evaluation of response to neoadjuvant therapy for breast cancer is the exemplary objective. Scope SNOMED CT is the sole international terminology standard that can represent structured pathology cancer data. How SNOMED CT will be used SNOMED CT is explicitly used to represent and normalize discrete data from surgical pathology reports for cancer retrieved from the EHR to support clinical research. Why SNOMED CT will be used Contact More information Learn more Get SNOMED CT Information about our license and fee structure Learn more Learn more Explore the wide range of resources available to our community of practice Subscribe to SNOMED International news Stay up to date on SNOMED news, features, developments and newsletters by subscribing to our news service. Subscribe

SNOMED International provides online courses, tutorials and learning pathways that help to extend your knowledge and understanding of SNOMED CT. Education SNOMED International provides online courses, tutorials and learning pathways that help to extend your knowledge and understanding of SNOMED CT SNOMED CT courses and certification SNOMED International offers a range of education courses and certification exams. Our courses provide a structured learning program for beginners through to advanced users of SNOMED CT, while our certification allow individuals to be recognized for their capabilities in specific skill areas. To apply for one of our courses or register for a certification exam, please visit our SNOMED CT Course Catalog. Course catalog SNOMED CT e-learning services To access these services please visit the SNOMED CT E-Learning Platform. SNOMED CT e-learning platform SNOMED CT starter tutorials The SNOMED CT Starter Tutorials provide an introduction to the key benefits and features of SNOMED CT. You can access these tutorials without creating an account on the E-Learning Platform. Starter tutorials SNOMED CT presentation library The SNOMED CT Presentation Library allows you to view a wide range of SNOMED CT education presentations. To access this service, please visit the Presentation Library. Presentation library Learn more Events Annual Business Meetings, Expo, and SNOMED CT Web Series Learn more Get SNOMED CT Information about our license and fee structure Learn more Get involved Find out how you can get involved Learn more Document library Access overviews, guides and specifications Subscribe to SNOMED International news Stay up to date on SNOMED news, features, developments and newsletters by subscribing to our news service. Subscribe Courses and certification E-learning services Starter tutorials Presentation library