Andorrà takes big step towards interoperability with SNOMED CT adoption Back 15 Jun 2023 Back SNOMED International has welcomed Andorra, a small, mountainous European country situated between France and Spain to its growing global organization. Andorra will join a vibrant community of 47 Members globally. Andorra will be represented at SNOMED International by Andorran Health Care System ( Servei Andorrà d’Atenció Sanitària , SAAS.) SAAS is a para-public management health system with regulated agreements and financing subsidized by social security through co-payment. It administers and manages the country’s publicly administered and funded healthcare resources, including one hospital, 11 primary care centres, a nursing home, and a school health service. With a population of just under 80,000, Andorra’s official language is Catalan. Andorra has embarked on a digital transformation project with the goal of digitizing services across the entire government and its national health system. This project highlights the need to take a comprehensive, intersectoral and interdisciplinary approach to health care, ensure better patient outcomes, and consolidate the system. Andorra is in the process of creating interoperable frameworks that support the meaningful sharing of health information. The adoption and use of standard terminologies within the electronic health record (EHR) are fundamental to these movements. Andorra’s health service began its digital journey in 2004 with a project to create an EHR system. Since 2017, according to law, all healthcare centers and professionals that are part of the public health system must report to the EHR the actions carried out on behalf of patients and, in general, all the other annotations that must be made to the EHR. The country’s National 2020 Health Plan highlights the need to build a national patient-centered digital health system. Andorra’s adoption of SNOMED CT aligns with and supports its digital transformation goals. SNOMED CT, a comprehensive, multilingual healthcare terminology, captures the care of individuals in an EHR and facilitates sharing, decision support and analytics, to support safe and effective health information exchange. “Andorra as a country is pleased to be a SNOMED International Member,” said Helena Mas Santuré, Andorra’s Health Minister. “We are looking to strengthen our health system and now our efforts are focused on digital transformation, because we are completely convinced that this step is essential in the development of an up-to-date efficient health system.” We are equally excited to welcome Andorra to SNOMED International, said SNOMED International CEO Don Sweete, adding, “We look forward to working with the country to implement SNOMED CT. Andorra’s commitment to making interoperability a key enabler across the entire government gives the country a leg up in terms of understanding the benefits of an international healthcare standard such as SNOMED CT and will serve as a guiding beacon as they implement and adopt the clinical terminology.” Visit Andorra’s Member page on the SNOMED International website to view the country’s representatives to the Member Forum and the General Assembly. Media inquiries Andorra: Silvia Bonet Perot Email: sbonet@saas.ad Maria Rendon Email: maria_rendon@govern.ad Rosa Vidal Email: Rosa_Vidal@govern.ad Kelly Kuru SNOMED International Email: comms@snomed.org

The healthcare landscape is increasingly witnessing the transformative potential of generative artificial intelligence (AI) across various applications, including the automation of clinical documentation and the enhancement of patient communication. Recent advances in large language model (LLM) architectures and transformer based sequence forecasting have opened new perspectives for longitudinal clinical decision support (CDS). However, a significant impediment to achieving equitable and effective healthcare delivery, particularly within the realm of AI applications, lies in the inherent linguistic diversity of global populations. This diversity encompasses not only the multitude of languages spoken worldwide but also the variations within those languages, including dialects and culturally specific expressions (i.e. practice). Generative AI models, often trained predominantly on English language data, frequently encounter difficulties in accurately processing and understanding different languages and their nuances. This limitation can lead to inaccurate translations, misinterpretations of critical medical information, and ultimately, the exacerbation of existing health disparities among different linguistic communities. This project explore the features and capabilities of SNOMED CT in the context of using LLMs and elucidate how they can effectively address the challenges posed by linguistic diversity in the application of generative AI within clinical practice, ultimately fostering more inclusive and accurate healthcare solutions. The presentation will demonstrate how the Foresight Timeline generation tool [i] using synthetic patient data based on various instances of the SNOMED Basic Synthetic Patient Data Generator (BSPG)[ii] performs with various AI models and languages (editions of SNOMED CT). [i] Foresight: https://foresight.sites.er.kcl.ac.uk/ [ii] BSPG: https://github.com/IHTSDO/health-data-analytics/blob/ui-prototyping/generator/README.md#basic-synthetic-patient-data-generator Back View Map Sorano.net SNOMED CT: Bridging language differences between training and querying AI models for healthcare Read More Country / Region EMEA Tags Artificial intelligence, Clinical Practice, Data analytics, Global/International, Implementation, Tooling The healthcare landscape is increasingly witnessing the transformative potential of generative artificial intelligence (AI) across various applications, including the automation of clinical documentation and the enhancement of patient communication. Recent advances in large language model (LLM) architectures and transformer based sequence forecasting have opened new perspectives for longitudinal clinical decision support (CDS). However, a significant impediment to achieving equitable and effective healthcare delivery, particularly within the realm of AI applications, lies in the inherent linguistic diversity of global populations. This diversity encompasses not only the multitude of languages spoken worldwide but also the variations within those languages, including dialects and culturally specific expressions (i.e. practice). Generative AI models, often trained predominantly on English language data, frequently encounter difficulties in accurately processing and understanding different languages and their nuances. This limitation can lead to inaccurate translations, misinterpretations of critical medical information, and ultimately, the exacerbation of existing health disparities among different linguistic communities. This project explore the features and capabilities of SNOMED CT in the context of using LLMs and elucidate how they can effectively address the challenges posed by linguistic diversity in the application of generative AI within clinical practice, ultimately fostering more inclusive and accurate healthcare solutions. The presentation will demonstrate how the Foresight Timeline generation tool [i] using synthetic patient data based on various instances of the SNOMED Basic Synthetic Patient Data Generator (BSPG)[ii] performs with various AI models and languages (editions of SNOMED CT). [i] Foresight: https://foresight.sites.er.kcl.ac.uk/ [ii] BSPG: https://github.com/IHTSDO/health-data-analytics/blob/ui-prototyping/generator/README.md#basic-synthetic-patient-data-generator Description This project aims to provide a framework to asses how SNOMED CT can contribute to semantic interoperability with generative AI. Overcoming the challenges posed by linguistic diversity in the application of generative AI within clinical practice (precision). Scope SNOMED CT (Systematized Nomenclature of Medicine – Clinical Terms) emerges as a comprehensive, standardized, and inherently multilingual clinical terminology system. Recognized as the most comprehensive clinical vocabulary available in any language, SNOMED CT holds substantial promise in acting as a bridge by providing a common semantic framework that transcends the barriers of different languages models. How SNOMED CT will be used To generate synthetic data for training or testing of the NLP pipeline (generative models). 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

The Canadian Institute for Health Information (CIHI) and Canada Health Infoway are partnering to modernize health information flows and create a connected health system in Canada. Early progress toward this goal was delivered in CIHI's published draft Version 1 of the Pan-Canadian Health Data Content Framework (PCHDCF). The PCHDCF is a comprehensive data content standard with common data architecture for all health-related data. Its core subset of essential data required for interoperability is known as the Canadian Core Data for Interoperability (CACDI). Health systems need standardized and disaggregated social data to implement systemic changes that advance health equity. Behavioural health data allow for holistic patient care in realms of prevention, risk management, and tailored interventions. Through a co-design process, CIHI is leading development of social care data elements and their value sets with logical data models, for representing sociodemographic, social determinants of health and behavioural health domains. This builds on CIHI's previous equity-focused data standards work and with reference to other international guiding standards. New SNOMED CT CA concepts and synonyms are being requested to fulfill Canadian context requirements. These new concepts can be elected for SNOMED CT International versions, thereby strengthening the coverage of SNOMED CT terms in the social and behavioural health domain for the entire SNOMED CT community to benefit from. Social and behavioural health-focused data content standards developed within the Connected Care initiative allow for meaningful information exchange across clinical and social care systems enabling patient-centred and equity-based care and which can be leveraged internationally. Back View Map Canadian Institute for Health Information (2 of 2) Developing Standard Terminology for Social Care in Support of Connected Care in Canada Read More Country / Region Americas Tags Clinical Practice, Collaboration, Data quality, Mapping The Canadian Institute for Health Information (CIHI) and Canada Health Infoway are partnering to modernize health information flows and create a connected health system in Canada. Early progress toward this goal was delivered in CIHI's published draft Version 1 of the Pan-Canadian Health Data Content Framework (PCHDCF). The PCHDCF is a comprehensive data content standard with common data architecture for all health-related data. Its core subset of essential data required for interoperability is known as the Canadian Core Data for Interoperability (CACDI). Health systems need standardized and disaggregated social data to implement systemic changes that advance health equity. Behavioural health data allow for holistic patient care in realms of prevention, risk management, and tailored interventions. Through a co-design process, CIHI is leading development of social care data elements and their value sets with logical data models, for representing sociodemographic, social determinants of health and behavioural health domains. This builds on CIHI's previous equity-focused data standards work and with reference to other international guiding standards. New SNOMED CT CA concepts and synonyms are being requested to fulfill Canadian context requirements. These new concepts can be elected for SNOMED CT International versions, thereby strengthening the coverage of SNOMED CT terms in the social and behavioural health domain for the entire SNOMED CT community to benefit from. Social and behavioural health-focused data content standards developed within the Connected Care initiative allow for meaningful information exchange across clinical and social care systems enabling patient-centred and equity-based care and which can be leveraged internationally. Description Work on the Pan-Canadian Health Data Content Framework includes defining social and behavioural health (lifestyle) data standards. Disaggregated socio-demographic and social risk and needs data allows for tailoring of patient specific health interventions. This will also provide an opportunity to aggregate data to measure health inequities affecting communities and populations to support systemic improvements. Structured data value sets are being adopted, adapted from other published standards or created anew where gaps exist. Value sets selected for representing data elements within social and behavioural domains are composed of SNOMED CT CA, LOINC, ICD-10-CA and HL7 codes. All value set work is driven by consensus with inputs from technical and terminological expertise and external consultation with clinicians, patients, policy makers, and researchers. Value sets are published and maintained on the Canada Health Infoway's FHIR Terminology Server (OntoServer). In the next draft publication of the Pan-Canadian Health Data Content Framework (Sep 2025) we aim to develop Canadian-context value sets for: * sociodemographic data elements such as race, ethnicity, Indigenous identity, gender, service language and for assessment of SDOH data elements such as housing stability, education attainment, access to food and access to transportation). * Behavioural health (lifestyle) risk assessment domains such as tobacco, vaping, alcohol and other substance use * social risk and social need assessment such as housing stability, educational attainment, income, access to food, transportation, utilities Future development work will define and develop standardized value sets for social care related diagnosis, patient goals and interventions. Scope SNOMED CT is being used for its foundation as an international clinical reference terminology that allows for the development of value sets that will standardize data collection and facilitate interoperability. For the purpose of the Pan-Canadian Health Data Content Framework, the Canadian edition of SNOMED CT CA is used to ensure the availability of Canadian specific content. This is in alignment with our national setting and context and encourages reuse of these optimized terms across different domains and settings across Canadian jurisdictions. How SNOMED CT will be used Several value sets composed of SNOMED CT CA concepts are being leveraged for the PCHDCF. Value set development includes adopting or adapting published value sets or composing new value sets where gaps are identified. Through a Request for Change process, new SNOMED CT CA concepts and/or synonyms are being requested to fulfill Canadian context requirements. This new SNOMED CT CA content can be potentially elected for SNOMED CT International versions. In this process we are strengthening the coverage of SNOMED CT terms in the social and behavioural health domain for the entire SNOMED CT community to benefit from. 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

SNOMED International SIGs embrace clinical engagement with Clinical Reference Groups Back 13 Apr 2017 Back For more information on SNOMED International's Clinical Reference Groups, please review our clinical resources . To enable continuous development of SNOMED CT, it is critical that its clinical content is relevant and up to date. To do this, SNOMED International relies on input from clinicians and clinical groups internationally. Given the significance of this relationship, SNOMED International, in consultation with its Healthcare Professional Coordination Group, made a decision to cease using the existing Special Interest Groups (SIGs) approach for clinical engagement along with a move to a virtually supported model. All clinical engagement activities undertaken by SNOMED International’s Clinical Engagement Team will flag prospective contributing contacts to a relevant Virtual Clinical Group. Why should clinicians continue their contributions as SIGs transition to Clinical Reference Groups? Engaging via Clinical Reference Groups provides clinicians with a mechanism to ensure that the content required by clinicians is included in SNOMED CT quickly and accurately. The Clinical Reference Groups model supports collaborations with external partners (professional groups and organizations, etc.) through the use of project groups where the collaboration has a specified deliverable, before transitioning to an editorial group to provide ongoing clinical validation. The model of Clinical Reference Groups will also support specifically focused work, bringing together groups with a common interest such as developing or migrating to a SNOMED CT based registry that is needed internationally. The SIGs will formally retire April 13, 2017 with the launch of the Clinical Reference Groups. Please visit the Clinical Participation homepage to learn more, or email info@snomed.org with your questions regarding approach and participation.

SNOMED International Welcomes Cyprus to the Global SNOMED CT Community Back 6 Sept 2018 Back London, United Kingdom, Sept. 06, 2018 (GLOBE NEWSWIRE) -- The Cyprus Ministry of Health and SNOMED International jointly announce the addition of Cyprus as the organization’s thirty-fourth Member. With a developing e-health program across the country’s hospital and health center landscape, Cyprus joins SNOMED International to bring structure and consistency in the sharing of health information for patient care, clinical decision support and research purposes. Within the European region, the promise of cross-border care mobility is believed to be the single most important revolution in healthcare. Preserving the sanctity of patient information through structured data becomes critical to this vision. SNOMED CT is the world’s most comprehensive and precise health terminology. Founded in 2007 by nine charter nations, SNOMED International is a not-for-profit, member-owned and driven international organization. “SNOMED CT is a core element in building a platform for accurate clinical information exchange and data analysis and SNOMED International applauds Cyprus’s commitment to this vision” states SNOMED International’s CEO, Don Sweete. “With the increasing need to support cross-border health, SNOMED CT is positioned as the best available core reference terminology for cross-border, national and regional eHealth deployments in Europe.” In recent years, Cyprus is dynamically entering the eHealth era. Codification is an essential part of this journey as health information should be captured, monitored, analyzed and disseminated among health professionals, health policy makers, and the public. Taking part in the European ‘eHealth Network’ project to establish cross border health care, of which the dominant terminology used is SNOMED CT, further supports the need for codification. Through this project, Cyprus has seen this as an opportunity to expand our codification horizons. For this reason, we joined SNOMED CT as a member country, in order to be able to promote health information coding, in a unifying way, among different local health software. The aim of which is to better guide our understanding and comparability of existing health information data. Vasos Scoutellas, Coordinator of the Health Monitoring Unit of the Ministry of Health recognizes the value of membership in SNOMED International for Cyprus. “At the Health Monitoring Unit of the Ministry of Health of Cyprus, myself, as the coordinator, and my colleagues, fully endorse the promotion, adoption and deployment of SNOMED CT in the health system of Cyprus. With its use, as a country, we will have a uniform way of documenting health issues. This will help us to have better and comparable statistics within the country.” Cyprus becomes the 21st Member in the European, Middle East and African region to join SNOMED International, setting the expectation for increased interoperability as well as the promise of leveraging learnings amongst its regional and international counterparts. SNOMED CT becomes part of the Cyprus national infrastructure to ensure the exchange of accurate, relevant and timely information across all the information systems to support direct care, self-care and secondary uses of health information.

Apelon, Inc. Back Apelon, Inc. Vendor Overview Apelon is an international informatics company offering professional services and software for terminology creation, deployment, mapping and maintenance. As terminology creation gives way in the marketplace to terminology deployment, our focus is on helping enterprises use their terminologies and their homegrown or third-party software to improve health and health care delivery. We've been working with controlled vocabularies for more than 20 years, and our consulting team boasts two SNOMED Consultant Terminologists and a SNOMED Implementation Advisor. SNOMED CT-enabled solutions Every project we undertake at Apelon considers SNOMED CT! Apelon's open source DTS terminology server (http://apelondts.org ) is used for terminology managements by governments, providers, pharmaceutical companies, EHR vendors and starving students for its easy-to-use interface and powerful APIs (Java, SOAP, FHIR). Scope of services Analytics, Chronic disease, Clinical coding, Clinical documentation, Diagnostic imaging, Drug, EHR, EMR, Lab, Middleware, Oncology, Order sets, Pharmacy, Telehealth Downloadable documents Office 750 Main Street, Suite 1500 Hartford CT 06103 USA http://www.apelon.com Contact details John S. Carter Vice President, Sales and Services +1 801 953 9815 sales@apelon.com Regions where operational Africa, Asia, Europe, Global, North America, Oceania, South America

The newly released 2023 Products & Services Catalog provides a complete list of our clinical terminology products, including tools, supporting services, and education. 2023 Products & Services Catalog features expanded implementation support services updated tooling The newly released 2023 Products & Services Catalog provides a complete list of our clinical terminology products, including tools, supporting services, and education. Back 19 Jan 2023 Back Each January, we publish an updated catalog of our SNOMED CT related products and services. The recently released 2023 Products & Services Catalog provides an overview of SNOMED International and our customers and stakeholders, and a comprehensive list of our clinical terminology products, including tools, supporting services and education. The document also includes a section on the value of SNOMED CT, with links to additional information such as case studies and videos. Available online and as a downloadable PDF file, the catalog features a section guiding you to the content most relevant to you, whether you are a new or long-term Member, an implementer in a non-Member country, a vendor, a clinician or part of one of our other stakeholder groups. It also highlights our global customer and stakeholder team available to support the use of SNOMED CT. What’s new this year? This year’s catalog features an expanded section outlining our implementation services, a reflection of the organization’s increased efforts on supporting Members throughout their entire implementation journey. The tooling section, which encompasses the software and services SNOMED International offers, is also more extensive and detailed than in last year’s catalog. Get involved Interested in learning more about or participating in our ever-expanding community of practice? Check out the link on the back cover, which takes you to our website listing the many opportunities SNOMED International offers to learn more about and participate in the development, improvement and maintenance of SNOMED CT, such as in a clinical reference or project group, or as a participant in our clinical, research and implementation webinar series or at other SNOMED International events, such as our yearly Expo and twice-yearly business meetings. “SNOMED International provides a wealth of information, learning resources, tools and documentation, all designed to support users wherever they are now and wherever they are headed in their SNOMED CT journey,” explains SNOMED International Chief Customer Officer Shelley Lipon. “Our Products & Services Catalog helps all our stakeholders better understand what is available to them and where to find those resources. It’s also exciting to see how the document continues to grow and further support all our stakeholders each year.”

High-quality clinical terminologies are essential for a connected and efficient healthcare ecosystem. Previous studies have shown the impact of quality issues on downstream applications, such as reduced recall and precision in cohort queries over EHRs. The literature presents several proposals to detect and/or resolve these quality issues. While these proposals typically employ either a lexical, structural, or machine learning-based approach, some combine different techniques to address the issues. This presentation outlines a series of experiments we conducted to improve the quality and clinical accuracy of the SNOMED CT terminology by identifying key areas for enhancement and proposing AI-enabled methods to automate the detection and correction of structural anomalies, such as primitive, misaligned, missing, and redundant concepts. Back View Map IQVIA Addressing SNOMED CT Structural Anomalies Through AI -Enabled Methods Read More Country / Region EMEA Tags Artificial intelligence, Data quality, Research High-quality clinical terminologies are essential for a connected and efficient healthcare ecosystem. Previous studies have shown the impact of quality issues on downstream applications, such as reduced recall and precision in cohort queries over EHRs. The literature presents several proposals to detect and/or resolve these quality issues. While these proposals typically employ either a lexical, structural, or machine learning-based approach, some combine different techniques to address the issues. This presentation outlines a series of experiments we conducted to improve the quality and clinical accuracy of the SNOMED CT terminology by identifying key areas for enhancement and proposing AI-enabled methods to automate the detection and correction of structural anomalies, such as primitive, misaligned, missing, and redundant concepts. Description The experiments we carried out aimed to address structural anomalies, such as primitive, misaligned, missing, and redundant concepts. Primitive concepts are those not fully defined by necessary conditions, making it impossible to automatically classify them or their subtypes into the hierarchy unless a sufficient condition exists for that concept. Intermediate primitives serve as both parents and children within the hierarchy, posing a challenge due to the manual effort they require. Misaligned concepts arise when the modelling of concepts does not follow the template for that sub-hierarchy, likely indicating inconsistent modelling within a sub-hierarchy. The missing concept anomaly refers to gaps where certain concepts that should logically exist within the hierarchy are absent, hindering accurate data representation and retrieval. The redundant concept anomaly occurs when multiple concepts essentially represent the same clinical idea, causing confusion among users, increasing clinical data fragmentation, and complicating the aggregation and analysis of information, along with the extra effort needed to maintain and update the terminology. Our experiments explored AI-enabled approaches, combined with lexical and logical-based techniques, to enhance the quality and clinical accuracy of the SNOMED CT terminology by identifying key areas for improvement and methods to automate the detection and correction of structural anomalies. The presentation will detail these approaches, the methods applied, the tools used, the outcomes achieved, and the lessons learned from the experimentation. A guideline for applying the more promising methods in real-world terminology authoring will also be outlined to conclude. Scope SNOMED CT is a widely used, multilingual clinical healthcare terminology that standardizes medical terms in electronic health records (EHRs). It enables healthcare providers to accurately document patient conditions, treatments, and outcomes using standardized terms, ensuring consistent recording and understanding of clinical information across various systems and locations. This standardization supports the seamless exchange of health information between healthcare providers and systems, facilitating coordinated patient care and public health reporting. Researchers also benefit, as it allows them to query and analyse large datasets of clinical information, leading to more reliable research outcomes through precise cohort identification and data analysis. Meanwhile, previous studies have shown the impact of quality issues on downstream applications. In conclusion, SNOMED CT is the perfect candidate for evaluating new techniques to address quality issues, given its comprehensiveness and crucial role in healthcare. How SNOMED CT will be used The SNOMED CT clinical terminology was chosen as the focus of our experiments aimed at assessing AI-driven methods to enhance its quality and clinical accuracy by automating the detection and correction of structural anomalies. 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

SNOMED International announces cancellation of 2020 April Business Meetings Back 9 Mar 2020 Back SNOMED International extends our thanks to you for your patience as we have continued to monitor the developing situation with COVID-19 (coronavirus). Made apparent by recent reports from the World Health Organization and the Centers for Disease Control and Prevention, there is no doubt that the virus continues to spread globally. In collaboration with the General Assembly Executive, the organization has been constantly involved in discussion over the past few weeks regarding the present situation. We have now made the difficult decision to cancel the face to face 2020 April Business Meetings to protect the health of our Community and do our part to prevent the spread of this outbreak. In place of the Community Updates session, we will provide you with a document outlining the headlines from the organization since October 2019 that you can review and then pose your follow up questions with organization representatives. While we are not rescheduling these meetings, we will support meetings to go ahead virtually where possible and be in touch with relevant participants. At this point, we plan to next convene face to face in Portugal, October 2020. We thank you for your ongoing support and encourage you to reach out to us with any questions or inquiries you have as a result of this decision.

Croatia's representative to SNOMED International is the Croatian Ministry of Health Croatia Croatia's representative to SNOMED International is the Croatian Ministry of Health Contact Details Croatian Ministry of Health Website: https://zdravstvo.gov.hr Email: pitajtenas@miz.hr Appointed Representatives General Assembly: Srebrenka Mesić Member Forum: Andreja Matkun, Višnja Antolković Ilić News articles Croatia prioritizes the quality and structure of ehealth data with SNOMED membership With a population of nearly 4 million, Croatia is the latest European country to join SNOMED International since the March 2022 announcement that the European Union (EU) will provide its Member States with 60 per cent funding towards SNOMED International membership until 2027, via the European Health and Digital Executive Agency (HaDEA). “Highly developed with a fully integrated, globalized economy, Croatia made eHealth a priority in its 2021-2027 national health development plan , which is consistent with our comprehensive healthcare reform," says Croatian health Minister Vili Beroš on the occasion of Croatia joining SNOMED International. The goals of the strategy include 36 measures in five categories: improved healthy lifestyles and more effective disease prevention; improvement of the health system; improvement of the model of care for key health challenges; making the health system a desirable place to work; and improving the financial sustainability of the health system. Learn more about the Croatian Ministry of Health's SNOMED CT approach. Back Learn more Global Patient Set Built from the globally recognized SNOMED CT terminology standard at no cost to users Learn more Get SNOMED CT Information about our license and fee structure Learn more Software and tools We develop and operate applications platforms to support our products and services Learn more Document library Access overviews, guides and specifications

Bart de Witte Opening Keynote Speaker Bart de Witte Keynote Speaker October 27, 2023 (09:00-10:00 EDT/ 13:00-14:00 UTC) (Sponsored by Clinical Architecture ) Dr. Campbell is the program director of the US Food and Drug Administration’s (FDA) Systemic Harmonization and Interoperability Enhancement for Laboratory Data (SHIELD) program – a public- private collaboration that was assembled in 2015 with a focus: improving the interoperability and utility of diagnostic data by “Describing the same test the same way anywhere in the Healthcare ecosystem”. Before joining FDA full-time, Dr. Campbell worked as Assistant National Director of Informatics for Kaiser Permanente, and as Director of Informatics Architecture for the US Department of Veterans Affairs (VA). With nearly 30-years of experience working in medical informatics and terminologies for encoding clinical data, Dr. Campbell has dedicated his career to improving clinical data representation and patient safety outcomes through the engineering of safer healthcare systems. Dr. Campbell’s dissertation work at Stanford University created the modern architecture for SNOMED, where he worked in collaboration with Kaiser Permanente and the College of American Pathologists to develop SNOMED RT. SNOMED RT was subsequently merged with the NHS Clinical Terms to form SNOMED CT in 2002. Dr. Campbell continued his involvement with SNOMED for over two decades in various roles, including as chair of the technical committee, and as a member of other editorial committees and groups. Dr. Campbell holds an MD from the University of Southern California and while completing his residency in Internal Medicine, obtained his PhD in Computer Science & Medical Informatics from Stanford University. Dr. Campbell’s work has received industry-wide recognition, including three FedHealthIT Innovation Awards, a FedHealthIT VA Hero of the week award, and the 2018 Open-Source Electronic Health Record Alliance (OSEHRA) Lifetime Achievement Award. Twitter handle: @kec4saferhealth Back

Information models define the logical structure of data, information, and knowledge, and include explicit bindings of standard codes to nodes in the data structure. Experience has shown that both the logical structure and the codes are necessary to allow unambiguous and computable representation of real world data. Because information models are logical models, they are independent of any specific data exchange syntax, and they can be used to automatically generate exchange formats like HL7 V2.X, HL7 C-CDA, and HL7 FHIR. Standard codes are bound to nodes in the data structure, and the meaning of a given code inherits context from its containing model. For instance, if a code for serum glucose concentration is used in an order model it means that a glucose measurement is requested, whereas, if the same code is used in a result model, it is the name of the result of the measurement. Using information models can dramatically reduce the number of codes in a terminology system because it prevents the creation of highly pre coordinated codes; post coordination of more generic codes can be used instead. This session will provide the basics of information modeling, explain its benefits, and provide an introduction to information modeling activities like openEHR, the HL7 Clinical Information Modeling Initiative, and the Graphite S2 approach. Back View Map Regenstrief - LOINC Information Models and Terminology: Two Essential Elements of Semantic Interoperability Read More Country / Region Americas Tags Implementation, Innovation, Mapping, Pre/postcoordination, Research Information models define the logical structure of data, information, and knowledge, and include explicit bindings of standard codes to nodes in the data structure. Experience has shown that both the logical structure and the codes are necessary to allow unambiguous and computable representation of real world data. Because information models are logical models, they are independent of any specific data exchange syntax, and they can be used to automatically generate exchange formats like HL7 V2.X, HL7 C-CDA, and HL7 FHIR. Standard codes are bound to nodes in the data structure, and the meaning of a given code inherits context from its containing model. For instance, if a code for serum glucose concentration is used in an order model it means that a glucose measurement is requested, whereas, if the same code is used in a result model, it is the name of the result of the measurement. Using information models can dramatically reduce the number of codes in a terminology system because it prevents the creation of highly pre coordinated codes; post coordination of more generic codes can be used instead. This session will provide the basics of information modeling, explain its benefits, and provide an introduction to information modeling activities like openEHR, the HL7 Clinical Information Modeling Initiative, and the Graphite S2 approach. Description The scope is all information modeling activities related to the representation of health and biomedical data, information, and knowledge. Scope SNOMED CT is the best source of codes for conditions, diagnoses, body parts, specimen types, substances, health interventions, etc. How SNOMED CT will be used Elements and nodes in the information model are explicitly bound to SNOMED CT concepts, or to value sets of SNOMED CT concepts. 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