Semantic Alignment between ICD-11 and SNOMED-CT By Marcie Wright RHIA, CHDA, CCS
World Health Organization (WHO) owns and publishes the International Classification of Diseases (ICD) WHO was entrusted with the ICD at its creation in 1948 and published the 6th version, ICD-6, that incorporated morbidity for the first time. The WHO Nomenclature Regulations, adopted in 1967, stipulated that Member States use the most current ICD revision for mortality and morbidity statistics. ICD has been revised and published in a series of editions to reflect advances in health and medical science over time.
The International Classification of Diseases (ICD) in the United States WHO has authorized the development of an adaptation of ICD-10 for use in the United States for U.S. government purposes. All modifications to ICD-10 must conform to WHO conventions. ICD- 10-CM was developed by a Technical Advisory Panel and extensive additional consultation with physician groups, clinical coders, and others to assure clinical accuracy and utility. ICD codes are currently the cornerstone of classifying diseases, injuries, health encounters and inpatient procedures. Public health officials at federal, state, and local levels rely on ICD coded data to conduct disease-related activities including statistics and claims reimbursement. https://www.cdc.gov/nchs/icd/icd10cm.htm
The International Classification of Diseases (ICD) in the United States The ICD-10-CM Coordination and Maintenance Committee is responsible to maintain the classification. A representative from the National Center for Health Statistics (NCHS) and one from the Centers for Medicare and Medicaid Services (CMS) co-chair the ICD-10-CM Coordination and Maintenance Committee meetings. Responsibility for maintenance of the ICD-10 is shared between these two agencies, with NCHS having lead responsibility for ICD-10- CM for diagnoses and CMS having lead responsibility for ICD-10-PCS for inpatient acute care procedures.
International Health Terminology Standards Development Organization (IHTSDO) maintains SNOMED CT SNOMED CT: Is the most comprehensive and precise, multilingual health terminology in the world. Assists with the electronic exchange of clinical health information. Can be mapped to other coding systems, such as ICD-10, which helps facilitate semantic interoperability. Is accepted as a common global language for health terms in over 50 countries. https://www.nlm.nih.gov/healthit/snomedct/snomed_overview.html
International Health Terminology Standards Development Organization (IHTSDO) maintains SNOMED CT SNOMED CT supports the following Meaningful Use Objectives: Maintain an up-to-date problem list of current and active diagnoses Record patient family health history as structure data Identify and report cancer cases to state cancer registries Record and track changes in patient vital signs Record patient smoking status Provide a summary record for each transition of care
World Health Organization s goal: To create a new generation in classification The revision process for ICD-11 is fundamentally different from previous ICD versions. Creation began in 2007: is computerized and supported by ontology-driven tools in an open social development environment. icat created as an electronic user interface to support world-wide participation. Goal to create semantic interoperability with other classifications and terminologies (meaningful data exchange). Each ICD class will correspond to exactly one class in SNOMED CT (different from mapping).
ICD-11 will introduce major changes to ICD Evolving from a focus on mortality and morbidity to a multi-purpose classification that encourages interoperability of various biomedical tools. Creates a multi-lingual international reference for research purposes. Ability to link to other terminologies in the EHR like SNOMED CT. In 2010, IHTSDO and WHO entered into a ground-breaking collaborative to harmonize the ICD-11 classification and SNOMED CT. https://www.snomed.org/about/partnerships/who
To harmonize ICD-11 and SNOMED CT ICD is being restructured to have a foundational component with an ontological core that maps to SNOMED CT. The IHTSDO is also developing a subset of SNOMED CT that serves as the basis of the ontological core of the ICD foundation component, referred to as Common Ontology. Maintaining the common ontology that will link ICD and SNOMED will be a new process into the future that will impact the process of updating and maintaining ICD in the U.S.
Common Ontology not the same as mapping To ensure full semantic interoperability between ICD and Snomed CT (SCT), a semantic alignment policy was developed which relates ICD classes to rule-based queries depending upon an ICD-11/SCT Common Ontology. (Rodrigues et. al. 2015) The harmonization could not simply be a mapping between representational entities (classes and concepts) of both systems. The consensus approach was to base the alignment around a Common Ontology. (Rodrigues et. al. 2015) Both IHTSDO and WHO have had to make adjustments to ICD and SCT in order to create this Common Ontology.
What is all of this supposed to mean?
The Common Ontology Purpose To create a common foundational subset that can capture data once at the point of care within the EHR. Supports communication with- Healthcare analysis and automated decision support through Natural Language Processing. Link together various classifications for health system management. Better communication between electronic health applications and Information systems.
Common problems with current data capture in electronic health records Majority of the information is in an unstructured data format as text. Captured structured data is in different languages which does not tell the same story when translated. EHR data is spread across multiple documents with specific peculiarities and data gaps. Currently requires manual abstraction to combine into an analytic data set. http://ascopubs.org/doi/full/10.1200/jop.2017.024224
Natural Language Processing and SNOMED CT SNOMED CT is used extensively behind the scenes within the EHR to support more sophisticated analytic facilities with Natural Language Processing (NLP) tools and reporting tools. A successful common ontology would allow NLP to convert documentation into the input of SNOMED CT to export a code in ICD-11 much more accurately.
Natural Language Processing Decision Support
Natural Language Processing If Then Statements Must comply with ICD classification principles like includes and excludes notes. This extensive set of inclusion and exclusions make mapping to and from SNOMED difficult (and coders essential). For instance, 23 IF..THEN rules are necessary to map Hypertension from SNOMED to ICD-10 (Rodrigues, 2015). Coders see this issue everyday when using Computer Assisted Coding (CAC) software. Oh the power of the human brain vs. IBM Watson
icat Developed by Stanford Center for Biomedical Informatics Research icat is a semantic Web platform built to support the collaborative authoring of ICD-11. Domain experts around the world use icat to author ICD classes, perform more changes, and to create links to external medical terminologies. Classification experts are interested in the organization of diseases in parent child hierarchies Domain experts are mainly medical doctors who use the platform to enter properties of diseases (for example, definitions, synonyms, clinical descriptions, manifestations) Project managers oversee the project and curate the content.
ICD-11 2017 Beta Draft Update Started in 2007 and is not complete. Twenty-two countries are currently participating in coding pilot testing of ICD-11. Goal of official release is May 2018 (does not apply to U.S.) http://www.who.int/classifications/icd/revision/icdprojectplan2015to 2018u.pdf?ua=1 Http://www.who.int/classifications/icd/revision/en/ https://icd.who.int/dev11/l-m/en
Resources Pöschko, J., Strohmaier, M., Tudorache, T., Noy, N. F., & Musen, M. A. (2012, March). Pragmatic Analysis of Crowd- Based Knowledge Production Systems with icat Analytics: Visualizing Changes to the ICD-11 Ontology. In AAAI Spring Symposium: Wisdom of the Crowd. Tudorache, T., Nyulas, C., Noy, N. F., Redmond, T., & Musen, M. A. (2011, November). icat: A collaborative authoring tool for ICD-11. In Workshop Ontologies come of Age in the Semantic Web (OCAS2011) 10 th International Semantic Web Conference Bonn, Germany, October 24, 2011 (p. 72). Tudorache, T., Falconer, S., Nyulas, C., Noy, N. F., & Musen, M. A. (2010, November). Will semantic web technologies work for the development of ICD-11?. In International Semantic Web Conference (pp. 257-272). Springer, Berlin, Heidelberg. Tudorache, T., Nyulas, C. I., Noy, N. F., & Musen, M. A. (2013, October). Using semantic web in ICD-11: three years down the road. In International Semantic Web Conference (pp. 195-211). Springer, Berlin, Heidelberg. Rodrigues, J. M., Robinson, D. J., Della Mea, V., Campbell, J. R., Rector, A. L., Schulz, S.,... & Millar, J. (2015). Semantic Alignment between ICD-11 and SNOMED CT. In MedInfo (pp. 790-794).