Clinical Terminology Shock and Awe: Difference between revisions
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'''Rationale''': The CTSA Program has always emphasized the need for data standards to promote sharing and comparison of data across the CTSA Consortium and beyond. Yet creation and adoption of such standards is still painfully slow. Urgent action remains necessary. History shows the high value of standard terms, definitions, and symbols (i.e. ontology) to science. But the creation and adoption of such standards often takes decades. Translational science requires a consistent set of standard ontologies spanning all scales, from molecule to organism to population. But clinical terminologies at the macroscale – such as SNOMED and ICD – inhibit translational science. They are inconsistent with successful micro-scale ontologies such as the Gene Ontology, and they also cannot change rapidly with the advance of science. Translational science must settle on standards that evolve in a way that is closely tied to scientific advance. In the case of chemical symbols and SI Units adoption proceeded in three overlapping stages. First came widespread recognition and understanding of the problem. Second, influential stakeholders helped to develop, test, and select appropriate standards. Third, once scientifically useful standards emerged, the community enforced them via peer review. How can we accelerate progress on clinical ontologies through all three stages? How, in other words, can we create and implement standard clinical ontologies that are open and sufficiently well disseminated to achieve consortium-wide adoption? | '''Rationale''': The CTSA Program has always emphasized the need for data standards to promote sharing and comparison of data across the CTSA Consortium and beyond. Yet creation and adoption of such standards is still painfully slow. Urgent action remains necessary. History shows the high value of standard terms, definitions, and symbols (i.e. ontology) to science. But the creation and adoption of such standards often takes decades. Translational science requires a consistent set of standard ontologies spanning all scales, from molecule to organism to population. But clinical terminologies at the macroscale – such as SNOMED and ICD – inhibit translational science. They are inconsistent with successful micro-scale ontologies such as the Gene Ontology, and they also cannot change rapidly with the advance of science. Translational science must settle on standards that evolve in a way that is closely tied to scientific advance. In the case of chemical symbols and SI Units adoption proceeded in three overlapping stages. First came widespread recognition and understanding of the problem. Second, influential stakeholders helped to develop, test, and select appropriate standards. Third, once scientifically useful standards emerged, the community enforced them via peer review. How can we accelerate progress on clinical ontologies through all three stages? How, in other words, can we create and implement standard clinical ontologies that are open and sufficiently well disseminated to achieve consortium-wide adoption? | ||
This workshop will convene stakeholders interested in identifying ways to harmonize clinical terminology resources with their counterparts at the molecular level. A consistent framework for ontologies that enable interoperability of systems, compatibility of data, and research reproducibility is the vision. Furthermore, we will address additional issues with clinical terminologies as they currently exist, specifically the problem that even professional coding with them has poor inter-coder reliability. This situation degrades the quality of terminology-encoded data below acceptable research standards. Lastly, we believe confusing and incoherent terminologies are a barrier to end-user usability of resources like EHRs and the data they produce. | |||
'''Goals''': The [http://ncorwiki.buffalo.edu/index.php/Clinical_and_Translational_Science_Ontology_Group Clinical and Translational Science Ontology Group] was established in 2012 to leverage the use of common ontologies to support different aspects of information-driven clinical and translational research. The focus of this meeting is to explore new and existing uses of common ontologies to support creation, sharing, and analysis of clinical data. | '''Goals''': The [http://ncorwiki.buffalo.edu/index.php/Clinical_and_Translational_Science_Ontology_Group Clinical and Translational Science Ontology Group] was established in 2012 to leverage the use of common ontologies to support different aspects of information-driven clinical and translational research. The focus of this meeting is to explore new and existing uses of common ontologies to support creation, sharing, and analysis of clinical data. | ||
Revision as of 12:03, 6 April 2016
Fifth Annual Workshop of the Clinical and Translational Science Ontology Group
Date: September 7-8, 2016
Venue: Ramada Hotel, Amherst, NY
Rationale: The CTSA Program has always emphasized the need for data standards to promote sharing and comparison of data across the CTSA Consortium and beyond. Yet creation and adoption of such standards is still painfully slow. Urgent action remains necessary. History shows the high value of standard terms, definitions, and symbols (i.e. ontology) to science. But the creation and adoption of such standards often takes decades. Translational science requires a consistent set of standard ontologies spanning all scales, from molecule to organism to population. But clinical terminologies at the macroscale – such as SNOMED and ICD – inhibit translational science. They are inconsistent with successful micro-scale ontologies such as the Gene Ontology, and they also cannot change rapidly with the advance of science. Translational science must settle on standards that evolve in a way that is closely tied to scientific advance. In the case of chemical symbols and SI Units adoption proceeded in three overlapping stages. First came widespread recognition and understanding of the problem. Second, influential stakeholders helped to develop, test, and select appropriate standards. Third, once scientifically useful standards emerged, the community enforced them via peer review. How can we accelerate progress on clinical ontologies through all three stages? How, in other words, can we create and implement standard clinical ontologies that are open and sufficiently well disseminated to achieve consortium-wide adoption?
This workshop will convene stakeholders interested in identifying ways to harmonize clinical terminology resources with their counterparts at the molecular level. A consistent framework for ontologies that enable interoperability of systems, compatibility of data, and research reproducibility is the vision. Furthermore, we will address additional issues with clinical terminologies as they currently exist, specifically the problem that even professional coding with them has poor inter-coder reliability. This situation degrades the quality of terminology-encoded data below acceptable research standards. Lastly, we believe confusing and incoherent terminologies are a barrier to end-user usability of resources like EHRs and the data they produce.
Goals: The Clinical and Translational Science Ontology Group was established in 2012 to leverage the use of common ontologies to support different aspects of information-driven clinical and translational research. The focus of this meeting is to explore new and existing uses of common ontologies to support creation, sharing, and analysis of clinical data.
Like its predecessors in the series, this meeting is designed to bring together clinical and translational scientists from across the CTSA Consortium who are interested in using ontologies to promote discoverability and interoperability of biomedical data.
Specific themes will include:
- Advancing reproducibility of clinical and translational research (BFO, OBI, LOINC)
- Advancing EHR interoperability (addressing SNOMED and meaningful use regulations whereby SNOMED CT is required for recording problem list and smoking status)
- Improving EHR data usability
- Improving SNOMED usability
- Advancing interoperability of clinical data generally and of EHR data in particular
- Improving EHR usability in the clinic
- i2b2, PCORnet, OMOP and other approaches to clinical data sharing
Persons interested in attending or in presenting at the meeting should write to Barry Smith.
Schedule
Wednesday, September 7
8:00am Registration and Breakfast
6:00pm Dinner
Thursday, September 8
8:00am Registration and Breakfast
4:00pm Close
Sponsors
Department of Biomedical Informatics, University at Buffalo
National Center for Ontological Research, Buffalo
Organizing Committee
Barry Smith (University at Buffalo)
William Hogan (University of Florida)
Participants
Jonathan Bona (Buffalo)
Mathias Brochhausen (Arkansas)
Werner Ceusters (Buffalo)
Alexander Diehl (Buffalo)
Willian Duncan (Buffalo)
Peter Elkin (Buffalo)
Fernanda Farinelli (Minas Gerais, Brazil)
Yongqun "Oliver" He (Ann Arbor)
William Hogan (Gainesville)
Mark Jensen (United Nations Environment Programme)
Edison Ong (Ann Arbor)
Rasmus Rosenberg Larsen (Buffalo)
Øystein Nytro (Trondheim, Norway)
Jihad Obeid (Charleston)
Jose Parente de Oliveira (ITA, Brazil)
Stefan Schulz (Graz, Austria)
Barry Smith (Buffalo)
