Clinical Terminology Shock and Awe
Fifth Annual Workshop of the Clinical and Translational Science Ontology Group
Announcement
THIS MEETING IS NOW FULL.
Are clinical terminologies and other healthcare data standards realizing their goals of system interoperability and data compatibility? Do they enhance or detract from EHR usability? How usable are the terminologies and standards themselves? Can systems developers understand them sufficiently well to be able to incorporate them successfully into EHR design? Can clinicians understand them well enough to reliably communicate to both computers and humans? Can researchers benefit from these standards? Do they enable translational science? Do they support or inhibit research reproducibility? What work remains to be done? What approaches are needed to realize the vision of interoperability and data compatibility?
The Clinical and Translational Science Ontology Group invites you to join us this September in Buffalo as we assess the state of the art in clinical terminologies and ontologies and build a research agenda for closing the "interoperability" and "data compatibility" gap. Our keynote speaker will be Dr. Stefan Schulz who will address the reliability of professional SNOMED CT coding and what ontological approaches might help to improve it.
Date
September 7-8, 2016
Venue
Call 1-716-636-7500 and ask for special UB room rate: $89 (2 queen beds), $99 (1 king bed)
Schedule Day 1: September 7
Wednesday Morning
8:00am Registration and Breakfast
8:45am Timothy F. Murphy: Welcoming remarks
- Dr Murphy is UB Senior Associate Dean for Clinical and Translational Research and Principal Investigator of the UB CTSA [1]
9:00am Ram D. Sriram (NIST): The role of NIST in facilitating EHR Meaningful Use
- Dr Sriram is Chief of the Software and Systems Division, Information Technology Laboratory, The National Institute of Standards and Technology (NIST). He leads the NIST team for technical evaluation of Electronic Health Record technology.
9:45am Ross Koppel (Penn): The Electronic Health Record: A survey of problems with reference to the research data needs of Clinical and Translational Science Summary
- Dr Koppel is Professor and Researcher in the University of Pennsylvania Sociology Department and world leader in research on the use of healthcare information technology.
10:30am Break
11:00am Yu Lin (FDA): Medical device evaluation based on real-world data integration: will Common Data Models work? (Title subject to revision)
11:20am Sivaram Arabandi (Health 2.0): Work Domain Ontology: Connecting clinical activities, information systems and knowledge assets Summary
12:00: Lunch
Wednesday - Afternoon
1:00pm James R. Campbell (Nebraska): Clinical terminology for personalized medicine: Deploying a common concept model for SNOMED CT and LOINC Observables in service of genomic medicine Summary
1:40pm Alan Ruttenberg (Buffalo): Using OWL and BFO to safely decongest SNOMED
2:20pm William Hogan (Florida): Representing configurations using Referent Tracking with an application to SNOMED CT
3:00pm Break
3:30pm Amanda Hicks (Florida): Gender identity data in the EHR: Motivations and challenges for getting it right
3:45pm Barry Smith (Buffalo): Clinical Terminology Shock and Awe
4:00pm Chris Stoeckert (Penn): Transforming and Unifying Research with Biomedical Ontologies: TURBO-charging clinical data at Penn
4:15pm Keynote address by Stefan Schulz (Graz): Coding clinical narratives: Causes and cures for inter-expert disagreements
- We will investigate the fitness for use of clinical terminologies to enable EHR interoperability. Information extraction from clinical narratives using NLP was identified as an important use case. For this purposes, terminology experts built a gold standard annotation for SNOMED CT and a UMLS extract, where shockingly low inter-annotator agreement values resulted. This talk will elucidate typical reasons for disagreement and point out how disgreement can be partially mitigated for SNOMED CT by exploiting its axiomatic basis, at least partially built on ontological grounds.
- Stefan Schulz is a professor of Medical Informatics at the Medical University of Graz, Austria. Trained as a physician, his research encompasses electronic health records, medical language processing, biomedical terminologies, and the application of formal ontologies for biomedical knowledge representation. He has contributed to the development of clinical terminology standards such as WHO classifications and SNOMED CT.
5:30pm Day 1 Closing Session, including presentation of certificates to scholarship winners by Margarita L. Dubocovich, SUNY Distinguished Professor and Chair of the Department of Pharmacology and Toxicology, Jacobs School of Medicine and Biomedical Sciences
Schedule Day 2: September 8
Thursday - Morning
8:00am Registration and Breakfast
8:45am Peter Elkin (Buffalo): Ontology-enabled IRB-free 5-Minute retrospective clinical trials Abstract
9:15am Werner Ceusters (Buffalo): MIROT: Minimal Information to be Referenced by an Ontology Term
9:45am Peter Winkelstein (Buffalo): Secondary Use of EHR Data: Does the emperor have clothes?
10:15am Break
10:45am Adrien Barton and Ryeyan Taseen (Sherbrooke): Ontologies to support Learning Health Systems
11:10am Sina Madani (Florida): Optimizing patient problem list entries through the use of SNOMED CT ontological relationships
11:25 Kei-Hoi Cheung (Yale / VA): Standardization of laboratory test identifiers for Veteran Affairs
12:00 Lunch
Thursday - Afternoon
1:00pm Øystein Nytrø (Trondheim): Discussion: Why clinical questions cannot be answered by Electronic Health Records
2:00pm Wrap-up session
Preparing a White Paper
4:00pm Close
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. 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.
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?
A key barrier to adoption of ontologies is the widespread perception among IT companies and programmers, especially EHR developers, that ontology is impractical and inaccessible to them. And thus ontology is not relevant. The perception is that merely adopting standard value sets in their proprietary information models is sufficient. But it is not. How do we demonstrate the value, and a practical and accessible path forward, for the adoption of BFO / RO / OBI / IAO / OGMS / HPO / GO / HDO / ChEBI / DrOn / OMRSE and other OBO ontologies in EHRs, i2b2, REDCap, and other systems in support of translational science?
This workshop will convene stakeholders interested in identifying ways to harmonize clinical terminology resources with their counterparts at the molecular level and make substantial progress in their implementation in every day clinical and research information systems, especially the EHR. A consistent framework for ontologies that enable interoperability of systems, compatibility of data, and research reproducibility is the vision.
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.
Persons interested in attending or in presenting at the meeting should write to Barry Smith.
Sponsors
Principal sponsor: Department of Biomedical Informatics, University at Buffalo
We are grateful also to the Buffalo Clinical and Translational Research Center for sponsoring four scholarships of $500 to early career researchers for attendance at the meeting. See here for details.
Organizing Committee
Barry Smith (University at Buffalo)
William Hogan (University of Florida)
Participants
Maurizio Almeida (Department of Information Theory and Management, Federal University of Minas Gerais, Brazil)
Sivaram Arabandi (Health 2.0, Houston)
Adrien Barton (University of Sherbrooke, Québec)
Jonathan Bona (Department of Biomedical Informatics, University at Buffalo)
Matt Burton (Applied Clinical Informatics, Mayo Clinic)
James R. Campbell (Department of Internal Medicine, University of Nebraska)
Werner Ceusters (Department of Biomedical Informatics, University at Buffalo)
Kei-Hoi Cheung (Yale Center for Medical Informatics and VA Connecticut Healthcare System)
James Cimino (Informatics Institute, School of Medicine, University of Alabama at Birmingham)
Alexander Diehl (Department of Neurology, University at Buffalo)
Willian Duncan (Roswell Park Cancer Institute, Buffalo)
Peter Elkin (Department of Biomedical Informatics, University at Buffalo)
Fernanda Farinelli (School of Information Science, Federal University of Minas Gerais, Brazil)
Josh Hanna (Health Outcomes and Policy, University of Florida, Gainesville)
Monica Harry (IHTSDO, Copenhagen)
Amanda Hicks (Health Outcomes and Policy, University of Florida, Gainesville)
William Hogan (Department of Biomedical Informatics, University of Florida, Gainesville)
Mark Jensen (Department of Biomedical Informatics, University at Buffalo)
Ross Koppel (Department of Sociology, University of Pennsylvania)
Anand Kumar (Clinical Science Radiology, Philips Healthcare, Cleveland)
Asiyah Lin (Food and Drug Administration, Silver Spring, MD)
Lesley MacNeil (IHTSDO, Copenhagen)
Sina Madani (MD Anderson Cancer Center, Houston)
Øystein Nytrø (Department of Computer and Information Science, Norwegian University of Science and Technology, Norway)
Jihad Obeid (Biomedical Informatics Center, Medical University of South Carolina, Charleston)
Anna Orlova (Senior Director for Standards, American Health Information Management Association (AHIMA))
Jose Parente de Oliveira (Instituto Tecnológico de Aeronáutica, Brazil)
Lyubov Remennik (NIH/CC/BTRIS, Bethesda, MD)
Rachel Richesson (Duke University School of Nursing)
Alan Ruttenberg (School of Dental Medicine, University at Buffalo)
Stefan Schulz (Medical University of Graz, Austria)
Dan Schlegel (Department of Biomedical Informatics, University at Buffalo)
Selja Seppälä (Health Outcomes and Policy, University of Florida, Gainesville)
Barry Smith (National Center for Ontological Research, University at Buffalo)
Dagobert Soergel (Department of Library and Information Studies, University at Buffalo)
Davide Sottara (College of Health Solutions - Arizona State University)
Ram Sriram (HealthIT, National Institute of Standards and Technology)
Chris Stoeckert (Computational Biology and Informatics Laboratory, University of Pennsylvania)
Ryeyan Taseen (University of Sherbrooke, Québec)
Mirela Vasconcelos (Health Outcomes and Policy, University of Florida, Gainesville)
Peter Winkelstein (Institute for Healthcare Informatics, University at Buffalo)
