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== '''Announcement''' ==
== '''Announcement''' ==
<span style="font-size:125%"><p>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?</p>  <p>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.</p></span>
<span style="font-size:125%"><p>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?</p>  <p>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.</p></span>


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[http://www.ramada.com/hotels/new-york/getzville/ramada-amherst-conference-center/hotel-overview Ramada Hotel, Amherst, NY]  
[http://www.ramada.com/hotels/new-york/getzville/ramada-amherst-conference-center/hotel-overview Ramada Hotel, Amherst, NY]  


Special "UB" room rate: $89 (2 queen beds), $99 (1 king bed)
Call 1-716-636-7500 and ask for special UB room rate: $89 (2 queen beds), $99 (1 king bed)


=='''Schedule (Preliminary Draft) Day 1'''==
=='''Schedule Day 1: September 7'''==


<u>Wednesday Morning</u>
<u>Wednesday Morning</u>
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8:00am '''Registration and Breakfast'''
8:00am '''Registration and Breakfast'''


9:00am '''The Electronic Health Record: A Survey of Problems with Special Reference to the Research Data Needs of Clinical and Translational Science'''
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 [http://www.buffaloctrc.org/]


Speakers will include: Ross Koppel (Penn), Barry Smith (Buffalo)
9:00am Ram D. Sriram (NIST): '''The role of NIST in facilitating EHR Meaningful Use'''  [http://ncor.buffalo.edu/CTSA/sriram.pptx Slides]
*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.'''


We will focus on the three broad families of problems identified identified by Koppel in [http://link.springer.com/chapter/10.1007/978-3-319-20765-0_6]: data standards, interoperability and usability.  
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''' [[Ross Koppel: EHR Problems | Summary]] / [http://ncor.buffalo.edu/CTSA/Koppel.pptx Slides]
*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.  


1. '''Data Standards''' – the format one uses to record the collected medical information:  
10:30am Break
*<span style="font-size:90%;">There were several available ontologies and data standards for defining almost all of the measures used in medicine in 2009. We could have chosen one and insisted that any system that could receive incentives and subsidies had to use that data standard. Without data standards, interoperability becomes almost impossible. Of course, there could have been a flexibility built into that process. For example, any system could be installed in 2009–2010 but that system had to incorporate the unified data standards within a year.</span>
*<span style="font-size:90%">… without unified data standards we cannot share information across systems; we fail to achieve real interoperability. The systems create towers of Babel and those towers become isolated from each other; a noisy but deaf city.</span>


2. '''Interoperability''': sending information from one system to another:
11:00am Anna Orlova (AHIMA) '''Understanding Information in EHR Systems: Achieving Semantic Interoperability Through Standards''' [http://ncor.buffalo.edu/CTSA/Orlova.pptx Slides]
*<span style="font-size:90%;">The problem of interoperability has been mastered in electronics and almost every other industry for over 40 years, often for several hundred. The major barrier in HIT was the aforementioned lack of a unified standard and the refusal of vendors to select a method of data transmission. Again, selecting any of the available methods in 2009 would have enabled the transmission and collection of medical information – a core, but still missing virtue of HIT. Several arguments are offered for the industry’s inability or refusal to create its own interoperability protocols or for its lack of agreement on existing interoperability protocols: </span>
*Dr Orlova is the Senior Director for Standards at the American Health Information Management Association.
*<span style="font-size:90%;">Vendors benefit from sales of entire suites of products …. By not allowing a vendor’s software and/or hardware to interact with other vendors’ systems, a vendor ensures sales of a combined package. </span>
*<span style="font-size:90%;">Because these systems are so expensive, because implementing them is three to five times more than just the initial software and hardware costs, and because the implementation process takes 3–5 years, opportunities for buyer remorse are limited or made unacceptable. The buyer is locked in; often wed to that system for a decade. The vendors thus seek to capture market share as soon as possible, and are encouraged to rush HIT products to market before they are sufficiently tested. … The vast funds involved, and the consequential career implications of those participating in HIT purchases enhance intimidation of critics and those who report problems with the technology. The general faith in technology and the sincere desire to see HIT improve medical workflow encourages so many to define critics as technophobes, incompetents, and non-team players. </span>
•<span style="font-size:90%;">Data loss threats: lack of interoperability makes switching HIT systems perilous, with dangers of massive data loss, which would be a catastrophic failure for healthcare institutions. … As with data standards, the ONC could have offered flexibility in the timing of an interoperability requirement. Thus, for example, any system would be acceptable to purchase in 2009–2010, but all systems would have to be able to use an agreed-upon exchange protocol within a year of installation. </span>


3. '''Usability''': defined as ease of use, ability to learn, effectiveness, efficiency, error tolerant, engaging, and responsive.
11:20am Davide Sottara (Arizona): '''Work Domain Ontology: Connecting clinical activities, information systems and knowledge assets''' [[Sivaram Arabandi: Work Domain Ontology | Summary ]] / [http://ncor.buffalo.edu/CTSA/Sottara.pdf Slides]
*<span style="font-size:90%;">HIT vendors have agreed that usability is dependent on:</span>
::<span style="font-size:90%;">The training and skill of the user</span>
::<span style="font-size:90%;">The implementation of specific systems in specific settings</span>
::<span style="font-size:90%;">The history of HIT use in any setting and by any user</span>
::<span style="font-size:90%;">The relationship of a specific system to the other IT systems with which it must interact</span>
::<span style="font-size:90%;">The physical environment (e.g., lighting, noise levels, quality of display screens).</span>
*<span style="font-size:90%;">All of these factors absolutely influence usability, often profoundly. But none of them should be allowed to obscure the reality that usability is intimately dependent on ''the design of the system''. Moreover, none of these factors means that usability is not measurable. Indeed, there are well-documented scientific methods for measuring usability, including measures that incorporate and acknowledge the other factors that affect use. As a thought experiment consider automobile safety. No one would deny that a car’s performance and braking ability are influenced by road conditions, the driver’s skill, and the driver’s alertness. Yet it would be absurd to insist that basic automobile design decisions do not seriously affect a car’s stability, safety and braking effectiveness. In contrast to the automobile analogy, HIT vendors have, until recently, defended their lack of focused attention on usability by reiterating the mantra that usability is subjective, too theoretical, or essentially unmeasurable. Some vendors have claimed that there is only scant proof of the relationship between usability and safety. At the same time, and apparently without irony, several vendors also note they have employed usability experts and that their own tests find their systems to be very usable.</span>


12:00: Lunch  
12:00: Lunch  
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<u>Wednesday - Afternoon</u>
<u>Wednesday - Afternoon</u>


1:00pm Olivier Bodenreider (NLM): '''SNOMED CT as Clinical Terminology Foundry harmonizing LOINC, GMDN, ICNP, ICD-11, OrphaNet and FMA'''
1:00pm Werner Ceusters (Buffalo): '''MIROT: Minimal Information to be Referenced by an Ontology Term'''
 
1:40pm 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''' [[Clinical Terminology for Personalized Medicine | Summary ]] / [http://ncor.buffalo.edu/CTSA/Campbell.pptx Slides]
 


2:00pm James R. Campbell (University of Nevada Medical Center): '''Clinical terminology for personalized medicine: Deploying a common concept model for SNOMED CT and LOINC Observables in service of genomic medicine''' [[Clinical Terminology for Personalized Medicine | Abstract ]]
2:20pm William Hogan (Florida): '''Representing configurations using Referent Tracking with an application to SNOMED CT''' [http://ncor.buffalo.edu/CTSA/Hogan.pptx Slides]


3:30pm Break
3:00pm Break


4pm: '''Keynote address by Stefan Schulz: Coding clinical narratives: Causes and cures for inter-expert disagreements'''
3:30pm Amanda Hicks (Florida): '''Gender identity data in the EHR: Motivations and challenges for getting it right''' [http://ncor.buffalo.edu/CTSA/Hicks.pptx Slides]
3:45pm Barry Smith (Buffalo): '''Clinical Terminology Shock and Awe''' [http://ncor.buffalo.edu/CTSA/Smith.pptx Slides]
 
4:00pm Chris Stoeckert (Penn): '''Transforming and Unifying Research with Biomedical Ontologies: TURBO-charging clinical data at Penn''' [http://ncor.buffalo.edu/CTSA/Schulz.pptx Slides]
 
4:15pm Keynote address by Stefan Schulz (Graz): '''Coding clinical narratives: Causes and cures for inter-expert disagreements''' [http://ncor.buffalo.edu/CTSA/Schulz.pptx Slides]


: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.
: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.
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:'''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.
:'''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.


=='''Schedule (Preliminary Draft) Day 2'''==
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
 
6:30pm Dinner (for those who have pre-registered) at [http://aromanorthfrench.com/ Trattoria Aroma on North French]
 
=='''Schedule Day 2: September 8'''==


<u>Thursday - Morning</u>
<u>Thursday - Morning</u>
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8:00am Registration and Breakfast
8:00am Registration and Breakfast


9:00am
8:30am Peter Elkin (Buffalo): '''Ontology-enabled observational research''' [http://ncor.buffalo.edu/CTSA/Elkin.pptx Slides]


Possible topics
9:00am  Alan Ruttenberg (Buffalo): '''Using OWL and BFO to safely decongest SNOMED''' [http://tinyurl.com/jdrbrvb Slides]
9:30m Jonathan Blaisure and Peter Winkelstein (Buffalo): '''Secondary Use of EHR Data: Does the emperor have clothes?''' [http://ncor.buffalo.edu/CTSA/Blaisure.pptx Blaisure Slides] [http://ncor.buffalo.edu/CTSA/Winkelstein.pdf Winkelstein Slides]


*A​dvanc​ing​ reproducibility ​of clinical and translational research (BFO, OBI, LOINC)
10:00 Yu Lin (FDA): '''Medical device evaluation based on synthesis of real-world evidence: application to breast implants''' [http://ncor.buffalo.edu/CTSA/Lin.pdf Slides]


*Advancing interoperability of clinical data generally and of EHR data in particular
10:20am Break


*​I​mproving SNOMED / CCD / c-CDA usability
10:45am Adrien Barton and Ryeyan Taseen (Sherbrooke): '''Ontologies to support [[Learning Health Systems]]''' [http://ncor.buffalo.edu/CTSA/Barton.pptx Slides]


*i2b2, PCORnet, OMOP, FHIR and other approaches to clinical data sharing 
11:10am Sina Madani (Florida): '''Optimizing patient problem list entries through the use of SNOMED CT ontological relationships''' [http://ncor.buffalo.edu/CTSA/Madani.pptx Slides]


*Interoperability
11:25 Kei-Hoi Cheung (Yale / VA): '''Standardization of laboratory test identifiers for Veteran Affairs''' [http://ncor.buffalo.edu/CTSA/Cheung.pptx Slides]
::The role of CDA


*Mismatch of EHR data with the needs of clinical and translational research
12:00 Lunch
::Patient data repositories
::The issue of coordination across the CTSA
::The role of CDISC


*​Advancing EHR interoperability​ (addressing SNOMED / CCD and meaningful use regulations whereby SNOMED CT is required for recording problem list and smoking status, and CCD is required for care summary)
<u>Thursday - Afternoon</u>


12:00 Lunch
1:00pm Øystein Nytrø (Trondheim): '''Discussion: Why clinical questions cannot be answered by Electronic Health Records''' [http://ncor.buffalo.edu/CTSA/nytro.pptx Slides]
2:00pm '''Wrap-up session'''


<u>Thursday - Afternoon</u>
Preparing a White Paper


1:00pm-4:00pm Wrapup sessions TBD
4:00pm '''Close'''


=='''Rationale'''==
=='''Rationale'''==
Line 110: Line 115:
Persons interested in attending or in presenting at the meeting should write to [mailto:phismith@buffalo.edu Barry Smith].
Persons interested in attending or in presenting at the meeting should write to [mailto:phismith@buffalo.edu Barry Smith].


== Sponsors ==
== '''Sponsor''' ==


Department of Biomedical Informatics, University at Buffalo
Principal sponsor: '''[http://www.smbs.buffalo.edu/biomedicalinformatics/ Department of Biomedical Informatics], University at Buffalo'''


National Center for Ontological Research, Buffalo
We are grateful also to the [http://www.buffaloctrc.org/ Buffalo Clinical and Translational Research Center] for sponsoring four scholarships of $500 to early career researchers for attendance at the meeting. See [http://ncor.buffalo.edu/CTSA/Ontology-Travel-Scholarship.pdf here] for details.


==Organizing Committee==
=='''Organizing Committee'''==


Barry Smith (University at Buffalo)
Barry Smith (University at Buffalo)
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William Hogan (University of Florida)
William Hogan (University of Florida)


== Participants ==
== '''Participants''' ==
 
Maurizio Almeida (Department of Information Theory and Management, Federal University of Minas Gerais, Brazil)
 
Sivaram Arabandi (ontopro, Houston)
 
Adrien Barton (University of Sherbrooke, Québec)
 
Jonathan Bona (Department of Biomedical Informatics, University at Buffalo)
 
Matt Burton (Applied Clinical Informatics, Mayo Clinic)


Sivaram Arabandi (Health 2.0, Houston)
James R. Campbell (Department of Internal Medicine, University of Nebraska)


Olivier Bodenreider (National Library of Medicine)
Werner Ceusters (Department of Biomedical Informatics, University at Buffalo)


Jonathan Bona (Buffalo)
Kei-Hoi Cheung (Yale Center for Medical Informatics and VA Connecticut Healthcare System)


Mathias Brochhausen (Arkansas)
James Cimino (Informatics Institute, School of Medicine, University of Alabama at Birmingham)


Werner Ceusters (Buffalo)
Alexander Diehl (Department of Neurology, University at Buffalo)


Kei-Hoi Cheung (Yale / VA Connecticut Healthcare System)
William Duncan (Roswell Park Cancer Institute, Buffalo)


Alexander Diehl (Buffalo)
Peter Elkin (Department of Biomedical Informatics, University at Buffalo)


Willian Duncan (Buffalo)
Fernanda Farinelli (School of Information Science, Federal University of Minas Gerais, Brazil)


Peter Elkin (Buffalo)
Josh Hanna (Health Outcomes and Policy, University of Florida, Gainesville)


Fernanda Farinelli (Minas Gerais, Brazil)
Monica Harry (IHTSDO, Copenhagen)


Yongqun "Oliver" He (Ann Arbor)
Amanda Hicks (Health Outcomes and Policy, University of Florida, Gainesville)


William Hogan (Gainesville)
William Hogan (Department of Biomedical Informatics, University of Florida, Gainesville)


Mark Jensen (United Nations Environment Programme)
Mark Jensen (Department of Biomedical Informatics, University at Buffalo)


Ross Koppel (University of Pennsylvania)
Ross Koppel (Department of Sociology, University of Pennsylvania)


Asiyah Lin (Food and Drug Administration)
Anand Kumar (Clinical Science Radiology, Philips Healthcare, Cleveland)


Sina Madani (MD Anderson Cancer Center)
Asiyah Lin (Food and Drug Administration, Silver Spring, MD)


Øystein Nytrø (Trondheim, Norway)
Lesley MacNeil (IHTSDO, Copenhagen)


Edison Ong (Ann Arbor)
Sina Madani (Department of Institutional Analytics and Informatics, MD Anderson Cancer Center, Houston)


Jihad Obeid (Charleston)
Øystein Nytrø (Department of Computer and Information Science, Norwegian University of Science and Technology, Norway)


Jose Parente de Oliveira (ITA, Brazil)
Jihad Obeid (Biomedical Informatics Center, Medical University of South Carolina, Charleston)


Rasmus Rosenberg Larsen (Buffalo)
Anna Orlova (American Health Information Management Association (AHIMA))


Alan Ruttenberg (Buffalo)
Jose Parente de Oliveira (Instituto Tecnológico de Aeronáutica, Brazil)


Stefan Schulz (Graz, Austria)
Lyubov Remennik (NIH/CC/BTRIS, Bethesda, MD)


Barry Smith (Buffalo)
Rachel Richesson (Duke University School of Nursing)


Dagobert Soergel (Buffalo)
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)
Ram Sriram (HealthIT, National Institute of Standards and Technology)
Chris Stoeckert (Institute for Biomedical Informatics, 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)

Latest revision as of 01:43, 8 March 2017

Fifth Annual Workshop of the Clinical and Translational Science Ontology Group

Announcement

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

Ramada Hotel, Amherst, NY

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 Slides

  • 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 / Slides

  • 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 Anna Orlova (AHIMA) Understanding Information in EHR Systems: Achieving Semantic Interoperability Through Standards Slides

  • Dr Orlova is the Senior Director for Standards at the American Health Information Management Association.

11:20am Davide Sottara (Arizona): Work Domain Ontology: Connecting clinical activities, information systems and knowledge assets Summary / Slides

12:00: Lunch

Wednesday - Afternoon

1:00pm Werner Ceusters (Buffalo): MIROT: Minimal Information to be Referenced by an Ontology Term

1:40pm 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 / Slides


2:20pm William Hogan (Florida): Representing configurations using Referent Tracking with an application to SNOMED CT Slides

3:00pm Break

3:30pm Amanda Hicks (Florida): Gender identity data in the EHR: Motivations and challenges for getting it right Slides

3:45pm Barry Smith (Buffalo): Clinical Terminology Shock and Awe Slides

4:00pm Chris Stoeckert (Penn): Transforming and Unifying Research with Biomedical Ontologies: TURBO-charging clinical data at Penn Slides

4:15pm Keynote address by Stefan Schulz (Graz): Coding clinical narratives: Causes and cures for inter-expert disagreements Slides

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

6:30pm Dinner (for those who have pre-registered) at Trattoria Aroma on North French

Schedule Day 2: September 8

Thursday - Morning

8:00am Registration and Breakfast

8:30am Peter Elkin (Buffalo): Ontology-enabled observational research Slides

9:00am Alan Ruttenberg (Buffalo): Using OWL and BFO to safely decongest SNOMED Slides

9:30m Jonathan Blaisure and Peter Winkelstein (Buffalo): Secondary Use of EHR Data: Does the emperor have clothes? Blaisure Slides Winkelstein Slides

10:00 Yu Lin (FDA): Medical device evaluation based on synthesis of real-world evidence: application to breast implants Slides

10:20am Break

10:45am Adrien Barton and Ryeyan Taseen (Sherbrooke): Ontologies to support Learning Health Systems Slides

11:10am Sina Madani (Florida): Optimizing patient problem list entries through the use of SNOMED CT ontological relationships Slides

11:25 Kei-Hoi Cheung (Yale / VA): Standardization of laboratory test identifiers for Veteran Affairs Slides

12:00 Lunch

Thursday - Afternoon

1:00pm Øystein Nytrø (Trondheim): Discussion: Why clinical questions cannot be answered by Electronic Health Records Slides

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.

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 (ontopro, 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)

William 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 (Department of Institutional Analytics and Informatics, 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 (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 (Institute for Biomedical Informatics, 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)

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