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Running Projects

OPMQoL: an ontology for pain and related disability, mental health and quality of life.    
(July 2011 - July 2013)
Supported by the National Institute of Dental and Craniofacial Research (NIH) grant 1 R01 DE021917-01A1
(Press release, video)

The goal of this project is to obtain better insight into the complexity of pain disorders, specifically concerning the assessment of different pain types as well as pain-related disablement and its association with mental health and quality of life. This will be achieved by developing an ontology which will then be used to integrate five existing datasets that broadly encompass the major types of pain (orofacial pains, temporomandibular disorder pain, headache) recognized to occur in the oral and associated regions and incorporating a broad array of measures consistent with a biopsychosocial perspective regarding pain.
The datasets cover the same domain, but are distinct in various respects:
(1) some variables are identical across datasets, others involving, for instance, somatization, depression and anxiety, are different because measured with distinct instruments;
(2) the data exhibit different levels of granularity;
(3) because of their distinct origins (US, UK, Sweden, Israel, and Germany), the datasets incorporate cultural influences related to pain report that have an impact on the comparability of the data sets, despite the use of common instruments.
The ontology will make it possible to describe the datasets in a uniform and formal way, and be general enough to include other datasets in the same domain once they become available.
The main clinical question that we will be able to answer by merging these datasets is how patho-anatomy and pathophysiology – in this case in the context of TMD and orofacial pains - have an impact on pain-related disablement and quality of life. Because the ontology will provide a formal representation of widely used assessment instruments in the domain of mental health, its applicability will exceed by far the more narrow domain that is covered in the proposed project for practical reasons.
The ontology will be built following the widely accepted and in Nature published principles adhered to in the Open Biomedical Ontology Foundry (OBO-Foundry, using Basic Formal Ontology (BFO), and Referent Tracking (RT) as generic semantic technologies. By working in collaboration with The International RDC/TMD Consortium Network, and the Orofacial Pain Special Interest Group of the International Association for the Study of Pain, this ontology is likely to become a standard in the domain.

Related literature

  • Smith B, Ceusters W, Goldberg LJ, Ohrbach R. Towards an Ontology of Pain. In: Mitsu Okada (ed.), Proceedings of the Conference on Logic and Ontology, Tokyo: Keio University Press, February 2011:23-32. (paper)
  • Hastings J, Ceusters W, Smith B, Mulligan K. Dispositions and processes in the Emotion Ontology. International Conference on Biomedical Ontology, Buffalo NY, July 28-30, 2011:71-78. (paper)
  • Nixdorf D, Drangsholt M, Ettlin D, Gaul C, de Leeuw R, Svensson P, Zakrzewska J, DeLaat A, Ceusters W. Classifying orofacial pains: a new proposal of taxonomy based on ontology. Journal of Oral Rehabilitation 2012;39(3):161-169. (PMC3383028, paper, final draft)
  • Ceusters W. SNOMED CT's RF2: is the Future Bright? Medical Informatics Europe Conference, MIE 2011, Oslo, Norway, August 28-31, 2011. Studies in Health Technology and Informatics 2011;169:829-833. (PMC3379709, paper, response to reviewers, slides)
  • Hastings J, Ceusters W, Smith B, Mulligan K. The Emotion Ontology: enabling interdisciplinary research in the affective sciences. In: Beigl M, Christiansen H, Roth-Berghofer TR, Kofod-Petersen A, Coventry KR, Schmidtke HR (Eds.) Modeling and Using Context; Proceedings of CONTEXT 2011, Karlsruhe, Germany, September 26-30, 2011, Lecture Notes in Artificial Intelligence 6967;119-123. (slides)
  • Hastings J, le Novère N, Ceusters W, Mulligan K, Smith B. Wanting what we don't want to want; representing addiction in interoperable bio-ontologies. International Conference on Biomedical Ontology (ICBO2012), Graz, Austria, July 22-25, 2012. (paper, response to reviewers)
  • Hastings J, Ceusters W, Jensen M, Mulligan K, Smith B. Representing mental functioning: Ontologies for mental health and disease. Workshop Towards an Ontology of Mental Functioning, International Conference on Biomedical Ontology, Graz, Austria, July 22, 2012. (paper)
  • Hastings J, Ceusters W, Mulligan K, Smith B. Annotating affective neuroscience data with the Emotion Ontology. Workshop Towards an Ontology of Mental Functioning, International Conference on Biomedical Ontology, Graz, Austria, July 22, 2012. (paper)
  • Ceusters W. An Information Artifact Ontology Perspective on Data Collections and Associated Representational Artifacts. Medical Informatics Europe Conference (MIE 2012), Pisa, Italy, August 26-29, 2012,Stud Health Technol Inform 2012;180:68-72. (Pubmed, final draft, response to 'reviewers')
  • Doing-Harris K, Meystre SM, Samore M, Ceusters W. Applying Ontological Realism to Medically Unexplained Syndromes. 14th World Congress on Medical and Health Informatics (MEDINFO 2013), accepted for publication.

Presentations

  • Foundations for an Ontology for pain-related disablement, mental health and quality of life (OPMQoL). Meeting on Pain and Neurological Disease Ontologies, SUNY at Buffalo, Jan 20, 2012. (slides)
  • Pain and Mental Health: a Case-Study in Information Driven Research.. Lecture as part of the Core Curriculum in Clinical And Translational Research Seminar Series (info), Buffalo, NY, February 22, 2012. (slides)
  • Assessment instruments and biomedical reality: examples in the pain domain. Ontology Dissemination Workshop, University at Buffalo, June, 13, 2012, Buffalo, NY. (slides)
  • Ontology: innovative approach to orofacial pain classification. IADR Satellite Symposium on Orofacial Pain Assessment: Classification, Biobehavior, QST, and Biomarkers, March 19, 2013, Seattle, WA. (abstract, slides)
  • A common framework for representing data and what they are about. Ontology seminar, April 1, 2013, Dept. of Philosophy, University at Buffalo, Buffalo, NY. (abstract, slides, recording)

Tutorials

  • Realism-Based Ontology for Integrating Individually Compiled Biomedical Data Repositories. 3-Hour tutorial as part of the Medical Informatics Europe Conference (MIE 2012), Pisa, Italy, August 26-29, 2012. (Tutorial outline, slides)
  • Biomedical Ontology and Referent Tracking: Introduction to Basic Principles. IADR Satellite Workshop on Orofacial Pain, March 20, 2013, Seattle, WA. (slides)




ProWATCH – MUS component    
(July 2011 - ...)

We are assisting Kristina Doing-Harris of the Department of Biomedical Informatics of the University of Utah in developing a realism-based ontology for the MUS (Medically Unexplained Syndromes) component of the ProWATCH project. This component is a joint project between the University of Utah and the Salt Lake City Veterans Health Administration and is being run by Stéphan Meystre, MD, PhD (at the University of Utah) and Matthew Samore, MD (at the VA). The project focuses on providing VA clinical research with methods and instruments for syndrome surveillance, on improving detection and mitigation of health problems in deployed veterans, and more specifically on the detection of medically unexplained syndromes (MUS) and emergent infectious diseases.

Much of the information contained in electronic medical records like the VA CPRS is recorded in unstructured narrative text format. Some information such as diagnoses, test, or treatments, is mostly based on a fairly stable collection of terms used by healthcare providers, partly represented in standard vocabularies shared by healthcare organizations. Clinical information reported by patients such as symptoms is often described in general English language and varies significantly more than the terminology used by healthcare providers.

Developing tools to effectively use information extracted from VA clinical documents depends on expertise in information extraction, ontology development, symptom identification, predictive modeling, and interactive information visualization. Thus, execution of the work entailed by this project depends on the capacity to work across a range of clinical areas, and to engage a scientific team that brings together experts from a variety of disciplines including epidemiology, infectious disease, mental health, computer science, biomedical informatics, and statistics.

Related literature

  • Doing-Harris K, Meystre SM, Samore M, Ceusters W. Applying Ontological Realism to Medically Unexplained Syndromes. 14th World Congress on Medical and Health Informatics (MEDINFO 2013), accepted for publication.
  • Doing-Harris K, Meystre SM, Samore M, Ceusters W. Domain and Application Ontologies for Medically Unexplained Syndromes. In American Medical Informatics Association 2012 Annual Symposium Proceedings, Chicago IL, November 3-7, 2012;1606.


SMART-Amy: a smart guide towards the diagnosis of systemic amyloidosis    
(April 2013 - ...)

We are assisting Paola Russo of the Laboratory for Biomedical Informatics "Mario Stefanelli" (BMI), Italy, in developing a realism-based ontology for the reality covered by diagnostic guidelines for systemic amyloidoses according to Ontological Realism and the OBO Foundry principles.

Systemic amyloidoses are a family of rare diseases that can cause multi-organ failure and be life-threatening. It is acknowledged and emphasized by public health strategies that the first priority to respond to rare diseases consists in improving their visibility and recognition, favoring an early diagnosis and, if possible, an early treatment. Due to the complexity and variety of rare diseases, they are usually managed and treated in a few referral centers that have the knowledge needed to assess diagnosis and treatment as well as the necessary tools (e.g. biomarkers, diagnostic techniques) to do so. The current practice to redirect patients to a few referral centers is indeed a way to guarantee the best quality of care, but in absence of effective public strategies promoting the recognition of patients affected by rare diseases on large scale, many patients remain deprived of this solution. This problem is even more dramatic whenever the disease is life threatening. In those cases, the diagnostic delay may lead to an early death despite of treatment initiation. The solution proposed by the SMART-Amy project is: 1) to develop a framework according to which it is possible to formally assess the degree to which a consensus diagnostic algorithm for systemic amyloidoses is emerging, integrating for instance the International Society of Amyloidosis (ISA) guidelines and best practices applied by referral centers, 2) to build a corresponding realism-based ontology to be used in 3) a clinical decision support system (CDSS) to make more reliably a diagnosis of systemic amyloidosis.

As an ancillary branch of the project core, BMI is implementing the AmyGuide interactive tool for smartphones and tablets in order to provide, both online and offline, patient-oriented information, combining information about the disease with hints to promote health behaviors and self-care, and to manage the demand for health services. It is built on top of the Gquest application for Android operating systems, a platform conceived for computerizing and administering questionnaires.

Related literature

  • Brochhausen M, Burgun-Parenthoine A, Ceusters W, Hasman A, Leong TY, Musen M, Oliveira J, Peleg M, Rector A, Schulz S. Discussion of “Biomedical Ontologies: Toward Scientific Debate”, Methods of Information in Medicine, 2011;50(3):217-36. (paper commented on, long version of my comments, published comments)
  • Smith B, Ashburner M, Rosse C, Bard J, Bug W, Ceusters W, Goldberg LJ, Eilbeck K, Ireland A, Mungall CJ, the OBI Consortium, Leontis N, Rocca-Serra P, Ruttenberg A, Sansone SA, Shah N, Whetzel PL, Lewis S. The OBO Foundry: Coordinated Evolution of Ontologies to Support Biomedical Data Integration. Nature Biotechnology 2007;25:1251-1255. (full paper)
  • Smith B, Ceusters W. Ontological Realism as a Methodology for Coordinated Evolution of Scientific Ontologies. Applied Ontology, 2010;5(3-4):139-188. (Published version, final draft)
  • Ceusters W, Smith B. Referent Tracking for Treatment Optimisation in Schizophrenic Patients. Journal of Web Semantics 4(3) 2006:229-36; Special issue on semantic web for the life sciences. (Long draft, published paper)


Referent Tracking enabled web sites    
(Sept 2008 - ...)

Did you ever think about the fact that when you are viewing a web page, you are not looking at a concrete file which is on some medium on the remote web server, but to an exact copy of that file which has been sent to your computer? In many cases, there is not even a concrete file on the server, but what you see through your browser has been assembled out of several components using, for instance, php. Logically, when you view the page at different times, assuming the browser refreshed its contents, you get each time a different copy, and so do other viewers. Moreover, in between two access events, the page on the remote server might have been changed.
RT-enabled websites keep track of these copies, of their distribution, and of the evolution of the web pages that they contain over time. Never saw one? Well, you are looking at one now. On Oct 2, 2008, the RTU RT-enabled web site went live. Each distributed page, at the time of a request, is branded with an Instance Unique Identifier (IUI) which is of course different from the IUI of the remote file. The IUI is printed on the right side of the menu bar.
In addition, a checksum is generated over the IUI taken together the content of the page in a way which protects authors against claims that certain information was there, when it actually was not. At the same, it is a guarantee for viewers that the authors cannot deny that specific information was there. The checksum is shown on the bottom of the page.
In the background, an RT-database keeps track of all the IUIs, including revisions and new versions of pages, as well as of when and to which IP address the copies were sent.
The RT-enabled website technology is available for licensing.



Making existing EHR systems RT compatible    (Dec 2006 - )

By advocating the use of instance unique identifiers to refer to the entities comprising the subject matter of patient health records, Referent Tracking promises many benefits to those who use health record data to improve patient care. One challenge ahead lies in furthering the adoption of the paradigm by developers of existing EHR applications. To meet this challenge, we have begun the process of integrating RT into commercial EHR applications A part of this process is an analysis of the extent to which the data collected by an EHR application needs to be reformulated to make it compatible with the requirements of RT, namely that the particulars assigned an IUI (for �instance unique identifier�) are instances of the kinds included in Basic Formal Ontology (BFO).

  • An initial exploratory analysis was carried out for Praxis which allowed us to identify the obstacles and the directions that future research in relation to this system should take. (Dec 2006 - July 2007)
  • A more in depth analysis was performed on MedtuityEMR which led to the formulation of a research proposal. (Dec 2006)
  • For Sigmund Software LLC, we explored how their Target Behavior Tracking system which is currently used within individual organizations can benefit from referent tracking to develop a cross-institutional knowledgebase linked to other behavioral assessment tools. (March 2007)


 

Past projects

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