Presentation made during the PCIRN AGM in Ottawa, April 2011

1. TOWARDS AN ADVERSE EVENT
REPORTING ONTOLOGY
PCIRN ANNUAL GENERAL MEETING
APRIL 20-21 2011
OTTAWA, ON
Mélanie Courtot and Ryan Brinkman on behalf of the
PCIRN IT support group

2. Current problem
 No standard reporting system for adverse events
(AE)
 PCIRN: Medical Dictionary of Regulatory Activities
(MedDRA)
 No definitions
 No unambiguous meaning of terms
 Loss of information, low data quality

3. How to solve it
 Use of standard definitions for AE reporting
 Ensuring that adverse events following immunization
(AEFIs) are reported in accordance to the selected
guideline
 Specification of signs and symptoms defining each AEFI
 Computer tractable
 Implemented in reporting systems

4. Help confirm reported diagnostic
 Suggests missing
information to reach
unambiguous case
determination
 For example, check
skin color to distinguish
seizure from
Hypotonic-
Hyporesponsive
Episode (HHE)

5. Enables complex data querying
 “which of my patients have an AEFI involving part
of the nervous system?”

6. Use of standards definitions
 Brighton collaboration
 Adopted by PHAC
 300 participants from patient care, public health, scientific,
pharmaceutical, regulatory and professional organizations
Bonhoeffer et al. Vaccine, 2002.
 Good applicability, sensitivity, and specificity
Kohl et al. Vaccine, 2007.
 Performs well against other standards
Erlewyn-Lajeunesse et al. Drug safety, 2010.
 Used within PCIRN
Gagnon et al., Journal of allergy and clinical immunology, 2010.

7. Brighton publication - seizure

8. Brighton case definition - seizure

9. Computer tractable
 Domain is modeled using an ontology.
 Each entity is defined textually
 Human readable definition, label
 Each entity is defined logically
 Relations to other entities
 Web Ontology Language (OWL) allows processing
by computer

10. Enables complex data querying
 Computer can infer link such as “Encephalitis unfolds
in the Nervous system”

11. Implementation in reporting systems
 Assist in confirming a reported clinical entity (e.g.,
seizure) at up to three levels of diagnostic certainty
 Checklist at data entry time
 Report on missing elements to confirm the event with
some degree of certainty
 Allow interoperability and querying on reports

12. Perspectives
 Early stage work
 Ontological
issues to solve
 Add more AEFIs
 Collaboration with Brighton
 Discussion with Dacima to implement into their
Electronic Data Capture system (Daciforms)

13. Acknowledgements
 PHAC/CIHR Influenza Research Network (PCIRN)
 IT support group: Jean-Paul Collet, Victor Espinosa,
Kim Marty, Lesley Sturrock, Nataliya Yuskiv, Evelyn
Chan
 PCIRN scholarship

14. Adverse event workshop
 July 26th 2011, Buffalo, USA
 Co-located with International Conference on
Biomedical Ontologies
 http://purl.org/net/aeicbo2011

15. Sources
 The development of standardized case definitions and guidelines for
adverse events following immunization. Kohl et al. Vaccine, Volume
25, Issue 31, 1 August 2007, Pages 5671-5674
 The Brighton Collaboration: addressing the need for standardized
case definitions of adverse events following immunization (AEFI)
Bonhoeffer et al., Vaccine
Volume 21, Issues 3-4, 13 December 2002, Pages 298-302
 Diagnostic Utility of Two Case Definitions for Anaphylaxis: A
Comparison Using a Retrospective Case Notes Analysis in the UK.
Erlewyn-Lajeunesse et al., Drug Safety, 2010 Jan 1; Vol. 33 (1), pp.
57-64.
 Safe vaccination of patients with egg allergy with an adjuvanted
pandemic H1N1 vaccine. Gagnon et al., Journal of allergy and
clinical immunology, 2010; Vol. 126, pp 317.