title: The logic of surveillance guidelines: an analysis of vaccine adverse event reports from an ontological perspective.
abstract: BACKGROUND
  When increased rates of adverse events following immunization are detected, regulatory action can be taken by public health agencies. However to be interpreted reports of adverse events must be encoded in a consistent way. Regulatory agencies rely on guidelines to help determine the diagnosis of the adverse events. Manual application of these guidelines is expensive, time consuming, and open to logical errors. Representing these guidelines in a format amenable to automated processing can make this process more efficient.
  
  
  RESULTS
  Using the Brighton anaphylaxis case definition, we show that existing clinical guidelines used as standards in pharmacovigilance can be logically encoded using a formal representation such as the Adverse Event Reporting Ontology we developed. We validated the classification of vaccine adverse event reports using the ontology against existing rule-based systems and a manually curated subset of the Vaccine Adverse Event Reporting System. However, we encountered a number of critical issues in the formulation and application of the clinical guidelines. We report these issues and the steps being taken to address them in current surveillance systems, and in the terminological standards in use.
  
  
  CONCLUSIONS
  By standardizing and improving the reporting process, we were able to automate diagnosis confirmation. By allowing medical experts to prioritize reports such a system can accelerate the identification of adverse reactions to vaccines and the response of regulatory agencies. This approach of combining ontology and semantic technologies can be used to improve other areas of vaccine adverse event reports analysis and should inform both the design of clinical guidelines and how they are used in the future.
  
  
  BACKGROUND
  Sufficient material to reproduce our results is available, including documentation, ontology, code and datasets, at http://purl.obolibrary.org/obo/aero.
authors.affiliation: BC Cancer Agency, Vancouver, British Columbia, Canada.
authors.forename: Mélanie
authors.initials: M
authors.lastname: Courtot
authors.affiliation: BC Cancer Agency, Vancouver, British Columbia, Canada; Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia, Canada.
authors.forename: Ryan R
authors.initials: RR
authors.lastname: Brinkman
authors.affiliation: School of Dental Medicine, University at Buffalo, New York, United States of America.
authors.forename: Alan
authors.initials: A
authors.lastname: Ruttenberg
mesh_terms: D066264:Datasets as Topic; D003936:Diagnosis, Computer-Assisted / Q000379:methods; D005260:Female; D019983:Guideline Adherence; D017408:Guidelines as Topic; D006801:Humans; D053118:Influenza A Virus, H1N1 Subtype; D007252:Influenza Vaccines / Q000008:administration & dosage / Q000009:adverse effects*; D008297:Male; D008954:Models, Biological; D060735:Pharmacovigilance; D011237:Predictive Value of Tests
chemical_list: D007252:Influenza Vaccines