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VICO: Ontology-based representation and integrative analysis of Vaccination Informed Consent forms.

Lin Y, Zheng J, He Y - J Biomed Semantics (2016)

Bottom Line: Third, VICO helps manage the complexity of the domain knowledge using logically defined ontological hierarchies and axioms.Fourth, VICO supports efficient query and comparison, e.g., through the Description Language (DL)-Query and SPARQL.Fifth, VICO helps discover new knowledge.

View Article: PubMed Central - PubMed

Affiliation: Unit for Laboratory Animal Medicine, University of Michigan Medical School, Ann Arbor, MI 48109 USA ; Department of Microbiology and Immunology, University of Michigan Medical School, Ann Arbor, MI 48109 USA ; Center for Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI 48109 USA ; Comprehensive Cancer Center, University of Michigan Medical School, 1301 MSRB III, 1150 W. Medical Dr., Ann Arbor, MI 48109 USA.

ABSTRACT

Background: Although signing a vaccination (or immunization) informed consent form is not a federal requirement in the US and Canada, such a practice is required by many states and pharmacies. The content and structures of these informed consent forms vary, which makes it hard to compare and analyze without standardization. To facilitate vaccination informed consent data standardization and integration, it is important to examine various vaccination informed consent forms, patient answers, and consent results. In this study, we report a Vaccination Informed Consent Ontology (VICO) that extends the Informed Consent Ontology and integrates related OBO foundry ontologies, such as the Vaccine Ontology, with a focus on vaccination screening questionnaire in the vaccination informed consent domain.

Results: Current VICO contains 993 terms, including 248 VICO specific terms and 709 terms imported from 17 OBO Foundry ontologies. VICO ontologically represents and integrates 12 vaccination informed consent forms from the Walgreens, Costco pharmacies, Rite AID, University of Maryland College Park, and the government of Manitoba, Canada. VICO extends Informed Consent Ontology (ICO) with vaccination screening questionnaires and questions. Our use cases and examples demonstrate five usages of VICO. First, VICO provides standard, robust and consistent representation and organization of the knowledge in different vaccination informed consent forms, questionnaires, and questions. Second, VICO integrates prior knowledge, e.g., the knowledge of vaccine contraindications imported from the Vaccine Ontology (VO). Third, VICO helps manage the complexity of the domain knowledge using logically defined ontological hierarchies and axioms. VICO glues multiple schemas that represent complex vaccination informed consent contents defined in different organizations. Fourth, VICO supports efficient query and comparison, e.g., through the Description Language (DL)-Query and SPARQL. Fifth, VICO helps discover new knowledge. For instance, by integrating the prior knowledge imported from the VO with a user's answer to informed consent questions (e.g., allergic reaction question) for a specific vaccination, we can infer whether or not the patient can be vaccinated with the vaccine.

Conclusions: The Vaccination Informed Consent Ontology (VICO) represents entities related to vaccination informed consents with a special focus on vaccination informed consent forms, and questionnaires and questions in the forms. Our use cases and examples demonstrated how VICO could support a platform for vaccination informed consent data standardization, data integration, and data queries.

No MeSH data available.


Related in: MedlinePlus

SPARQL query of shared and different questions in Costco and Walgreens vaccination informed consent forms. a Query common questions. b Query different questions. The two screenshots show the query executions and results generated using the Protégé OWL editor
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Fig5: SPARQL query of shared and different questions in Costco and Walgreens vaccination informed consent forms. a Query common questions. b Query different questions. The two screenshots show the query executions and results generated using the Protégé OWL editor

Mentions: For example, SPARQL queries were used to compare Costco and Walgreen vaccination informed consent forms. Figure 5 shows how a SPARQL query can be used to identify the common (Fig. 5a) and different (Fig. 5b) questions raised in Costco and Walgreen vaccination informed consent forms. In this SPARQL, we used an object property ‘documented by’ that represents the relation between an informed consent form and an organization (e.g., pharmacy) (Fig. 5b). Our comparative analysis using SPARQL queries found 39 unique questions listed in Walgreens and Costco vaccination informed consent forms (Table 1). Among these questions, 12 questions are shared by both forms, six questions are listed by Costco form only, and 21 questions are unique to the Walgreen form. Compared to the Costco form, four more questions are listed in the Walgreens form. Note that Walgreens unique question “question on whether fainted or felt dizzy after immunization” (question #19) is the subclass of Costco unique question “question on reaction after immunization” (question #18) in VICO. Similarly, “question whether currently sick” (question #13) used by Costco is the parent term of “question whether currently sick with a moderate to high fever, vomiting/diarrhea” (question #21) used by Walgreens. These observations reveal that although both Costco and Walgreens ask the adverse events after vaccination, Walgreens asks more specific and narrower questions.Fig. 5


VICO: Ontology-based representation and integrative analysis of Vaccination Informed Consent forms.

Lin Y, Zheng J, He Y - J Biomed Semantics (2016)

SPARQL query of shared and different questions in Costco and Walgreens vaccination informed consent forms. a Query common questions. b Query different questions. The two screenshots show the query executions and results generated using the Protégé OWL editor
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4837519&req=5

Fig5: SPARQL query of shared and different questions in Costco and Walgreens vaccination informed consent forms. a Query common questions. b Query different questions. The two screenshots show the query executions and results generated using the Protégé OWL editor
Mentions: For example, SPARQL queries were used to compare Costco and Walgreen vaccination informed consent forms. Figure 5 shows how a SPARQL query can be used to identify the common (Fig. 5a) and different (Fig. 5b) questions raised in Costco and Walgreen vaccination informed consent forms. In this SPARQL, we used an object property ‘documented by’ that represents the relation between an informed consent form and an organization (e.g., pharmacy) (Fig. 5b). Our comparative analysis using SPARQL queries found 39 unique questions listed in Walgreens and Costco vaccination informed consent forms (Table 1). Among these questions, 12 questions are shared by both forms, six questions are listed by Costco form only, and 21 questions are unique to the Walgreen form. Compared to the Costco form, four more questions are listed in the Walgreens form. Note that Walgreens unique question “question on whether fainted or felt dizzy after immunization” (question #19) is the subclass of Costco unique question “question on reaction after immunization” (question #18) in VICO. Similarly, “question whether currently sick” (question #13) used by Costco is the parent term of “question whether currently sick with a moderate to high fever, vomiting/diarrhea” (question #21) used by Walgreens. These observations reveal that although both Costco and Walgreens ask the adverse events after vaccination, Walgreens asks more specific and narrower questions.Fig. 5

Bottom Line: Third, VICO helps manage the complexity of the domain knowledge using logically defined ontological hierarchies and axioms.Fourth, VICO supports efficient query and comparison, e.g., through the Description Language (DL)-Query and SPARQL.Fifth, VICO helps discover new knowledge.

View Article: PubMed Central - PubMed

Affiliation: Unit for Laboratory Animal Medicine, University of Michigan Medical School, Ann Arbor, MI 48109 USA ; Department of Microbiology and Immunology, University of Michigan Medical School, Ann Arbor, MI 48109 USA ; Center for Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI 48109 USA ; Comprehensive Cancer Center, University of Michigan Medical School, 1301 MSRB III, 1150 W. Medical Dr., Ann Arbor, MI 48109 USA.

ABSTRACT

Background: Although signing a vaccination (or immunization) informed consent form is not a federal requirement in the US and Canada, such a practice is required by many states and pharmacies. The content and structures of these informed consent forms vary, which makes it hard to compare and analyze without standardization. To facilitate vaccination informed consent data standardization and integration, it is important to examine various vaccination informed consent forms, patient answers, and consent results. In this study, we report a Vaccination Informed Consent Ontology (VICO) that extends the Informed Consent Ontology and integrates related OBO foundry ontologies, such as the Vaccine Ontology, with a focus on vaccination screening questionnaire in the vaccination informed consent domain.

Results: Current VICO contains 993 terms, including 248 VICO specific terms and 709 terms imported from 17 OBO Foundry ontologies. VICO ontologically represents and integrates 12 vaccination informed consent forms from the Walgreens, Costco pharmacies, Rite AID, University of Maryland College Park, and the government of Manitoba, Canada. VICO extends Informed Consent Ontology (ICO) with vaccination screening questionnaires and questions. Our use cases and examples demonstrate five usages of VICO. First, VICO provides standard, robust and consistent representation and organization of the knowledge in different vaccination informed consent forms, questionnaires, and questions. Second, VICO integrates prior knowledge, e.g., the knowledge of vaccine contraindications imported from the Vaccine Ontology (VO). Third, VICO helps manage the complexity of the domain knowledge using logically defined ontological hierarchies and axioms. VICO glues multiple schemas that represent complex vaccination informed consent contents defined in different organizations. Fourth, VICO supports efficient query and comparison, e.g., through the Description Language (DL)-Query and SPARQL. Fifth, VICO helps discover new knowledge. For instance, by integrating the prior knowledge imported from the VO with a user's answer to informed consent questions (e.g., allergic reaction question) for a specific vaccination, we can infer whether or not the patient can be vaccinated with the vaccine.

Conclusions: The Vaccination Informed Consent Ontology (VICO) represents entities related to vaccination informed consents with a special focus on vaccination informed consent forms, and questionnaires and questions in the forms. Our use cases and examples demonstrated how VICO could support a platform for vaccination informed consent data standardization, data integration, and data queries.

No MeSH data available.


Related in: MedlinePlus