Commoning Semantic Interoperability in Healthcare

Bestek, Mate; Grönvall, Erik; Saad-Sulonen, Joanna

doi:10.5334/ijc.1157

Cited by 5 publications

(2 citation statements)

References 54 publications

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“…Without semantic interoperability, similar or identical concepts may be captured by different terms perceived or constructed as separate or multiple entities. 25 Wellknown models and taxonomies like the QI Plan-Do-Study-Act (PDSA) model, Consolidated Framework for Implementation Research (CFIR), and cause-and-effect analysis can promote interoperability in managing and exchanging digital information through collective applications in use cases.…”

Section: Commonly Employed Quality Improvement and Implementation Sci...mentioning

confidence: 99%

Developing a Quality Improvement Implementation Taxonomy for Organizational Employee Wellness Initiatives

Gao,

Vaclavik,

Jeffery

et al. 2024

Appl Clin Inform

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Background Standardized taxonomies (STs) facilitate knowledge representation and semantic interoperability within health care provision and research. However, a gap exists in capturing knowledge representation to classify, quantify, qualify, and codify the intersection of evidence and quality improvement (QI) implementation. This interprofessional case report leverages a novel semantic and ontological approach to bridge this gap. Objectives This report had two objectives. First, it aimed to synthesize implementation barrier and facilitator data from employee wellness QI initiatives across Veteran Affairs health care systems through a semantic and ontological approach. Second, it introduced an original framework of this use-case-based taxonomy on implementation barriers and facilitators within a QI process. Methods We synthesized terms from combined datasets of all-site implementation barriers and facilitators through QI cause-and-effect analysis and qualitative thematic analysis. We developed the Quality Improvement and Implementation Taxonomy (QIIT) classification scheme to categorize synthesized terms and structure. This framework employed a semantic and ontological approach. It was built upon existing terms and models from the QI Plan, Do, Study, Act phases, the Consolidated Framework for Implementation Research domains, and the fishbone cause-and-effect categories. Results The QIIT followed a hierarchical and relational classification scheme. Its taxonomy was linked to four QI Phases, five Implementing Domains, and six Conceptual Determinants modified by customizable Descriptors and Binary or Likert Attribute Scales. Conclusion This case report introduces a novel approach to standardize the process and taxonomy to describe evidence translation to QI implementation barriers and facilitators. This classification scheme reduces redundancy and allows semantic agreements on concepts and ontological knowledge representation. Integrating existing taxonomies and models enhances the efficiency of reusing well-developed taxonomies and relationship modeling among constructs. Ultimately, employing STs helps generate comparable and sharable QI evaluations for forecast, leading to sustainable implementation with clinically informed innovative solutions.

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Section: Commonly Employed Quality Improvement and Implementation Sci...mentioning

confidence: 99%

Developing a Quality Improvement Implementation Taxonomy for Organizational Employee Wellness Initiatives

Gao,

Vaclavik,

Jeffery

et al. 2024

Appl Clin Inform

View full text Add to dashboard Cite

show abstract

“…Without semantic interoperability, similar or identical concepts may be captured by different terms perceived or constructed as separate or multiple entities. 25 Well-known models and taxonomies like the QI Plan-Do-Study-Act (PDSA) model, Consolidated Framework for Implementation Research (CFIR), and cause-and-effect analysis can promote interoperability in managing and exchanging digital information through collective applications in use cases.…”

Section: Commonly Employed Qi and Implementation Science Vocabulary A...mentioning

confidence: 99%

Developing a Quality Improvement Implementation Taxonomy for Organizational Employee Wellness Initiatives

Gao,

Vaclavik,

Jeffery

et al. 2023

Appl Clin Inform

View full text Add to dashboard Cite

Background: Standardized taxonomies facilitate knowledge representation and semantic interoperability within healthcare provision and research. However, a gap exists in capturing knowledge representation to classify, quantify, qualify, and codify the intersection of evidence and quality improvement (QI) implementation. This interprofessional case report leverages a novel semantic and ontological approach to bridge this gap. Objectives: This report has 2 objectives. First, it aimed to synthesize implementation barrier and facilitator data from employee wellness QI initiatives across XXX healthcare systems through a semantic and ontological approach. Second, it introduced an original framework of this use-case-based taxonomy on implementation barriers and facilitators within a QI process. Methods: We synthesized terms from combined datasets of all-site implementation barriers and facilitators through QI cause-and-effect analysis and qualitative thematic analysis. We developed the Quality Improvement and Implementation Taxonomy (QIIT) classification scheme to categorize synthesized terms and structure. This framework employed a semantic and ontological approach. It built upon existing terms and models from the QI Plan, Do, Study, Act phases, the Consolidated Framework for Implementation Research domains, and the fishbone cause-and-effect categories. Results: The QIIT followed a hierarchical and relational classification scheme. Its taxonomy was linked to 4 QI Phases, 5 Implementing Domains, 6 Conceptual Determinants modified by customizable Descriptors and Binary or Likert Attribute Scales. Conclusion: This case report introduces a novel approach to standardize the process and taxonomy to describe evidence translation to QI implementation barriers and facilitators. This classification scheme reduces redundancy and allows semantic agreements on concepts and ontological knowledge representation. Integrating existing taxonomies and models enhances the efficiency of reusing well-developed taxonomies and relationship modeling among constructs. Ultimately, employing standardized taxonomies helps generate comparable and sharable QI evaluations for forecast, leading to sustainable implementation with clinically informed innovative solutions.

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Health Data Semantics: Exploring Requirements for Sustainable Health Systems

Bestek

Grönvall

2023

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Commoning Semantic Interoperability in Healthcare

Cited by 5 publications

References 54 publications

Developing a Quality Improvement Implementation Taxonomy for Organizational Employee Wellness Initiatives

Developing a Quality Improvement Implementation Taxonomy for Organizational Employee Wellness Initiatives

Developing a Quality Improvement Implementation Taxonomy for Organizational Employee Wellness Initiatives

Health Data Semantics: Exploring Requirements for Sustainable Health Systems

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