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Updated: Jan 17, 2026

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
Published on: September 20, 2018
Digital health interventions use cases: Classification and taxonomy development, a scoping review
Stuart Harrison1, Saif Ul Islam1, Hazif Muhammad Waseem1
1Institute of Digital Healthcare, WMG, University of Warwick, Coventry, UK.
Objective:
Exploring complex of digital health interventions (DHI), use cases, and applications in healthcare. Applications include integrated care architectures, mobile health, clinical decision support systems, and risk stratification. Thematic analysis aims to provide context for assurance methodologies aligned to DHIs. Use cases, patient outcomes, stakeholders, digital health technologies utilized, and the relationships will be established as a taxonomy.
Methods:
Design - Scoping Review using PRISMA methodology, Data Sources from Engineering Village (Compendex and Inspec), PubMed, and OVID Embase (2019-2024). We introduce categories of DHIs and use cases. Records only relevant to the research question were included. We were interested in ontologies recorded in literature; screening was performed by independent reviewer(s). A further review was completed after this initial screening.
Results:
Studies provide insight into the classification of DHIs, extending from workflow design, relationship analysis between common themes, and behavioural change intervention in mobile applications. The 41 included studies revealed four primary use case categories: diagnosis (n=12), detection/measurement (n=18), classification (n=7), and therapeutics (n=6), with some DHIs performing more than one use case. Four stakeholder groups were identified: patients, healthcare professionals, manufacturers, and regulators.
Conclusions:
This method of hazard assessment, analysis and use of ontologies (DHI and HSC) improves the justification of safety claims and evidence articulation. DHI's incorporation of AI and other innovative technologies enhances the effectiveness of interventions. The operational aspects of implementing DHIs require consideration of the intended purpose, as well as a lack of experience or understanding of potential complex clinical decision support systems. We provide a classification of DHIs, extended from workflow design and behavioral change intervention, including use cases, resulting in a taxonomy of digital health technologies.
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