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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.

Digital Health
|September 22, 2025
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Summary

Digital health interventions (DHIs) are classified into four use cases: diagnosis, detection/measurement, classification, and therapeutics. This research establishes a taxonomy for DHIs, aiding in safety and effectiveness assessments.

Keywords:
Digital health interventionclinical decision support systemtaxonomyuse cases

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Area of Science:

  • Digital Health
  • Healthcare Informatics
  • Health Technology Assessment

Background:

  • Digital health interventions (DHIs) encompass a range of applications including integrated care, mobile health, clinical decision support, and risk stratification.
  • Understanding the complex landscape of DHIs is crucial for developing effective assurance methodologies.

Purpose of the Study:

  • To explore and classify digital health interventions (DHIs), their use cases, and applications in healthcare.
  • To establish a taxonomy of DHIs, including use cases, patient outcomes, stakeholders, and technologies, to provide context for assurance methodologies.

Main Methods:

  • A scoping review utilizing PRISMA methodology was conducted.
  • Data sources included Engineering Village (Compendex, Inspec), PubMed, and OVID Embase from 2019-2024.
  • Included records were screened for relevance to DHIs and their ontologies, with independent reviewer screening.

Main Results:

  • Forty-one studies were included, revealing four primary DHI use case categories: diagnosis (n=12), detection/measurement (n=18), classification (n=7), and therapeutics (n=6).
  • Multiple use cases were identified for some DHIs.
  • Four stakeholder groups were identified: patients, healthcare professionals, manufacturers, and regulators.

Conclusions:

  • A classification of DHIs, extending from workflow design and behavioral change interventions, was developed.
  • The integration of AI and innovative technologies in DHIs enhances intervention effectiveness.
  • A taxonomy of digital health technologies, including use cases, is presented to improve safety claim justification and evidence articulation.