Care delivery
Telemedicine, virtual care, patient navigation, disease management, remote monitoring, and connected care pathways.
Definition and taxonomy
What is Digital Health?
A practical definition for research, market comparison, strategy, and investment analysis.
Working definition
Digital Health applies digital technology and data to healthcare
Digital Health is the use of software, connected devices, data, and computational methods to improve healthcare delivery, diagnosis, treatment, monitoring, access, operations, research, and health outcomes.
The term is broad by design. It includes technologies used by patients, clinicians, researchers, health systems, payers, life-sciences companies, and public-health organisations. A useful definition therefore needs a taxonomy that separates materially different products, users, workflows, evidence standards, and business models.
Market scope
Major areas within Digital Health
Clinical and diagnostic tools
Digital diagnostics, clinical decision support, imaging software, biomarkers, and software used in regulated medical workflows.
Health operations
Clinical administration, workflow software, interoperability, revenue-cycle tools, workforce systems, and healthcare infrastructure.
Research and life sciences
Drug discovery, clinical-trial technology, real-world evidence, decentralised research, and digital tools supporting development and commercialisation.
Insurance and population health
Underwriting, benefits, member engagement, risk management, prevention, and population-level analytics.
Consumer health
Wellness, prevention, behaviour change, health education, self-management, and consumer-facing health services.
Why structure matters
Taxonomy makes the market comparable
Labels such as “AI healthcare”, “virtual care”, or “patient engagement” are not sufficiently precise for serious analysis. Companies using the same technology may serve different users, operate in different workflows, face different regulation, and sell through entirely different channels.
A taxonomy groups entities consistently. An ontology goes further by describing relationships among companies, products, technologies, therapeutic areas, customer groups, evidence, partnerships, and markets. Together they make it possible to compare like with like and to state clearly where a conclusion does and does not apply.
Research principles
A defensible classification should be
Operational
Defined by what a product does, who uses it, and where it sits in the healthcare workflow.
Evidence-aware
Able to distinguish marketing claims from regulatory, scientific, clinical, and commercial evidence.
Time-specific
Preserving how a company, product, or market was classified at a particular point in time.
Transparent
Clear enough that another researcher can understand the inclusion criteria and reproduce the comparison.