Digital health is the use of information and communications technology to support health and healthcare. The World Health Organization frames it as an umbrella covering eHealth — the use of ICT for health — together with emerging areas such as advanced computing, data science, and connected devices.

The term is broad by design, encompassing infrastructure like electronic health records, services like remote consultation, consumer tools like health applications and wearables, and regulated products like digital therapeutics. What unites them is that value comes from information moving differently: reaching someone sooner, being available where a decision is made, or being captured continuously rather than at intervals.

The Main Domains of Digital Health

Electronic Health Records and Clinical Systems

The electronic health record is the longitudinal digital record of a patient's care. Around it sit computerised order entry, electronic prescribing, results reporting, clinical decision support, and departmental systems for laboratory, radiology, pharmacy, and theatre management.

Benefits include legibility, availability across sites, structured data supporting audit and research, and the ability to embed safety checks such as allergy and interaction alerts. Documented drawbacks include substantial documentation burden, alert fatigue when warnings are excessive or poorly targeted, and workflow changes that consume clinician time. Both effects are consistently reported, and the balance depends heavily on implementation and configuration rather than on the technology itself.

Telehealth and Telemedicine

Telehealth covers the delivery of health services at a distance: video and telephone consultations, store-and-forward transmission of images or data for later specialist review, remote monitoring, and tele-mentoring between clinicians. Established applications include follow-up consultations, mental health therapy, dermatology triage, stroke assessment through telestroke networks, and specialist input to remote or under-served locations.

Limitations are equally clear. Physical examination is constrained, procedures are impossible, some conditions require in-person assessment, and effectiveness depends on connectivity and on the patient's ability to use the technology. Licensing, cross-border practice, and reimbursement rules shape what is possible in a given jurisdiction.

Mobile Health and Consumer Applications

mHealth refers to health services and information delivered through mobile devices: medication reminders, symptom trackers, chronic disease self-management tools, appointment and results access through patient portals, and public health messaging. In many lower-resource settings, mobile platforms have supported community health worker programmes, supply chain management, and health information delivery where other infrastructure is limited.

Wearables and Sensors

Consumer wearables measure heart rate, activity, sleep, and in some cases electrocardiogram rhythm or blood oxygen. Clinical-grade sensors include continuous glucose monitors, cardiac patch monitors, and implantable loop recorders. The distinction between consumer wellness devices and regulated medical devices turns on claimed intended purpose: the same hardware may be unregulated when marketed for fitness and regulated when marketed to detect a medical condition.

Remote Patient Monitoring

Remote monitoring transmits physiological or symptom data from a patient's home to a clinical team, used in heart failure, hypertension, diabetes, respiratory disease, post-operative recovery, and pregnancy. Its effectiveness depends less on the sensing technology than on the clinical service wrapped around it: who reviews the data, how quickly, and what action follows.

Digital Therapeutics

Digital therapeutics are software products intended to prevent, manage, or treat a medical condition, typically delivering structured therapeutic content — often cognitive behavioural approaches — for conditions including insomnia, substance use disorders, and some mental health and chronic conditions. They are regulated as medical devices in major jurisdictions and are expected to demonstrate clinical effectiveness through trials.

Health Data, Analytics, and AI

Analytics applied to routinely collected data supports population health management, risk stratification, quality measurement, operational planning, and research. Artificial intelligence applications extend this to image analysis, prediction, and language processing. These functions depend on data being interoperable and of adequate quality.

Health Information Exchange and Interoperability

Interoperability is the ability of systems to exchange information and use it meaningfully. Standards including HL7 FHIR for data exchange, SNOMED CT for clinical terminology, LOINC for laboratory observations, and DICOM for imaging provide the technical basis. Without them, digital health produces isolated systems that cannot inform one another.

What Digital Health Can and Cannot Do

Demonstrated Value

  • Improving access where distance, mobility, or specialist scarcity are barriers.
  • Making information available at the point of decision, reducing duplicate testing and unsafe prescribing.
  • Supporting continuous rather than episodic measurement in chronic disease management.
  • Enabling audit, quality measurement, and research on routinely collected data.
  • Automating administrative work that consumes clinical time.

Recognised Limitations

  • Uneven evidence. Many products reach market with limited or no outcome evidence. Evaluation frameworks scaling evidence requirements to risk and claimed benefit have been developed in several countries in response.
  • Digital exclusion. Benefits accrue to those with connectivity, devices, skills, and language access — often not those with the greatest health need. Deployment without attention to this can widen inequity.
  • Workload displacement. Digital tools frequently shift work rather than removing it, sometimes onto clinicians and sometimes onto patients.
  • Data quality. Analytics inherit the limitations of the records they use, which are generated for care and billing rather than for analysis.
  • Fragmentation. Poorly integrated systems create multiple logins, duplicate entry, and information that fails to reach the person who needs it.

Regulation, Privacy, and Safety

Regulatory status depends on intended purpose. Software intended for a medical purpose — diagnosis, treatment, monitoring of disease — is generally regulated as a medical device, through device pathways in the United States and under the Medical Device Regulation in the European Union. General wellness products fall outside that scope, though the boundary is determined by claims made rather than by technical capability.

Health data are subject to data protection law, including the General Data Protection Regulation in the European Union and sector-specific frameworks elsewhere. Core obligations typically include a lawful basis for processing, purpose limitation, data minimisation, security safeguards, transparency, and rights of access and correction. Consumer health applications frequently fall outside clinical data protections, and their data-sharing practices have been a recurrent concern.

Safety governance covers clinical risk management for health IT, cybersecurity of connected devices and systems, business continuity planning for outages, and incident reporting. Health systems have experienced significant disruption from cyber incidents, making resilience a patient safety matter rather than purely a technical one.

Digital Health in Global Context

The World Health Organization has promoted national digital health strategies emphasising that technology should serve health system goals rather than being adopted for its own sake, and that governance, interoperability standards, workforce capability, and infrastructure must be addressed together.

In lower-resource settings, mobile-first approaches have supported community health programmes, disease surveillance, supply chain management, and health worker training. Recurrent challenges include fragmentation of small pilot projects that never scale, dependence on external funding, limited local technical capacity, and infrastructure constraints including electricity and connectivity.

Sources

  • World Health Organization — Global Strategy on Digital Health; digital health guidance and classifications
  • U.S. Food and Drug Administration — digital health policies; software as a medical device
  • European Commission — Medical Device Regulation; European Health Data Space
  • HL7 — FHIR interoperability standard
  • SNOMED International and Regenstrief Institute — clinical terminology and LOINC standards
  • Organisation for Economic Co-operation and Development — health data governance