Wearables & Consumer Health Technology

Purpose

Scope

Requirements

• Consumer-generated data must be interpreted in the context of the device, sensor, algorithm, Intended Use and available validation.
• Displayed precision is not automatically clinical accuracy. A highly detailed numerical display must not be treated as clinically accurate solely because of the precision with which it is presented.
• Consumer and clinical-use contexts must be distinguished. Consumer label ≠ clinical validity. Intended Use, Claims, available validation and the specific context of use matter. A device or feature intended for wellness, fitness or general information must not be treated without sufficient basis as though it were validated for diagnostic or clinical decision-making.
• Professionals must distinguish raw measurement, derived metric, algorithmic score and clinical interpretation. Each processing step may introduce additional assumptions, models, transformations and sources of error.
• Proprietary or algorithmic scores such as readiness, recovery, sleep, stress, biological age or similar composite scores must not be treated as validated clinical outcomes solely because of their technical presentation. Proprietary score ≠ validated clinical interpretation.
• Validation of a device or algorithm must match the specific claim and context of use. Device, Sensor, Algorithm, Population, Setting and Outcome should be considered when transferring evidence. Where relevant, performance should also be assessed across material user groups or subgroups for which comparability may matter.
• Validation of one device generation, software version or algorithm must not automatically be transferred to materially changed hardware, software, sensors or computational models. Validation belongs to a defined version and context, not to a product name forever.
• Single values and trends must be distinguished. Trends are meaningfully comparable only where the device, measurement method and relevant conditions of use are sufficiently comparable.
• Missing, erroneous or artifact-affected data must be considered as possible data-quality problems and must not be interpreted as biological change without appropriate assessment.
• Wearable data may be useful for education, monitoring or trend observation without thereby becoming clinically validated measurements or diagnostic findings.
• Wearable data must not automatically be equated with laboratory data or clinical measurements. This also applies to consumer CGM and other continuously generated measurements: a real-time or trend value is not automatically equivalent to a laboratory value or diagnosis. Where biomarkers or laboratory-like interpretations are involved, H-02 Biomarkers & Laboratory Data also applies.
• Health claims based on wearable or consumer-technology data must comply with H-01 Health Information & Claims and U-03 Evidence & Scientific Communication.
• Professionals may draw individualized conclusions or recommendations from consumer data only to the extent supported by competence, role, applicable rules and context.
• A disclaimer expands neither the clinical validity of a device nor the Professional's Scope of Practice.
• Abnormal or unexpected consumer data must neither be presented as confirmed diagnosis nor dismissed without appropriate context. Where professional assessment is outside scope, appropriate referral is required.
• Where red flags or possible acute danger are present, IHPSO Referral Levels and local emergency procedures apply. An alert is a signal for attention, not automatically a diagnosis. An alert should be interpreted in the context of device function, data quality, symptoms and situation. Consumer device alerts do not replace medical triage.
• Professionals, Providers and Organisations must handle personal device data with appropriate confidentiality and comply with applicable privacy, consent, access and security requirements. The legal status of such data may depend on who holds it, how it is used, the service involved and the applicable jurisdiction. H-03 does not replace legal privacy assessment.
• Data sharing, screenshots, dashboards or public case examples must not disclose personal or identifiable health information unless an appropriate basis and required consent or other lawful basis exists.
• Where an IHPSO Evidence Classification is used, it must apply to a specific device, algorithm, measurement or outcome claim and must not be assigned broadly to an entire device or product category.