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Applied Use Case

Remote Monitoring & Virtual Wards

A handover problem disguised as a device problem

Remote monitoring generates data. But data without governance is noise. Virtual wards and remote monitoring create handover problems: who owns the alert, who escalates, who closes the loop. The Seven Flows make it safe.

The technology works. The governance doesn't.

Remote monitoring is often framed as a device problem - connectivity, data quality, integration. But the harder problem is governance: when an alert fires, who is responsible? When data crosses organisational boundaries, who can act on it? When the patient deteriorates, how does escalation work?

Alert ownership

A device generates an alert. The patient is on a virtual ward. The GP is clinically responsible. The monitoring service sees the data. Who acts? Without explicit responsibility, alerts go unacknowledged.

Escalation pathways

Patient deteriorates at 2am. Data shows it. But what's the escalation path? 111? A&E? Community response team? The device knows something is wrong. The system doesn't know what to do.

Consent across boundaries

Monitoring data collected by the acute trust. Patient now at home. Community team needs to see it. Social care might need access. Was consent given for this? Is sharing lawful?

Closing the loop

Alert was sent. Someone acted. But did the outcome feed back? Did the referring team learn what happened? Without closed loops, same failures repeat.

Governance infrastructure for device data

Each flow addresses a specific governance failure in remote monitoring. Together, they create the substrate for safe, scalable virtual wards.

Identity

Patient-device binding

Ensure data from the device belongs to the right patient. Identity verified across the monitoring pathway, not assumed from device registration.

Consent

Sharing across organisations

Explicit consent for monitoring data to flow to community teams, GPs, acute services. Evaluated at each handover, not assumed from initial setup.

Provenance

Data quality and source

Know where monitoring data came from, what device generated it, how it was validated. Clinical decisions based on data of known quality.

Clinical Intent

Why this monitoring

Thresholds are clinically defined, not device defaults. The reason for monitoring is explicit. Receiving teams understand the clinical context.

Alert & Responsibility

Who owns the alert

When an alert fires, responsibility is explicit. Someone is named, reachable, and accountable. Acknowledgement is required, not assumed.

Service Routing

Escalation pathways

Alerts route to the right service based on clinical context. Escalation paths are defined, tested, auditable. Patients reach appropriate care.

Outcome

Closed loops

What happened after the alert? Outcomes documented, feedback loops closed, learning captured. Virtual ward impact becomes measurable.

The infrastructure that implements the flows

SteadyTrace is our remote monitoring platform built on the Seven Flows. Device agnostic, clinically governed, designed for neighbourhood health.

Multi-device ingestion

Apple Watch, Fitbit, Withings, CGMs, clinical-grade RPM devices - single integration, unified governance.

Clinical validation

Physiological plausibility checks, data quality scoring, device fingerprinting. Data validated before it reaches clinical teams.

Protocol-driven thresholds

Clinician-defined protocols, not device defaults. Thresholds linked to clinical intent. Context preserved.

Governed escalation

Alerts route with responsibility assignment. Acknowledgement required. Escalation paths auditable.

Outcome tracking

Episodes close with documented outcomes. Feedback loops inform system learning.

Standards-based

UK Core FHIR R4, SNOMED CT, DCB 0129/0160 alignment. No proprietary lock-in.

Where governed remote monitoring helps

Virtual Wards

Hospital-at-home with governance

Patients monitored at home instead of hospital beds. Alerts escalate to the right team. Responsibility transfers are explicit. Outcomes documented for system learning.

Long-term Conditions

COPD, heart failure, diabetes monitoring

Continuous monitoring with clinically meaningful thresholds. Deterioration detected early. Escalation reaches the right service with context.

Post-discharge

Recovery monitoring after acute episodes

Patients leave hospital with monitoring in place. Complications caught before readmission. Community teams receive governed handovers.

Frailty

Neighbourhood-level monitoring for at-risk populations

Movement, activity, vital signs for frail patients. Alerts to community teams with context. Proactive intervention before crisis.

Ready to govern your remote monitoring?

We work with neighbourhood health teams who want virtual wards that work - with governance infrastructure that makes device data clinically safe.

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