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Chronic liver disease · monitoring In co-design — tertiary hepatology

MyLiverHealth

Decompensation in chronic liver disease happens fast — but the system watches it slowly. We are configuring continuous monitoring on top of clinic-based care, so the call lands before the crisis does.

Layer
Consumer + clinician intelligence
Status
In co-design — tertiary hepatology setting
Funding
Co-investigator partnership · pipeline
Partners
Tertiary hepatology service · clinical co-investigators
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Liver disease decompensates suddenly. The system watches it through infrequent visits.

Patients with chronic liver disease can move from stable to decompensated in days. Standard monitoring is clinic-based and intermittent. By the time someone presents at hospital, they are often already in crisis — and admission, with all its costs and harms, becomes the system's only response.

Liver decompensation has well-known early signals — weight changes from fluid retention, encephalopathy onset, GI symptoms. But the people best positioned to notice these signals are the patient and their family, in the home, day by day. The clinician who can act on them is at the hospital, weeks away in the appointment cycle.

In the gap between clinical contacts, the patient and family carry the watchful work alone, often without the structured tools or clinical reference points to know what counts as concerning. Most reach the hospital only when the trajectory is already bad — when the system's only available response is admission.

The configuration is upside down. The signal happens at home; the response capacity sits at the hospital; nothing connects them between visits.

Continuous monitoring at home, integrated with the clinical team that can act.

MyLiverHealth is being designed as a daily weight-transmission app with automated clinical alerts — moving the noticing work into the patient's daily life, with the recognising and risk-carrying work supported by an integrated clinician dashboard.

Operation 01
Noticing
Before

Decompensation signals were noticed by patient and family without structured guidance, then surfaced sporadically at clinical visits.

After

Daily weight transmission via app, plus structured symptom check-ins, capture early signals as they emerge — at home, in real time.

Operation 02
Recognising
Before

Pattern recognition happened at clinic visits, with whatever data the patient could recall. Significant changes between visits were often missed.

After

Automated alerts flag significant weight changes and symptom patterns. Clinician sees the trend, not just the snapshot.

Operation 03
Carrying risk
Before

Risk between visits sat entirely with patient and family. They escalated to ED when worried — often when the trajectory was already bad.

After

Risk is shared: continuous monitoring infrastructure provides clinician visibility, so escalation happens earlier and with better information.

Operation 04
Making the call
Before

The clinical call typically came reactively — at hospital admission, when decompensation was already established.

After

The call lands proactively — clinic intervention, medication adjustment, or early outpatient management — before a crisis develops.

Where it operates and under what governance.

MyLiverHealth is in active co-design with a tertiary hepatology service, clinical co-investigators, and patient partners. The configuration is being prototyped on the CareMappr workbench before any commitment to a pilot — the Sandpit's standard sequence.

Like every Sandpit configuration, the system supports clinical authority — it does not generate diagnostic recommendations or replace clinical judgment. It surfaces continuous data into the clinician's workflow.

What the configuration is producing.

MyLiverHealth is in co-design phase. Outcomes will be defined and measured against the configuration once it enters governed pilot.

Earlier
detection of decompensation signals — before crisis presentation
design objective, in co-design
Continuous
visibility for the clinical team between visits
design objective
Fewer
avoidable hospital admissions for decompensation
projected outcome

When the four operations are mapped honestly, the answer is often that noticing belongs with the patient, and the system's job is to make that noticing visible to clinicians who can act. That's a configuration problem, not a technology problem.

The Sandpit method, demonstrated across the system.

Same method, different domains.

Each Sandpit configuration applies the same four-operation decomposition to a different capacity problem. What stays constant is the method.

Have a similar capacity challenge?

Bring it to the Sandpit. We'll diagnose where capacity is lost, configure what should change, and test it in a governed live setting before you commit at scale.