CLOGS

The tool followed a simple 'Track, get trends, apply advice' structure on a daily, weekly and monthly basis.

Many families in Singapore rely on foreign domestic workers (FDWs) to support elderly loved ones at home, including during serious illness and end-of-life care. These caregivers often spend the most time with patients day to day, yet have little structured support to recognise what matters, communicate changes clearly, or know when to escalate concerns.

Over the past month, we explored how changes in health, comfort, and wellbeing are noticed and acted upon in home caregiving contexts. We focused on helping caregivers (including FDWs) surface early signals of deterioration, without turning them into clinicians or increasing their burden.

Rather than formal training, this work centres on structured observation, shared language, and timely escalation — helping caregivers capture what they already see in ways families and clinicians can meaningfully act on.

Opportunity: Why this matters

Palliative care in Singapore is often introduced late. While 70–80% of people who die would benefit from palliative care, only about 40% receive it, typically very close to death. A major contributor is that early signs of decline at home are missed, normalised, or not escalated in time.

Families and FDWs may notice changes — fatigue, pain, confusion, emotional distress — but these observations are informal, inconsistently communicated, and hard for clinicians to act on between appointments.

Across interviews, we saw a consistent pattern:

• Caregivers already observe and track informally, but without structure

• Judgement-heavy moments are the hardest to navigate

• Clinicians lack visibility into what happens between visits

This matters in a rapidly ageing society where most older adults prefer to age at home and serious illness is increasingly managed in households. When early signs are missed, the cost is human: avoidable distress, crisis hospitalisations, and loss of dignity.

What success would look like

We are still refining how best to measure impact and what the baselines are, but early discussions point to three meaningful indicators:

• Caregivers and FDWs feel more confident noticing and escalating concerns, without guessing or overstepping.

• Clinicians receive earlier, clearer signals that support better prioritisation and intervention.

• Care outcomes improve through earlier escalation and fewer last-minute crises.

Caregivers captured 9 symptoms on a 0-5 scale everyday, expressed in simpler terms to reduce abstraction.

Velocity: What we built and learned

Over the past month, we developed and tested caregiver logging prototypes with caregivers, FDWs, and palliative care clinicians.

We achieved:

• Designed simple, non-clinical prompts reflecting real home observations

• Embedded moment-of-need guidance without replacing professional judgement

• Iterated language, emotional realism, and escalation clarity based on feedback

Key learnings:

• Structure reduces cognitive and emotional load for caregivers

• Judgement (“is this concerning?”) is harder than task execution

• Logging only works if someone is clearly responsible for responding

• Standalone tools risk shifting burden onto caregivers

All data was showcased in both a long form timeline and week by week breakdown

Traction: Early signals from real users

Testing with caregivers, FDWs, and clinicians surfaced consistent signals:

• Caregivers immediately recognised the scenarios as real

• Logs helped translate vague concern into clearer signals

• FDWs valued having shared language rather than relying on intuition

• Clinicians emphasised that value lies in earlier visibility and agreed escalation, not caregiver training

These signals suggest genuine relevance, and point clearly toward integration with care workflows, not standalone tools.

What’s next: Clinician-shaped caregiver logs

The next phase focuses on testing a build-your-own logs model, where clinicians create small, patient-specific logging tools tailored to what matters most for that individual.

1. Move from fixed checklists to clinician-shaped logs

Rather than one-size-fits-all tracking, clinicians can:

• Select or remove prompts per patient

• Focus logs on key risks or concerns

• Keep logging intentionally small and targeted

This reframes logging from “daily assessment” to purposeful observation.

2. Use log design to clarify care intent and escalation

Shaping a log forces clarity on:

• What changes matter

• When escalation is needed

• Who is responsible for responding

The log becomes a shared contract between clinician and caregiver, translating care intent into everyday observation.

3. Test signal quality, not data volume

We will explore whether clinician-shaped logs:

• Produce clearer, more actionable signals

• Reduce noise and alert fatigue

• Support earlier, more confident decisions

This will be tested qualitatively first, through case walkthroughs and reflection.

4. Keep caregiver effort low

This model only works if it respects caregiver capacity:

• Logs that take 1–2 minutes

• Simple, FDW-friendly language

• Prompts that evolve as conditions change

5. Decide, with evidence, whether to scale

At the end of the next phase, we aim to answer:

• Does this surface earlier, clearer signals?

• Does it reduce caregiver uncertainty without adding burden?

• Does it fit real-world care workflows?

If the answers are weak, we pivot or stop. If strong, this model could form the basis for a scalable, integrated caregiver–clinician logging approach aligned with national palliative care priorities.