Understand the barrier
Start with what is difficult in practice rather than assuming a diagnosis tells you what someone needs.
About Work Health Lab
Evidence should be useful, traceable and honest about its limits.
Work Health Lab is an independent research and tools project for employers dealing with the point where health and work meet: sickness absence, returning to work, workplace barriers, adjustments and support.
Why it exists
Recording an absence is not the same as working out what should happen next.
Employers have plenty of forms, policies and systems for recording what happened. The harder problem is understanding what is getting in the way of successful work, what could change, and what should be reviewed next.
Connect it to the work
Look at the tasks, environment, hours, demands and support around the person.
Turn evidence into action
Use research, official guidance and data to make the next conversation or decision more useful.
Who is behind it
Created by Duncan Trevithick.
Duncan builds software and data products. Work Health Lab is being built to make difficult work-and-health information easier to understand and more useful in real decisions.
Scope of expertise
Work Health Lab does not present its founder as a clinician, occupational-health practitioner or employment lawyer. The site is designed to make source material, public data and practical next steps easier to use, not to replace qualified professional judgement.
How the research works
A published number should be traceable back to its source.
The research pipeline is deliberately more mechanical than a normal article: official source data → stored source record → defined calculation → published result and method.
1. Use identifiable sources
Current structured data includes NHS England fit-note statistics and Office for Health Improvement and Disparities Fingertips data. Other pages link to official guidance and published evidence where it is used.
2. Keep the source record
Source snapshots are retained so a calculated result can be tied back to the material used to produce it.
3. Define the calculation
Derived statistics use named calculation rules. Shares should expose their numerator and denominator where possible, rather than publishing an unexplained score.
4. Publish the limits
Geography, coverage, time period and important methodological limits belong beside the finding, not hidden after it.
AI and automation
Work Health Lab does not create statistics by asking an AI model to estimate them. AI may help classify or organise source material and support drafting, but numerical research claims should be calculated from stored source data using defined rules and remain traceable to the underlying source.
Editorial standard
What we try to make true of every useful page.
The aim is not to sound authoritative. It is to make it easy for a reader to see what is known, where it came from and what still needs judgement.
- Keep important sources visible.
- Separate sourced facts from interpretation and practical suggestions.
- Show the period and geography behind statistics.
- Do not claim first-party employer evidence that does not exist.
- Update computed research when its source data changes.
- Correct errors rather than preserving a claim because it has already been published.
Commercial transparency
Some tools are free. Work Health Lab may also sell paid planning tools.
The business model should be visible rather than disguised as editorial independence. A commercial product may sit beside free research and tools, but it does not change how a public statistic is calculated or what source it comes from.
Work Health Lab is not medical or legal advice.
Decisions about an individual's health, treatment, legal rights or complex employment situation may need an appropriately qualified professional.