How to use the lab
From idea to decision
A structured way to test what would need to be true for an intervention to create value.
How the sandboxes are used
Each sandbox helps structure assumptions, test value, and clarify what needs validating next.
What this process does
Intervention idea
Start with a plausible service change or intervention.
Translate assumptions
Turn the idea into explicit assumptions about scale, risk, effect, and cost.
Observe model signal
Review the implied effect on events, cost, and value.
Test uncertainty
Change assumptions to see where the case is robust or fragile.
Clarify what to validate
Identify what matters most and what needs testing next.
Intervention idea
Start with a plausible service change or intervention.
Translate assumptions
Turn the idea into explicit assumptions about scale, risk, effect, and cost.
Observe model signal
Review the implied effect on events, cost, and value.
Test uncertainty
Change assumptions to see where the case is robust or fragile.
Clarify what to validate
Identify what matters most and what needs testing next.
In practice
Two example decision questions
Falls prevention (SafeStep)
Question
Can a falls prevention programme reduce admissions and bed use enough to create value?
Set the base case
Review what the model suggests
Check what matters
Decision signal
The programme appears valuable if it meaningfully reduces falls in a sufficiently high-risk population at a controlled delivery cost.
Waiting list optimisation (WaitWise)
Question
Can waiting list interventions reduce pressure without simply shifting activity elsewhere?
Set the base case
Review what the model suggests
Check what matters
Decision signal
Value is created only if unnecessary activity is genuinely reduced, not redistributed.
Falls prevention (SafeStep)
Question
Can a falls prevention programme reduce admissions and bed use enough to create value?
Set the base case
Review what the model suggests
Check what matters
Decision signal
The programme appears valuable if it meaningfully reduces falls in a sufficiently high-risk population at a controlled delivery cost.
Waiting list optimisation (WaitWise)
Question
Can waiting list interventions reduce pressure without simply shifting activity elsewhere?
Set the base case
Review what the model suggests
Check what matters
Decision signal
Value is created only if unnecessary activity is genuinely reduced, not redistributed.
What this process does not do
- It does not produce a final answer.
- It does not replace formal evaluation.
- It does not remove uncertainty.
What it gives instead
A clearer decision.
This is likely to work if these conditions hold.
One consistent question
Across all sandboxes, the same question sits underneath the model:
What would need to be true for this to create value?