Here's a concept from decision theory that I think is especially useful in healthcare, business, and everyday life.
It's called the value of information.
The basic question is:
How much would knowing something change what I should do?
We often assume that having more information is inherently beneficial.
Sometimes it is.
But information has costs.
Time.
Money.
Attention.
Potential anxiety.
And sometimes the new information doesn't meaningfully change the available decisions.
A clinical example
Imagine a patient with uncomplicated low back pain.
The clinical examination suggests a low-risk presentation.
There are no concerning neurological findings or other red flags.
The patient asks whether an MRI would help.
The relevant question isn't simply whether the MRI might reveal something.
It might.
The more important question is whether the information would change management in a way that improves the patient's outcome.
If the likely treatment plan remains the same regardless of the imaging result, the expected clinical value of the test may be limited.
Of course, imaging can become valuable when there are concerning findings, significant neurological deficits, or circumstances in which the results would alter treatment.
The principle isn't that testing is bad.
It's that testing should be connected to decisions.
A business example
Imagine you're considering purchasing a new piece of equipment for your physical therapy clinic.
You could spend weeks researching every available option.
Read dozens of reviews.
Compare technical specifications.
Ask other clinicians.
But suppose you've already identified two products that satisfy your clinical requirements and fit your budget.
At some point, additional research may have very little chance of changing your decision.
The value of another hour of investigation becomes small.
A parenting example
A child asks whether he can stay up an additional 15 minutes.
You might try to predict exactly how those 15 minutes will affect his mood tomorrow.
But perhaps the decision is low stakes and easily reversible.
You may not need more information.
You may simply need to choose a reasonable boundary and observe the result.
The formal idea
In decision theory, the expected value of information depends on whether new knowledge improves the quality of the decision enough to justify obtaining it.
A simplified approach is to ask:
What would I do if the answer were yes?
What would I do if the answer were no?
If both answers lead to the same action, the information may have limited immediate decision value.
That isn't universally true. Information can also provide reassurance, improve understanding, establish prognosis, or have value for future decisions.
But the question is an excellent starting point.
Why I like this concept
It changes how you approach uncertainty.
Instead of trying to eliminate uncertainty before acting, you identify which uncertainties actually matter.
Some uncertainties deserve careful investigation.
Others can remain unresolved without preventing a good decision.