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Flowing Evidence into Cost Analysis: Powerful Ways with Number-needed-to-treat (NNT)

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Cost Analysis & NNT Example

This example serves several purposes.

  • It illustrates the critical importance of including time period in NNT in order to better understand efficacy.
  • It shows how you can use NNT in an effectiveness and cost analysis.

1. Read the fictional scenario below. This is typical of the kinds of issues faced by doctors, P & T committees, QI staff, etc., daily.

2. Think about your reaction.

3. Then look at the graphic to see how important NNT can be. Remember, NNT is always to be associated the length of the time of study. This example drives this home.

Fictional Scenario

  • Lifetime risk of hip fracture in women is 15% with significant mortality (20-30% of women die in the first year following hip fracture).
  • HRT is now found to have many risks. Other fracture prevention drugs have risks. There is a new (fictional) drug on the market that has fewer risks and that many docs are starting to use on high and moderate risk women. The drug is getting a lot of press attention and has good evidence behind it.
  • Many women in your organization are requesting information and treatment for prevention of fractures. Many are asking about this new drug.
  • One year of treatment is cheaper than alendronate.

Should you treat these women with this new drug? How do you decide?


In our fictional scenario, by switching from our current care to our new drug, we will have done the following:

  • Significantly reduced quality of care. We will now prevent roughly 80 hip fractures compared to roughly 138 prevented with current treatment in a course of 14.5 years.
  • Significantly increased our expenses. We will now have spent $3.6MM less in prevention treatment, but will have significant new expenses due to the increase in hip fractures.

This examples shows several things:

  1. You can do a simple, yet powerful "back-of-the-envelope" analysis using a spreadsheet tool.
  2. You need to look at prevalence data in your population, consider what you are currently doing, assess the evidence and then do sensitivity analyses to explore potential impacts of practice change.
  3. Flowing evidence into your cost analysis is highly important and revealing. In this instance we see that even though a new drug may be less expense per year of treatment, we are actually significantly reducing our quality of care AND increasing our expenses by making a switch.
  4. To compute a cost per benefit, which you can then use for comparison purposes:

    Quick Equation #1: NNT x study period x dollars per time unit

    OR #2: NNT x study period cost

  5. Many times people talk about NNT without including the appropriate associated time period. We see by this example, that it is this difference in time periods between the old agent and the new that has made the significant difference.


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