Answer to Question #198193 in Excel for Duke Banda

Question

(b) Compute the Expected Value perfect Information (EVPI) and interpret it.

Answer 1

The expected value of perfect information is the price that a healthcare decision maker would be willing to pay to have perfect information regarding all factors that influence which treatment choice is preferred as the result of a cost-effectiveness analysis. This is the value (in money terms) of removing all uncertainty from such an analysis. EVPI is calculated as the difference in the monetary value of health gain associated with a decision between therapy alternatives between when the choice is made on the basis of with currently available information (i.e. uncertainty in the factors of interest) and when the choice is made based on perfect information (no uncertainty in all factors).

Example

Suppose you have an objective variable V and decision variable D, which is discrete (a list of possible values), and one or more uncertain variables, X, defined by probability distributions. The expected value of V given decision D, and the uncertainties about X is simply: Mean(V)

An optimal decision before you have any further information about X (sometimes called the Bayes' decision), is Db=ArgMax(Mean(V),D)

The expected value given this decision is: Whatif(Mean(V),D,Db)

or more simply Max(Mean(V),D)

Given a particular value of Xi of X, the optimal decision would be Di=EhatIf(ArgMax(V,D),X,Xi)

The value of the objective given Di would be: Mean(Max(V,D)

The EVPI is simply the difference: EVPI= Mean(Max(V,D))-Max(Mean(V),D)