Bayesian network approach to Drug Economics Decision Making

Consider the following problem:

A relatively cheap drug (drug A) has been used for many years to treat patients with disease X. The drug is considered quite successful since data reveals that 85% of patients using it have a ‘good outcome’ which means they survive for at least 2 years. The drug is also quite cheap, costing on average $100 for a prolonged course. The overall “financial benefit” of the drug (which assumes a ‘good outcome’ is worth $5000 and is defined as this figure minus the cost) has a mean of $4985.

There is an alternative drug (drug B) that a number of specialists in disease X strongly recommend. However, the data reveals that only 65% of patients using drug B survive for at least 2 years (Fig. 1(b)). Moreover, the average cost of a prolonged course is $500. The overall “financial benefit” of the drug has a mean of just $2777.

On seeing the data the Health Authority recommends a ban against the use of drug B. Is this a rational decision?

The answer turns out to be no. The short paper here explains this using a simple Bayesian network model that you can run (by downloading the free copy of AgenaRisk)