M. Arias and F. J. Díez. Cost-effectiveness analysis with influence diagrams. Technical Report CISIAD-14-02, UNED, Madrid, 2014.
17 pages. PDF (487 KB), BibTeX entry.
Introduction: Cost-effectiveness analysis (CEA) is used increasingly in medicine to determine whether
the health benefit of an intervention outweighs the economic cost. Decision trees, the standard deci-
sion modeling technique for non-temporal domains, can only perform CEAs for very small problems.
Objective: To develop a method for CEA in problems involving several dozen variables.
Methods: We explain how to build influence diagrams (IDs) that explicitly represent cost and effectiveness. We propose an algorithm for evaluating cost-effectiveness IDs directly, i.e., without expanding an equivalent decision tree.
Results: The evaluation of an ID returns a set of intervals for the willingness to pay—separated by incremental cost-effectiveness ratios (ICERs)—and, for each interval, the cost, the effectiveness, and the optimal intervention. The algorithm that evaluates the ID directly is in general much more effi- cient than the brute-force method, which is in turn more efficient than the expansion of an equivalent decision tree. Using OpenMarkov, an open-source software tool that implements this algorithm, we have been able to perform CEAs on two medical IDs whose equivalent decision trees contain billions of branches.
Conclusion: IDs can perform CEA on many problems that could not be analyzed with decision trees.
- M. Arias and F. J. Díez. Cost-effectiveness analysis with sequential decisions. Technical Report CISIAD-11-01. UNED, Madrid, Spain, 2011.
- Cost-effectiveness analysis with OpenMarkov.