Yebra, MarBermejo, IñigoPalacios Alonso, Miguel ÁngelArias Calleja, Manuel::virtual::3078::600Luque Gallego, Manuel::virtual::3079::600Pérez Martín, Jorge::virtual::3080::600Díez Vegas, Francisco Javier::virtual::6771::600Arias Calleja, ManuelLuque Gallego, ManuelPérez Martín, JorgeDíez Vegas, Francisco JavierArias Calleja, ManuelLuque Gallego, ManuelPérez Martín, JorgeDíez Vegas, Francisco JavierArias Calleja, ManuelLuque Gallego, ManuelPérez Martín, JorgeDíez Vegas, Francisco Javier2024-05-202024-05-202017-01-11http://doi.org/10.1177/0272989X16685088https://hdl.handle.net/20.500.14468/12450Markov influence diagrams (MIDs) are a new type of probabilistic graphical models that extend influence diagrams in the same way as Markov decision trees extend decision trees. They have been designed to build state-transition models, mainly in medicine, and perform cost-effectiveness analysis. Using a causal graph that may contain several variables per cycle, MIDs can model various features of the patient without multiplying the number of states; in particular, they can represent the history of the patient without using tunnel states. OpenMarkov, an open-source tool, allows the decision analyst to build and evaluate MIDs—including cost-effectiveness analysis and several types of deterministic and probabilistic sensitivity analysis—with a graphical user interface, without writing any code. This way, MIDs can be used to easily build and evaluate complex models whose implementation as spreadsheets or decision trees would be cumbersome or unfeasible in practice. Furthermore, many problems that previously required discrete event simulation can be solved with MIDs, i.e., within the paradigm of state-transition models, in which many health economists feel more comfortable.eninfo:eu-repo/semantics/openAccessjournal articleMarkov modelsinfluence diagramscost-effectiveness analysisoutcomes research