Search Results (Author:"Perez-Martin,Jorge", Display Type:"Artículo de revista", isMemberOf:"bibliuned:Setarticulo", Journal Name:"Medical Decision Making") - e-spacio
http://e-spacio.uned.es/fez/
Universidad Nacional de Educación a DistanciaspFez 2.1 RC3http://blogs.law.harvard.edu/tech/rssEvaluation of Markov models with discontinuities
http://e-spacio.uned.es/fez/view/bibliuned:95-Jperez-003
Background. Several methods, such as the half-cycle correction and the life-table method, were developed to attenuate the error introduced in Markov models by the discretization of time. Elbasha and Chhatwal have proposed alternative “corrections” based on numerical integration techniques. They present an example whose results suggest that the trapezoidal rule, which is equivalent to the half-cycle correction, is not as accurate as Simpson’s 1/3 and 3/8 rules. However, they did not take into consideration the impact of discontinuities. Objective. To propose a method for evaluating Markov models with discontinuities. Design. Applying the trapezoidal rule, we derive a method that consists of adjusting the model by setting the cost at each point of discontinuity to the mean of the left and right limits of the cost function. We then take from the literature a model with a cycle length of 1 year and a discontinuity on the cost function and compare our method with other “corrections” using as the gold standard an equivalent model with a cycle length of 1 day. Results. As expected, for this model, the life-table method is more accurate than assuming that transitions occur at the beginning or the end of cycles. The application of numerical integration techniques without taking into account the discontinuity causes large errors. The model with averaged cost values yields very small errors, especially for the trapezoidal and the 1/3 Simpson rules. Conclusion. In the case of discontinuities, we recommend applying the trapezoidal rule on an averaged model because this method has a mathematical justification, and in our empirical evaluation, it was more accurate than the sophisticated 3/8 Simpson rule.2020-06-18T00:29:16Z
Pérez-Martín, Jorge
og Bermejo, Iñigo
og Díez, Francisco J.
Markov influence diagrams: a graphical tool for cost-effectiveness analysis
http://e-spacio.uned.es/fez/view/bibliuned:95-Jperez-002
Markov 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.2020-06-17T22:57:50Z
Díez, Francisco J.
og Yebra, Mar
og Bermejo, Iñigo
og Palacios-Alonso, Miguel Angel
og Arias Calleja, Manuel
og Luque, Manuel
og Pérez-Martín, Jorge