Affiliation:
1. Department of Artificial Intelligence, Universidad Nacional de Educación a Distancia (UNED), 28040 Madrid, Spain
Abstract
Cost-effectiveness analysis (CEA) is used increasingly in medicine to determine whether the health benefit of an intervention is worth the economic cost. Discrete event simulation (DES) is playing an increasing role in CEA thanks to several advantages, such as the possibility of modeling time and heterogeneous populations. It is usually implemented with general-purpose programming languages or commercial software packages. To our knowledge, no artificial intelligence technique has been applied to DES for CEA. Our objective is to develop a graphical representation, an algorithm, and a software tool that allows non-programmers to easily build models and perform CEA. We present DESnets (discrete event simulation networks) as a new type of probabilistic graphical model inspired by probabilistic influence diagrams, an algorithm for evaluating and an implementation as an OpenMarkov plug-in. DESnets are compared qualitatively and empirically with six alternative tools using as a running example a model about osteoporosis by the British National Institute for Health and Care Excellence (NICE). In our experiments, the implementation of DESnets allowed the building of a typical DES model declaratively. Its evaluation process ranked among the most efficient. DESnets compare favorably with alternative tools in terms of ease of use, expressive power, transparency, and computational efficiency.
Funder
Spanish Government, co-financed by the European Regional Development
UNED and the Spanish Ministry of Science and Innovation through the Technical Support Staff program
Subject
General Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)
Reference51 articles.
1. Drummond, M.F., Sculpher, M.J., Claxton, K., Stoddart, G.L., and Torrance, G.W. (2015). Methods for the Economic Evaluation of Health Care Programmes, Oxford University Press. [4th ed.].
2. A taxonomy of model structures for economic evaluation of health technologies;Brennan;Health Econ.,2006
3. Modeling good research practices—Overview: A report of the ISPOR-SMDM Modeling Good Research Practices Task Force-1;Caro;Value Health,2012
4. Matching the model with the evidence: Comparing discrete event simulation and state-transition modeling for time-to-event predictions in a cost-effectiveness analysis of treatment in metastatic colorectal cancer patients;Degeling;Cancer Epidemiol.,2018
5. Cohort versus patient level simulation for the economic evaluation of single versus combination immuno-oncology therapies in metastatic melanoma;Gibson;J. Med. Econ.,2019