Automated Generation of Discrete Event Simulation Models for the Economic Assessment of Interventions for Rare Diseases Using the RaDiOS Ontology

Abstract

Collection and synthesis of evidence is a key task in the development of the simulation models required for health technology assessment (HTA). The implementation of some of these models, such as discrete event simulation (DES) models, presents technical difficulties and requires higher technical skills. This work presents a method to extract the knowledge stored in an ontology, Rare Disease Ontology for Simulation (RaDiOS), to generate a DES model. RaDiOS is a domain ontology focused on collecting evidence on rare diseases for simulation models. We reviewed and enhanced the ontology to increase its semantic expressiveness. Besides, we developed a transformation tool (RaDiOS-MTT) to automatically generate DES models from the knowledge stored in the ontology. We defined a set of “synthetic” diseases, with simple natural histories, represented them in RaDiOS, and compared the results of the automatically generated simulation models with their manually created counterparts. Afterwards, we used a case study on a real intervention (newborn screening for profound biotinidase deficiency) to validate our approach. The automatically generated models for the synthetic diseases mimicked their programmatic counterparts in structure and results. The same happened to the model for profound biotinidase deficiency.