English

Abstract

The approach of ProHTA (Prospective Health Technology Assessment) is to understand the impact of medical processes and technologies as early as possible. Therefore, simulation techniques are utilized to estimate the effects of innovative health technologies and find potentials of efficiency enhancement within the supply chain of healthcare. Data management for healthcare simulations is required as heterogeneous data is needed both as simulation input data and for validation purposes. The main problem is the heterogeneity of the data and the initially unknown and continuously changing demands of the simulation. Also, data quality considerations are necessary to quantify the reliability of simulation output. A solution has to consider all of these aspects and must be extensible to cope with changing requirements. As the structure of the data is not known in advance, a generic database schema is required. This paper proposes an approach to store heterogeneous statistical data in an RDF-triplestore. Semantic annotations based on conceptual models are utilized to describe the datasets. Additionally, a special query language helps loading the data into the simulation. The feasibility of the approach has been demonstrated in a prototype implementation. We discuss the benefits of this approach as well as remaining challenges and issues.