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Decision Support for Health Policy and Planning: Methods, Models and Technologies based on Existing Health Care Data

Austrian COMET k-project (Competence Centre for Excellent Technologies)
Coordinator: Vienna University of Technology, 10 Austrian partners

Duration: July 2014 – June 2018, currently past-project data analysis phase

The Austrian health care system incurs costs of over EUR 30 billion per year (Statistik Austria 2013). The bulk of the costs (77 %) are publicly financed. While the volume of health services required is increasing (e.g., because of demographic change), resources remain limited. Basing health policy and planning decisions on research evidence can help to tackle this problem. There is an urgent need for the evaluation of new health technologies, services, infrastructure, and organizational changes as well as for the development of improved technologies for the analysis, planning and control of health systems. The UK, for example, spent about 1.5 % of the health system costs on research and development in 2011 (HM Treasury 2013). A solution to these challenges, which countries face world-wide, would thus carry a market potential of up to EUR 350 million per year for Austria.

Today, decision support in health care is usually based on evidence from studies of limited size, but not yet on the analysis of large volumes of routinely collected health care data (“real world” data). The reason for this deficiency is that the need for technical solutions grows with the volume of data and the number of different data sources that must be linked. Despite great advances made during the last decade, decision support technology for health policy and planning, with general applicability and reproducible solutions, is still not available.

DEXHELPP is dedicated to filling this gap by combining academic excellence with professional implementation in order to develop new methods and technologies that, based on the existing data, help (1) analysing the status quo, (2) making reliable prognoses, and (3) evaluating the consequences of interventions. The research programme focuses on all relevant interdisciplinary topics, with approaches and research questions from data security and data management (e.g., record linkage, k-anonymity), statistical methods (e.g., robust statistics), causal inference, mathematical and decision-analytic modelling and simulation (e.g., parameterisation, validation), visualization, and public health. The K-Project will run a scientific research server with routine data in order to test the developed methods.

The project is designed to cover all relevant areas within this complex process, from data management via analysis and modelling through to user friendly presentation of results and quality assurance. For this task, existing cooperation schemes provide a firm substantial and conceptual knowledge base. All relevant fundamental technological competencies from academic and applied research are provided by the consortium members coming from universities, competence centres, and R&D SMEs (Research & Development Small and Medium Enterprises). The latter add their marketing know-how to the new solutions. Some of the most important actual decision-makers in Austria complete the consortium with their application-oriented expertise.

Beyond the potential on the Austrian market, there is a great and growing demand on the international market. DEXHELPP is optimally positioned for both national as well as for international emerging markets in a medium- and long-term perspective.

Professor Heinz Katschnig, CEO of IMEHPS.research, is the responsible key researcher for Project 1.4 ‘Pathways of Service Utilization’