Demographic Change, Morbidity and Utilization: Projection of the Outpatient Volume of Services.

AIM: The influence of the demographic change and the impact on the entire health care system have been discussed by different theories (Expansion of Morbidity, Compression of Morbidity, Bimodality of Morbidity). This paper aims to project for the outpatient health care of statutory health insurance, the influence of the demographic development, the size and structure of statutory health insured and the change in morbidity based utilization on the outpatient volume of services for 2020. METHOD: Considered impact factors and their trend specifications are separately modelled and modular combined as components of scenarios. RESULTS: The compound annual growth rate of the outpatient volume of services varies between almost 0 and 2.2%. CONCLUSION: For 2020 a moderate increase of outpatient volume of services for statutory health insurance is expected, if costs of dying are taken into account, even though cross-sectional data for 2011 show a decrease in expenditure profiles with increased age. Projections with the scenario technique can support strategic decision making by estimating likely trends and effects of measures given the causal process in health care systems.

A model integration approach linking signalling and gene-regulatory logic with kinetic metabolic models.

Systems biology has to increasingly cope with large- and multi-scale biological systems. Many successful in silico representations and simulations of various cellular modules proved mathematical modelling to be an important tool in gaining a solid understanding of biological phenomena. However, models spanning different functional layers (e.g. metabolism, signalling and gene regulation) are still scarce. Consequently, model integration methods capable of fusing different types of biological networks and various model formalisms become a key methodology to increase the scope of cellular processes covered by mathematical models. Here we propose a new integration approach to couple logical models of signalling or/and gene-regulatory networks with kinetic models of metabolic processes. The procedure ends up with an integrated dynamic model of both layers relying on differential equations. The feasibility of the approach is shown in an illustrative case study integrating a kinetic model of central metabolic pathways in hepatocytes with a Boolean logical network depicting the hormonally induced signal transduction and gene regulation events involved. In silico simulations demonstrate the integrated model to qualitatively describe the physiological switch-like behaviour of hepatocytes in response to nutritionally regulated changes in extracellular glucagon and insulin levels. A simulated failure mode scenario addressing insulin resistance furthermore illustrates the pharmacological potential of a model covering interactions between signalling, gene regulation and metabolism.