Waiting times in the ambulatory sector - the case of chronically Ill patients

Aims: First, the influence of determinants on the waiting times of chronically ill patients in the ambulatory sector is investigated. The determinants are subdivided into four groups: (1) need, (2) socio-economic factors, (3) health system and (4) patient time pressures. Next, the influence of waiting times on the annual number of consultations is examined to assess whether the existing variation in waiting times influences the frequency of medical examinations. The waiting times of chronically ill patients are analysed since regular ambulatory care for this patient group could both improve treatment outcomes and lower costs. Data sources: Individual data from the 2010 Representative Survey conducted by the National Association of Statutory Health Insurance Physicians (KBV) together with regional data from the Federal Office of Construction and Regional Planning. Study design: This is a retrospective observational study. The dependent variables are waiting times in the ambulatory sector and the number of consultations of General Practitioners (GPs) and specialist physicians in the year 2010. The explanatory variables of interest are ‘need’ and ‘health system’ in the first model and ‘length of waiting times’ in the second. Negative binomial models with random effects are used to estimate the incidence rate ratios of increased waiting times and number of consultations. Subsequently, the models are stratified by urban and rural areas. Results: In the pooled regression the factor ‘privately insured’ shortens the waiting time for treatment by a specialist by approximately 28% (about 3 days) in comparison with members of the statutory health insurance system. The category of insurance has no influence on the number of consultations of GPs. In addition, the regression results stratified by urban and rural areas show that in urban areas the factor ‘privately insured’ reduces the waiting time for specialists by approximately 35% (about 3.3 days) while in rural areas there is no evidence of statistical influence. In neither of the models, however, does the waiting time have a documentable effect on the number of consultations in the ambulatory sector. Conclusions: In our random sample, characteristics of the health care system have an influence on the waiting time for specialists, but the waiting time has no documentable effect on the number of consultations in the ambulatory sector. In the present analysis this applies to consultations of both GPs and specialists. Nevertheless, it does not rule out the possibility that the length of waiting times might influence the treatment outcomes of certain patient populations

Revisiting Health Inequalities in Germany

Background: Our aim is a wide-ranging analysis of the determinants of health ine-qualities, which scrutinizes the propositions of the main theoretical approaches (ma-terialist or neo-materialist approach, cultural and behavioural approaches, psycho-social explanations, the life-course perspective and the newer capability approach) within one model thereby offering insights into their relative explanatory power. Methods: Using Fields’s (2004) regression techniques we decompose total variance into its factors and thereby generate insights about the contribution of specific vari-ables (and approaches) to explain health inequalities in Germany. Moreover, we stratify our sample by age and compare the contribution of each of the factors (con-stituting the different approaches) in four age groups. Data: The data is taken from the 2006 wave of the German Socioeconomic Panel (GSOEP). The GSOEP is a representative longitudinal study of private households and their members above the age of 16, which was started in 1984 and originally consisted of 12 000 individuals. We use the physical health scores derived from the 2006 GSOEP data wave as the dependent variable in our analysis. The scores are derived using an algorithm presented by Anderson et al., which is based on the 2004 GSOEP data wave as the norm sample. Furthermore, we use a comprehensive set of covariates capturing information on demographics, socio-economic background, life-style, social capital, self-assessed stress levels, feelings of national belonging, insurance status and regional levels of pollution, crime, noise and provision of health care to test the relative weight of the theoretical explanations. Results: Overall, we find that understanding the mechanisms of health inequalities crucially depends on taking a holistic perspective on individual’s health. Socio-eco-nomic factors, working conditions and lifestyle independently, interacted and com-pounded explain variation in health in specific age-groups in our analysis. Studies which take a reductionist approach and do not allow for the possibility that health inequalities are generated by a complex co-action of many factors may forego in-sightful findings. Online-Version published by Universitätsverlag der TU Berlin (www.univerlag.tu-berlin.de)

Optimal design of stimulus experiments for robust discrimination of biochemical reaction networks

Motivation: Biochemical reaction networks in the form of coupled ordinary differential equations (ODEs) provide a powerful modeling tool for understanding the dynamics of biochemical processes. During the early phase of modeling, scientists have to deal with a large pool of competing nonlinear models. At this point, discrimination experiments can be designed and conducted to obtain optimal data for selecting the most plausible model. Since biological ODE models have widely distributed parameters due to, e.g. biologic variability or experimental variations, model responses become distributed. Therefore, a robust optimal experimental design (OED) for model discrimination can be used to discriminate models based on their response probability distribution functions (PDFs). Results: In this work, we present an optimal control-based methodology for designing optimal stimulus experiments aimed at robust model discrimination. For estimating the time-varying model response PDF, which results from the nonlinear propagation of the parameter PDF under the ODE dynamics, we suggest using the sigma-point approach. Using the model overlap (expected likelihood) as a robust discrimination criterion to measure dissimilarities between expected model response PDFs, we benchmark the proposed nonlinear design approach against linearization with respect to prediction accuracy and design quality for two nonlinear biological reaction networks. As shown, the sigma-point outperforms the linearization approach in the case of widely distributed parameter sets and/or existing multiple steady states. Since the sigma-point approach scales linearly with the number of model parameter, it can be applied to large systems for robust experimental planning. Availability: An implementation of the method in MATLAB/AMPL is available at http://www.uni-magdeburg.de/ivt/svt/person/rf/roed.html. Contact: [email protected] Supplementary information: Supplementary data are are available at Bioinformatics online

Power-to-Syngas: A Parareal Optimal Control Approach

A chemical plant layout for the production of syngas from renewable power, H2O and biogas, is presented to ensure a steady productivity of syngas with a constant H2-to-CO ratio under time-dependent electricity provision. An electrolyzer supplies H2 to the reverse water-gas shift reactor. The system compensates for a drop in electricity supply by gradually operating a tri-reforming reactor, fed with pure O2 directly from the electrolyzer or from an intermediate generic buffering device. After the introduction of modeling assumptions and governing equations, suitable reactor parameters are identified. Finally, two optimal control problems are investigated, where computationally expensive model evaluations are lifted viaparareal and necessary objective derivatives are calculated via the continuous adjoint method. For the first time, modeling, simulation, and optimal control are applied to a combination of the reverse water-gas shift and tri-reforming reactor, exploring a promising pathway in the conversion of renewable power into chemicals

Singular Points of Reactive Distillation Systems

For the conceptual design of countercurrently operated reactive distillation columns, fast methods are needed to estimate potential top and bottom products. The possible column bottom product composition can be determined from the stable singular points of a batch reactive reboiler. In a similar manner the top product composition can be obtained from the stable singular points of a batch reactive condenser. Geometrically, the singular points of both batch processes are located on a common potential singular point surface (PSPS) whose trajectory depends on the reaction stoichiometry and the phase equilibria. At the singular points, the PSPS intersects a reaction kinetic surface that is dependent on the reaction rate expression and the phase equilibrium of a reference component. Based on the singularity analysis, a single-feed reactive distillation column can be designed. Several hypothetical and real reaction systems are analyzed to illustrate the singularity analysis and the design procedure. Copyright © 1999–2013 John Wiley & Sons, Inc. All Rights Reserved. [accessed 2013 August 15th