Inequality in health care utilization in Germany? Theoretical and empirical evidence for specialist consultation

Aim: In view of increasing concern about a two-class system in the German health care sector, this study investigates the relevance of health insurance schemes and other socioeconomic characteristics to the level of specialist health care provision. Subjects and Methods: Referring to Ronald M. Andersen’s model of health care utilization and more content-based approaches, we implement a negative binomial hurdle regression to estimate the number of specialist visits within the last 12 months. Our data source is the German sample of the first wave of the Survey of Health, Ageing and Retirement in Europe (SHARE) in 2004. Results: The results show that men’s number of specialist visits is markedly sensitive to predisposing and enabling factors, whereas women’s health care utilization depends less on such socioeconomic characteristics. With reference to previous findings concerning general practitioner consultation, the assumption of a bipolar health care system providing general practitioner care primarily to the statutory insured and specialist care to the privately insured is supported empirically as to men. Education, which is considered to be highly correlated with health lifestyles, has a positive effect on medical health care. Every additional year of education increases by about 10% the probability of men seeking specialist consultation. Furthermore, the results indicate an unfavorable situation for the self-employed concerning health care because of their specific employment situation and health insurance coverage. Discussion: The research results suggest the existence of relevant differences in the amount of specialist consultation according to health insurance and other socioeconomic features. Further research could concentrate on the question of whether these inequalities in utilization levels indicate overprovision or underprovision of ambulant health care. Moreover, we recommend longitudinal research that is particularly suited to detangle age and cohort effects

Feasibility Analysis of Open-government Data for the Automated Calculation of the Micro-climatic Attributes of Urban Units of Observation in the City of Vienna

A quantified analysis of the urban climate in general and the urban heat island phenomena in particular is a complex endeavor and requires a variety of data streams. Urban units of observations are meant to specify well-defined spatial domains within a city toward the representation and study of the microclimatic conditions (e.g., via simulation applications). The European Union generally mandates the implementation of open data interfaces. Administrative data is made publicly accessible to increase transparency and to support participation and collaboration. The present contribution analyses the feasibility of open government data for the automated calculation of the microclimatic attributes of urban units of observation in the city of Vienna. The proposed algorithms and framework are briefly introduced to explain which data sources are needed and how the data is classified. Suitable data sources include geo- referenced, two- and three- dimensional vector, raster as well as semantic data. A sample application scenario presents the results of aspect ratio calculation using the example of the inner city of Vienna

A high-speed tunable beam splitter for feed-forward photonic quantum information processing

We realize quantum gates for path qubits with a high-speed, polarization-independent and tunable beam splitter. Two electro-optical modulators act in a Mach-Zehnder interferometer as high-speed phase shifters and rapidly tune its splitting ratio. We test its performance with heralded single photons, observing a polarization-independent interference contrast above 95%. The switching time is about 5.6 ns, and a maximal repetition rate is 2.5 MHz. We demonstrate tunable feed-forward operations of a single-qubit gate of path-encoded qubits and a two-qubit gate via measurement-induced interaction between two photons

Fluorescence optical imaging feature selection with machine learning for differential diagnosis of selected rheumatic diseases

Background and objectiveAccurate and fast diagnosis of rheumatic diseases affecting the hands is essential for further treatment decisions. Fluorescence optical imaging (FOI) visualizes inflammation-induced impaired microcirculation by increasing signal intensity, resulting in different image features. This analysis aimed to find specific image features in FOI that might be important for accurately diagnosing different rheumatic diseases.Patients and methodsFOI images of the hands of patients with different types of rheumatic diseases, such as rheumatoid arthritis (RA), osteoarthritis (OA), and connective tissue diseases (CTD), were assessed in a reading of 20 different image features in three phases of the contrast agent dynamics, yielding 60 different features for each patient. The readings were analyzed for mutual differential diagnosis of the three diseases (One-vs-One) and each disease in all data (One-vs-Rest). In the first step, statistical tools and machine-learning-based methods were applied to reveal the importance rankings of the features, that is, to find features that contribute most to the model-based classification. In the second step machine learning with a stepwise increasing number of features was applied, sequentially adding at each step the most crucial remaining feature to extract a minimized subset that yields the highest diagnostic accuracy.ResultsIn total, n = 605 FOI of both hands were analyzed (n = 235 with RA, n = 229 with OA, and n = 141 with CTD). All classification problems showed maximum accuracy with a reduced set of image features. For RA-vs.-OA, five features were needed for high accuracy. For RA-vs.-CTD ten, OA-vs.-CTD sixteen, RA-vs.-Rest five, OA-vs.-Rest eleven, and CTD-vs-Rest fifteen, features were needed, respectively. For all problems, the final importance ranking of the features with respect to the contrast agent dynamics was determined.ConclusionsWith the presented investigations, the set of features in FOI examinations relevant to the differential diagnosis of the selected rheumatic diseases could be remarkably reduced, providing helpful information for the physician

Ageing in Europe. Empirical Analysis with the Survey of Health, Ageing and Retirement in Europe

Dieser Band versammelt Beiträge zu ausgewählten Konsequenzen der Bevölkerungsalterung, die auf ein Forschungspraktikum im Fach Bevölkerungswissenschaft an der Universität Bamberg zurückgehen. Die behandelten Untersuchungsgegenstände umfassen die Determinanten intergenerationaler instrumenteller Transfers im europäischen Vergleich, die Effekte von Arbeitsmarktstrukturen auf freiwillige und unfreiwillige Frühverrentung in Deutschland sowie den Zusammenhang von Versicherungsart und der Inanspruchnahme allgemeinmedizinischer Leistungen im Alter. Diese aktuellen sozialwissenschaftlichen Fragestellungen werden anhand der Daten der ersten Welle des Survey of Health, Ageing and Retirement in Europe (SHARE) empirisch untersucht.This volume brings together selected contributions on the consequences of population ageing which evolved in an empirical research training course in population studies at the University of Bamberg. The topics ranged from the determinants of intergenerational instrumental transfers in a European comparative perspective, the effects of labor market structures on voluntary and involuntary early retirement in Germany as well as the relation between private and public health insurance and medical treatment for aged people. These actual research questions were empirically investigated using the first wave of the Survey of Health, Ageing and Retirement in Europe (SHARE)

Evaluation of the Temporal Muscle Thickness as an Independent Prognostic Biomarker in Patients with Primary Central Nervous System Lymphoma.

In this study, we assessed the prognostic relevance of temporal muscle thickness (TMT), likely reflecting patient's frailty, in patients with primary central nervous system lymphoma (PCNSL). In 128 newly diagnosed PCNSL patients TMT was analyzed on cranial magnetic resonance images. Predefined sex-specific TMT cutoff values were used to categorize the patient cohort. Survival analyses, using a log-rank test as well as Cox models adjusted for further prognostic parameters, were performed. The risk of death was significantly increased for PCNSL patients with reduced muscle thickness (hazard ratio of 3.189, 95% CI: 2-097-4.848, p < 0.001). Importantly, the results confirmed that TMT could be used as an independent prognostic marker upon multivariate Cox modeling (hazard ratio of 2.504, 95% CI: 1.608-3.911, p < 0.001) adjusting for sex, age at time of diagnosis, deep brain involvement of the PCNSL lesions, Eastern Cooperative Oncology Group (ECOG) performance status, and methotrexate-based chemotherapy. A TMT value below the sex-related cutoff value at the time of diagnosis is an independent adverse marker in patients with PCNSL. Thus, our results suggest the systematic inclusion of TMT in further translational and clinical studies designed to help validate its role as a prognostic biomarker