Leonie Sundmacher

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. 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. 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. 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. 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.

To investigate whether negative changes in their own health (i.e. health shocks) or in that of a smoking or obese household member, lead smokers to quit smoking and obese individuals to lose weight. The study is informed by economic models (‘rational addiction’ and ‘demand for health’ models) which offer hypotheses on the relationship between health shocks and health-related behaviour. Each hypothesis was tested applying a discrete-time hazard model with random effects using up to ten waves of the German Socioeconomic Panel (GSOEP) and statistics on cigarette, food and beverage prices provided by the Federal Statistical Office. Health shocks had a significant positive impact on the probability that smokers quit during the same year in which they experienced the health shock. Health shocks of a smoking household member between year t−2 and t−1 also motivated smoking cessation, although statistical evidence for this was weaker. Health shocks experienced by obese individuals or their household members had, on the other hand, no significant effect on weight loss, as measured by changes in Body Mass Index (BMI). The results of the study suggest that smokers are aware of the risks associated with tobacco consumption, know about effective strategies to quit smoking, and are willing to quit for health-related reasons. In contrast, there was no evidence for changes in health-related behaviour among obese individuals after a health shock.

The common starting point of many studies scrutinizing the factors underlying health inequalities is that material, cultural-behavioural, and psycho-social factors affect the distribution of health systematically through income, education, occupation, wealth or similar indicators of socioeconomic structure. However, little is known regarding if and to what extent these factors can assert systematic influence on the distribution of health of a population independent of the effects channelled through income, education, or wealth. Using representative data from the German Socioeconomic Panel, we apply Fields' regression based decomposition techniques to decompose variations in health into its sources. Controlling for income, education, occupation, and wealth, we assess the relative importance of the explanatory factors over and above their effect on the variation in health channelled through the commonly applied measures of socioeconomic status. The analysis suggests that three main factors persistently contribute to variance in health: the capability score, cultural-behavioural variables and to a lower extent, the materialist approach. Of the three, the capability score illustrates the explanatory power of interaction and compound effects as it captures the individual's socioeconomic, social, and psychological resources in relation to his/her exposure to life challenges. Models that take a reductionist perspective and do not allow for the possibility that health inequalities are generated by factors over and above their effect on the variation in health channelled through one of the socioeconomic measures are underspecified and may fail to capture the determinants of health inequalities.

Fragestellung: Ziel der Studie war eine kleinräumige Darstellung der regionalen Unterschiede der häufigsten medizinisch vermeidbaren Sterbefälle für die 439 Kreise und kreisfreien Städte in Deutschland. Methode: Die Studie basiert auf der Todesursachenstatistik der Statistischen Ämter der Bundesländer. Die diagnosebezogenen Sterbefälle im Zeitraum 2000 bis 2004 wurden altersstandardisiert und hinsichtlich ihrer regionalen Verteilung analysiert. Berücksichtigt wurden neben ischämischen Herzkrankheiten und Krankheiten des zerebrovaskulären Systems auch Hypertonie und Hochdruckkrankheiten, Leberkrankheiten, Verkehrsunfälle, mehrere Krebserkrankungen sowie 24 weitere Todesursachen, die als medizinisch vermeidbar klassifiziert wurden. Ergebnisse und Schlussfolgerung: Während die länderbezogene Betrachtung nur grobe Aussagen über ein Nordost-Süd-Gefälle zulässt, zeigen sich auf Kreisebene indikationsspezifisch große Unterschiede. Insgesamt führen bösartige Erkrankungen der weiblichen Brust und der Lunge, Bronchien und Trachea bei Männern die Liste der vermeidbaren Sterbefälle an. Der vielfach diskutierte Ost-West-Unterschied der Mortalität wird vor allem durch eine Konzentration von Herz-Kreislauferkrankungen mit Todesfolge in den neuen Bundesländern bedingt. Der Grund für diesen Trend ist vermutlich eine Kombination aus unterschiedlichen Lebens- und Ernährungsgewohnheiten zu Zeiten der DDR und einer aktuell schlechteren sozioökonomischen Lage in den neuen Bundesländern. Bei den meisten karzinogenen Krankheiten ist ein Ost-West-Gefälle hingegen nicht zu erkennen. Hier zeichnet sich ein Nord-Süd Gradient ab. Ob diese Ungleichheit durch strukturelle Faktoren des Gesundheitssystems wie Arzt- oder Krankenhausbettendichte bedingt ist oder ob Faktoren außerhalb des Gesundheitswesens, wie der sozioökonomische Status dafür verantwortlich sind, sollte Gegenstand weiterer Forschung sein. Aim: The aim of this study is to identify small areas in Germany burdened by exceptionally high rates of amenable mortality using the 439 counties as unit of analysis. Methods: To overcome shortcomings of conventional mortality measures, we construct an indicator for amenable mortality (AM) which captures deaths that should not occur given current medical knowledge and technology. We age-standardize individual-level data on mortality for the years 2000–2004 and plot the distribution of disease-specific AM on country maps. We consider deaths following ischaemic heart disease, cerebrovascular diseases, hypertension, diseases of the liver, traffic accidents, several cancer types and 24 other diseases that are classified as amenable to health care. The data is taken from the causes-of-death statistics (provided by Destatis). Results: AM significantly differs between small areas within and between German federal states (Bundeslaender). Breast cancer and lung cancer in men are the most common AM-causes in Germany. The often discussed mortality-gap between East and West Germany is predominantly driven by differences in amenable deaths following cardiovascular diseases. However, the maps of most carcinogenic deaths show a north-south gradient rather than an east-west difference.