1,386 research outputs found
Country differences in the diagnosis and management of coronary heart disease : a comparison between the US, the UK and Germany
Background
The way patients with coronary heart disease (CHD) are treated is partly determined by non-medical factors. There is a solid body of evidence that patient and physician characteristics influence doctors' management decisions. Relatively little is known about the role of structural issues in the decision making process. This study focuses on the question whether doctors' diagnostic and therapeutic decisions are influenced by the health care system in which they take place. This non-medical determinant of medical decision-making was investigated in an international research project in the US, the UK and Germany.
Methods
Videotaped patients within an experimental study design were used. Experienced actors played the role of patients with symptoms of CHD. Several alternative versions were taped featuring the same script with patients of different sex, age and social status. The videotapes were shown to 384 randomly selected primary care physicians in the three countries under study. The sample was stratified on gender and duration of professional experience. Physicians were asked how they would diagnose and manage the patient after watching the video vignette using a questionnaire with standardised and open-ended questions.
Results
Results show only small differences in decision making between British and American physicians in essential aspects of care. About 90% of the UK and US doctors identified CHD as one of the possible diagnoses. Further similarities were found in test ordering and lifestyle advice. Some differences between the US and UK were found in the certainty of the diagnoses, prescribed medications and referral behaviour. There are numerous significant differences between Germany and the other two countries. German physicians would ask fewer questions, they would order fewer tests, prescribe fewer medications and give less lifestyle advice.
Conclusion
Although all physicians in the three countries under study were presented exactly the same patient, some disparities in the diagnostic and patient management decisions were evident. Since other possible influences on doctors treatment decisions are controlled within the experimental design, characteristics of the health care system seem to be a crucial factor within the decision making process
Assortment optimisation under a general discrete choice model: A tight analysis of revenue-ordered assortments
The assortment problem in revenue management is the problem of deciding which
subset of products to offer to consumers in order to maximise revenue. A simple
and natural strategy is to select the best assortment out of all those that are
constructed by fixing a threshold revenue and then choosing all products
with revenue at least . This is known as the revenue-ordered assortments
strategy. In this paper we study the approximation guarantees provided by
revenue-ordered assortments when customers are rational in the following sense:
the probability of selecting a specific product from the set being offered
cannot increase if the set is enlarged. This rationality assumption, known as
regularity, is satisfied by almost all discrete choice models considered in the
revenue management and choice theory literature, and in particular by random
utility models. The bounds we obtain are tight and improve on recent results in
that direction, such as for the Mixed Multinomial Logit model by
Rusmevichientong et al. (2014). An appealing feature of our analysis is its
simplicity, as it relies only on the regularity condition.
We also draw a connection between assortment optimisation and two pricing
problems called unit demand envy-free pricing and Stackelberg minimum spanning
tree: These problems can be restated as assortment problems under discrete
choice models satisfying the regularity condition, and moreover revenue-ordered
assortments correspond then to the well-studied uniform pricing heuristic. When
specialised to that setting, the general bounds we establish for
revenue-ordered assortments match and unify the best known results on uniform
pricing.Comment: Minor changes following referees' comment
The failure of suicide prevention in primary care: family and GP perspectives - a qualitative study
Background Although Primary care is crucial for suicide prevention, clinicians tend to report completed suicides in their care as non-preventable. We aimed to examine systemic inadequacies in suicide prevention from the perspectives of bereaved family members and GPs.Methods Qualitative study of 72 relatives or close friends bereaved by suicide and 19 General Practitioners who have experienced the suicide of patients.Results Relatives highlight failures in detecting symptoms and behavioral changes and the inability of GPs to understand the needs of patients and their social contexts. A perceived overreliance on anti-depressant treatment is a major source of criticism by family members. GPs tend to lack confidence in the recognition and management of suicidal patients, and report structural inadequacies in service provision.Conclusions Mental health and primary care services must find innovative and ethical ways to involve families in the decision-making process for patients at risk of suicide
Broken symmetry states and divergent resistance in suspended bilayer graphene
Graphene [1] and its bilayer have generated tremendous excitement in the
physics community due to their unique electronic properties [2]. The intrinsic
physics of these materials, however, is partially masked by disorder, which can
arise from various sources such as ripples [3] or charged impurities [4].
Recent improvements in quality have been achieved by suspending graphene flakes
[5,6], yielding samples with very high mobilities and little charge
inhomogeneity. Here we report the fabrication of suspended bilayer graphene
devices with very little disorder. We observe fully developed quantized Hall
states at magnetic fields of 0.2 T, as well as broken symmetry states at
intermediate filling factors , , and . The
devices exhibit extremely high resistance in the state that grows
with magnetic field and scales as magnetic field divided by temperature. This
resistance is predominantly affected by the perpendicular component of the
applied field, indicating that the broken symmetry states arise from many-body
interactions.Comment: 23 pages, including 4 figures and supplementary information; accepted
to Nature Physic
Sources of Variation in Physician Adherence with Clinical Guidelines: Results from a Factorial Experiment
BACKGROUND: Health services research has documented the magnitude of health care variations. Few studies focus on provider level sources of variation in clinical decision making-for example, which primary care providers are likely to follow clinical guidelines, with which types of patient. OBJECTIVES: To estimate: (1) the extent of primary care provider adherence to practice guidelines and the unconfounded influence of (2) patient attributes and (3) physician characteristics on adherence with clinical practice guidelines. DESIGN: In a factorial experiment, primary care providers were shown clinically authentic video vignettes with actors portrayed different “patients” with identical signs of coronary heart disease (CHD). Different types of providers were asked how they would manage the different “patients” with identical CHD symptoms. Measures were taken to protect external validity. RESULTS: Adherence to some guidelines is high (over 50% of physicians would follow a third of the recommended actions), yet there is low adherence to many of them (less than 20% would follow another third). Female patients are less likely than males to receive 4 of 5 types of physical examination (p < .03); older patients are less likely to be advised to stop smoking (p < .03). Race and SES of patients had no effect on provider adherence to guidelines. A physicians’ level of experience (age) appears to be important with certain patients. CONCLUSIONS: Physician adherence with guidelines varies with different types of “patient” and with the length of clinical experience. With this evidence it is possible to appropriately target interventions to reduce health care variations by improving physician adherence with clinical guidelines
A dynamic network approach for the study of human phenotypes
The use of networks to integrate different genetic, proteomic, and metabolic
datasets has been proposed as a viable path toward elucidating the origins of
specific diseases. Here we introduce a new phenotypic database summarizing
correlations obtained from the disease history of more than 30 million patients
in a Phenotypic Disease Network (PDN). We present evidence that the structure
of the PDN is relevant to the understanding of illness progression by showing
that (1) patients develop diseases close in the network to those they already
have; (2) the progression of disease along the links of the network is
different for patients of different genders and ethnicities; (3) patients
diagnosed with diseases which are more highly connected in the PDN tend to die
sooner than those affected by less connected diseases; and (4) diseases that
tend to be preceded by others in the PDN tend to be more connected than
diseases that precede other illnesses, and are associated with higher degrees
of mortality. Our findings show that disease progression can be represented and
studied using network methods, offering the potential to enhance our
understanding of the origin and evolution of human diseases. The dataset
introduced here, released concurrently with this publication, represents the
largest relational phenotypic resource publicly available to the research
community.Comment: 28 pages (double space), 6 figure
Microscopic Polarization in Bilayer Graphene
Bilayer graphene has drawn significant attention due to the opening of a band
gap in its low energy electronic spectrum, which offers a promising route to
electronic applications. The gap can be either tunable through an external
electric field or spontaneously formed through an interaction-induced symmetry
breaking. Our scanning tunneling measurements reveal the microscopic nature of
the bilayer gap to be very different from what is observed in previous
macroscopic measurements or expected from current theoretical models. The
potential difference between the layers, which is proportional to charge
imbalance and determines the gap value, shows strong dependence on the disorder
potential, varying spatially in both magnitude and sign on a microscopic level.
Furthermore, the gap does not vanish at small charge densities. Additional
interaction-induced effects are observed in a magnetic field with the opening
of a subgap when the zero orbital Landau level is placed at the Fermi energy
Mapping gene associations in human mitochondria using clinical disease phenotypes
Nuclear genes encode most mitochondrial proteins, and their mutations cause diverse and debilitating clinical disorders. To date, 1,200 of these mitochondrial genes have been recorded, while no standardized catalog exists of the associated clinical phenotypes. Such a catalog would be useful to develop methods to analyze human phenotypic data, to determine genotype-phenotype relations among many genes and diseases, and to support the clinical diagnosis of mitochondrial disorders. Here we establish a clinical phenotype catalog of 174 mitochondrial disease genes and study associations of diseases and genes. Phenotypic features such as clinical signs and symptoms were manually annotated from full-text medical articles and classified based on the hierarchical MeSH ontology. This classification of phenotypic features of each gene allowed for the comparison of diseases between different genes. In turn, we were then able to measure the phenotypic associations of disease genes for which we calculated a quantitative value that is based on their shared phenotypic features. The results showed that genes sharing more similar phenotypes have a stronger tendency for functional interactions, proving the usefulness of phenotype similarity values in disease gene network analysis. We then constructed a functional network of mitochondrial genes and discovered a higher connectivity for non-disease than for disease genes, and a tendency of disease genes to interact with each other. Utilizing these differences, we propose 168 candidate genes that resemble the characteristic interaction patterns of mitochondrial disease genes. Through their network associations, the candidates are further prioritized for the study of specific disorders such as optic neuropathies and Parkinson disease. Most mitochondrial disease phenotypes involve several clinical categories including neurologic, metabolic, and gastrointestinal disorders, which might indicate the effects of gene defects within the mitochondrial system. The accompanying knowledgebase (http://www.mitophenome.org/) supports the study of clinical diseases and associated genes
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Risk measures for direct real estate investments with non-normal or unknown return distributions
The volatility of returns is probably the most widely used risk measure for real estate. This is rather surprising since a number of studies have cast doubts on the view that volatility can capture the manifold risks attached to properties and corresponds to the risk attitude of investors. A central issue in this discussion is the statistical properties of real estate returns—in contrast to neoclassical capital market theory they are mostly non-normal and often unknown, which render many statistical measures useless. Based on a literature review and an analysis of data from Germany we provide evidence that volatility alone is inappropriate for measuring the risk of direct real estate.
We use a unique data sample by IPD, which includes the total returns of 939 properties across different usage types (56% office, 20% retail, 8% others and 16% residential properties) from 1996 to 2009, the German IPD Index, and the German Property Index. The analysis of the distributional characteristics shows that German real estate returns in this period were not normally distributed and that a logistic distribution would have been a better fit. This is in line with most of the current literature on this subject and leads to the question which indicators are more appropriate to measure real estate risks. We suggest that a combination of quantitative and qualitative risk measures more adequately captures real estate risks and conforms better with investor attitudes to risk. Furthermore, we present criteria for the purpose of risk classification
A quantitative risk assessment of waterborne infectious disease in the inundation area of a tropical monsoon region
Flooding and inundation are annual events that occur during the rainy season in Cambodia, and inundation has a strong relationship with human health. This study simulated the coliform bacteria distribution using a hydraulic model and estimated the impact of inundation on public health using a dose–response model. The model parameters were calibrated using field survey data from Cambodia and obtained good agreement with the coliform group count distribution. The results suggest that the impact of inundation on human health is most noticeable in residential areas. The annual average risk of infection during medium-sized flood events is 0.21. The risk due to groundwater use ranges from 0.12 to 0.17 in inundation areas and reaches as high as 0.23 outside the inundation areas. The risk attributed to groundwater use is therefore higher than that for surface water use (0.02–0.06), except in densely populated areas at the city center. There is a high risk for infection with waterborne disease in residential areas, and the annual average risk during small flood events is 0.94. An assessment of possible countermeasures to reduce the risk shows that the control of inundation may bring more risk to public health in Cambodia. Shallower inundation water (<0.3 m) leads to a higher risk of infection, but if the depth is greater than 2 m, the risk is low in residential areas.The simulated results explain the spatial distributions of infection risk, which are vitally important for determining the highest priority places with relatively high risk and will be helpful for decision makers when considering the implementation of countermeasures
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