Entry and Competition in Local Hospital Markets

There has been considerable consolidation in the hospital industry in recent years. Over 900 deals occurred from 1994-2000, and many local markets, even in large urban areas, have been reduced to monopolies, duopolies or triopolies. This surge in consolidation has led to concern about its effect on competition in local markets for hospital services. In this paper we examine the impact of market structure on competition in local hospital markets – specifically, does competition increase with the number of firms? We extend the entry model developed by Bresnahan and Reiss to make use of quantity information and apply it to data on the US hospital industry. The results from the estimation are striking. In the hospital markets we examine, entry leads to markets quickly becoming competitive. Entry reduces variable profits and increases quality. Indeed, most of the effects of entry come from having a second and possibly a third firm enter the market. The use of quantity information allows us to infer that entry is welfare increasing.analysis of health care markets

Household Demand for Employer-Based Health Insurance

We use the 1996 Medical Expenditure Panel Survey to estimate a model of household demand for employer-based health insurance, explicitly investigating differences in behavior between households with two potential sources of coverage and those with one source. Own and cross-price elasticities are estimated for three types of health plans, including exclusive provider organizations, any provider organizations, and mixed provider organizations. We find that the premium, family size, income, and wealth significantly affect demand. Our elasticity estimates reveal an overall, small behavioral response to changes in price with respect to health plan switching and take-up. Finally, we discuss the implications of our findings with respect to employer benefit design.

Moral Hazard Matters: Measuring Relative Rates of Underinsurance Using Threshold Measures

This paper illustrates the impact of moral hazard for estimating relative rates of underinsurance and to present an adjustment method to correct for this source of bias. Individuals or households are often classified as underinsured if out-of-pocket spending on medical care relative to income exceeds some threshold. We show that, without adjustment, this common threshold measure of underinsurance will underestimate the number with low levels of insurance coverage due to moral hazard. We propose an adjustment method and apply it to the specific case of estimating the difference in rates of underinsurance among small- versus large-firm workers with full-year, employer-sponsored insurance. Using data from the 2005 Medical Expenditure Panel Survey, we find that after applying the adjustment, the underinsurance rate of small-firm households increases by approximately 20% with the adjustment for moral hazard and the difference in underinsurance rates between large firm and small firm households widens substantially. Adjusting for moral hazard makes a sizeable difference in the estimated prevalence of underinsurance using a threshold measure.

COP27 climate change conference: urgent action needed for Africa and the world

The 2022 report of the Intergovernmental Panel on Climate Change (IPCC) paints a dark picture of the future of life on earth, characterised by ecosystem collapse, species extinction, and climate hazards such as heatwaves and floods.1 These are all linked to physical and mental health problems, with direct and indirect consequences of increased morbidity and mortality. To avoid these catastrophic health effects across all regions of the globe, there is broad agreement—as 231 health journals argued together in 2021—that the rise in global temperature must be limited to less than 1.5oC compared with pre-industrial levels

CONSTRUCCIÓN DE UN MODELO DE PREDICCIÓN PARA APOYO AL DIAGNÓSTICO DE DIABETES (CONSTRUCTION OF A PREDICTION MODEL TO SUPPORT THE DIABETES DIAGNOSIS)

ResumenEn el presente trabajo se procesaron datos relevantes de 768 pacientes para apoyar en la predicción de diabetes de las personas. Entre las variables consideradas en el estudio se emplearon: glucosa, presión sanguínea, insulina, edad, entre otros, por medio de sistemas de aprendizaje automático y sistemas expertos con aprendizaje supervisado para generar árboles de decisión, así como el análisis de resultados del algoritmo de predicción J48, con las herramientas BigML y Weka, respectivamente. Esta investigación será la base para desarrollar un sistema experto que apoye los diagnósticos de diabetes en comunidades rurales que carezcan de personal médico o equipo.Palabra(s) Clave: Aprendizaje supervisado, BigML, Machine Learning, Sistema experto, Weka. AbstractIn the present work, relevant data of 768 patients were processed to help the prediction of diabetes in people. Among the variables considered in the study were used: glucose, blood pressure, insulin, age, to name a few, through of machine learning and expert systems with supervised learning to generate decision trees, as well as the analysis of results of prediction algorithm J48, using the BigML and Weka tools, respectively. This research will be the start for developing an expert system that helps diabetes diagnoses in marginalized people that lack doctors or equipment.Keywords: BigML, Expert system, Machine Learning, Supervised learning, Weka

Monoids and Maximal Codes

In recent years codes that are not Uniquely Decipherable (UD) are been studied partitioning them in classes that localize the ambiguities of the code. A natural question is how we can extend the notion of maximality to codes that are not UD. In this paper we give an answer to this question. To do this we introduce a partial order in the set of submonoids of a monoid showing the existence, in this poset, of maximal elements that we call full monoids. Then a set of generators of a full monoid is, by definition, a maximal code. We show how this definition extends, in a natural way, the existing definition concerning UD codes and we find a characteristic property of a monoid generated by a maximal UD code.Comment: In Proceedings WORDS 2011, arXiv:1108.341

A new elaboration process of the superconducting Tl2Ba2Cu1O6 phase with Tc=90K

International audienceWe have synthesized high quality ceramic Tl2Ba2Cu1O6+δ (2201) samples using the high pressure, high temperature route. At high oxygen content, the structure is orthorhombic and the samples are metallic but non-superconducting. Upon lowering the oxygen content, the symmetry changes from orthorhombic to tetragonal or pseudo-tetragonal. In the latter phase, the maximum superconducting critical temperature reaches 92 K. Optical micrographs show large 2201 grains and some traces of impurity phases like Tl2Ba2O5, Ba2Cu3Ox and CuO. X-ray diffraction shows only the 2201 phase. Plasma emission spectroscopy indicates that the global sample stoichiometry is Tl:Ba:Cu=2:2:1. This analysis proves that the high pressure route effectively prevents the thallium evaporation. HREM investigations exclude the possibility of cation vacancies. Microprobe analyses (EDAX) show no variation of the cation stoichiometry between the 2201 grains. X-ray diffraction on a superconducting single crystal yields a refined composition Tl1.94Ba2Cu1.06O6

Construction of a dairy microbial genome catalog opens new perspectives for the metagenomic analysis of dairy fermented products

Microbial communities of traditional cheeses are complex and insufficiently characterized. The origin, safety and functional role in cheese making of these microbial communities are still not well understood. Metagenomic analysis of these communities by high throughput shotgun sequencing is a promising approach to characterize their genomic and functional profiles. Such analyses, however, critically depend on the availability of appropriate reference genome databases against which the sequencing reads can be aligned. We built a reference genome catalog suitable for short read metagenomic analysis using a low-cost sequencing strategy. We selected 142 bacteria isolated from dairy products belonging to 137 different species and 67 genera, and succeeded to reconstruct the draft genome of 117 of them at a standard or high quality level, including isolates from the genera Kluyvera, Luteococcus and Marinilactibacillus, still missing from public database. To demonstrate the potential of this catalog, we analysed the microbial composition of the surface of two smear cheeses and one blue-veined cheese, and showed that a significant part of the microbiota of these traditional cheeses was composed of microorganisms newly sequenced in our study. Our study provides data, which combined with publicly available genome references, represents the most expansive catalog to date of cheese-associated bacteria. Using this extended dairy catalog, we revealed the presence in traditional cheese of dominant microorganisms not deliberately inoculated, mainly Gram-negative genera such as Pseudoalteromonas haloplanktis or Psychrobacter immobilis, that may contribute to the characteristics of cheese produced through traditional methods.https://doi.org/10.1186/1471-2164-15-110