Ranking Hospitals on Surgical Mortality: The Importance of Reliability Adjustment

We examined the implications of reliability adjustment on hospital mortality with surgery.We used national Medicare data (2003–2006) for three surgical procedures: coronary artery bypass grafting (CABG), abdominal aortic aneurysm (AAA) repair, and pancreatic resection.We conducted an observational study to evaluate the impact of reliability adjustment on hospital mortality rankings. Using hierarchical modeling, we adjusted hospital mortality for reliability using empirical Bayes techniques. We assessed the implication of this adjustment on the apparent variation across hospitals and the ability of historical hospital mortality rates (2003–2004) to forecast future mortality (2005–2006).The net effect of reliability adjustment was to greatly diminish apparent variation for all three operations. Reliability adjustment was also particularly important for identifying hospitals with the lowest future mortality. Without reliability adjustment, hospitals in the “best” quintile (2003–2004) with pancreatic resection had a mortality of 7.6 percent in 2005–2006; with reliability adjustment, the “best” hospital quintile had a mortality of 2.7 percent in 2005–2006. For AAA repair, reliability adjustment also improved the ability to identify hospitals with lower future mortality. For CABG, the benefits of reliability adjustment were limited to the lowest volume hospitals.Reliability adjustment results in more stable estimates of mortality that better forecast future performance. This statistical technique is crucial for helping patients select the best hospitals for specific procedures, particularly uncommon ones, and should be used for public reporting of hospital mortality.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/79322/1/HESR_1158_sm_appendix2.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/79322/2/j.1475-6773.2010.01158.x.pd

Observational Intensity Bias Associated with Illness Adjustment: Cross Sectional Analysis of Insurance Claims

Objective: To determine the bias associated with frequency of visits by physicians in adjusting for illness, using diagnoses recorded in administrative databases. Setting: Claims data from the US Medicare program for services provided in 2007 among 306 US hospital referral regions. Design: Cross sectional analysis. Participants 20% sample of fee for service Medicare beneficiaries residing in the United States in 2007 (n=5 153 877)

(EIN)FACH? : Komplexität, Wissen, Fortschritt und die Grenzen der Germanistik

Spätestens seit den gesellschaftlichen Modernisierungsschüben in den sechziger Jahren identifiziert auch die Germanistik Erkenntnis- und Wissenszuwachs, ja allgemeiner den "Fortschritt" ihres Fachs, mit Komplexitätserhöhung. Vor diesem Hintergrund erscheint es mir wenig plausibel, die seitdem erfolgten inneren Ausdifferenzierungen und interdisziplinären Grenzüberschreitungen als durch Identitätsverlust, Zerstreuung und Desintegration gekennzeichnete Niedergangsszenarien zu beschreiben. Die Veränderungen gehorchen der immanenten Logik germanistischer Forschung, einer "disziplinierten", auf Leistung ausgerichteten, an kooperativen Großforschungsvorhaben partizipierenden Wissensproduktion

Inflammation, insulin resistance, and diabetes-mendelian randomization using CRP haplotypes points upstream

Background Raised C-reactive protein (CRP) is a risk factor for type 2 diabetes. According to the Mendelian randomization method, the association is likely to be causal if genetic variants that affect CRP level are associated with markers of diabetes development and diabetes. Our objective was to examine the nature of the association between CRP phenotype and diabetes development using CRP haplotypes as instrumental variables. Methods and Findings We genotyped three tagging SNPs (CRP + 2302G > A; CRP + 1444T > C; CRP + 4899T > G) in the CRP gene and measured serum CRP in 5,274 men and women at mean ages 49 and 61 y (Whitehall II Study). Homeostasis model assessment-insulin resistance (HOMA-IR) and hemoglobin A1c (HbA1c) were measured at age 61 y. Diabetes was ascertained by glucose tolerance test and self-report. Common major haplotypes were strongly associated with serum CRP levels, but unrelated to obesity, blood pressure, and socioeconomic position, which may confound the association between CRP and diabetes risk. Serum CRP was associated with these potential confounding factors. After adjustment for age and sex, baseline serum CRP was associated with incident diabetes (hazard ratio = 1.39 [95% confidence interval 1.29-1.51], HOMA-IR, and HbA1c, but the associations were considerably attenuated on adjustment for potential confounding factors. In contrast, CRP haplotypes were not associated with HOMA-IR or HbA1c (p=0.52-0.92). The associations of CRP with HOMA-IR and HbA1c were all null when examined using instrumental variables analysis, with genetic variants as the instrument for serum CRP. Instrumental variables estimates differed from the directly observed associations (p=0.007-0.11). Pooled analysis of CRP haplotypes and diabetes in Whitehall II and Northwick Park Heart Study II produced null findings (p=0.25-0.88). Analyses based on the Wellcome Trust Case Control Consortium (1,923 diabetes cases, 2,932 controls) using three SNPs in tight linkage disequilibrium with our tagging SNPs also demonstrated null associations. Conclusions Observed associations between serum CRP and insulin resistance, glycemia, and diabetes are likely to be noncausal. Inflammation may play a causal role via upstream effectors rather than the downstream marker CRP

A global surveillance system for crop diseases

To satisfy a growing demand for food, global agricultural production must increase by 70% by 2050. However, pests and crop diseases put global food supplies at risk. Worldwide, yield losses caused by pests and diseases are estimated to average 21.5% in wheat, 30.0% in rice, 22.6% in maize, 17.2% in potato, and 21.4% in soybean (1); these crops account for half of the global human calorie intake (2). Climate change and global trade drive the distribution, host range, and impact of plant diseases (3), many of which can spread or reemerge after having been under control (4). Though many national and regional plant protection organizations (NPPOs and RPPOs) work to monitor and contain crop disease outbreaks, many countries, particularly low-income countries (LICs), do not efficiently exchange information, delaying coordinated responses to prevent disease establishment and spread. To improve responses to unexpected crop disease spread, we propose a Global Surveillance System (GSS) that will extend and adapt established biosecurity practices and networking facilities into LICs, enabling countries and regions to quickly respond to emerging disease outbreaks to stabilize food supplies, enhancing global food protection

Physiologic Characterization of Type 2 Diabetes–Related Loci

For the past two decades, genetics has been widely explored as a tool for unraveling the pathogenesis of diabetes. Many risk alleles for type 2 diabetes and hyperglycemia have been detected in recent years through massive genome-wide association studies and evidence exists that most of these variants influence pancreatic β-cell function. However, risk alleles in five loci seem to have a primary impact on insulin sensitivity. Investigations of more detailed physiologic phenotypes, such as the insulin response to intravenous glucose or the incretion hormones, are now emerging and give indications of more specific pathologic mechanisms for diabetes-related risk variants. Such studies have shed light on the function of some loci but also underlined the complex nature of disease mechanism. In the future, sequencing-based discovery of low-frequency variants with higher impact on intermediate diabetes-related traits is a likely scenario and identification of new pathways involved in type 2 diabetes predisposition will offer opportunities for the development of novel therapeutic and preventative approaches

Modelling the impact of women’s education on fertility in Malawi

Many studies have suggested that there is an inverse relationship between education and number of children among women from sub-Saharan Africa countries, including Malawi. However, a crucial limitation of these analyses is that they do not control for the potential endogeneity of education. The aim of our study is to estimate the role of women’s education on their number of children in Malawi, accounting for the possible presence of endogeneity and for nonlinear effects of continuous observed confounders. Our analysis is based on micro data from the 2010 Malawi Demographic Health Survey, and uses a flexible instrumental variable regression approach. The results suggest that the relationship of interest is affected by endogeneity and exhibits an inverted U-shape among women living in rural areas of Malawi, whereas it exhibits an inverse (nonlinear) relationship for women living in urban areas

Monetary Policy Regimes and the Volatility of Long-Term Interest Rates

This paper addresses two important questions that have, so far, been studied separately in the literature. First, the paper aims at explaining the high volatility of long-term interest rates observed in the data, which is hard to replicate using standard macro models. Building a small-scale macroeconomic model and estimating it on U.S. and U.K. data, I show that the policy responses of a central bank that is uncertain about the natural rate of unemployment can explain this volatility puzzle. Second, the paper aims at shedding new light on the distinction between rules and discretion in monetary policy. My empirical results show that using yield curve data may facilitate the empirical discrimination between different monetary policy regimes and that U.S. monetary policy is best understood as originating from a discretionary regime since 1960

Social Spending and Aggregate Welfare in Developing and Transition Economies

Notwithstanding the unprecedented attention devoted to reducing poverty and fostering human development via scaling up social sector spending, there is surprisingly little rigorous empirical work on the question of whether social spending is effective in achieving these goals. This paper examines the impact of government spending on the social sectors (health, education, and social protection) on two major indicators of aggregate welfare (the Inequality-adjusted Human Development Index and child mortality), using a panel dataset comprising 55 developing and transition countries from 1990 to 2009. We find that government social spending has a significantly positive causal effect on the Inequality-adjusted Human Development Index, while government expenditure on health has a significant negative impact on child mortality rate. These results are fairly robust to the method of estimation, the use of alternative instruments to control for the endogeneity of social spending, the set of control variables included in the regressions, and the use of alternative samples