Costs of Measuring Outcomes of Acute Hospital Care in a Longitudinal Outcomes Measurement System

It is widely acknowledged that the measurement of outcomes of care and the comparison of outcomes over time within health care providers and risk-adjusted comparisons among providers are important parts of improving quality and cost-effectiveness of care. However, few studies have assessed the costs of measuring outcomes of care. We sought to evaluate the personnel and financial resources spent for a prospective assessment of outcomes of acute hospital care by health professionals in internal medicine. The study included 15 primary care hospitals participating in a longitudinal outcomes measurement program and 2005 patients over an assessment period with an average duration of 6 months. Each hospital project manager participated in a previously-tested structured 30-minute telephone interview. Outcome measures include time spent by the individual job titles in implementing and running the outcomes measurement program. Job-title-specific times were used to calculate costs from the hospitals' perspective. One-time costs (C2132 + 1352) and administrative costs (95 97 per week) varied substantially. Costs per patient were fairly stable at around 20. We estimated that the total cost for each hospital to assess outcomes of care for accreditation (10 tracer diagnoses over 6 months) would be 9700 and that continuous monitoring of outcomes (5 tracer diagnoses) would cost 12,400 per year. This study suggests that outcomes of acute hospital care can be assessed with limited resources and that standardized training programs would reduce variability in overall costs. This study should help hospital decision makers to estimate the necessary funding for outcomes measurement initiatives

Mapping the genetic architecture of gene expression in human liver

Genetic variants that are associated with common human diseases do not lead directly to disease, but instead act on intermediate, molecular phenotypes that in turn induce changes in higher-order disease traits. Therefore, identifying the molecular phenotypes that vary in response to changes in DNA and that also associate with changes in disease traits has the potential to provide the functional information required to not only identify and validate the susceptibility genes that are directly affected by changes in DNA, but also to understand the molecular networks in which such genes operate and how changes in these networks lead to changes in disease traits. Toward that end, we profiled more than 39,000 transcripts and we genotyped 782,476 unique single nucleotide polymorphisms (SNPs) in more than 400 human liver samples to characterize the genetic architecture of gene expression in the human liver, a metabolically active tissue that is important in a number of common human diseases, including obesity, diabetes, and atherosclerosis. This genome-wide association study of gene expression resulted in the detection of more than 6,000 associations between SNP genotypes and liver gene expression traits, where many of the corresponding genes identified have already been implicated in a number of human diseases. The utility of these data for elucidating the causes of common human diseases is demonstrated by integrating them with genotypic and expression data from other human and mouse populations. This provides much-needed functional support for the candidate susceptibility genes being identified at a growing number of genetic loci that have been identified as key drivers of disease from genome-wide association studies of disease. By using an integrative genomics approach, we highlight how the gene RPS26 and not ERBB3 is supported by our data as the most likely susceptibility gene for a novel type 1 diabetes locus recently identified in a large-scale, genome-wide association study. We also identify SORT1 and CELSR2 as candidate susceptibility genes for a locus recently associated with coronary artery disease and plasma low-density lipoprotein cholesterol levels in the process. © 2008 Schadt et al

Generation of stable heading representations in diverse visual scenes

Many animals rely on an internal heading representation when navigating in varied environments1-10. How this representation is linked to the sensory cues that define different surroundings is unclear. In the fly brain, heading is represented by 'compass' neurons that innervate a ring-shaped structure known as the ellipsoid body3,11,12. Each compass neuron receives inputs from 'ring' neurons that are selective for particular visual features13-16; this combination provides an ideal substrate for the extraction of directional information from a visual scene. Here we combine two-photon calcium imaging and optogenetics in tethered flying flies with circuit modelling, and show how the correlated activity of compass and visual neurons drives plasticity17-22, which flexibly transforms two-dimensional visual cues into a stable heading representation. We also describe how this plasticity enables the fly to convert a partial heading representation, established from orienting within part of a novel setting, into a complete heading representation. Our results provide mechanistic insight into the memory-related computations that are essential for flexible navigation in varied surroundings