The utilisation of health research in policy-making: Concepts, examples and methods of assessment

The importance of health research utilisation in policy-making, and of understanding the mechanisms involved, is increasingly recognised. Recent reports calling for more resources to improve health in developing countries, and global pressures for accountability, draw greater attention to research-informed policy-making. Key utilisation issues have been described for at least twenty years, but the growing focus on health research systems creates additional dimensions. The utilisation of health research in policy-making should contribute to policies that may eventually lead to desired outcomes, including health gains. In this article, exploration of these issues is combined with a review of various forms of policy-making. When this is linked to analysis of different types of health research, it assists in building a comprehensive account of the diverse meanings of research utilisation. Previous studies report methods and conceptual frameworks that have been applied, if with varying degrees of success, to record utilisation in policy-making. These studies reveal various examples of research impact within a general picture of underutilisation. Factors potentially enhancing utilisation can be identified by exploration of: priority setting; activities of the health research system at the interface between research and policy-making; and the role of the recipients, or 'receptors', of health research. An interfaces and receptors model provides a framework for analysis. Recommendations about possible methods for assessing health research utilisation follow identification of the purposes of such assessments. Our conclusion is that research utilisation can be better understood, and enhanced, by developing assessment methods informed by conceptual analysis and review of previous studies

Central serous chorioretinopathy: An evidence-based treatment guideline.

Central serous chorioretinopathy (CSC) is a relatively common disease that causes vision loss due to macular subretinal fluid leakage and it is often associated with reduced vision-related quality of life. In CSC, the leakage of subretinal fluid through defects in the retinal pigment epithelial layer's outer blood-retina barrier appears to occur secondary to choroidal abnormalities and dysfunction. The treatment of CSC is currently the subject of controversy, although recent data obtained from several large randomized controlled trials provide a wealth of new information that can be used to establish a treatment algorithm. Here, we provide a comprehensive overview of our current understanding regarding the pathogenesis of CSC, current therapeutic strategies, and an evidence-based treatment guideline for CSC. In acute CSC, treatment can often be deferred for up to 3-4 months after diagnosis; however, early treatment with either half-dose or half-fluence photodynamic therapy (PDT) with the photosensitive dye verteporfin may be beneficial in selected cases. In chronic CSC, half-dose or half-fluence PDT, which targets the abnormal choroid, should be considered the preferred treatment. If PDT is unavailable, chronic CSC with focal, non-central leakage on angiography may be treated using conventional laser photocoagulation. CSC with concurrent macular neovascularization should be treated with half-dose/half-fluence PDT and/or intravitreal injections of an anti-vascular endothelial growth factor compound. Given the current shortage of verteporfin and the paucity of evidence supporting the efficacy of other treatment options, future studies-ideally, well-designed randomized controlled trials-are needed in order to evaluate new treatment options for CSC

Physics, Astrophysics and Cosmology with Gravitational Waves

Gravitational wave detectors are already operating at interesting sensitivity levels, and they have an upgrade path that should result in secure detections by 2014. We review the physics of gravitational waves, how they interact with detectors (bars and interferometers), and how these detectors operate. We study the most likely sources of gravitational waves and review the data analysis methods that are used to extract their signals from detector noise. Then we consider the consequences of gravitational wave detections and observations for physics, astrophysics, and cosmology.Comment: 137 pages, 16 figures, Published version <http://www.livingreviews.org/lrr-2009-2

Assessment and optimisation of normalisation methods for dual-colour antibody microarrays

<p>Abstract</p> <p>Background</p> <p>Recent advances in antibody microarray technology have made it possible to measure the expression of hundreds of proteins simultaneously in a competitive dual-colour approach similar to dual-colour gene expression microarrays. Thus, the established normalisation methods for gene expression microarrays, e.g. loess regression, can in principle be applied to protein microarrays. However, the typical assumptions of such normalisation methods might be violated due to a bias in the selection of the proteins to be measured. Due to high costs and limited availability of high quality antibodies, the current arrays usually focus on a high proportion of regulated targets. Housekeeping features could be used to circumvent this problem, but they are typically underrepresented on protein arrays. Therefore, it might be beneficial to select invariant features among the features already represented on available arrays for normalisation by a dedicated selection algorithm.</p> <p>Results</p> <p>We compare the performance of several normalisation methods that have been established for dual-colour gene expression microarrays. The focus is on an invariant selection algorithm, for which effective improvements are proposed. In a simulation study the performances of the different normalisation methods are compared with respect to their impact on the ability to correctly detect differentially expressed features. Furthermore, we apply the different normalisation methods to a pancreatic cancer data set to assess the impact on the classification power.</p> <p>Conclusions</p> <p>The simulation study and the data application demonstrate the superior performance of the improved invariant selection algorithms in comparison to other normalisation methods, especially in situations where the assumptions of the usual global loess normalisation are violated.</p

Is eco-efficiency in greenhouse gas emissions converging among European Union countries?

Eco-efficiency refers to the ability to produce more goods and services with less impact on the environment and less consumption of natural resources. This issue has become a matter of concern that is receiving increasing attention from politicians, scientists and researchers. Furthermore, greenhouse gases emitted as a result of production processes have a marked impact on the environment and are also the foremost culprit of global warming and climate change. This paper assesses convergence in eco-efficiency in greenhouse gas emissions in the European Union. Eco-efficiency is assessed at both country and greenhouse-gas-specific levels using Data Envelopment Analysis techniques and directional distance functions, as recently proposed by Picazo-Tadeo et al. (Eur J Oper Res, 220:798–809, 2012). Convergence is then evaluated using the Phillips and Sul (Econometrica, 75:1771–1855, 2007) approach that allows testing for the existence of convergence groups. Although the results point to the existence of different convergence clubs depending on the specific pollutant considered, they signal the existence of at least four clear groups of countries. The first two groups are core European Union high-income countries (Benelux, Germany, Italy, Austria, the United Kingdom and Scandinavian countries). A third club is made up of peripheral countries (Spain, Ireland, Portugal and Greece) together with some Eastern countries (Latvia and Slovenia), while the remaining clubs consist of groups containing Eastern European countries

Technical efficiency of peripheral health units in Pujehun district of Sierra Leone: a DEA application

BACKGROUND: The Data Envelopment Analysis (DEA) method has been fruitfully used in many countries in Asia, Europe and North America to shed light on the efficiency of health facilities and programmes. There is, however, a dearth of such studies in countries in sub-Saharan Africa. Since hospitals and health centres are important instruments in the efforts to scale up pro-poor cost-effective interventions aimed at achieving the United Nations Millennium Development Goals, decision-makers need to ensure that these health facilities provide efficient services. The objective of this study was to measure the technical efficiency (TE) and scale efficiency (SE) of a sample of public peripheral health units (PHUs) in Sierra Leone. METHODS: This study applied the Data Envelopment Analysis approach to investigate the TE and SE among a sample of 37 PHUs in Sierra Leone. RESULTS: Twenty-two (59%) of the 37 health units analysed were found to be technically inefficient, with an average score of 63% (standard deviation = 18%). On the other hand, 24 (65%) health units were found to be scale inefficient, with an average scale efficiency score of 72% (standard deviation = 17%). CONCLUSION: It is concluded that with the existing high levels of pure technical and scale inefficiency, scaling up of interventions to achieve both global and regional targets such as the MDG and Abuja health targets becomes far-fetched. In a country with per capita expenditure on health of about US$7, and with only 30% of its population having access to health services, it is demonstrated that efficiency savings can significantly augment the government's initiatives to cater for the unmet health care needs of the population. Therefore, we strongly recommend that Sierra Leone and all other countries in the Region should institutionalise health facility efficiency monitoring at the Ministry of Health headquarter (MoH/HQ) and at each health district headquarter

The multiplex bead array approach to identifying serum biomarkers associated with breast cancer

Introduction Breast cancer is the most common type of cancer seen in women in western countries. Thus, diagnostic modalities sensitive to early-stage breast cancer are needed. Antibody-based array platforms of a data-driven type, which are expected to facilitate more rapid and sensitive detection of novel biomarkers, have emerged as a direct, rapid means for profiling cancer-specific signatures using small samples. In line with this concept, our group constructed an antibody bead array panel for 35 analytes that were selected during the discovery step. This study was aimed at testing the performance of this 35-plex array panel in profiling signatures specific for primary non-metastatic breast cancer and validating its diagnostic utility in this independent population. Methods Thirty-five analytes were selected from more than 50 markers through screening steps using a serum bank consisting of 4,500 samples from various types of cancer. An antibody-bead array of 35 markers was constructed using the Luminex (TM) bead array platform. A study population consisting of 98 breast cancer patients and 96 normal subjects was analysed using this panel. Multivariate classification algorithms were used to find discriminating biomarkers and validated with another independent population of 90 breast cancer and 79 healthy controls. Results Serum concentrations of epidermal growth factor, soluble CD40-ligand and proapolipoprotein A1 were increased in breast cancer patients. High-molecular-weight-kininogen, apolipoprotein A1, soluble vascular cell adhesion molecule-1, plasminogen activator inhibitor-1, vitamin-D binding protein and vitronectin were decreased in the cancer group. Multivariate classification algorithms distinguished breast cancer patients from the normal population with high accuracy (91.8% with random forest, 91.5% with support vector machine, 87.6% with linear discriminant analysis). Combinatorial markers also detected breast cancer at an early stage with greater sensitivity. Conclusions The current study demonstrated the usefulness of the antibody-bead array approach in finding signatures specific for primary non-metastatic breast cancer and illustrated the potential for early, high sensitivity detection of breast cancer. 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REPORT Whole-Exome Sequencing Links a Variant in DHDDS to Retinitis Pigmentosa

Increasingly, mutations in genes causing Mendelian disease will be supported by individual and small families only; however, exome sequencing studies have thus far focused on syndromic phenotypes characterized by low locus heterogeneity. In contrast, retinitis pigmentosa (RP) is caused by &gt;50 known genes, which still explain only half of the clinical cases. In a single, one-generation, nonsyndromic RP family, we have identified a gene, dehydrodolichol diphosphate synthase (DHDDS), demonstrating the power of combining whole-exome sequencing with rapid in vivo studies. DHDDS is a highly conserved essential enzyme for dolichol synthesis, permitting global N-linked glycosylation. Zebrafish studies showed virtually identical photoreceptor defects as observed with N-linked glycosylation-interfering mutations in the light-sensing protein rhodopsin. The identified Lys42Glu variant likely arose from an ancestral founder, because eight of the nine identified alleles in 27,174 control chromosomes were of confirmed Ashkenazi Jewish ethnicity. These findings demonstrate the power of exome sequencing linked to functional studies when faced with challenging study designs and, importantly, link RP to the pathways of N-linked glycosylation, which promise new avenues for therapeutic interventions. Retinitis pigmentosa (RP) refers to a large group of genetically heterogeneous retinal degenerative disorders characterized by early rod photoreceptor dysfunction followed by progressive rod and cone photoreceptor dysfunction and photoreceptor death (MIM 268000). Impaired night vision followed by impaired peripheral vision generally starts in adolescence to young adulthood, with subsequent impaired central vision in later life. We studied a family of Ashkenazi Jewish (AJ) origin in which three out of four siblings (two females and one male) were diagnosed with RP in their teenage years ( To identify the genetic cause of this likely recessive subtype of RP, we screened all genes known to harbor RP mutations and found that they were negative for mutations. Classic linkage approaches were not applicable because of the size of the nonconsanguineous family, so we performed whole-exome sequencing in the three affected siblings and one unaffected sibling (Whole Human Exome Capture kit, Roche). We produced approximately 10 gigabases (Gb) of paired-end 75 bp sequence reads per individual on the Illumina GAII platform. To test the overall quality of the sequence data, we compared the genotypes of variants found in the sequence data to variants derived from genotyping via a genome-wide SN