Practical lessons for dealing with inequalities in health impact assessment

This publication is a companion to Addressing inequalities through health impact assessment (Taylor et al., 2003a), which described what a focus on inequalities could achieve, offered case study examples, and outlined promising practice. This bulletin discusses recent publications and presents a further two case studies that attempt to address health inequalities through the use of HIA. .

Improving Health and Reducing Inequalities: A Practical Guide to Health Impact Assessment

(WHIASU) A basic guide to conducting a HIA. 1. Health impact assessment is a tool that can help organisations to assess the possible consequences of their decisions on people۪s health and well-being, thereby helping to develop more integrated policies and programmes. 2. This document has been developed as a practical guide to health impact assessment. It is designed to meet the needs of a variety of organisations by explaining the concept, the process and its flexibility, and by providing templates that can be adjusted to suit. 3. The Welsh Assembly Government is committed to developing the use of health impact assessment in Wales as a part of its strategy to improve health and wellbeing and to reduce health inequalities. This practical guide has been prepared by the Welsh Health Impact Assessment Support Unit, which was established by the Welsh Assembly Government to encourage and support organisations and groups in Wales to use the approach. 4. The development and use of health impact assessment will contribute to the ongoing development and implementation of local health, social care and wellbeing strategies, which is a joint statutory responsibility for Local Health Boards and local authorities. It can also contribute to Community Strategies which, given their overarching nature and breadth and depth, can address social, economic and environmental determinants of health, and to the implementation of Communities First, the Welsh Assembly Government۪s crosscutting regeneration programme. 5. The development of Health Challenge Wales as the national focus for improving health in Wales reinforces efforts to prevent ill health. Tools such as health impact assessment can help organisations and groups in all sectors to identify ways in which they can help people to improve their health.

Anti Bullying Procedures for Primary and Post Primary Schools - Appendix 2 Practical tips for building a positive school culture and climate

Anti Bullying Procedures for Primary and Post Primary Schools - Appendix 2 Practical tips for building a positive school culture and climate. Provided by the Department of Education and Skills, Ireland.

WePreserve 2009: DPE/Planets/CASPAR/nestor Joint Training Event: The Preservation challenge: basic concepts and practical applications (Barcelona, 23-27 març 2009)

Reseña del congreso WePreserve 2009 que tuvo lugar los pasados 23 al 27 de marzo en Barcelona, organizadopor la Facultad de Biblioteconomía y Documentación de la Universitat de Barcelona, con la colaboración del Institut d'Estudis Catalans, la Biblioteca de Catalunya y el Consorci de Biblioteques de Barcelona. El seminario 2009 WePreserve se celebra anualmente desde el año 2007 y participan todas las figuras de referencia europeas en materia de investigación en sistemas y metodologías que garantizan la preservación digital de los documentos: Digital Preservation Europe (DPE), Preservation and Long-term Access Through Networked Services (Planets), Cultural Artistic and Scientific Knowledge for Preservation, Access and Retrieval (CASPAR), y Network of expertise in Digital long-term preservation (nestor).

TNF-alpha blockers in inflammatory bowel diseases: practical consensus recommendations and a user's guide.

More than seventy years after their initial characterisation, the aetiology of inflammatory bowel diseases remains elusive. A recent review evaluating the incidence trends of the last 25 years concluded that an increasing incidence has been observed almost worldwide. A north-south gradient is still found in Europe. Genetic associations are variably reproduced worldwide and indicate a strong impact of environmental factors. Tumour necrosis factor alpha (TNF-alpha) has been shown to play a critical role in the pathogenesis of inflammatory bowel disease (IBD). TNF-alpha blockers are biological agents that specifically target this key cytokine in the inflammatory process and have become a mainstay in the therapy of inflammatory bowel diseases. This paper reviews the necessary investigations before using such agents, the use of such agents in pregnancy and lactation, the role of co-immunosuppression, how to monitor efficacy and safety, dose-adaptation, and the decision as to when to switch to another TNF-alpha blocker. Finally it gives recommendations for special situations. Currently there are three TNF-alpha blockers available for clinical use in IBD in Switzerland: infliximab (Remicade), adalimumab (Humira) and certolizumab pegol (Cimzia). Infliximab is a chimeric monoclonal antibody composed of a human IgG1 constant region and a murine variable region and is administered intravenously. Adalimumab is a humanised monoclonal antibody, with both human IgG1 constant and variable regions. Certolizumab pegol is a pegylated, humanised monoclonal anti-TNF fragment antigen binding fragment. Both adalimumab and certolizumab pegol are administered by subcutaneous injection. The efficacy and safety of TNF-alpha blockers in Crohn's disease has been reviewed. The authors conclude that the three above-mentioned agents are effective in luminal Crohn's disease. In fistulizing Crohn's disease, TNF-alpha blockers other than infliximab require additional investigation.

Dilatation pyélocalicielle chez le nouveau-né: attitude pratique pour le pédiatre [Antenatally detected hydronephrosis: practical approach for the pediatrician]

Approximately 1% of the fetuses present some dilatation of their urinary tract in utero. More than 50% of these antenatally detected hydronephrosis will disappear spontaneously after birth. The other 50% comprises ureteropelvic junction obstruction, vesico-ureteral reflux and primary megaureters. Postnatal radiological evaluation (renal ultrasonography and VCUG) is performed in every infant with a significantly dilated renal pelvis (> 8 mm between 20 and 30 weeks or > 10 mm after 30 weeks in utero). Renal nuclear scan should be done in every child with significant/worsening post-natal hydronephrosis. Antibioprophylaxis will be started from birth to prevent urinary tract infection. Medical or surgical approach will be chosen in the light of the uroradiological exam results and the clinical progress.

Correcting Measurement Error Bias in Interaction Models with Small Samples

Several methods have been suggested to estimate non-linear models with interaction terms in the presence of measurement error. Structural equation models eliminate measurement error bias, but require large samples. Ordinary least squares regression on summated scales, regression on factor scores and partial least squares are appropriate for small samples but do not correct measurement error bias. Two stage least squares regression does correct measurement error bias but the results strongly depend on the instrumental variable choice. This article discusses the old disattenuated regression method as an alternative for correcting measurement error in small samples. The method is extended to the case of interaction terms and is illustrated on a model that examines the interaction effect of innovation and style of use of budgets on business performance. Alternative reliability estimates that can be used to disattenuate the estimates are discussed. A comparison is made with the alternative methods. Methods that do not correct for measurement error bias perform very similarly and considerably worse than disattenuated regression

Moderating effects of management control systems and innovation on performance. Simple methods for correcting the effects of measurement error for interaction effects in small samples

In the accounting literature, interaction or moderating effects are usually assessed by means of OLS regression and summated rating scales are constructed to reduce measurement error bias. Structural equation models and two-stage least squares regression could be used to completely eliminate this bias, but large samples are needed. Partial Least Squares are appropriate for small samples but do not correct measurement error bias. In this article, disattenuated regression is discussed as a small sample alternative and is illustrated on data of Bisbe and Otley (in press) that examine the interaction effect of innovation and style of use of budgets on performance. Sizeable differences emerge between OLS and disattenuated regression

Error and complexity of random walk Monte Carlo radiosity

The author studies the error and complexity of the discrete random walk Monte Carlo technique for radiosity, using both the shooting and gathering methods. The author shows that the shooting method exhibits a lower complexity than the gathering one, and under some constraints, it has a linear complexity. This is an improvement over a previous result that pointed to an O(n log n) complexity. The author gives and compares three unbiased estimators for each method, and obtains closed forms and bounds for their variances. The author also bounds the expected value of the mean square error (MSE). Some of the results obtained are also shown

Identification of factors associated with diagnostic error in primary care.

BACKGROUND Missed, delayed or incorrect diagnoses are considered to be diagnostic errors. The aim of this paper is to describe the methodology of a study to analyse cognitive aspects of the process by which primary care (PC) physicians diagnose dyspnoea. It examines the possible links between the use of heuristics, suboptimal cognitive acts and diagnostic errors, using Reason's taxonomy of human error (slips, lapses, mistakes and violations). The influence of situational factors (professional experience, perceived overwork and fatigue) is also analysed. METHODS Cohort study of new episodes of dyspnoea in patients receiving care from family physicians and residents at PC centres in Granada (Spain). With an initial expected diagnostic error rate of 20%, and a sampling error of 3%, 384 episodes of dyspnoea are calculated to be required. In addition to filling out the electronic medical record of the patients attended, each physician fills out 2 specially designed questionnaires about the diagnostic process performed in each case of dyspnoea. The first questionnaire includes questions on the physician's initial diagnostic impression, the 3 most likely diagnoses (in order of likelihood), and the diagnosis reached after the initial medical history and physical examination. It also includes items on the physicians' perceived overwork and fatigue during patient care. The second questionnaire records the confirmed diagnosis once it is reached. The complete diagnostic process is peer-reviewed to identify and classify the diagnostic errors. The possible use of heuristics of representativeness, availability, and anchoring and adjustment in each diagnostic process is also analysed. Each audit is reviewed with the physician responsible for the diagnostic process. Finally, logistic regression models are used to determine if there are differences in the diagnostic error variables based on the heuristics identified. DISCUSSION This work sets out a new approach to studying the diagnostic decision-making process in PC, taking advantage of new technologies which allow immediate recording of the decision-making process.

Practical signal-to-noise ratio quantification for sensitivity encoding: Application to coronary MR angiography.

Purpose: To develop and evaluate a practical method for the quantification of signal-to-noise ratio (SNR) on coronary MR angiograms (MRA) acquired with parallel imaging.Materials and Methods: To quantify the spatially varying noise due to parallel imaging reconstruction, a new method has been implemented incorporating image data acquisition followed by a fast noise scan during which radio-frequency pulses, cardiac triggering and navigator gating are disabled. The performance of this method was evaluated in a phantom study where SNR measurements were compared with those of a reference standard (multiple repetitions). Subsequently, SNR of myocardium and posterior skeletal muscle was determined on in vivo human coronary MRA.Results: In a phantom, the SNR measured using the proposed method deviated less than 10.1% from the reference method for small geometry factors (<= 2). In vivo, the noise scan for a 10 min coronary MRA acquisition was acquired in 30 s. Higher signal and lower SNR, due to spatially varying noise, were found in myocardium compared with posterior skeletal muscle.Conclusion: SNR quantification based on a fast noise scan is a validated and easy-to-use method when applied to three-dimensional coronary MRA obtained with parallel imaging as long as the geometry factor remains low.

Use of Two-Part Regression Calibration Model to Correct for Measurement Error in Episodically Consumed Foods in a Single-Replicate Study Design: EPIC Case Study.

In epidemiologic studies, measurement error in dietary variables often attenuates association between dietary intake and disease occurrence. To adjust for the attenuation caused by error in dietary intake, regression calibration is commonly used. To apply regression calibration, unbiased reference measurements are required. Short-term reference measurements for foods that are not consumed daily contain excess zeroes that pose challenges in the calibration model. We adapted two-part regression calibration model, initially developed for multiple replicates of reference measurements per individual to a single-replicate setting. We showed how to handle excess zero reference measurements by two-step modeling approach, how to explore heteroscedasticity in the consumed amount with variance-mean graph, how to explore nonlinearity with the generalized additive modeling (GAM) and the empirical logit approaches, and how to select covariates in the calibration model. The performance of two-part calibration model was compared with the one-part counterpart. We used vegetable intake and mortality data from European Prospective Investigation on Cancer and Nutrition (EPIC) study. In the EPIC, reference measurements were taken with 24-hour recalls. For each of the three vegetable subgroups assessed separately, correcting for error with an appropriately specified two-part calibration model resulted in about three fold increase in the strength of association with all-cause mortality, as measured by the log hazard ratio. Further found is that the standard way of including covariates in the calibration model can lead to over fitting the two-part calibration model. Moreover, the extent of adjusting for error is influenced by the number and forms of covariates in the calibration model. For episodically consumed foods, we advise researchers to pay special attention to response distribution, nonlinearity, and covariate inclusion in specifying the calibration model.

Practical applications of quantum molecular similarity measures (QMSM): programs and examples

Es descriu l'aproximació de Capes Atòmiques dins de la teoria de la Semblança Molecular Quàntica. Partint només de dades teòriques, s'ha trobat una relació entre estructura molecular i activitat biològica per a diversos conjunts de molècules. Es descriuen els aspectes teòrics de la Semblança Molecular Quàntica i alguns exemples d'aplicació

Practical management of sunitinib toxicities in the treatment of pancreatic neuroendocrine tumors.

Pancreatic neuroendocrine tumors (pNETs) are infrequent malignancies which manifest in both functional (hormone-secreting) and more commonly non-functional (non-secreting) forms. The oral multitargeted tyrosine kinase inhibitor sunitinib and mammalian target of rapamycin (mTOR) inhibitor everolimus are approved as targeted therapies for patients with well-differentiated, non-resectable disease and evidence of disease progression. The recent approval of sunitinib for the management of advanced pNET is based on a continuous daily dosing (CDD) schedule that differs from the intermittent 4weeks on/2weeks off (4/2) schedule approved for sunitinib in advanced renal cell carcinoma (RCC) and imatinib-resistant gastrointestinal stromal tumor (GIST). Therefore, although clinicians may be familiar with therapy management approaches for sunitinib in advanced RCC and GIST, there is less available experience for the management of patients with a CDD schedule. Here, we discuss the similarities and differences in the treatment of pNET with sunitinib compared with advanced RCC and GIST. In particular, we focus on the occurrence and management of sunitinib-related toxicity in patients with pNET by drawing on experience in these other malignancies. We aim to provide a relevant and useful guide for clinicians treating patients with pNET covering the management of events such as fatigue, mucositis, hand-foot syndrome, and hypertension.

Adaptively weighted maximum likelihood estimation of discrete distributions

SummaryDiscrete data arise in various research fields, typically when the observations are count data.I propose a robust and efficient parametric procedure for estimation of discrete distributions. The estimation is done in two phases. First, a very robust, but possibly inefficient, estimate of the model parameters is computed and used to indentify outliers. Then the outliers are either removed from the sample or given low weights, and a weighted maximum likelihood estimate (WML) is computed.The weights are determined via an adaptive process such that if the data follow the model, then asymptotically no observation is downweighted.I prove that the final estimator inherits the breakdown point of the initial one, and that its influence function at the model is the same as the influence function of the maximum likelihood estimator, which strongly suggests that it is asymptotically fully efficient.The initial estimator is a minimum disparity estimator (MDE). MDEs can be shown to have full asymptotic efficiency, and some MDEs have very high breakdown points and very low bias under contamination. Several initial estimators are considered, and the performances of the WMLs based on each of them are studied.It results that in a great variety of situations the WML substantially improves the initial estimator, both in terms of finite sample mean square error and in terms of bias under contamination. Besides, the performances of the WML are rather stable under a change of the MDE even if the MDEs have very different behaviors.Two examples of application of the WML to real data are considered. In both of them, the necessity for a robust estimator is clear: the maximum likelihood estimator is badly corrupted by the presence of a few outliers.This procedure is particularly natural in the discrete distribution setting, but could be extended to the continuous case, for which a possible procedure is sketched.RésuméLes données discrètes sont présentes dans différents domaines de recherche, en particulier lorsque les observations sont des comptages.Je propose une méthode paramétrique robuste et efficace pour l'estimation de distributions discrètes. L'estimation est faite en deux phases. Tout d'abord, un estimateur très robuste des paramètres du modèle est calculé, et utilisé pour la détection des données aberrantes (outliers). Cet estimateur n'est pas nécessairement efficace. Ensuite, soit les outliers sont retirés de l'échantillon, soit des faibles poids leur sont attribués, et un estimateur du maximum de vraisemblance pondéré (WML) est calculé.Les poids sont déterminés via un processus adaptif, tel qu'asymptotiquement, si les données suivent le modèle, aucune observation n'est dépondérée.Je prouve que le point de rupture de l'estimateur final est au moins aussi élevé que celui de l'estimateur initial, et que sa fonction d'influence au modèle est la même que celle du maximum de vraisemblance, ce qui suggère que cet estimateur est pleinement efficace asymptotiquement.L'estimateur initial est un estimateur de disparité minimale (MDE). Les MDE sont asymptotiquement pleinement efficaces, et certains d'entre eux ont un point de rupture très élevé et un très faible biais sous contamination. J'étudie les performances du WML basé sur différents MDEs.Le résultat est que dans une grande variété de situations le WML améliore largement les performances de l'estimateur initial, autant en terme du carré moyen de l'erreur que du biais sous contamination. De plus, les performances du WML restent assez stables lorsqu'on change l'estimateur initial, même si les différents MDEs ont des comportements très différents.Je considère deux exemples d'application du WML à des données réelles, où la nécessité d'un estimateur robuste est manifeste : l'estimateur du maximum de vraisemblance est fortement corrompu par la présence de quelques outliers.La méthode proposée est particulièrement naturelle dans le cadre des distributions discrètes, mais pourrait être étendue au cas continu.