Gestão da qualidade: avaliação do processo de acreditação do Hospital Divina Providência

A temática desta pesquisa surgiu da análise do projeto de acreditação hospitalar do Hospital Divina Providência (HDP) junto à Organização Nacional de Acreditação - ONA do Governo Federal do Brasil – no município de Marituba da Região Metropolitana de Belém, objetivando mensurar o grau de entendimento dos colaboradores, usuários e gestores sobre o processo de Acreditação desenvolvido na Instituição. A metodologia utilizada para realização da pesquisa caracteriza-se como exploratória descritiva com abordagem quantitativa e quantitativa, de amostra probabilística por acessibilidade, aplicada aos três tipos de elementos acima mencionados, com o intuito de verificar, qual o nível de conhecimentos sobre o assunto abordado, e como eles veem a empresa inserida nesse tema. No decorrer do estudo, foi analisado quão grande tem se tornado a abordagem no Brasil e mundo, e como os hospitais têm adotado as certificações de qualidade como um fator de competitividade no mercado e de reconhecimento. Conclui-se que, a entidade não mantém um sistema de aprimoramento de gestão da qualidade com vistas a uma certificação de acreditação juntos aos colaboradores e gestores, de forma a auxiliá-los no desenvolvimento e amadurecimento do referido processo. Percebe-se também, que não há conformidade e nem integração de ideias a respeito do tema abordado entre gestores e colaboradores do HDP.

Development of practical methodology and indicators for on-farm animal welfare assessment

163 p.

Threshold detection: matching statistical methodology to ecological questions and conservation planning objectives

Two types of ecological thresholds are now being widely used to develop conservation targets: breakpoint-based thresholds represent tipping points where system properties change dramatically, whereas classification thresholds identify groups of data points with contrasting properties. Both breakpoint-based and classification thresholds are useful tools in evidence-based conservation. However, it is critical that the type of threshold to be estimated corresponds with the question of interest and that appropriate statistical procedures are used to determine its location. On the basis of their statistical properties, we recommend using piecewise regression methods to identify breakpoint-based thresholds and discriminant analysis or classification and regression trees to identify classification thresholds.

Quantification of the probability of containment failure caused by an in-vessel steam explosion for the Sizewell B PWR

AEA Technology has provided an assessment of the probability of α-mode containment failure for the Sizewell B PWR. After a preliminary review of the methodologies available it was decided to use the probabilistic approach described in the paper, based on an extension of the methodology developed by Theofanous et al. (Nucl. Sci. Eng. 97 (1987) 259–325). The input to the assessment is 12 probability distributions; the bases for the quantification of these distributions are discussed. The α-mode assessment performed for the Sizewell B PWR has demonstrated the practicality of the event-tree method with input data represented by probability distributions. The assessment itself has drawn attention to a number of topics, which may be plant and sequence dependent, and has indicated the importance of melt relocation scenarios. The α-mode failure probability following an accident that leads to core melt relocation to the lower head for the Sizewell B PWR has been assessed as a few parts in 10 000, on the basis of current information. This assessment has been the first to consider elevated pressures (6 MPa and 15 MPa) besides atmospheric pressure, but the results suggest only a modest sensitivity to system pressure.

Convectively coupled equatorial waves: A new methodology for identifying wave structures in observational data

Convectively coupled equatorial waves are fundamental components of the interaction between the physics and dynamics of the tropical atmosphere. A new methodology, which isolates individual equatorial wave modes, has been developed and applied to observational data. The methodology assumes that the horizontal structures given by equatorial wave theory can be used to project upper- and lower-tropospheric data onto equatorial wave modes. The dynamical fields are first separated into eastward- and westward-moving components with a specified domain of frequency–zonal wavenumber. Each of the components for each field is then projected onto the different equatorial modes using the y structures of these modes given by the theory. The latitudinal scale yo of the modes is predetermined by data to fit the equatorial trapping in a suitable latitude belt y = ±Y. The extent to which the different dynamical fields are consistent with one another in their depiction of each equatorial wave structure determines the confidence in the reality of that structure. Comparison of the analyzed modes with the eastward- and westward-moving components in the convection field enables the identification of the dynamical structure and nature of convectively coupled equatorial waves. In a case study, the methodology is applied to two independent data sources, ECMWF Reanalysis and satellite-observed window brightness temperature (Tb) data for the summer of 1992. Various convectively coupled equatorial Kelvin, mixed Rossby–gravity, and Rossby waves have been detected. The results indicate a robust consistency between the two independent data sources. Different vertical structures for different wave modes and a significant Doppler shifting effect of the background zonal winds on wave structures are found and discussed. It is found that in addition to low-level convergence, anomalous fluxes induced by strong equatorial zonal winds associated with equatorial waves are important for inducing equatorial convection. There is evidence that equatorial convection associated with Rossby waves leads to a change in structure involving a horizontal structure similar to that of a Kelvin wave moving westward with it. The vertical structure may also be radically changed. The analysis method should make a very powerful diagnostic tool for investigating convectively coupled equatorial waves and the interaction of equatorial dynamics and physics in the real atmosphere. The results from application of the analysis method for a reanalysis dataset should provide a benchmark against which model studies can be compared.

Exploitation of Geostationary Earth Radiation Budget data using simulations from a numerical weather prediction model: Methodology and data validation

We describe a new methodology for comparing satellite radiation budget data with a numerical weather prediction (NWP) model. This is applied to data from the Geostationary Earth Radiation Budget (GERB) instrument on Meteosat-8. The methodology brings together, in near-real time, GERB broadband shortwave and longwave fluxes with simulations based on analyses produced by the Met Office global NWP model. Results for the period May 2003 to February 2005 illustrate the progressive improvements in the data products as various initial problems were resolved. In most areas the comparisons reveal systematic errors in the model's representation of surface properties and clouds, which are discussed elsewhere. However, for clear-sky regions over the oceans the model simulations are believed to be sufficiently accurate to allow the quality of the GERB fluxes themselves to be assessed and any changes in time of the performance of the instrument to be identified. Using model and radiosonde profiles of temperature and humidity as input to a single-column version of the model's radiation code, we conduct sensitivity experiments which provide estimates of the expected model errors over the ocean of about ±5–10 W m−2 in clear-sky outgoing longwave radiation (OLR) and ±0.01 in clear-sky albedo. For the more recent data the differences between the observed and modeled OLR and albedo are well within these error estimates. The close agreement between the observed and modeled values, particularly for the most recent period, illustrates the value of the methodology. It also contributes to the validation of the GERB products and increases confidence in the quality of the data, prior to their release.

Development of a methodology to investigate the importance of chemical speciation on the bioavailability of contaminants to Eisenia andrei

The uptake of metals by earthworms occurs predominantly via the soil pore water, or via an uptake route which is related to the soil pore water metal concentration. However, it has been suggested that the speciation of the metal is also important. A novel technique is described which exposes Eisenia andrei Bouche to contaminant bearing solutions in which the chemical factors affecting its speciation may be individually and systematically manipulated. In a preliminary experiment, the LC50 for copper nitrate was 0.046 mg l(-1) (95 % confidence intervals: 0.03 and 0.07 mg l(-1)). There was a significant positive correlation between earthworm mortality and bulk copper concentration in solution (R-2 = 0.88, P less than or equal to 0.001), and a significant positive increase in earthworm tissue copper concentration with increasing copper concentration in solution (R-2 = 0.97, P less than or equal to 0.001). It is anticipated that quantifying the effect of soil solution chemical speciation on copper bioavailability will provide an excellent aid to understanding the importance of chemical composition and the speciation of metals, in the calculation of toxicological parameters.

Human exposure modelling for chemical risk assessment: a review of current approaches and research and policy implications

A wide variety of exposure models are currently employed for health risk assessments. Individual models have been developed to meet the chemical exposure assessment needs of Government, industry and academia. These existing exposure models can be broadly categorised according to the following types of exposure source: environmental, dietary, consumer product, occupational, and aggregate and cumulative. Aggregate exposure models consider multiple exposure pathways, while cumulative models consider multiple chemicals. In this paper each of these basic types of exposure model are briefly described, along with any inherent strengths or weaknesses, with the UK as a case study. Examples are given of specific exposure models that are currently used, or that have the potential for future use, and key differences in modelling approaches adopted are discussed. The use of exposure models is currently fragmentary in nature. Specific organisations with exposure assessment responsibilities tend to use a limited range of models. The modelling techniques adopted in current exposure models have evolved along distinct lines for the various types of source. In fact different organisations may be using different models for very similar exposure assessment situations. This lack of consistency between exposure modelling practices can make understanding the exposure assessment process more complex, can lead to inconsistency between organisations in how critical modelling issues are addressed (e.g. variability and uncertainty), and has the potential to communicate mixed messages to the general public. Further work should be conducted to integrate the various approaches and models, where possible and regulatory remits allow, to get a coherent and consistent exposure modelling process. We recommend the development of an overall framework for exposure and risk assessment with common approaches and methodology, a screening tool for exposure assessment, collection of better input data, probabilistic modelling, validation of model input and output and a closer working relationship between scientists and policy makers and staff from different Government departments. A much increased effort is required is required in the UK to address these issues. The result will be a more robust, transparent, valid and more comparable exposure and risk assessment process. (C) 2006 Elsevier Ltd. All rights reserved.

Uncertainties in annual riverine phosphorus load estimation: Impact of load estimation methodology, sampling frequency, baseflow index and catchment population density

Models developed to identify the rates and origins of nutrient export from land to stream require an accurate assessment of the nutrient load present in the water body in order to calibrate model parameters and structure. These data are rarely available at a representative scale and in an appropriate chemical form except in research catchments. Observational errors associated with nutrient load estimates based on these data lead to a high degree of uncertainty in modelling and nutrient budgeting studies. Here, daily paired instantaneous P and flow data for 17 UK research catchments covering a total of 39 water years (WY) have been used to explore the nature and extent of the observational error associated with nutrient flux estimates based on partial fractions and infrequent sampling. The daily records were artificially decimated to create 7 stratified sampling records, 7 weekly records, and 30 monthly records from each WY and catchment. These were used to evaluate the impact of sampling frequency on load estimate uncertainty. The analysis underlines the high uncertainty of load estimates based on monthly data and individual P fractions rather than total P. Catchments with a high baseflow index and/or low population density were found to return a lower RMSE on load estimates when sampled infrequently than those with a tow baseflow index and high population density. Catchment size was not shown to be important, though a limitation of this study is that daily records may fail to capture the full range of P export behaviour in smaller catchments with flashy hydrographs, leading to an underestimate of uncertainty in Load estimates for such catchments. Further analysis of sub-daily records is needed to investigate this fully. Here, recommendations are given on load estimation methodologies for different catchment types sampled at different frequencies, and the ways in which this analysis can be used to identify observational error and uncertainty for model calibration and nutrient budgeting studies. (c) 2006 Elsevier B.V. All rights reserved.

Experimental crop growing in Jordan to develop methodology for the identification of ancient crop irrigation

Crop irrigation has long been recognized as having been important for the evolution of social complexity in several parts of the world. Structural evidence for water management, as in the form of wells, ditches and dams, is often difficult to interpret and may be a poor indicator of past irrigation that may have had no need for such constructions. It would be of considerable value, therefore, to be able to infer past irrigation directly from archaeo-botanical remains, and especially the type of archaeo-botanical remains that are relatively abundant in the archaeological record, such as phytoliths. Building on the pioneering work of Rosen and Wiener (1994), this paper describes a crop-growing experiment designed to explore the impact of irrigation on the formation of phytoliths within cereals. If it can be shown that a systemic and consistent relationship exists between phytolith size, structure and the intensity of irrigation, and if various taphonomic and palaeoenvironmental processes can be controlled for, then the presence of past irrigation can feasibly be inferred from the phytoliths recovered from the archaeological record.

An application of the GLUE methodology for estimating the parameters of the INCA-N model

The conceptual and parameter uncertainty of the semi-distributed INCA-N (Integrated Nutrients in Catchments-Nitrogen) model was studied using the GLUE (Generalized Likelihood Uncertainty Estimation) methodology combined with quantitative experimental knowledge, the concept known as 'soft data'. Cumulative inorganic N leaching, annual plant N uptake and annual mineralization proved to be useful soft data to constrain the parameter space. The INCA-N model was able to simulate the seasonal and inter-annual variations in the stream-water nitrate concentrations, although the lowest concentrations during the growing season were not reproduced. This suggested that there were some retention processes or losses either in peatland/wetland areas or in the river which were not included in the INCA-N model. The results of the study suggested that soft data was a way to reduce parameter equifinality, and that the calibration and testing of distributed hydrological and nutrient leaching models should be based both on runoff and/or nutrient concentration data and the qualitative knowledge of experimentalist. (c) 2006 Elsevier B.V. All rights reserved.