Performance evaluation of hospitals that provide care in the public health system, Brazil

OBJECTIVE To analyze if size, administrative level, legal status, type of unit and educational activity influence the hospital network performance in providing services to the Brazilian Unified Health System.METHODS This cross-sectional study evaluated data from the Hospital Information System and the Cadastro Nacional de Estabelecimentos de Saúde (National Registry of Health Facilities), 2012, in Sao Paulo, Southeastern Brazil. We calculated performance indicators, such as: the ratio of hospital employees per bed; mean amount paid for admission; bed occupancy rate; average length of stay; bed turnover index and hospital mortality rate. Data were expressed as mean and standard deviation. The groups were compared using analysis of variance (ANOVA) and Bonferroni correction.RESULTS The hospital occupancy rate in small hospitals was lower than in medium, big and special-sized hospitals. Higher hospital occupancy rate and bed turnover index were observed in hospitals that include education in their activities. The hospital mortality rate was lower in specialized hospitals compared to general ones, despite their higher proportion of highly complex admissions. We found no differences between hospitals in the direct and indirect administration for most of the indicators analyzed.CONCLUSIONS The study indicated the importance of the scale effect on efficiency, and larger hospitals had a higher performance. Hospitals that include education in their activities had a higher operating performance, albeit with associated importance of using human resources and highly complex structures. Specialized hospitals had a significantly lower rate of mortality than general hospitals, indicating the positive effect of the volume of procedures and technology used on clinical outcomes. The analysis related to the administrative level and legal status did not show any significant performance differences between the categories of public hospitals.

Performance of the Vitek 2 system software version 5.03 in the bacterial identification and antimicrobial susceptibility test: evaluation study of clinical and reference strains of Gram-positive cocci

Introduction. The genera Enterococcus, Staphylococcus and Streptococcus are recognized as important Gram-positive human pathogens. The aim of this study was to evaluate the performance of Vitek 2 in identifying Gram-positive cocci and their antimicrobial susceptibilities. Methods. One hundred four isolates were analyzed to determine the accuracy of the automated system for identifying the bacteria and their susceptibility to oxacillin and vancomycin. Results. The system correctly identified 77.9% and 97.1% of the isolates at the species and genus levels, respectively. Additionally, 81.8% of the Vitek 2 results agreed with the known antimicrobial susceptibility profiles. Conclusion. Vitek 2 correctly identified the commonly isolated strains; however, the limitations of the method may lead to ambiguous findings.

Fuzzy expert system in the prediction of neonatal resuscitation

In view of the importance of anticipating the occurrence of critical situations in medicine, we propose the use of a fuzzy expert system to predict the need for advanced neonatal resuscitation efforts in the delivery room. This system relates the maternal medical, obstetric and neonatal characteristics to the clinical conditions of the newborn, providing a risk measurement of need of advanced neonatal resuscitation measures. It is structured as a fuzzy composition developed on the basis of the subjective perception of danger of nine neonatologists facing 61 antenatal and intrapartum clinical situations which provide a degree of association with the risk of occurrence of perinatal asphyxia. The resulting relational matrix describes the association between clinical factors and risk of perinatal asphyxia. Analyzing the inputs of the presence or absence of all 61 clinical factors, the system returns the rate of risk of perinatal asphyxia as output. A prospectively collected series of 304 cases of perinatal care was analyzed to ascertain system performance. The fuzzy expert system presented a sensitivity of 76.5% and specificity of 94.8% in the identification of the need for advanced neonatal resuscitation measures, considering a cut-off value of 5 on a scale ranging from 0 to 10. The area under the receiver operating characteristic curve was 0.93. The identification of risk situations plays an important role in the planning of health care. These preliminary results encourage us to develop further studies and to refine this model, which is intended to implement an auxiliary system able to help health care staff to make decisions in perinatal care.

Time-series forecasting of pollutant concentration levels using particle swarm optimization and artificial neural networks

This study evaluates the application of an intelligent hybrid system for time-series forecasting of atmospheric pollutant concentration levels. The proposed method consists of an artificial neural network combined with a particle swarm optimization algorithm. The method not only searches relevant time lags for the correct characterization of the time series, but also determines the best neural network architecture. An experimental analysis is performed using four real time series and the results are shown in terms of six performance measures. The experimental results demonstrate that the proposed methodology achieves a fair prediction of the presented pollutant time series by using compact networks.

Use of experimental design in the optimisation of a solid phase preconcentration system for Cobalt determination by GFAAS

In this work is proposed a solid phase preconcentration system of Co2+ ions and its posterior determination by GFAAS in which fractional factorial design and response surface methodology (RSM) were used for optimization of the variables associated with preconcentration system performance. The method is based on cobalt extraction as a complex Co2+-PAN (1:2) in a mini-column of polyurethane foam (PUF) impregnated with 1-(2-pyridylazo)-naphthol (PAN) followed by elution with HCl solution and its determination by GFAAS. The chemical and flow variables studied were pH, buffer concentration, eluent concentration and preconcentration and elution flow rates. Results obtained from fractional factorial design 2(5-1) showed that only the variables pH, buffer concentration and interaction (pH X buffer concentration) based on analysis of variance (ANOVA) were statistically significant at 95% confidence level. Under optimised conditions, the method provided an enrichment factor of 11.6 fold with limit of detection and quantification of 38 and 130 ng L-1, respectively, and linear range varying from 0.13 to 10 µg L-1. The precision (n = 9) assessed by relative standard deviation (RSD) was respectively 5.18 and 2.87% for 0.3 and 3.0 µg L-1 cobalt concentrations.

Performance of an anaerobic-aerobic reactor and kinetic study of organic matter removal of cattle slaughterhouse effluent

This paper sought to evaluate the behavior of an upflow Anaerobic-Aerobic Fixed Bed Reactor (AAFBR) in the treatment of cattle slaughterhouse effluent and determine apparent kinetic constants of the organic matter removal. The AAFBR was operated with no recirculation (Phase I) and with 50% of effluent recirculation (Phase II), with θ of 11h and 8h. In terms of pH, bicarbonate alkalinity and volatile acids, the results indicated the reactor ability to maintain favorable conditions for the biological processes involved in the organic matter removal in both operational phases. The average removal efficiencies of organic matter along the reactor height, expressed in terms of raw COD, were 49% and 68% in Phase I and 54% and 86% in Phase II for θ of 11h and 8h, respectively. The results of the filtered COD indicated removal efficiency of 52% and k = 0.0857h-1 to θ of 11h and 42% and k = 0.0880h-1 to θ of 8h in the Phase I. In Phase II, the removal efficiencies were 59% and 51% to θ of 11h and 8h, with k = 0.1238h-1 and k = 0.1075 h-1, respectively. The first order kinetic model showed good adjustment and described adequately the kinetics of organic matter removal for θ of 11h, with r² equal to 0.9734 and 0.9591 to the Phases I and II, respectively.

Kinematic analysis and modelling of biped locomotion systems

This paper presents the kinematic study of robotic biped locomotion systems. The main purpose is to determine the kinematic characteristics and the system performance during walking. For that objective, the prescribed motion of the biped is completely characterised in terms of five locomotion variables: step length, hip height, maximum hip ripple, maximum foot clearance and link lengths. In this work, we propose four methods to quantitatively measure the performance of the walking robot: energy analysis, perturbation analysis, lowpass frequency response and locomobility measure. These performance measures are discussed and compared in determining the robustness and effectiveness of the resulting locomotion.

Analysis of emergency braking performance with particular consideration of temperature effects on brakes

During vehicle deceleration due to braking there is friction between the lining surface and the brake drum or disc. In this process the kinetic energy of vehicle is turned into thermal energy that raises temperature of the components. The heating of the brake system in the course of braking is a great problem, because besides damaging the system, it may also affect the wheel and tire, which can cause accidents. In search of the best configuration that considers the true conditions of use, without passing the safety limits, models and formulations are presented with respect to the brake system, considering different braking conditions and kinds of brakes. Some modeling was analyzed using well-known methods. The flat plate model considering energy conservation was applied to a bus, using for this a computer program. The vehicle is simulated to undergo an emergency braking, considering the change of temperature on the lining-drum. The results include deceleration, braking efficiency, wheel resistance, normal reaction on the tires and the coefficient of adhesion. Some of the results were compared with dynamometer tests made by FRAS-LE and others were compared with track tests made by Mercedes-Benz. The convergence between the results and the tests is sufficient to validate the mathematical model. The computer program makes it possible to simulate the brake system performance in the vehicle. It assists the designer during the development phase and reduces track tests.

Sistema para realização de medidas de luminescência com excitação por Raios X

In this work is presented a versatile system for X-ray excited optical luminescence (XEOL) measurements. The apparatus was assembled from a sample holder connected to an optical fiber responsibly for the acquisition of the scintillation signal. The spectrum is registered with a CCD coupled in a spectrograph provided with diffraction gratings. The system performance was analyzed by exciting GdAlO3:Eu3+ 3.0 at.% with X-rays from a diffractometer and measuring the emission spectra. The system can be used to obtain precise and reliable spectroscopic properties of samples with various conformations without the loss of the required safety when dealing with ionizing radiations.

MODELING A COMPUTER APPLICATION FOR MANAGEMENT OF MAINTENANCE ACTIVITIES OF UNPAVED ROADS

ABSTRACTThis study presents a contribution to the modeling of a computer application employing a method of serviceability performance for unpaved roads, aiming the management of maintenance/restoration activities of the primary surface layer. The proposed methodology consisted of field inspections during dry (April to September) and rainy (October to March) periods, during which objective evaluations were performed to survey of defects and their densities and degrees of severity. To aid the functional classification of analyzed road sections and the determination of the defect with major influence on the serviceability of these roads, the method of serviceability performance proposed by Silva (2009)was implemented in the Visual Basic for Applications (VBA) language in Microsoft Excel software. With the use of the computer application proposed it was possible to identify among the defects analyzed in field, through the index of serviceability of the sampling unit per defect type (ISUdef), which one had the greatest influence on determining the relative serviceability index per road section (IST). The results allow us to conclude that the computer application Road achieved satisfactory results, since the objective evaluation criteria applied to road sections denotes consistency regarding their serviceability.

Artificial neural network models for predicting 1-year mortality in elderly patients with intertrochanteric fractures in China

The mortality rate of older patients with intertrochanteric fractures has been increasing with the aging of populations in China. The purpose of this study was: 1) to develop an artificial neural network (ANN) using clinical information to predict the 1-year mortality of elderly patients with intertrochanteric fractures, and 2) to compare the ANN's predictive ability with that of logistic regression models. The ANN model was tested against actual outcomes of an intertrochanteric femoral fracture database in China. The ANN model was generated with eight clinical inputs and a single output. ANN's performance was compared with a logistic regression model created with the same inputs in terms of accuracy, sensitivity, specificity, and discriminability. The study population was composed of 2150 patients (679 males and 1471 females): 1432 in the training group and 718 new patients in the testing group. The ANN model that had eight neurons in the hidden layer had the highest accuracies among the four ANN models: 92.46 and 85.79% in both training and testing datasets, respectively. The areas under the receiver operating characteristic curves of the automatically selected ANN model for both datasets were 0.901 (95%CI=0.814-0.988) and 0.869 (95%CI=0.748-0.990), higher than the 0.745 (95%CI=0.612-0.879) and 0.728 (95%CI=0.595-0.862) of the logistic regression model. The ANN model can be used for predicting 1-year mortality in elderly patients with intertrochanteric fractures. It outperformed a logistic regression on multiple performance measures when given the same variables.