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.

Dynamic network data envelopment analysis for university hospitals evaluation

ABSTRACT OBJECTIVE To develop an assessment tool to evaluate the efficiency of federal university general hospitals. METHODS Data envelopment analysis, a linear programming technique, creates a best practice frontier by comparing observed production given the amount of resources used. The model is output-oriented and considers variable returns to scale. Network data envelopment analysis considers link variables belonging to more than one dimension (in the model, medical residents, adjusted admissions, and research projects). Dynamic network data envelopment analysis uses carry-over variables (in the model, financing budget) to analyze frontier shift in subsequent years. Data were gathered from the information system of the Brazilian Ministry of Education (MEC), 2010-2013. RESULTS The mean scores for health care, teaching and research over the period were 58.0%, 86.0%, and 61.0%, respectively. In 2012, the best performance year, for all units to reach the frontier it would be necessary to have a mean increase of 65.0% in outpatient visits; 34.0% in admissions; 12.0% in undergraduate students; 13.0% in multi-professional residents; 48.0% in graduate students; 7.0% in research projects; besides a decrease of 9.0% in medical residents. In the same year, an increase of 0.9% in financing budget would be necessary to improve the care output frontier. In the dynamic evaluation, there was progress in teaching efficiency, oscillation in medical care and no variation in research. CONCLUSIONS The proposed model generates public health planning and programming parameters by estimating efficiency scores and making projections to reach the best practice frontier.

Family health nursing care: weaknesses and strengths in the Unified Health System

OBJECTIVETo analyze the weaknesses and strengths of nursing care in the Family Health Strategy and its interfaces with the Unified Health System network.METHODA qualitative study performed by means of semi-structured interviews and systematic observations, with the participation of a nursing team of 15 people from October of 2012 to January of 2013.RESULTSStrengths that were emphasized: the nurse's versatility in conducting users within the unit and the health system, therefore directly acting upon access to these services. The nurse is the main subject that participates in the care processes for the person, family and social groups. Weaknesses that were highlighted: fragile embracement and low resolution of users' and families' problems.CONCLUSIONThe nursing care process in health units still lacks collective articulation, involvement of the team, and decentralization of the decisions.

CLASSIFICATION OF FOREST ROADS AND DETERMINATION OF ROUTE USING GEOGRAPHIC INFORMATION SYSTEM

ABSTRACT Geographic Information System (GIS) is an indispensable software tool in forest planning. In forestry transportation, GIS can manage the data on the road network and solve some problems in transportation, such as route planning. Therefore, the aim of this study was to determine the pattern of the road network and define transport routes using GIS technology. The present research was conducted in a forestry company in the state of Minas Gerais, Brazil. The criteria used to classify the pattern of forest roads were horizontal and vertical geometry, and pavement type. In order to determine transport routes, a data Analysis Model Network was created in ArcGIS using an Extension Network Analyst, allowing finding a route shorter in distance and faster. The results showed a predominance of horizontal geometry classes average (3) and bad (4), indicating presence of winding roads. In the case of vertical geometry criterion, the class of highly mountainous relief (4) possessed the greatest extent of roads. Regarding the type of pavement, the occurrence of secondary coating was higher (75%), followed by primary coating (20%) and asphalt pavement (5%). The best route was the one that allowed the transport vehicle travel in a higher specific speed as a function of road pattern found in the study.

Rainfall erosivity for the State of Rio de Janeiro estimated by artificial neural network

The Artificial Neural Networks (ANNs) are mathematical models method capable of estimating non-linear response plans. The advantage of these models is to present different responses of the statistical models. Thus, the objective of this study was to develop and to test ANNs for estimating rainfall erosivity index (EI30) as a function of the geographical location for the state of Rio de Janeiro, Brazil and generating a thematic visualization map. The characteristics of latitude, longitude e altitude using ANNs were acceptable to estimating EI30 and allowing visualization of the space variability of EI30. Thus, ANN is a potential option for the estimate of climatic variables in substitution to the traditional methods of interpolation.

Silting in the dense reservoir network of the Pereira de Miranda catchment

This study aims to analyze the impacts of the reservoir network within Pereira de Miranda - CE catchment (also called Pentecoste) over sediment transport and storage capacity of the system. The survey of the "damming" was carried out using satellite images. We identified 502 erosion units, derived from overlaying maps of the Universal Soil Loss Equation parameters, which allowed the estimation of localized erosion in the basin and identification of areas potentially generating sediment. In order to estimate silting in Pentecoste reservoir, different system structure scenarios were considered. An average erosion rate of 59 t ha-1year-1 was estimated. According to the model, the silting of Pentecoste reservoir may vary from 1.1 to 2.6% per decade, depending on the scenario considered. It is also observed that the reservoirs upstream can retain up to 58% of the sediment that would reach the Pentecoste reservoir. Very small reservoirs with a capacity of up to 100,000 m³, although representing only 1.83% of the system water availability, are able to retain almost 8% of total sediment produced.

Comparative analysis of different meat traceability systems using multiple criteria and a social network approach

The adoption of a proper traceability system is being incorporated into meat production practices as a method of gaining consumer confidence. The various partners operating in the chain of meat production can be considered a social network, and they have the common goal of generating a communication process that can ensure each characteristic of the product, including safety. This study aimed to select the most appropriate meat traceability system “from farm to fork” that could be applied to Brazilian beef and pork production for international trade. The research was done in three steps. The first used the analytical hierarchy process (AHP) for selecting the best on-farm livestock traceability. In the second step, the actors in the meat production chain were identified to build a framework and defined each role in the network. In the third step, the selection of the traceability system was done. Results indicated that with an electronic traceability system, it is possible to acquire better connections between the links in the chain and to provide the means for managing uncertainties by creating structures that facilitate information flow more efficiently.

Expression of extracellular matrix components and their receptors in the central nervous system during experimental Toxoplasma gondii and Trypanosoma cruzi infection

Alterations in extracellular matrix (ECM) expression in the central nervous system (CNS) usually associated with inflammatory lesions have been described in several pathological situations including neuroblastoma and demyelinating diseases. The participation of fibronectin (FN) and its receptor, the VLA-4 molecule, in the migration of inflammatory cells into the CNS has been proposed. In Trypanosoma cruzi infection encephalitis occurs during the acute phase, whereas in Toxoplasma infection encephalitis is a chronic persisting process. In immunocompromised individuals such as AIDS patients, T. cruzi or T. gondii infection can lead to severe CNS damage. At the moment, there are no data available regarding the molecules involved in the entrance of inflammatory cells into the CNS during parasitic encephalitis. Herein, we characterized the expression of the ECM components FN and laminin (LN) and their receptors in the CNS of T. gondii- and T. cruzi-infected mice. An increased expression of FN and LN was detected in the meninges, leptomeninges, choroid plexus and basal lamina of blood vessels. A fine FN network was observed involving T. gondii-free and T. gondii-containing inflammatory infiltrates. Moreover, perivascular spaces presenting a FN-containing filamentous network filled with a4+ and a5+ cells were observed. Although an increased expression of LN was detected in the basal lamina of blood vessels, the CNS inflammatory cells were a6-negative. Taken together, our results suggest that FN and its receptors VLA-4 and VLA-5 might be involved in the entrance, migration and retention of inflammatory cells into the CNS during parasitic infections.

The conservative physiology of the immune system

Current immunological opinion disdains the necessity to define global interconnections between lymphocytes and regards natural autoantibodies and autoreactive T cells as intrinsically pathogenic. Immunological theories address the recognition of foreignness by independent clones of lymphocytes, not the relations among lymphocytes or between lymphocytes and the organism. However, although extremely variable in cellular/molecular composition, the immune system preserves as invariant a set of essential relations among its components and constantly enacts contacts with the organism of which it is a component. These invariant relations are reflected, for example, in the life-long stability of profiles of reactivity of immunoglobulins formed by normal organisms (natural antibodies). Oral contacts with dietary proteins and the intestinal microbiota also result in steady states that lack the progressive quality of secondary-type reactivity. Autoreactivity (natural autoantibody and autoreactive T cell formation) is also stable and lacks the progressive quality of clonal expansion. Specific immune responses, currently regarded as the fundament of the operation of the immune system, may actually result from transient interruptions in this stable connectivity among lymphocytes. More permanent deficits in interconnectivity result in oligoclonal expansions of T lymphocytes, as seen in Omenn's syndrome and in the experimental transplantation of a suboptimal diversity of syngeneic T cells to immunodeficient hosts, which also have pathogenic consequences. Contrary to theories that forbid autoreactivity as potentially pathogenic, the physiology of the immune system is conservative and autoreactive. Pathology derives from failures of these conservative mechanisms.

An artificial neural network model for prediction of quality characteristics of apples during convective dehydration

In this study, the effects of hot-air drying conditions on color, water holding capacity, and total phenolic content of dried apple were investigated using artificial neural network as an intelligent modeling system. After that, a genetic algorithm was used to optimize the drying conditions. Apples were dried at different temperatures (40, 60, and 80 °C) and at three air flow-rates (0.5, 1, and 1.5 m/s). Applying the leave-one-out cross validation methodology, simulated and experimental data were in good agreement presenting an error < 2.4 %. Quality index optimal values were found at 62.9 °C and 1.0 m/s using genetic algorithm.