Promoting Success in the Introduction of Health Information Systems

The significant number of publications describing unsuccessful cases in the introduction of health information systems makes it advisable to analyze the factors that may be contributing to such failures. However, the very notion of success is not equally assumed in all publications. Based in a literature review, the authors argue that the introduction of systems must be based in an eclectic combination of knowledge fields, adopting methodologies that strengthen the role of organizational culture and human resources in this project, as a whole. On the other hand, the authors argue that the introduction of systems should be oriented by a previously defined matrix of factors, against which the success can be measured.

Automatic modeling of pectus excavatum corrective prosthesis using artificial neural networks

Pectus excavatum is the most common deformity of the thorax. Pre-operative diagnosis usually includes Computed Tomography (CT) to successfully employ a thoracic prosthesis for anterior chest wall remodeling. Aiming at the elimination of radiation exposure, this paper presents a novel methodology for the replacement of CT by a 3D laser scanner (radiation-free) for prosthesis modeling. The complete elimination of CT is based on an accurate determination of ribs position and prosthesis placement region through skin surface points. The developed solution resorts to a normalized and combined outcome of an artificial neural network (ANN) set. Each ANN model was trained with data vectors from 165 male patients and using soft tissue thicknesses (STT) comprising information from the skin and rib cage (automatically determined by image processing algorithms). Tests revealed that ribs position for prosthesis placement and modeling can be estimated with an average error of 5.0 ± 3.6 mm. One also showed that the ANN performance can be improved by introducing a manually determined initial STT value in the ANN normalization procedure (average error of 2.82 ± 0.76 mm). Such error range is well below current prosthesis manual modeling (approximately 11 mm), which can provide a valuable and radiation-free procedure for prosthesis personalization.

Automatic modeling of pectus excavatum corrective prosthesis using artificial neural networks

Pectus excavatum is the most common deformity of the thorax. Pre-operative diagnosis usually includes Computed Tomography (CT) to successfully employ a thoracic prosthesis for anterior chest wall remodeling. Aiming at the elimination of radiation exposure, this paper presents a novel methodology for the replacement of CT by a 3D laser scanner (radiation-free) for prosthesis modeling. The complete elimination of CT is based on an accurate determination of ribs position and prosthesis placement region through skin surface points. The developed solution resorts to a normalized and combined outcome of an artificial neural network (ANN) set. Each ANN model was trained with data vectors from 165 male patients and using soft tissue thicknesses (STT) comprising information from the skin and rib cage (automatically determined by image processing algorithms). Tests revealed that ribs position for prosthesis placement and modeling can be estimated with an average error of 5.0 ± 3.6 mm. One also showed that the ANN performance can be improved by introducing a manually determined initial STT value in the ANN normalization procedure (average error of 2.82 ± 0.76 mm). Such error range is well below current prosthesis manual modeling (approximately 11 mm), which can provide a valuable and radiation-free procedure for prosthesis personalization.

Artificial neural networks for automatic modelling of the pectus excavatum corrective prosthesis

Pectus excavatum is the most common deformity of the thorax and usually comprises Computed Tomography (CT) examination for pre-operative diagnosis. Aiming at the elimination of the high amounts of CT radiation exposure, this work presents a new methodology for the replacement of CT by a laser scanner (radiation-free) in the treatment of pectus excavatum using personally modeled prosthesis. The complete elimination of CT involves the determination of ribs external outline, at the maximum sternum depression point for prosthesis placement, based on chest wall skin surface information, acquired by a laser scanner. The developed solution resorts to artificial neural networks trained with data vectors from 165 patients. Scaled Conjugate Gradient, Levenberg-Marquardt, Resilient Back propagation and One Step Secant gradient learning algorithms were used. The training procedure was performed using the soft tissue thicknesses, determined using image processing techniques that automatically segment the skin and rib cage. The developed solution was then used to determine the ribs outline in data from 20 patient scanners. Tests revealed that ribs position can be estimated with an average error of about 6.82±5.7 mm for the left and right side of the patient. Such an error range is well below current prosthesis manual modeling (11.7±4.01 mm) even without CT imagiology, indicating a considerable step forward towards CT replacement by a 3D scanner for prosthesis personalization.

Information and investor behavior surrounding earnings announcements

Preliminary version

The role of discriminant analysis in the refinement of customer satisfaction assessment

OBJECTIVE: To test discriminant analysis as a method of turning the information of a routine customer satisfaction survey (CSS) into a more accurate decision-making tool. METHODS: A 7-question, 10-multiple choice, self-applied questionnaire was used to study a sample of patients seen in two outpatient care units in Valparaíso, Chile, one of primary care (n=100) and the other of secondary care (n=249). Two cutting points were considered in the dependent variable (final satisfaction score): satisfied versus unsatisfied, and very satisfied versus all others. Results were compared with empirical measures (proportion of satisfied individuals, proportion of unsatisfied individuals and size of the median). RESULTS: The response rate was very high, over 97.0% in both units. A new variable, medical attention, was revealed, as explaining satisfaction at the primary care unit. The proportion of the total variability explained by the model was very high (over 99.4%) in both units, when comparing satisfied with unsatisfied customers. In the analysis of very satisfied versus all other customers, significant relationship was identified only in the case of the primary care unit, which explained a small proportion of the variability (41.9%). CONCLUSIONS: Discriminant analysis identified relationships not revealed by the previous analysis. It provided information about the proportion of the variability explained by the model. It identified non-significant relationships suggested by empirical analysis (e.g. the case of the relation very satisfied versus others in the secondary care unit). It measured the contribution of each independent variable to the explanation of the variation of the dependent one.

Design of a new test chamber for evaluation of the toxicity of rubber infill

A test chamber was projected and built (according to ISO 16000-9 Standard) to simulate atmospheric conditions experienced by rubber infill (when applied in synthetic turf pitches) and measure accurately the airborne emissions of pollutants such as dusts and volatile organic compounds (VOC), as well as pollutants present in leachates. It should be pointed out that standard ISO 16000-9 is only concerned with the determination of the emission of VOC from building products and furnishing (not specific of synthetic turf materials), whereas other standards are concerned with the emission of leachates only. This procedure is to be considered as a technical option to the lysimeter "global turf system evaluation" when the rubber infill alone is to be evaluated. The advantage of the proposed option considering this "test chamber" is its simplicity and economy. This test chamber is actually installed and being used for tests in LAIST.

Histogram-based DNA analysis for the visualization of chromosome, genome and species information

We describe a novel approach to explore DNA nucleotide sequence data, aiming to produce high-level categorical and structural information about the underlying chromosomes, genomes and species. The article starts by analyzing chromosomal data through histograms using fixed length DNA sequences. After creating the DNA-related histograms, a correlation between pairs of histograms is computed, producing a global correlation matrix. These data are then used as input to several data processing methods for information extraction and tabular/graphical output generation. A set of 18 species is processed and the extensive results reveal that the proposed method is able to generate significant and diversified outputs, in good accordance with current scientific knowledge in domains such as genomics and phylogenetics.

Scheduling distributed energy resources in an isolated grid - an artificial neural network approach

Power Systems (PS), have been affected by substantial penetration of Distributed Generation (DG) and the operation in competitive environments. The future PS will have to deal with large-scale integration of DG and other distributed energy resources (DER), such as storage means, and provide to market agents the means to ensure a flexible and secure operation. Virtual power players (VPP) can aggregate a diversity of players, namely generators and consumers, and a diversity of energy resources, including electricity generation based on several technologies, storage and demand response. This paper proposes an artificial neural network (ANN) based methodology to support VPP resource schedule. The trained network is able to achieve good schedule results requiring modest computational means. A real data test case is presented.

Combining artificial intelligence techniques for the training of power system control centre operators

Control Centre operators are essential to assure a good performance of Power Systems. Operators’ actions are critical in dealing with incidents, especially severe faults, like blackouts. In this paper we present an Intelligent Tutoring approach for training Portuguese Control Centre operators in incident analysis and diagnosis, and service restoration of Power Systems, offering context awareness and an easy integration in the working environment.

An integrated system to support electricity tariff contract definition

This paper presents an integrated system that helps both retail companies and electricity consumers on the definition of the best retail contracts and tariffs. This integrated system is composed by a Decision Support System (DSS) based on a Consumer Characterization Framework (CCF). The CCF is based on data mining techniques, applied to obtain useful knowledge about electricity consumers from large amounts of consumption data. This knowledge is acquired following an innovative and systematic approach able to identify different consumers’ classes, represented by a load profile, and its characterization using decision trees. The framework generates inputs to use in the knowledge base and in the database of the DSS. The rule sets derived from the decision trees are integrated in the knowledge base of the DSS. The load profiles together with the information about contracts and electricity prices form the database of the DSS. This DSS is able to perform the classification of different consumers, present its load profile and test different electricity tariffs and contracts. The final outputs of the DSS are a comparative economic analysis between different contracts and advice about the most economic contract to each consumer class. The presentation of the DSS is completed with an application example using a real data base of consumers from the Portuguese distribution company.

Determinants of vaccination after the Colombian health system reform

OBJECTIVE: To assess the effects of individual, household and healthcare system factors on poor children's use of vaccination after the reform of the Colombian health system. METHODS: A household survey was carried out in a random sample of insured poor population in Bogota, in 1999. The conceptual and analytical framework was based on the Andersen's Behavioral Model of Health Services Utilization. It considers two units of analysis for studying vaccination use and its determinants: the insured poor population, including the children and their families characteristics; and the health care system. Statistical analysis were carried out by chi-square test with 95% confidence intervals, multivariate regression models and Cronbach's alpha coefficient. RESULTS: The logistic regression analysis showed that vaccination use was related not only to population characteristics such as family size (OR=4.3), living area (OR=1.7), child's age (OR=0.7) and head-of-household's years of schooling (OR=0.5), but also strongly related to health care system features, such as having a regular health provider (OR=6.0) and information on providers' schedules and requirements for obtaining care services (OR=2.1). CONCLUSIONS: The low vaccination use and the relevant relationships to health care delivery systems characteristics show that there are barriers in the healthcare system, which should be assessed and eliminated. Non-availability of regular healthcare and deficient information to the population are factors that can limit service utilization.

Avaliação dos comportamentos de pastejo e suas relações com caracteres individuais dos bovinos de corte

Pós-graduação em Zootecnia - FCAV

Comorbidity adjustment index for the international classification of diseases, 10

OBJECTIVE: To develop a Charlson-like comorbidity index based on clinical conditions and weights of the original Charlson comorbidity index. METHODS: Clinical conditions and weights were adapted from the International Classification of Diseases, 10th revision and applied to a single hospital admission diagnosis. The study included 3,733 patients over 18 years of age who were admitted to a public general hospital in the city of Rio de Janeiro, southeast Brazil, between Jan 2001 and Jan 2003. The index distribution was analyzed by gender, type of admission, blood transfusion, intensive care unit admission, age and length of hospital stay. Two logistic regression models were developed to predict in-hospital mortality including: a) the aforementioned variables and the risk-adjustment index (full model); and b) the risk-adjustment index and patient's age (reduced model). RESULTS: Of all patients analyzed, 22.3% had risk scores >1, and their mortality rate was 4.5% (66.0% of them had scores >1). Except for gender and type of admission, all variables were retained in the logistic regression. The models including the developed risk index had an area under the receiver operating characteristic curve of 0.86 (full model), and 0.76 (reduced model). Each unit increase in the risk score was associated with nearly 50% increase in the odds of in-hospital death. CONCLUSIONS: The risk index developed was able to effectively discriminate the odds of in-hospital death which can be useful when limited information is available from hospital databases.

Implementação e validação de um método de avaliação do perfil de ácidos gordos e do teor de gordura em alimentos por cromatografia gasosa

Nos dias de hoje é necessário criar hábitos de vida mais saudáveis que contribuam para o bem-estar da população. Adoptar medidas e práticas de modo regular e disciplinado, pode diminuir o risco do aparecimento de determinadas doenças, como a obesidade, as doenças cardiovasculares, a hipertensão, a diabetes, alguns tipos de cancro e tantas outras. É também importante salientar que, uma alimentação cuidada dá saúde e aumenta a esperança média de vida. Em Portugal, nos últimos anos, os costumes alimentares da população têm vindo a alterar-se significativamente. As refeições caseiras confeccionadas com produtos frescos dão lugar à designada “cultura do fast food”. Em contrapartida, os consumidores são cada vez mais exigentes, estando em permanente alerta no que se refere ao estado dos alimentos. A rotulagem de um produto, para além da função publicitária, tem vindo a ser objecto de legislação específica de forma a fornecer informação simples e clara, correspondente à composição, qualidade, quantidade, validade ou outras características do produto. Estas informações devem ser acessíveis a qualquer tipo de público, com mais ou menos formação e de qualquer estrato social. A qualidade e segurança dos produtos deve basear-se na garantia de que todos os ingredientes, materiais de embalagem e processos produtivos são adequados à produção de produtos seguros, saudáveis e saborosos. A Silliker Portugal, S.A. é uma empresa independente de prestação de serviços para o sector agro-alimentar, líder mundial na prestação de serviços para a melhoria da qualidade e segurança alimentar. A Silliker dedica-se a ajudar as empresas a encontrar soluções para os desafios actuais do sector, oferecendo uma ampla gama de serviços, onde se inclui o serviço de análises microbiológicas, químicas e sensorial; consultadoria em segurança alimentar e desenvolvimento; auditorias; rotulagem e legislação. A actualização permanente de procedimentos na procura de uma melhoria contínua é um dos objectivos da empresa. Para responder a um dos desafios colocados à Silliker, surgiu este trabalho, que consistiu no desenvolvimento de um novo método para determinação de ácidos gordos e da gordura total em diferentes tipos de alimentos e comparação dos resultados, com os obtidos com o método analítico até então adoptado. Se a gordura é um elemento de grande importância na alimentação, devido às suas propriedades nutricionais e organoléticas, recentemente, os investigadores têm focado a sua atenção nos mais diversos ácidos gordos (saturados, monoinsaturados e polinsaturados), em particular nos ácidos gordos essenciais e nos isómeros do ácido linoleico conjugado (CLA), uma mistura de isómeros posicionais e geométricos do ácido linoleico com actividade biológica importante. A técnica usada nas determinações foi a cromatografia gasosa com ionização de chama, GC-FID, tendo as amostras sido previamente tratadas e extraídas de acordo com o tipo de matriz. A metodologia analítica desenvolvida permitiu a correcta avaliação do perfil em ácidos gordos, tendo-se para isso usado uma mistura de 37 ésteres metílicos, em que o ácido gordo C13:0 foi usado como padrão interno. A identificação baseou-se nos tempos de retenção de cada ácido gordo da mistura e para a quantificação usaram-se os factores de resposta. A validação do método implementado foi baseada nos resultados obtidos no estudo de três matrizes relativas a materiais certificados pela BIPEA (Bureau Interprofessionnel des Etudes Analytiques), para o que foram efectuadas doze réplicas de cada matriz. Para cada réplica efectuada foi calculado o teor de matéria gorda, sendo posteriormente o resultado comparado com o emitido pela entidade certificada. Após análise de cada constituinte foi também possível calcular o teor em ácidos gordos saturados, monoinsaturados e polinsaturados. A determinação do perfil em ácidos gordos dos materiais certificados foi aceitável atendendo aos valores obtidos, os quais se encontravam no intervalo de valores admissíveis indicados nos relatórios. A quantificação da matéria gorda no que se refere à matriz de “Paté à Tartinier” apresentou um z-score de 4,3, o que de acordo com as exigências internas da Silliker, não é válido. Para as outras duas matrizes (“Mélange Nutritif” e “Plat cuisiné à base de viande”) os valores de z-score foram, respectivamente, 0,7 e -1,0, o que permite concluir a validade do método. Para que o método possa vir a ser adoptado como método alternativo é necessário um estudo mais alargado relativamente a amostras com diferentes composições. O método foi aplicado na análise de amostras de fiambre, leite gordo, queijo, ovo com ómega 3, amendoim e óleo de girassol, e os resultados foram comparados com os obtidos pelo método até então adoptado.