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Purpose: In today’s medical field, it is an essential quality competency for staff to not only recognize the importance of patient decision-making and the skills to support it, but also implement it. This study aimed to establish a training program on decision support for healthcare professionals and examine its effectiveness. Method: We conducted the training at a medical institution and conducted a questionnaire survey at two points before and after the training. A total of 88 nurses and doctors participated in the survey. Result: We developed a two-hour training on the knowledge and skills needed for decision support. Questionnaire results showed improvements in literacy and efficacy before and after the training. Discussion: It was confirmed that the training led to an in-depth understanding of the participants’ decision support, and increased the sense of efficacy in their daily work, particularly through responding to patients according to patients’ cognitive and physical assessments, and in actively supporting those who have difficulty in making decisions. There were references to the significance of re-learning and the possibility of applying the training to difficult situations in participants comments. In the future, it is necessary to study decision support with reference toco-operation in the medical field where collaboration among multiple professions is indispensable.
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Objective To study the effective text mining methods by mining the information in electronic medical records( EMR) in order to achieve their value in support of decision-making. Methods Two thousand and five hundred EMR of gastric cancer patients were randomly divided into training group ( n＝1500) and testing group( n＝1000) . The words in the text of EMR of training group were identified using dictionary in combination with statistical methods. The segmented words were clustered according to the co-occurrence frequency of each segmented word and the treatment plan extracted from EMR. The matched number of words in each cluster from the text of EMR of training group was recorded. A decision-making support model of Bayes discrimination function was established according to the matched number of words in each cluster from the text of EMR of training group and treatment plan to verify the EMR in training group and to evaluate the words segmenting methods and the discrimination model. Results Fifty randomly selected RME showed that the recall rate, accurate rate and F-1 value of segmented words were 74. 24%, 82.30% and 78.06% respectively. The accurate rate of the established discrimination model was 62% for the identification of EMR of testing group when the segmented words were clustered into 5 categories. Conclusion The efficiency of dictionary in combination with statistical methods is good for identifying words from the text of EMR. Cluster-based text mining of EMR can achieve the decision-making support value of EMR, but the accuracy of the established decision-making support model is not as high as expected. Further study is thus necessary to identify the words from the text of EMR and the process of segmented words in establishing the decision-making support model.
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RESUMO A Avaliação do Ciclo de Vida (ACV) vem sendo utilizada como apoio à tomada de decisão para avaliação e escolha de sistemas de gerenciamento de resíduos sólidos urbanos (RSU). O objetivo desta pesquisa foi analisar cenários de gerenciamento de resíduos para o município de Garibaldi, Rio Grande do Sul, por meio da técnica da ACV. Cinco cenários foram simulados integrando processos de reciclagem, compostagem, digestão anaeróbia e incineração, para os quais foi elaborado o Inventário do Ciclo de Vida, utilizando o programa computacional IWM-2, que calcula os subprodutos das tecnologias de tratamento avaliadas e seus respectivos inventários do ciclo de vida, em termos de consumo de energia, emissões à água, ao ar, e ao solo. Para a Avaliação do Impacto do Ciclo de Vida, foram aplicados cálculos atribuídos às categorias de impacto ambiental: mudanças climáticas, formação de foto-oxidantes, acidificação, eutrofização, toxicidade humana e aos indicadores uso de energia e disposição de resíduos sólidos secos e orgânicos em aterro. Os cenários que contemplaram a reciclagem associada à compostagem, a reciclagem associada à digestão anaeróbia seguida por compostagem e a reciclagem associada à compostagem com a incineração de rejeitos e com recuperação de energia apresentaram o melhor desempenho ambiental, de modo que são indicados como possíveis soluções de tratamento dos RSU para o município estudado.
ABSTRACT The Life Cycle Assessment (LCA) has emerged as an effective technique to evaluate municipal solid waste management systems (MSW), serving as support for decision making of the best model to be adopted. The objective of this research was to analyze scenarios through the LCA technique in the city of Garibaldi, Rio Grande do Sul, Brazil, comparing different alternatives of treatment and final disposal of MSW under the environmental aspect, and contribute to decision making, based on the study of the city of Garibaldi (RS). Five scenarios were simulated integrating processes such as recycling, composting, anaerobic digestion and incineration, for which the Life Cycle Inventory was prepared by means of the IWM-2 software, which calculates the evaluated treatment technologies by products and their respective life cycle inventories, in terms of energy consumption, emissions to water, air, and soil. For the Life Cycle Impact Assessment, calculations were applied to the categories of environmental impact, namely climate change, photo-oxidants formation, acidification, eutrophication and human toxicity, and indicators of energy use and recyclable and organic waste disposal into landfills. The scenarios that contemplated recycling associated with composting, recycling associated with anaerobic digestion followed by composting, and recycling associated with composting with incineration of waste and with energy recovery presented the best environmental performance, so they are indicated as possible treatment solutions for municipal solid waste in the case that was analyzed.
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<b>Objective：</b>There are few reports on decision-making support at palliative care clinics in designated regional cancer care hospitals. This study clarified the types of decisionmaking support patients with cancer and their families were provided by specialized outpatient palliative care services.<b> Method：</b>We retrospectively examined the medical records of 110 patients who had been referred to the palliative care clinic for home care between April 2012 and March 2014. <b>Results：</b>The median duration of receiving services from the palliative care clinic was 23 days（range：1～492 days）. The mean number of visits to the clinic was 4.7 visits（range：1～29 visits）. A total of 89 patients（80％）needed decision-making support. Of those 89 patients, 33（30％）required support in making a decision about anticancer treatment. Twenty-six（78％）of those 33 patients had just received the diagnosis or were receiving anticancer treatment. <b>Conclusion：</b>The study suggested that decision-making support in early stages is an important role for a palliative care clinic in a designated regional cancer care hospital.
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Objetivo Determinar la efectividad del método multicriterio Pugh para la selección de tecnologías biomédicas en el proceso de nuevas adquisiciones. Materiales y Métodos Se realizó un estudio de los métodos multicriterios de toma de decisión. El método seleccionado fue el método "Datum" o Pugh. Se realizó el cálculo y caracterización del tamaño de la muestra de los expertos que participarían en el ensayo. Se obtuvo una muestra de 23 expertos. Se realizó el ejercicio de selección de la tecnología de electrocardiografía, empleando el método de toma de decisión seleccionado. Resultados De las 46 pruebas realizadas el modelo más utilizado como referencia fue el modelo codificado como "3". El modelo que más fue seleccionado como la "mejor opción" fue el equipo o modelo "5". Conclusiones. El método Pugh resultó ser efectivo para la toma de decisión a la hora de seleccionar tecnologías biomédicas, pues en un 87 por ciento de los casos siempre se obtuvo el mismo modelo de referencia como el óptimo.
Objective Determining the Pugh multicriteria method's effectiveness as a selection tool when acquiring new technology. Materials and Methods The state of the art regarding multicriteria method use was studied; the Datum or Pugh method was selected. The size of the sample of experts participating in the trial was calculated and characterised; a data sample of 23 experts was thus obtained. Electrocardiography technology was selected by using the selected decision-making method; 5 models from different providers were used. Results 46 tests were conducted. The model labelled "3" was selected as referent in most cases, whilst the model labelled "5" was selected as being the best option in most cases. Conclusions The Pugh method was effective as a method for decision-making when selecting biomedical technologies as the same model was always selected by the experts as being the best option in 87 percent of the tests applied.