938 resultados para survivorship care models


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O trabalho analisa a potencialidade do desenvolvimento de alian??as entre o p??blico e o privado na gest??o p??blica municipal brasileira da sa??de. A relev??ncia da quest??o pauta-se na transfer??ncia de responsabilidade da presta????o de servi??os de sa??de para os munic??pios, posterior ?? promulga????o da Constitui????o Federal, aliada ?? limita????o da capacidade de gest??o dos mesmos. As an??lises aqui tratadas referem-se ??s alian??as previstas no arcabou??o legal brasileiro, estabelecidas entre o ente p??blico e o terceiro setor. Essas alian??as s??o introduzidas pela reforma do aparelho do Estado, em 1995, no ??mbito da qual se utilizou a estrat??gia de publiciza????o que tratou do fortalecimento dessa alian??a entre o Estado e o Terceiro Setor. A partir dos modelos poss??veis de parcerias com o terceiro setor, este estudo apresenta uma an??lise do modelo das organiza????es sociais (OS), trazendo ?? luz estrat??gias e desafios para sua implementa????o.

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Purpose – The health and social care sector is receiving growing attention due to the increased life expectancy and to the public demand for a better quality of life and better health services. New cost-efficient approaches are required, and the paper aims to present and discuss the main results of a study undertaken in a Portuguese municipality on the perceived relevance of an e-marketplace of social and healthcare services for the inhabitants in general, and for people with special needs in particular, and the identification of the most relevant services to be offered through this platform. Design/methodology/approach – A wide survey was undertaken to identify the needs of potential users and their expectancies with relation to the proposed platform. The results of the study are a support for the project promoters to understand the viability of the solution and the requirements to the deployment of the pilot experiment, as well as to drive the selection of domains of activities/classes of services to be offered by the platform. Findings – Services such as information about healthcare services, home monitoring/accompanying services 24 hours per day, and personal hygiene services provided at home are the ones recognized by the inquired citizens as the most important, which indicates that the potential users will be mostly people with special needs or their family or caregivers. Originality/value – While still at a preliminary development phase, the project represents a good opportunity to develop a totally innovative service with high potential impact for the senior population and for individuals with special needs.

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The exponential increase of home-bound persons who live alone and are in need of continuous monitoring requires new solutions to current problems. Most of these cases present illnesses such as motor or psychological disabilities that deprive of a normal living. Common events such as forgetfulness or falls are quite common and have to be prevented or dealt with. This paper introduces a platform to guide and assist these persons (mostly elderly people) by providing multisensory monitoring and intelligent assistance. The platform operates at three levels. The lower level, denominated ‘‘Data acquisition and processing’’performs the usual tasks of a monitoring system, collecting and processing data from the sensors for the purpose of detecting and tracking humans. The aim is to identify their activities in an intermediate level called ‘‘activity detection’’. The upper level, ‘‘Scheduling and decision-making’’, consists of a scheduler which provides warnings, schedules events in an intelligent manner and serves as an interface to the rest of the platform. The idea is to use mobile and static sensors performing constant monitoring of the user and his/her environment, providing a safe environment and an immediate response to severe problems. A case study on elderly fall detection in a nursery home bedroom demonstrates the usefulness of the proposal.

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The health and social care sector is receiving growing attention for the last years, due to the increased life expectancy, the public demand for a better quality of life and for better health services. These requirements can be met with more cost-efficient approaches and using new technology-based solutions for providing services. The paper presents and discusses some of the main results of a study undertaken in Guimarães, a Municipality at the North of Portugal, on the perceived relevance of an e-Marketplace of social and healthcare services for the inhabitants in general, and in particular for people with special needs; the study also included the identification of the most relevant services to be offered by this platform and allowed concluding that such an e-Marketplace is of recognized relevance and that it is expected a good adhesion from the population.

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The relation between patient and physician in most modern Health Care Sys- tems is sparse, limited in time and very in exible. On the other hand, and in contradiction with several recent studies, most physicians do not rely their patient diagnostics evaluations on intertwined psychological and social nature factors. Facing these problems and trying to improve the patient/physician relation we present a mobile health care solution to im- prove the interaction between the physician and his patients. The solution serves not only as a privileged mean of communication between physicians and patients but also as an evolutionary intelligent platform delivering a mobile rule based system.

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We estimate and compare the performance of Portuguese-based mutual funds that invest in the domestic market and in the European market using unconditional and conditional models of performance evaluation. Besides applying both partial and full conditional models, we use European information variables, instead of the most common local ones, and consider stochastically detrended conditional variables in order to avoid spurious regressions. The results suggest that mutual fund managers are not able to outperform the market, presenting negative or neutral performance. The incorporation of conditioning information in performance evaluation models is supported by our findings, as it improves the explanatory power of the models and there is evidence of both time-varying betas and alphas related to the public information variables. It is also shown that the number of lags to be used in the stochastic detrending procedure is a critical choice, as it will impact the significance of the conditioning information. In addition, we observe a distance effect, since managers who invest locally seem to outperform those who invest in the European market. However, after controlling for public information, this effect is slightly reduced. Furthermore, the results suggest that survivorship bias has a small impact on performance estimates.

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This paper examines the performance of Portuguese equity funds investing in the domestic and in the European Union market, using several unconditional and conditional multi-factor models. In terms of overall performance, we find that National funds are neutral performers, while European Union funds under-perform the market significantly. These results do not seem to be a consequence of management fees. Overall, our findings are supportive of the robustness of conditional multi-factor models. In fact, Portuguese equity funds seem to be relatively more exposed to smallcaps and more value-oriented. Also, they present strong evidence of time-varying betas and, in the case of the European Union funds, of time-varying alphas too. Finally, in terms of market timing, our tests suggest that mutual fund managers in our sample do not exhibit any market timing abilities. Nevertheless, we find some evidence of timevarying conditional market timing abilities but only at the individual fund level.

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Abstract. Interest in design and development of graphical user interface (GUIs) is growing in the last few years. However, correctness of GUI's code is essential to the correct execution of the overall software. Models can help in the evaluation of interactive applications by allowing designers to concentrate on its more important aspects. This paper describes our approach to reverse engineering abstract GUI models directly from the Java/Swing code.

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Color model representation allows characterizing in a quantitative manner, any defined color spectrum of visible light, i.e. with a wavelength between 400nm and 700nm. To accomplish that, each model, or color space, is associated with a function that allows mapping the spectral power distribution of the visible electromagnetic radiation, in a space defined by a set of discrete values that quantify the color components composing the model. Some color spaces are sensitive to changes in lighting conditions. Others assure the preservation of certain chromatic features, remaining immune to these changes. Therefore, it becomes necessary to identify the strengths and weaknesses of each model in order to justify the adoption of color spaces in image processing and analysis techniques. This chapter will address the topic of digital imaging, main standards and formats. Next we will set the mathematical model of the image acquisition sensor response, which enables assessment of the various color spaces, with the aim of determining their invariance to illumination changes.

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Current software development relies increasingly on non-trivial coordination logic for com- bining autonomous services often running on di erent platforms. As a rule, however, in typical non-trivial software systems, such a coordination layer is strongly weaved within the application at source code level. Therefore, its precise identi cation becomes a major methodological (and technical) problem which cannot be overestimated along any program understanding or refactoring process. Open access to source code, as granted in OSS certi cation, provides an opportunity for the devel- opment of methods and technologies to extract, from source code, the relevant coordination information. This paper is a step in this direction, combining a number of program analysis techniques to automatically recover coordination information from legacy code. Such information is then expressed as a model in Orc, a general purpose orchestration language

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The relation between patient and physician in most modern Health Care Systems is sparse, limited in time and very inflexible. On the other hand, and in contradiction with several recent studies, most physicians do not rely their patient diagnostics evaluations on intertwined psychological and social nature factors. Facing these problems and trying to improve the patient/physician relation we present a mobile health care solution to improve the interaction between the physician and his patients. The solution serves not only as a privileged mean of communication between physicians and patients but also as an evolutionary intelligent platform delivering a mobile rule based system.

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The authors are developing a pilot project for a Municipality in the North of Portugal, envisaging the definition and implementation of an e-marketplace for healthcare and social services, in order to facilitate the interaction between healthcare and social services professionals and people with special needs (or their relatives). Based on the results of a survey on user needs analysis and expectations conducted in 2011, the paper discusses the relevance and interest of such platforms and the main drivers and motivations of the population for using such services, as well as which services would motivate citizens to use the platform. The results of the study will be used to select the products and services perceived to be the most desired by the potential users. The paper thus makes three main contributions: (1) the results of the study confirm the interest and the perceived potential of such a service, from the end-users perspective; (2) the findings support the advantage of expanding this pilot project to a full scale implementation; and (3) the performed analysis improves our understanding of the relations between the characteristics of the inquired population and the perceived interest in such platforms.

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In a Europe increasingly aging, it is now recognized the importance and potential of the service industry for ageing well based on information and communication technologies (ICT), as exemplified by the electronic market of social services and health care, the GuiMarket, proposed by the authors. However, this new range of services requires that individuals have advanced digital skills to fully participate in society. Based on the results of a survey made on a sample of 315 individuals, this paper discusses the importance granted GuiMarket and the intended frequency of use, concluding there is a close relationship between ICT access and use that respondents anticipate making of GuiMarket and alike services.

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A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.

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A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.