Assessing an Adolescent's Capacity for Autonomous Decision-Making in Clinical Care.

The purpose of this article is to provide policy guidance on how to assess the capacity of minor adolescents for autonomous decision-making without a third party authorization, in the field of clinical care. In June 2014, a two-day meeting gathered 20 professionals from all continents, working in the field of adolescent medicine, neurosciences, developmental and clinical psychology, sociology, ethics, and law. Formal presentations and discussions were based on a literature search and the participants' experience. The assessment of adolescent decision-making capacity includes the following: (1) a review of the legal context consistent with the principles of the Convention on the Rights of the Child; (2) an empathetic relationship between the adolescent and the health care professional/team; (3) the respect of the adolescent's developmental stage and capacities; (4) the inclusion, if relevant, of relatives, peers, teachers, or social and mental health providers with the adolescent's consent; (5) the control of coercion and other social forces that influence decision-making; and (6) a deliberative stepwise appraisal of the adolescent's decision-making process. This stepwise approach, already used among adults with psychiatric disorders, includes understanding the different facets of the given situation, reasoning on the involved issues, appreciating the outcomes linked with the decision(s), and expressing a choice. Contextual and psychosocial factors play pivotal roles in the assessment of adolescents' decision-making capacity. The evaluation must be guided by a well-established procedure, and health professionals should be trained accordingly. These proposals are the first to have been developed by a multicultural, multidisciplinary expert panel.

Prototype of a web-based participative decision support platform in natural hazards and risk management

This paper presents the current state and development of a prototype web-GIS (Geographic Information System) decision support platform intended for application in natural hazards and risk management, mainly for floods and landslides. This web platform uses open-source geospatial software and technologies, particularly the Boundless (formerly OpenGeo) framework and its client side software development kit (SDK). The main purpose of the platform is to assist the experts and stakeholders in the decision-making process for evaluation and selection of different risk management strategies through an interactive participation approach, integrating web-GIS interface with decision support tool based on a compromise programming approach. The access rights and functionality of the platform are varied depending on the roles and responsibilities of stakeholders in managing the risk. The application of the prototype platform is demonstrated based on an example case study site: Malborghetto Valbruna municipality of North-Eastern Italy where flash floods and landslides are frequent with major events having occurred in 2003. The preliminary feedback collected from the stakeholders in the region is discussed to understand the perspectives of stakeholders on the proposed prototype platform.

The influence of decision-maker effort and case complexity on appealed rulings subject to multi-categorical selection

This study extends the standard econometric treatment of appellate court outcomes by 1) considering the role of decision-maker effort and case complexity, and 2) adopting a multi-categorical selection process of appealed cases. We find evidence of appellate courts being affected by both the effort made by first-stage decision makers and case complexity. This illustrates the value of widening the narrowly defined focus on heterogeneity in individual-specific preferences that characterises many applied studies on legal decision-making. Further, the majority of appealed cases represent non-random sub-samples and the multi-categorical selection process appears to offer advantages over the more commonly used dichotomous selection models.

An ABC for decision making

The present study was aimed at proposing a systematic evaluation of cranial computed tomography, identifying the main aspects to be analyzed in order to facilitate the decision making process regarding diagnosis and management in emergency settings. The present descriptive study comprised a literature review at the following databases: Access Medicine and Access Emergency Medicine (McGraw- Hill Education); British Medical Journal Evidence Center; UptoDate; Bireme; PubMed; Lilacs; SciELO; ProQuest; Micromedex (Thomson Reuters); Embase. Once the literature review was completed, the authors identified the main diseases with tomographic repercussions and proposed the present system to evaluate cranial computed tomography images. An easy-to-memorize ABC system will facilitate the decision making in emergency settings, as it covers the main diseases encountered by intensivists and emergency physicians, and provides a sequential guidance about anatomical structures to be investigated as well as their respective alterations.

The forced adoption of a fast-track appraisal process for a breast cancer treatment in UK

Trastuzumab (Herceptin ®, Roche) is approved in UK for the treatment of the metastatic breast cancer since 2001. As of 2005, concomitantly with the publication of 3 studies that showed it produces a 50% reduction of the recurrence rates of breast cancer, trastuzumab started to be prescribed in the earlt adjuvant treatrnent of this disease. Und June 2006, trastuzumab did not have both: 1) regulatory approval and 2) NICE [National Institute for Health and Clinical Excellence] recommendation for the use in early stages of breast cancer. During the period until June 2006, the trastuzumab use in those patients was not reimbursed and because the cost of trastuzumab is equal with the yearly UK average income, most of patients could not self fund their treatrnent. Before the publication of the final NICE guidance, the new data of trastuzumab in early breast cancer raised enormous patient and professional interest and expectations. A great volume of public and professional pressure was generated to transcend a system by which Primary Care Trusts can reimburse a treatment only after a formal guidance was issued. This paper draw on a case study depicting and analyzing the process by which regulatory approval and NICE recommendations were achieved in a record time and how trastuzumab became a standard treatment on early adjuvant breast cancer. According to the data we gathered in this work we were witnessing one of the fastest processes of adoption of a health care technology since the creation of NICE, in 1999. This study addresses the following research question: How and why does the adoption pattern of trastuzumab differ from the rational decision-making model of the reimbursement process in UK? [Author, p. 4]

Magnetic resonance imaging of the vagina: an overview for radiologists with emphasis on clinical decision making

AbstractMagnetic resonance imaging is a method with high contrast resolution widely used in the assessment of pelvic gynecological diseases. However, the potential of such method to diagnose vaginal lesions is still underestimated, probably due to the scarce literature approaching the theme, the poor familiarity of radiologists with vaginal diseases, some of them relatively rare, and to the many peculiarities involved in the assessment of the vagina. Thus, the authors illustrate the role of magnetic resonance imaging in the evaluation of vaginal diseases and the main relevant findings to be considered in the clinical decision making process.

Approximation to the theory of affinities to manage the problems of the groupping process

New economic and enterprise needs have increased the interest and utility of the methods of the grouping process based on the theory of uncertainty. A fuzzy grouping (clustering) process is a key phase of knowledge acquisition and reduction complexity regarding different groups of objects. Here, we considered some elements of the theory of affinities and uncertain pretopology that form a significant support tool for a fuzzy clustering process. A Galois lattice is introduced in order to provide a clearer vision of the results. We made an homogeneous grouping process of the economic regions of Russian Federation and Ukraine. The obtained results gave us a large panorama of a regional economic situation of two countries as well as the key guidelines for the decision-making. The mathematical method is very sensible to any changes the regional economy can have. We gave an alternative method of the grouping process under uncertainty.

Offering planning process development: Bridging the Offering Gaps and Consolidating Top Priority Needs in Product Offering

The aim of this Thesis is to study how to manage the front-end of the offering planning process. This includes actual process development and methods to gather and analyze information to achieve the best outcome in customer oriented product offering. Study is carried out in two parts: theoretical part and company related part. Theoretical framework is created introducing different types of approaches to manage product planning processes. Products are seen as platforms and they are broken down to subsystems to show different parts of the development. With the help of the matrix-based approaches product platform related information is gathered and analyzed. In this kind of analysis business/market drivers and cus-tomer/competitor information are connected with product subsystems. This gives possibilities to study product gaps/needs and possible future ideas/scenarios in different customer segments. Company related part consists of offering planning process development in real company environment. Process formation includes documents and tools that guide planning from the information gathering to the prioritization and decision making.

Searching for consensus in ahp-group decision making. A bayesian perspective

This paper sets out to identify the initial positions of the different decisionmakers who intervene in a group decision making process with a reducednumber of actors, and to establish possible consensus paths between theseactors. As a methodological support, it employs one of the most widely-knownmulticriteria decision techniques, namely, the Analytic Hierarchy Process(AHP). Assuming that the judgements elicited by the decision makers follow theso-called multiplicative model (Crawford and Williams, 1985; Altuzarra et al.,1997; Laininen and Hämäläinen, 2003) with log-normal errors and unknownvariance, a Bayesian approach is used in the estimation of the relative prioritiesof the alternatives being compared. These priorities, estimated by way of themedian of the posterior distribution and normalised in a distributive manner(priorities add up to one), are a clear example of compositional data that will beused in the search for consensus between the actors involved in the resolution ofthe problem through the use of Multidimensional Scaling tools

Group preference structures in AHP–group decision making

This paper presents a procedure that allows us to determine the preference structures(PS) associated to each of the different groups of actors that can be identified in a groupdecision making problem with a large number of individuals. To that end, it makesuse of the Analytic Hierarchy Process (AHP) (Saaty, 1980) as the technique to solvediscrete multicriteria decision making problems. This technique permits the resolutionof multicriteria, multienvironment and multiactor problems in which subjective aspectsand uncertainty have been incorporated into the model, constructing ratio scales correspondingto the priorities relative to the elements being compared, normalised in adistributive manner (wi = 1). On the basis of the individuals’ priorities we identifydifferent clusters for the decision makers and, for each of these, the associated preferencestructure using, to that end, tools analogous to those of Multidimensional Scaling.The resulting PS will be employed to extract knowledge for the subsequent negotiationprocesses and, should it be necessary, to determine the relative importance of thealternatives being compared using anyone of the existing procedures

Outsourcing process in pharmaceutical product development

The aim of this study was to create an outsourcing process for pharmaceutical product development. This study focuses on two main questions. The first question is “What is the outsourcing process model?” In the second phase key success factors of the outsourcing process are identified. As a result of the literature reviews, a general outsourcing process was created. Transaction cost economics and resource based view were used to derived a theoretical framework to the process by combining the existing processes presented in the literature. The model of process is considered used to the outsourcing broadly. The general outsourcing process was then developed further with the key factors that affect the success of pharmaceutical product development and the interviews of pharmaceutical outsourcing experts. The result of the research was the process consists of seven phases with key activities and expected outputs for each of the phases. In addition, the strategic decision-making framework for outsourcing decision in pharmaceutical product development is giving as well as the tools for selecting supplier and preparing structured contract. This study also gives some recommendations for managing the outsourcing process.

Cost evaluation process for competitors' products

A company’s capability to map out its cost position compared to other market players is important for competitive decision making. One aspect of cost position is direct product cost that illustrates the cost efficiency of a company’s product designs. If a company can evaluate and compare its own and other market players’ direct product costs, it can implement better decisions in product development and management, manufacturing, sourcing, etc. The main objective of this thesis was to develop a cost evaluation process for competitors’ products. This objective includes a process description and an analysis tool for cost evaluations. Additionally, process implementation is discussed as well. The main result of this thesis was a process description consisting of a sixteen steps process and an Excel based analysis tool. Since literature was quite limited in this field, the solution proposal was combined from many different theoretical concepts. It includes influences from reverse engineering, product cost assessment, benchmarking and cost based decision making. This solution proposal will lead to more systematic and standardized cost position analyses and result in better cost transparency in decision making.

Implementing a change management process into enterprise performance management applications

Information technology service management has become an important task in delivering information for management purposes. Especially applications containing information for decision making need to be agile and ready for changes. The aim of this study was to find a solution for successful implementation of an ITIL based change management process to enterprise resource management applications managed by the target organization. Literature review of the study introduces frameworks that are important for success of an IT project implementation. In addition an overview of ITIL and ITIL based change management process is presented. The result of the study was a framework of actions that are needed to accomplish to be successful in change management process implementation. It was noticed that defining success criterions, critical success factors and success measures is important for achieving the goals of the implementation project.

MCMC Analysis for Optimization of Stochastic Models

In any decision making under uncertainties, the goal is mostly to minimize the expected cost. The minimization of cost under uncertainties is usually done by optimization. For simple models, the optimization can easily be done using deterministic methods.However, many models practically contain some complex and varying parameters that can not easily be taken into account using usual deterministic methods of optimization. Thus, it is very important to look for other methods that can be used to get insight into such models. MCMC method is one of the practical methods that can be used for optimization of stochastic models under uncertainty. This method is based on simulation that provides a general methodology which can be applied in nonlinear and non-Gaussian state models. MCMC method is very important for practical applications because it is a uni ed estimation procedure which simultaneously estimates both parameters and state variables. MCMC computes the distribution of the state variables and parameters of the given data measurements. MCMC method is faster in terms of computing time when compared to other optimization methods. This thesis discusses the use of Markov chain Monte Carlo (MCMC) methods for optimization of Stochastic models under uncertainties .The thesis begins with a short discussion about Bayesian Inference, MCMC and Stochastic optimization methods. Then an example is given of how MCMC can be applied for maximizing production at a minimum cost in a chemical reaction process. It is observed that this method performs better in optimizing the given cost function with a very high certainty.

Communicative and Anticipatory Decision-Making Supported by Bayesian Networks

The purpose of this research is to draw up a clear construction of an anticipatory communicative decision-making process and a successful implementation of a Bayesian application that can be used as an anticipatory communicative decision-making support system. This study is a decision-oriented and constructive research project, and it includes examples of simulated situations. As a basis for further methodological discussion about different approaches to management research, in this research, a decision-oriented approach is used, which is based on mathematics and logic, and it is intended to develop problem solving methods. The approach is theoretical and characteristic of normative management science research. Also, the approach of this study is constructive. An essential part of the constructive approach is to tie the problem to its solution with theoretical knowledge. Firstly, the basic definitions and behaviours of an anticipatory management and managerial communication are provided. These descriptions include discussions of the research environment and formed management processes. These issues define and explain the background to further research. Secondly, it is processed to managerial communication and anticipatory decision-making based on preparation, problem solution, and solution search, which are also related to risk management analysis. After that, a solution to the decision-making support application is formed, using four different Bayesian methods, as follows: the Bayesian network, the influence diagram, the qualitative probabilistic network, and the time critical dynamic network. The purpose of the discussion is not to discuss different theories but to explain the theories which are being implemented. Finally, an application of Bayesian networks to the research problem is presented. The usefulness of the prepared model in examining a problem and the represented results of research is shown. The theoretical contribution includes definitions and a model of anticipatory decision-making. The main theoretical contribution of this study has been to develop a process for anticipatory decision-making that includes management with communication, problem-solving, and the improvement of knowledge. The practical contribution includes a Bayesian Decision Support Model, which is based on Bayesian influenced diagrams. The main contributions of this research are two developed processes, one for anticipatory decision-making, and the other to produce a model of a Bayesian network for anticipatory decision-making. In summary, this research contributes to decision-making support by being one of the few publicly available academic descriptions of the anticipatory decision support system, by representing a Bayesian model that is grounded on firm theoretical discussion, by publishing algorithms suitable for decision-making support, and by defining the idea of anticipatory decision-making for a parallel version. Finally, according to the results of research, an analysis of anticipatory management for planned decision-making is presented, which is based on observation of environment, analysis of weak signals, and alternatives to creative problem solving and communication.