Publication trends of shared decision making in 15 high impact medical journals: a full-text review with bibliometric analysis.

BACKGROUND: Shared Decision Making (SDM) is increasingly advocated as a model for medical decision making. However, there is still low use of SDM in clinical practice. High impact factor journals might represent an efficient way for its dissemination. We aimed to identify and characterize publication trends of SDM in 15 high impact medical journals. METHODS: We selected the 15 general and internal medicine journals with the highest impact factor publishing original articles, letters and editorials. We retrieved publications from 1996 to 2011 through the full-text search function on each journal website and abstracted bibliometric data. We included publications of any type containing the phrase "shared decision making" or five other variants in their abstract or full text. These were referred to as SDM publications. A polynomial Poisson regression model with logarithmic link function was used to assess the evolution across the period of the number of SDM publications according to publication characteristics. RESULTS: We identified 1285 SDM publications out of 229,179 publications in 15 journals from 1996 to 2011. The absolute number of SDM publications by journal ranged from 2 to 273 over 16 years. SDM publications increased both in absolute and relative numbers per year, from 46 (0.32% relative to all publications from the 15 journals) in 1996 to 165 (1.17%) in 2011. This growth was exponential (P < 0.01). We found fewer research publications (465, 36.2% of all SDM publications) than non-research publications, which included non-systematic reviews, letters, and editorials. The increase of research publications across time was linear. Full-text search retrieved ten times more SDM publications than a similar PubMed search (1285 vs. 119 respectively). CONCLUSION: This review in full-text showed that SDM publications increased exponentially in major medical journals from 1996 to 2011. This growth might reflect an increased dissemination of the SDM concept to the medical community.

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

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.

Improving strategic decision-making with simulation based decision support systems

Combating climate change is one of the key tasks of humanity in the 21st century. One of the leading causes is carbon dioxide emissions due to usage of fossil fuels. Renewable energy sources should be used instead of relying on oil, gas, and coal. In Finland a significant amount of energy is produced using wood. The usage of wood chips is expected to increase in the future significantly, over 60 %. The aim of this research is to improve understanding over the costs of wood chip supply chains. This is conducted by utilizing simulation as the main research method. The simulation model utilizes both agent-based modelling and discrete event simulation to imitate the wood chip supply chain. This thesis concentrates on the usage of simulation based decision support systems in strategic decision-making. The simulation model is part of a decision support system, which connects the simulation model to databases but also provides a graphical user interface for the decisionmaker. The main analysis conducted with the decision support system concentrates on comparing a traditional supply chain to a supply chain utilizing specialized containers. According to the analysis, the container supply chain is able to have smaller costs than the traditional supply chain. Also, a container supply chain can be more easily scaled up due to faster emptying operations. Initially the container operations would only supply part of the fuel needs of a power plant and it would complement the current supply chain. The model can be expanded to include intermodal supply chains as due to increased demand in the future there is not enough wood chips located close to current and future power plants.

Immediate Decision-Making and Information Needs in Intensive Care Coordination

The aim of this study was to develop a theoretical model for information integration to support the deci¬sion making of intensive care charge nurses, and physicians in charge – that is, ICU shift leaders. The study focused on the ad hoc decision-making and immediate information needs of shift leaders during the management of an intensive care unit’s (ICU) daily activities. The term ‘ad hoc decision-making’ was defined as critical judgements that are needed for a specific purpose at a precise moment with the goal of ensuring instant and adequate patient care and a fluent flow of ICU activities. Data collection and research analysis methods were tested in the identification of ICU shift leaders’ ad hoc decision-making. Decision-making of ICU charge nurses (n = 12) and physicians in charge (n = 8) was observed using a think-aloud technique in two university-affiliated Finnish ICUs for adults. The ad hoc decisions of ICU shift leaders were identified using an application of protocol analysis. In the next phase, a structured online question¬naire was developed to evaluate the immediate information needs of ICU shift leaders. A national survey was conducted in all Finnish, university-affiliated hospital ICUs for adults (n = 17). The questionnaire was sent to all charge nurses (n = 515) and physicians in charge (n = 223). Altogether, 257 charge nurses (50%) and 96 physicians in charge (43%) responded to the survey. The survey was also tested internationally in 16 Greek ICUs. From Greece, 50 charge nurses out of 240 (21%) responded to the survey. A think-aloud technique and protocol analysis were found to be applicable for the identification of the ad hoc decision-making of ICU shift leaders. During one day shift leaders made over 200 ad hoc decisions. Ad hoc decisions were made horizontally, related to the whole intensive care process, and vertically, concerning single intensive care incidents. Most of the ICU shift leaders’ ad hoc decisions were related to human resources and know-how, patient information and vital signs, and special treatments. Commonly, this ad hoc decision-making involved several multiprofessional decisions that constituted a bundle of immediate decisions and various information needs. Some of these immediate information needs were shared between the charge nurses and the physicians in charge. The majority of which concerned patient admission, the organisation and management of work, and staff allocation. In general, the information needs of charge nurses were more varied than those of physicians. It was found that many ad hoc deci-sions made by the physicians in charge produced several information needs for ICU charge nurses. This meant that before the task at hand was completed, various kinds of information was sought by the charge nurses to support the decision-making process. Most of the immediate information needs of charge nurses were related to the organisation and management of work and human resources, whereas the information needs of the physicians in charge mainly concerned direct patient care. Thus, information needs differ between professionals even if the goal of decision-making is the same. The results of the international survey confirmed these study results for charge nurses. Both in Finland and in Greece the information needs of charge nurses focused on the organisation and management of work and human resources. Many of the most crucial information needs of Finnish and Greek ICU charge nurses were common. In conclusion, it was found that ICU shift leaders make hundreds of ad hoc decisions during the course of a day related to the allocation of resources and organisation of patient care. The ad hoc decision-making of ICU shift leaders is a complex multi-professional process, which requires a lot of immediate information. Real-time support for information related to patient admission, the organisation and man¬agement of work, and allocation of staff resources is especially needed. The preliminary information integration model can be applied when real-time enterprise resource planning systems are developed for intensive care daily management

Evidencing and Sharing Value with Decision Making Models in an Industrial Maintenance Network

The objective of this thesis is to concretize the potential benefits that the industrial maintenance case network could achieve through using the value-based life-cycle model and the flexible asset management model. It is also inspected what factors prevent value creation and sharing in the maintenance contract practices of the case network. This thesis is a case study which utilizes modelling. Four scenarios were developed to demonstrate value creation in the future. The data was partly provided by the collaborating company, partly gathered from public financial statement information. The results indicate that value has been created through the past maintenance of the collaborating company’s rod mill and that profitability of the collaborating company has been mostly on satisfactory level during the past few years. Potential value might be created by increasing the share of proactive maintenance of the rod mill in the future. Profitability of the network could be improved in the future through flexible asset management operations. The main obstacle for value creation and sharing seems to be the lack of sufficient trust between the network members.

Decision making and decision support in service systems

This thesis is a literature study that develops a conceptual model of decision making and decision support in service systems. The study is related to the Ä-Logi, Intelligent Service Logic for Welfare Sector Services research project, and the objective of the study is to develop the necessary theoretical framework to enable further research based on the research project results and material. The study first examines the concepts of service and service systems, focusing on understanding the characteristics of service systems and their implications for decision making and decision support to provide the basis for the development of the conceptual model. Based on the identified service system characteristics, an integrated model of service systems is proposed that views service systems through a number of interrelated perspectives that each offer different, but complementary, implications on the nature of decision making and the requirements for decision support in service systems. Based on the model, it is proposed that different types of decision making contexts can be identified in service systems that may be dominated by different types of decision making processes and where different types of decision support may be required, depending on the characteristics of the decision making context and its decision making processes. The proposed conceptual model of decision making and decision support in service systems examines the characteristics of decision making contexts and processes in service systems, and their typical requirements for decision support. First, a characterization of different types of decision making contexts in service systems is proposed based on the Cynefin framework and the identified service system characteristics. Second, the nature of decision making processes in service systems is proposed to be dual, with both rational and naturalistic decision making processes existing in service systems, and having an important and complementary role in decision making in service systems. Finally, a characterization of typical requirements for decision support in service systems is proposed that examines the decision support requirements associated with different types of decision making processes in characteristically different types of decision making contexts. It is proposed that decision support for the decision making processes that are based on rational decision making can be based on organizational decision support models, while decision support for the decision making processes that are based on naturalistic decision making should be based on supporting the decision makers’ situation awareness and facilitating the development of their tacit knowledge of the system and its tasks. Based on the proposed conceptual model a further research process is proposed. The study additionally provides a number of new perspectives on the characteristics of service systems, and the nature of decision making and requirements for decision support in service systems that can potentially provide a basis for further discussion and research, and support the practice alike.

Fuzzy real option analysis in patent related decision making and patent valuation

The shift towards a knowledge-based economy has inevitably prompted the evolution of patent exploitation. Nowadays, patent is more than just a prevention tool for a company to block its competitors from developing rival technologies, but lies at the very heart of its strategy for value creation and is therefore strategically exploited for economic pro t and competitive advantage. Along with the evolution of patent exploitation, the demand for reliable and systematic patent valuation has also reached an unprecedented level. However, most of the quantitative approaches in use to assess patent could arguably fall into four categories and they are based solely on the conventional discounted cash flow analysis, whose usability and reliability in the context of patent valuation are greatly limited by five practical issues: the market illiquidity, the poor data availability, discriminatory cash-flow estimations, and its incapability to account for changing risk and managerial flexibility. This dissertation attempts to overcome these impeding barriers by rationalizing the use of two techniques, namely fuzzy set theory (aiming at the first three issues) and real option analysis (aiming at the last two). It commences with an investigation into the nature of the uncertainties inherent in patent cash flow estimation and claims that two levels of uncertainties must be properly accounted for. Further investigation reveals that both levels of uncertainties fall under the categorization of subjective uncertainty, which differs from objective uncertainty originating from inherent randomness in that uncertainties labelled as subjective are highly related to the behavioural aspects of decision making and are usually witnessed whenever human judgement, evaluation or reasoning is crucial to the system under consideration and there exists a lack of complete knowledge on its variables. Having clarified their nature, the application of fuzzy set theory in modelling patent-related uncertain quantities is effortlessly justified. The application of real option analysis to patent valuation is prompted by the fact that both patent application process and the subsequent patent exploitation (or commercialization) are subject to a wide range of decisions at multiple successive stages. In other words, both patent applicants and patentees are faced with a large variety of courses of action as to how their patent applications and granted patents can be managed. Since they have the right to run their projects actively, this flexibility has value and thus must be properly accounted for. Accordingly, an explicit identification of the types of managerial flexibility inherent in patent-related decision making problems and in patent valuation, and a discussion on how they could be interpreted in terms of real options are provided in this dissertation. Additionally, the use of the proposed techniques in practical applications is demonstrated by three fuzzy real option analysis based models. In particular, the pay-of method and the extended fuzzy Black-Scholes model are employed to investigate the profitability of a patent application project for a new process for the preparation of a gypsum-fibre composite and to justify the subsequent patent commercialization decision, respectively; a fuzzy binomial model is designed to reveal the economic potential of a patent licensing opportunity.

The psychophysics of decision making in a two-direction random dot motion target selection task

La tâche de kinématogramme de points aléatoires est utilisée avec le paradigme de choix forcé entre deux alternatives pour étudier les prises de décisions perceptuelles. Les modèles décisionnels supposent que les indices de mouvement pour les deux alternatives sont encodés dans le cerveau. Ainsi, la différence entre ces deux signaux est accumulée jusqu’à un seuil décisionnel. Cependant, aucune étude à ce jour n’a testé cette hypothèse avec des stimuli contenant des mouvements opposés. Ce mémoire présente les résultats de deux expériences utilisant deux nouveaux stimuli avec des indices de mouvement concurrentiels. Parmi une variété de combinaisons d’indices concurrentiels, la performance des sujets dépend de la différence nette entre les deux signaux opposés. De plus, les sujets obtiennent une performance similaire avec les deux types de stimuli. Ces résultats supportent un modèle décisionnel basé sur l’accumulation des indices de mouvement net et suggèrent que le processus décisionnel peut intégrer les signaux de mouvement à partir d’une grande gamme de directions pour obtenir un percept global de mouvement.

A theoretical and experimental dissociation of two models of decision‐making

La prise de décision est un processus computationnel fondamental dans de nombreux aspects du comportement animal. Le modèle le plus souvent rencontré dans les études portant sur la prise de décision est appelé modèle de diffusion. Depuis longtemps, il explique une grande variété de données comportementales et neurophysiologiques dans ce domaine. Cependant, un autre modèle, le modèle d’urgence, explique tout aussi bien ces mêmes données et ce de façon parcimonieuse et davantage encrée sur la théorie. Dans ce travail, nous aborderons tout d’abord les origines et le développement du modèle de diffusion et nous verrons comment il a été établi en tant que cadre de travail pour l’interprétation de la plupart des données expérimentales liées à la prise de décision. Ce faisant, nous relèveront ses points forts afin de le comparer ensuite de manière objective et rigoureuse à des modèles alternatifs. Nous réexaminerons un nombre d’assomptions implicites et explicites faites par ce modèle et nous mettrons alors l’accent sur certains de ses défauts. Cette analyse servira de cadre à notre introduction et notre discussion du modèle d’urgence. Enfin, nous présenterons une expérience dont la méthodologie permet de dissocier les deux modèles, et dont les résultats illustrent les limites empiriques et théoriques du modèle de diffusion et démontrent en revanche clairement la validité du modèle d'urgence. Nous terminerons en discutant l'apport potentiel du modèle d'urgence pour l'étude de certaines pathologies cérébrales, en mettant l'accent sur de nouvelles perspectives de recherche.

Individual Decision-Making and Inflation Persistence

The traditional task of a central bank is to preserve price stability and, in doing so, not to impair the real economy more than necessary. To meet this challenge, it is of great relevance whether inflation is only driven by inflation expectations and the current output gap or whether it is, in addition, influenced by past inflation. In the former case, as described by the New Keynesian Phillips curve, the central bank can immediately and simultaneously achieve price stability and equilibrium output, the so-called ‘divine coincidence’ (Blanchard and Galí 2007). In the latter case, the achievement of price stability is costly in terms of output and will be pursued over several periods. Similarly, it is important to distinguish this latter case, which describes ‘intrinsic’ inflation persistence, from that of ‘extrinsic’ inflation persistence, where the sluggishness of inflation is not a ‘structural’ feature of the economy but merely ‘inherited’ from the sluggishness of the other driving forces, inflation expectations and output. ‘Extrinsic’ inflation persistence is usually considered to be the less challenging case, as policy-makers are supposed to fight against the persistence in the driving forces, especially to reduce the stickiness of inflation expectations by a credible monetary policy, in order to reestablish the ‘divine coincidence’. The scope of this dissertation is to contribute to the vast literature and ongoing discussion on inflation persistence: Chapter 1 describes the policy consequences of inflation persistence and summarizes the empirical and theoretical literature. Chapter 2 compares two models of staggered price setting, one with a fixed two-period duration and the other with a stochastic duration of prices. I show that in an economy with a timeless optimizing central bank the model with the two-period alternating price-setting (for most parameter values) leads to more persistent inflation than the model with stochastic price duration. This result amends earlier work by Kiley (2002) who found that the model with stochastic price duration generates more persistent inflation in response to an exogenous monetary shock. Chapter 3 extends the two-period alternating price-setting model to the case of 3- and 4-period price durations. This results in a more complex Phillips curve with a negative impact of past inflation on current inflation. As simulations show, this multi-period Phillips curve generates a too low degree of autocorrelation and too early turnings points of inflation and is outperformed by a simple Hybrid Phillips curve. Chapter 4 starts from the critique of Driscoll and Holden (2003) on the relative real-wage model of Fuhrer and Moore (1995). While taking the critique seriously that Fuhrer and Moore’s model will collapse to a much simpler one without intrinsic inflation persistence if one takes their arguments literally, I extend the model by a term for inequality aversion. This model extension is not only in line with experimental evidence but results in a Hybrid Phillips curve with inflation persistence that is observably equivalent to that presented by Fuhrer and Moore (1995). In chapter 5, I present a model that especially allows to study the relationship between fairness attitudes and time preference (impatience). In the model, two individuals take decisions in two subsequent periods. In period 1, both individuals are endowed with resources and are able to donate a share of their resources to the other individual. In period 2, the two individuals might join in a common production after having bargained on the split of its output. The size of the production output depends on the relative share of resources at the end of period 1 as the human capital of the individuals, which is built by means of their resources, cannot fully be substituted one against each other. Therefore, it might be rational for a well-endowed individual in period 1 to act in a seemingly ‘fair’ manner and to donate own resources to its poorer counterpart. This decision also depends on the individuals’ impatience which is induced by the small but positive probability that production is not possible in period 2. As a general result, the individuals in the model economy are more likely to behave in a ‘fair’ manner, i.e., to donate resources to the other individual, the lower their own impatience and the higher the productivity of the other individual. As the (seemingly) ‘fair’ behavior is modelled as an endogenous outcome and as it is related to the aspect of time preference, the presented framework might help to further integrate behavioral economics and macroeconomics.

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

This paper sets out to identify the initial positions of the different decision makers who intervene in a group decision making process with a reduced number of actors, and to establish possible consensus paths between these actors. As a methodological support, it employs one of the most widely-known multicriteria decision techniques, namely, the Analytic Hierarchy Process (AHP). Assuming that the judgements elicited by the decision makers follow the so-called multiplicative model (Crawford and Williams, 1985; Altuzarra et al., 1997; Laininen and Hämäläinen, 2003) with log-normal errors and unknown variance, a Bayesian approach is used in the estimation of the relative priorities of the alternatives being compared. These priorities, estimated by way of the median of the posterior distribution and normalised in a distributive manner (priorities add up to one), are a clear example of compositional data that will be used in the search for consensus between the actors involved in the resolution of the 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 group decision making problem with a large number of individuals. To that end, it makes use of the Analytic Hierarchy Process (AHP) (Saaty, 1980) as the technique to solve discrete multicriteria decision making problems. This technique permits the resolution of multicriteria, multienvironment and multiactor problems in which subjective aspects and uncertainty have been incorporated into the model, constructing ratio scales corresponding to the priorities relative to the elements being compared, normalised in a distributive manner (wi = 1). On the basis of the individuals’ priorities we identify different clusters for the decision makers and, for each of these, the associated preference structure using, to that end, tools analogous to those of Multidimensional Scaling. The resulting PS will be employed to extract knowledge for the subsequent negotiation processes and, should it be necessary, to determine the relative importance of the alternatives being compared using anyone of the existing procedures

Does uncertainty cause inertia in decision making? An experimental study of the role of regret aversion and indecisiveness

Previous research has shown that often there is clear inertia in individual decision making---that is, a tendency for decision makers to choose a status quo option. I conduct a laboratory experiment to investigate two potential determinants of inertia in uncertain environments: (i) regret aversion and (ii) ambiguity-driven indecisiveness. I use a between-subjects design with varying conditions to identify the effects of these two mechanisms on choice behavior. In each condition, participants choose between two simple real gambles, one of which is the status quo option. I find that inertia is quite large and that both mechanisms are equally important.