A conceptual framework for automating the operational and strategic decision-making process in the health care delivery system.

PubMed

Ruohonen, Toni; Ennejmy, Mohammed

2013-01-01

Making reliable and justified operational and strategic decisions is a really challenging task in the health care domain. So far, the decisions have been made based on the experience of managers and staff, or they are evaluated with traditional methods, using inadequate data. As a result of this kind of decision-making process, attempts to improve operations usually have failed or led to only local improvements. Health care organizations have a lot of operational data, in addition to clinical data, which is the key element for making reliable and justified decisions. However, it is progressively problematic to access it and make usage of it. In this paper we discuss about the possibilities how to exploit operational data in the most efficient way in the decision-making process. We'll share our future visions and propose a conceptual framework for automating the decision-making process.

Data Driven Decision Making in the Social Studies

ERIC Educational Resources Information Center

Ediger, Marlow

2010-01-01

Data driven decision making emphasizes the importance of the teacher using objective sources of information in developing the social studies curriculum. Too frequently, decisions of teachers have been made based on routine and outdated methods of teaching. Valid and reliable tests used to secure results from pupil learning make for better…

Analysis of the decision-making process of nurse managers: a collective reflection.

PubMed

Eduardo, Elizabete Araujo; Peres, Aida Maris; de Almeida, Maria de Lourdes; Roglio, Karina de Dea; Bernardino, Elizabeth

2015-01-01

to analyze the decision-making model adopted by nurses from the perspective of some decision-making process theories. qualitative approach, based on action research. Semi-structured questionnaires and seminars were conducted from April to June 2012 in order to understand the nature of decisions and the decision-making process of nine nurses in position of managers at a public hospital in Southern Brazil. Data were subjected to content analysis. data were classified in two categories: the current situation of decision-making, which showed a lack of systematization; the construction and collective decision-making, which emphasizes the need to develop a decision-making model. the decision-making model used by nurses is limited because it does not consider two important factors: the limits of human rationality, and the external and internal organizational environments that influence and determine right decisions.

Data warehousing: toward knowledge management.

PubMed

Shams, K; Farishta, M

2001-02-01

With rapid changes taking place in the practice and delivery of health care, decision support systems have assumed an increasingly important role. More and more health care institutions are deploying data warehouse applications as decision support tools for strategic decision making. By making the right information available at the right time to the right decision makers in the right manner, data warehouses empower employees to become knowledge workers with the ability to make the right decisions and solve problems, creating strategic leverage for the organization. Health care management must plan and implement data warehousing strategy using a best practice approach. Through the power of data warehousing, health care management can negotiate bettermanaged care contracts based on the ability to provide accurate data on case mix and resource utilization. Management can also save millions of dollars through the implementation of clinical pathways in better resource utilization and changing physician behavior to best practices based on evidence-based medicine.

Automated Decision-Making and Big Data: Concerns for People With Mental Illness.

PubMed

Monteith, Scott; Glenn, Tasha

2016-12-01

Automated decision-making by computer algorithms based on data from our behaviors is fundamental to the digital economy. Automated decisions impact everyone, occurring routinely in education, employment, health care, credit, and government services. Technologies that generate tracking data, including smartphones, credit cards, websites, social media, and sensors, offer unprecedented benefits. However, people are vulnerable to errors and biases in the underlying data and algorithms, especially those with mental illness. Algorithms based on big data from seemingly unrelated sources may create obstacles to community integration. Voluntary online self-disclosure and constant tracking blur traditional concepts of public versus private data, medical versus non-medical data, and human versus automated decision-making. In contrast to sharing sensitive information with a physician in a confidential relationship, there may be numerous readers of information revealed online; data may be sold repeatedly; used in proprietary algorithms; and are effectively permanent. Technological changes challenge traditional norms affecting privacy and decision-making, and continued discussions on new approaches to provide privacy protections are needed.

Protocol-based care: the standardisation of decision-making?

PubMed

Rycroft-Malone, Jo; Fontenla, Marina; Seers, Kate; Bick, Debra

2009-05-01

To explore how protocol-based care affects clinical decision-making. In the context of evidence-based practice, protocol-based care is a mechanism for facilitating the standardisation of care and streamlining decision-making through rationalising the information with which to make judgements and ultimately decisions. However, whether protocol-based care does, in the reality of practice, standardise decision-making is unknown. This paper reports on a study that explored the impact of protocol-based care on nurses' decision-making. Theoretically informed by realistic evaluation and the promoting action on research implementation in health services framework, a case study design using ethnographic methods was used. Two sites were purposively sampled; a diabetic and endocrine unit and a cardiac medical unit. Within each site, data collection included observation, postobservation semi-structured interviews with staff and patients, field notes, feedback sessions and document review. Data were inductively and thematically analysed. Decisions made by nurses in both sites were varied according to many different and interacting factors. While several standardised care approaches were available for use, in reality, a variety of information sources informed decision-making. The primary approach to knowledge exchange and acquisition was person-to-person; decision-making was a social activity. Rarely were standardised care approaches obviously referred to; nurses described following a mental flowchart, not necessarily linked to a particular guideline or protocol. When standardised care approaches were used, it was reported that they were used flexibly and particularised. While the logic of protocol-based care is algorithmic, in the reality of clinical practice, other sources of information supported nurses' decision-making process. This has significant implications for the political goal of standardisation. The successful implementation and judicious use of tools such as protocols and guidelines will likely be dependant on approaches that facilitate the development of nurses' decision-making processes in parallel to paying attention to the influence of context.

Data-based Decision-making: Teachers' Comprehension of Curriculum-based Measurement Progress-monitoring Graphs

ERIC Educational Resources Information Center

van den Bosch, Roxette M.; Espin, Christine A.; Chung, Siuman; Saab, Nadira

2017-01-01

Teachers have difficulty using data from Curriculum-based Measurement (CBM) progress graphs of students with learning difficulties for instructional decision-making. As a first step in unraveling those difficulties, we studied teachers' comprehension of CBM graphs. Using think-aloud methodology, we examined 23 teachers' ability to…

[Value-based cancer care. From traditional evidence-based decision making to balanced decision making within frameworks of shared values].

PubMed

Palazzo, Salvatore; Filice, Aldo; Mastroianni, Candida; Biamonte, Rosalbino; Conforti, Serafino; Liguori, Virginia; Turano, Salvatore; De Simone, Rosanna; Rovito, Antonio; Manfredi, Caterina; Minardi, Stefano; Vilardo, Emmanuelle; Loizzo, Monica; Oriolo, Carmela

2016-04-01

Clinical decision making in oncology is based so far on the evidence of efficacy from high-quality clinical research. Data collection and analysis from experimental studies provide valuable insight into response rates and progression-free or overall survival. Data processing generates valuable information for medical professionals involved in cancer patient care, enabling them to make objective and unbiased choices. The increased attention of many scientific associations toward a more rational resource consumption in clinical decision making is mirrored in the Choosing Wisely campaign against the overuse or misuse of exams and procedures of little or no benefit for the patient. This cultural movement has been actively promoting care solutions based on the concept of "value". As a result, the value-based decision-making process for cancer care should not be dissociated from economic sustainability and from ethics of the affordability, also given the growing average cost of the most recent cancer drugs. In support of this orientation, the National Comprehensive Cancer Network (NCCN) has developed innovative and "complex" guidelines based on values, defined as "evidence blocks", with the aim of assisting the medical community in making overall sustainable choices.

Towards an integrated approach to natural hazards risk assessment using GIS: with reference to bushfires.

PubMed

Chen, Keping; Blong, Russell; Jacobson, Carol

2003-04-01

This paper develops a GIS-based integrated approach to risk assessment in natural hazards, with reference to bushfires. The challenges for undertaking this approach have three components: data integration, risk assessment tasks, and risk decision-making. First, data integration in GIS is a fundamental step for subsequent risk assessment tasks and risk decision-making. A series of spatial data integration issues within GIS such as geographical scales and data models are addressed. Particularly, the integration of both physical environmental data and socioeconomic data is examined with an example linking remotely sensed data and areal census data in GIS. Second, specific risk assessment tasks, such as hazard behavior simulation and vulnerability assessment, should be undertaken in order to understand complex hazard risks and provide support for risk decision-making. For risk assessment tasks involving heterogeneous data sources, the selection of spatial analysis units is important. Third, risk decision-making concerns spatial preferences and/or patterns, and a multicriteria evaluation (MCE)-GIS typology for risk decision-making is presented that incorporates three perspectives: spatial data types, data models, and methods development. Both conventional MCE methods and artificial intelligence-based methods with GIS are identified to facilitate spatial risk decision-making in a rational and interpretable way. Finally, the paper concludes that the integrated approach can be used to assist risk management of natural hazards, in theory and in practice.

Effects of a Data-Based Decision-Making Intervention for Teachers on Students' Mathematical Achievement

ERIC Educational Resources Information Center

van der Scheer, Emmelien A.; Visscher, Adrie J.

2018-01-01

Data-based decision making (DBDM) is an important element of educational policy in many countries, as it is assumed that student achievement will improve if teachers worked in a data-based way. However, studies that evaluate rigorously the effects of DBDM on student achievement are scarce. In this study, the effects of an intensive…

Building the Foundation for Data-Based Decision Making: Creating Consensus on Language and Concepts

ERIC Educational Resources Information Center

Crum, Karen

2009-01-01

Data Based Decision Making (DBDM), the process of gathering, analyzing, applying, and sharing data in order to promote school improvement, has recently become a prominent process in the quest to assist students in attaining educational success and helping schools meet accountability benchmarks (Wayman, 2005; Poynton & Carey, 2006). This…

Why a Data-Based Decision-Making Intervention Works in Some Schools and Not in Others

ERIC Educational Resources Information Center

Keuning, Trynke; Van Geel, Marieke; Visscher, Adrie

2017-01-01

The use of data for adaptive, tailor-made education can be beneficial for students with learning difficulties. While evaluating the effects of a data-based decision-making (DBDM) intervention on student outcomes, considerable variation between intervention effects, ranging from high-intervention effects to small or even negative intervention…

Data-Based Decision Making in Teams: Enablers and Barriers

ERIC Educational Resources Information Center

Bolhuis, Erik; Schildkamp, Kim; Voogt, Joke

2016-01-01

Data use is becoming more important in higher education. In this case study, a team of teachers from a teacher education college was supported in data-based decision making by means of the data team procedure. This data team studied the reasons why students drop out. A team's success depends in part on whether the team is able to develop and apply…

Methods and decision making on a Mars rover for identification of fossils

NASA Technical Reports Server (NTRS)

Eberlein, Susan; Yates, Gigi

1989-01-01

A system for automated fusion and interpretation of image data from multiple sensors, including multispectral data from an imaging spectrometer is being developed. Classical artificial intelligence techniques and artificial neural networks are employed to make real time decision based on current input and known scientific goals. Emphasis is placed on identifying minerals which could indicate past life activity or an environment supportive of life. Multispectral data can be used for geological analysis because different minerals have characteristic spectral reflectance in the visible and near infrared range. Classification of each spectrum into a broad class, based on overall spectral shape and locations of absorption bands is possible in real time using artificial neural networks. The goal of the system is twofold: multisensor and multispectral data must be interpreted in real time so that potentially interesting sites can be flagged and investigated in more detail while the rover is near those sites; and the sensed data must be reduced to the most compact form possible without loss of crucial information. Autonomous decision making will allow a rover to achieve maximum scientific benefit from a mission. Both a classical rule based approach and a decision neural network for making real time choices are being considered. Neural nets may work well for adaptive decision making. A neural net can be trained to work in two steps. First, the actual input state is mapped to the closest of a number of memorized states. After weighing the importance of various input parameters, the net produces an output decision based on the matched memory state. Real time, autonomous image data analysis and decision making capabilities are required for achieving maximum scientific benefit from a rover mission. The system under development will enhance the chances of identifying fossils or environments capable of supporting life on Mars

Decision-making processes for the uptake and implementation of family-based therapy by eating disorder treatment teams: a qualitative study.

PubMed

Kimber, Melissa; Couturier, Jennifer; Jack, Susan; Niccols, Alison; Van Blyderveen, Sherry; McVey, Gail

2014-01-01

To explore the decision-making processes involved in the uptake and implementation of evidence-based treatments (EBTs), namely, family-based treatment (FBT), among therapists and their administrators within publically funded eating disorder treatment programs in Ontario, Canada. Fundamental qualitative description guided sampling, data collection, and analytic decisions. Forty therapists and 11 administrators belonging to a network of clinicians treating eating disorders completed an in-depth interview regarding the decision-making processes involved in EBT uptake and implementation within their organizations. Content analysis and the constant comparative technique were used to analyze interview transcripts, with 20% of the data independently double-coded by a second coder. Therapists and their administrators identified the importance of an inclusive change culture in evidence-based practice (EBP) decision-making. Each group indicated reluctance to make EBP decisions in isolation from the other. Additionally, participants identified seven stages of decision-making involved in EBT adoption, beginning with exposure to the EBT model and ending with evaluating the impact of the EBT on patient outcomes. Support for a stage-based decision-making process was in participants' indication that the stages were needed to demonstrate that they considered the costs and benefits of making a practice change. Participants indicated that EBTs endorsed by the Provincial Network for Eating Disorders or the Academy for Eating Disorders would more likely be adopted. Future work should focus on integrating the important decision-making processes identified in this study with known implementation models to increase the use of low-cost and effective treatments, such as FBT, within eating disorder treatment programs. Copyright © 2013 Wiley Periodicals, Inc.

Multi-criteria clinical decision support: A primer on the use of multiple criteria decision making methods to promote evidence-based, patient-centered healthcare.

PubMed

Dolan, James G

2010-01-01

Current models of healthcare quality recommend that patient management decisions be evidence-based and patient-centered. Evidence-based decisions require a thorough understanding of current information regarding the natural history of disease and the anticipated outcomes of different management options. Patient-centered decisions incorporate patient preferences, values, and unique personal circumstances into the decision making process and actively involve both patients along with health care providers as much as possible. Fundamentally, therefore, evidence-based, patient-centered decisions are multi-dimensional and typically involve multiple decision makers.Advances in the decision sciences have led to the development of a number of multiple criteria decision making methods. These multi-criteria methods are designed to help people make better choices when faced with complex decisions involving several dimensions. They are especially helpful when there is a need to combine "hard data" with subjective preferences, to make trade-offs between desired outcomes, and to involve multiple decision makers. Evidence-based, patient-centered clinical decision making has all of these characteristics. This close match suggests that clinical decision support systems based on multi-criteria decision making techniques have the potential to enable patients and providers to carry out the tasks required to implement evidence-based, patient-centered care effectively and efficiently in clinical settings.The goal of this paper is to give readers a general introduction to the range of multi-criteria methods available and show how they could be used to support clinical decision-making. Methods discussed include the balance sheet, the even swap method, ordinal ranking methods, direct weighting methods, multi-attribute decision analysis, and the analytic hierarchy process (AHP).

Autonomy and Accountability: Teacher Perspectives on Evidence-Based Practice and Decision-Making for Students with Intellectual and Developmental Disabilities

ERIC Educational Resources Information Center

Greenway, Rosanne; McCollow, Meaghan; Hudson, Roxanne F.; Peck, Charles; Davis, Carol A.

2013-01-01

The purpose of this study was to examine teacher perspectives about evidence-based practices (EBP) and decision-making for students with intellectual and developmental disabilities. Given the current EBP movement, our study sought to understand practitioner definitions and perspectives on EBP and decision-making. Interview data from nine special…

Reconciliation of Decision-Making Heuristics Based on Decision Trees Topologies and Incomplete Fuzzy Probabilities Sets

PubMed Central

Doubravsky, Karel; Dohnal, Mirko

2015-01-01

Complex decision making tasks of different natures, e.g. economics, safety engineering, ecology and biology, are based on vague, sparse, partially inconsistent and subjective knowledge. Moreover, decision making economists / engineers are usually not willing to invest too much time into study of complex formal theories. They require such decisions which can be (re)checked by human like common sense reasoning. One important problem related to realistic decision making tasks are incomplete data sets required by the chosen decision making algorithm. This paper presents a relatively simple algorithm how some missing III (input information items) can be generated using mainly decision tree topologies and integrated into incomplete data sets. The algorithm is based on an easy to understand heuristics, e.g. a longer decision tree sub-path is less probable. This heuristic can solve decision problems under total ignorance, i.e. the decision tree topology is the only information available. But in a practice, isolated information items e.g. some vaguely known probabilities (e.g. fuzzy probabilities) are usually available. It means that a realistic problem is analysed under partial ignorance. The proposed algorithm reconciles topology related heuristics and additional fuzzy sets using fuzzy linear programming. The case study, represented by a tree with six lotteries and one fuzzy probability, is presented in details. PMID:26158662

Reconciliation of Decision-Making Heuristics Based on Decision Trees Topologies and Incomplete Fuzzy Probabilities Sets.

PubMed

Doubravsky, Karel; Dohnal, Mirko

2015-01-01

Complex decision making tasks of different natures, e.g. economics, safety engineering, ecology and biology, are based on vague, sparse, partially inconsistent and subjective knowledge. Moreover, decision making economists / engineers are usually not willing to invest too much time into study of complex formal theories. They require such decisions which can be (re)checked by human like common sense reasoning. One important problem related to realistic decision making tasks are incomplete data sets required by the chosen decision making algorithm. This paper presents a relatively simple algorithm how some missing III (input information items) can be generated using mainly decision tree topologies and integrated into incomplete data sets. The algorithm is based on an easy to understand heuristics, e.g. a longer decision tree sub-path is less probable. This heuristic can solve decision problems under total ignorance, i.e. the decision tree topology is the only information available. But in a practice, isolated information items e.g. some vaguely known probabilities (e.g. fuzzy probabilities) are usually available. It means that a realistic problem is analysed under partial ignorance. The proposed algorithm reconciles topology related heuristics and additional fuzzy sets using fuzzy linear programming. The case study, represented by a tree with six lotteries and one fuzzy probability, is presented in details.

Whose Values? Whose Risk? Exploring Decision Making About Trial of Labor After Cesarean.

PubMed

Charles, Sonya; Wolf, Allison B

2018-06-01

In this article, we discuss decision making during labor and delivery, specifically focusing on decision making around offering women a trial of labor after cesarean section (TOLAC). Many have discussed how humans are notoriously bad at assessing risks and how we often distort the nature of various risks surrounding childbirth. We will build on this discussion by showing that physicians make decisions around TOLAC not only based on distortions of risk, but also based on personal values (i.e. what level of risk are you comfortable with or what types of risks are you willing to take) rather than medical data (or at least medical data alone). As a result of this, we will further suggest that the party who is best epistemically situated to make decisions about TOLAC is the woman herself.

Using Data-Based Inquiry and Decision Making To Improve Instruction.

ERIC Educational Resources Information Center

Feldman, Jay; Tung, Rosann

2001-01-01

Discusses a study of six schools using data-based inquiry and decision-making process to improve instruction. Findings identified two conditions to support successful implementation of the process: administrative support, especially in providing teachers learning time, and teacher leadership to encourage and support colleagues to own the process.…

Improving Child Outcomes with Data-Based Decision Making: Interpreting and Using Data

ERIC Educational Resources Information Center

Gischlar, Karen L.; Hojnoski, Robin L.; Missall, Kristen N.

2009-01-01

This article is the third in a series describing the steps in using data-based decision making to inform intervention and, ultimately, improve outcomes for children. Whereas the first two articles describe identifying and measuring important behaviors to target for intervention, the purpose of this article is to describe basic considerations in…

Curriculum-Based Measurement of Reading Progress Monitoring: The Importance of Growth Magnitude and Goal Setting in Decision Making

ERIC Educational Resources Information Center

Van Norman, Ethan R.; Christ, Theodore J.; Newell, Kirsten W.

2017-01-01

Research regarding the technical adequacy of growth estimates from curriculum-based measurement of reading progress monitoring data suggests that current decision-making frameworks are likely to yield inaccurate recommendations unless data are collected for extensive periods of time. Instances where data may not need to be collected for long…

Schools and Data: The Educator's Guide for Using Data to Improve Decision Making

ERIC Educational Resources Information Center

Creighton, Theodore B.

2006-01-01

Since the first edition of "Schools and Data", the No Child Left Behind Act has swept the country, and data-based decision making is no longer an option for educators. Today's educational climate makes it imperative for all schools to collect data and use statistical analysis to help create clear goals and recognize strategies for…

Simulation of California's Major Reservoirs Outflow Using Data Mining Technique

NASA Astrophysics Data System (ADS)

Yang, T.; Gao, X.; Sorooshian, S.

2014-12-01

The reservoir's outflow is controlled by reservoir operators, which is different from the upstream inflow. The outflow is more important than the reservoir's inflow for the downstream water users. In order to simulate the complicated reservoir operation and extract the outflow decision making patterns for California's 12 major reservoirs, we build a data-driven, computer-based ("artificial intelligent") reservoir decision making tool, using decision regression and classification tree approach. This is a well-developed statistical and graphical modeling methodology in the field of data mining. A shuffled cross validation approach is also employed to extract the outflow decision making patterns and rules based on the selected decision variables (inflow amount, precipitation, timing, water type year etc.). To show the accuracy of the model, a verification study is carried out comparing the model-generated outflow decisions ("artificial intelligent" decisions) with that made by reservoir operators (human decisions). The simulation results show that the machine-generated outflow decisions are very similar to the real reservoir operators' decisions. This conclusion is based on statistical evaluations using the Nash-Sutcliffe test. The proposed model is able to detect the most influential variables and their weights when the reservoir operators make an outflow decision. While the proposed approach was firstly applied and tested on California's 12 major reservoirs, the method is universally adaptable to other reservoir systems.

Goal-Directed Decision Making with Spiking Neurons.

PubMed

Friedrich, Johannes; Lengyel, Máté

2016-02-03

Behavioral and neuroscientific data on reward-based decision making point to a fundamental distinction between habitual and goal-directed action selection. The formation of habits, which requires simple updating of cached values, has been studied in great detail, and the reward prediction error theory of dopamine function has enjoyed prominent success in accounting for its neural bases. In contrast, the neural circuit mechanisms of goal-directed decision making, requiring extended iterative computations to estimate values online, are still unknown. Here we present a spiking neural network that provably solves the difficult online value estimation problem underlying goal-directed decision making in a near-optimal way and reproduces behavioral as well as neurophysiological experimental data on tasks ranging from simple binary choice to sequential decision making. Our model uses local plasticity rules to learn the synaptic weights of a simple neural network to achieve optimal performance and solves one-step decision-making tasks, commonly considered in neuroeconomics, as well as more challenging sequential decision-making tasks within 1 s. These decision times, and their parametric dependence on task parameters, as well as the final choice probabilities match behavioral data, whereas the evolution of neural activities in the network closely mimics neural responses recorded in frontal cortices during the execution of such tasks. Our theory provides a principled framework to understand the neural underpinning of goal-directed decision making and makes novel predictions for sequential decision-making tasks with multiple rewards. Goal-directed actions requiring prospective planning pervade decision making, but their circuit-level mechanisms remain elusive. We show how a model circuit of biologically realistic spiking neurons can solve this computationally challenging problem in a novel way. The synaptic weights of our network can be learned using local plasticity rules such that its dynamics devise a near-optimal plan of action. By systematically comparing our model results to experimental data, we show that it reproduces behavioral decision times and choice probabilities as well as neural responses in a rich set of tasks. Our results thus offer the first biologically realistic account for complex goal-directed decision making at a computational, algorithmic, and implementational level. Copyright © 2016 the authors 0270-6474/16/361529-18$15.00/0.

Goal-Directed Decision Making with Spiking Neurons

PubMed Central

Lengyel, Máté

2016-01-01

Behavioral and neuroscientific data on reward-based decision making point to a fundamental distinction between habitual and goal-directed action selection. The formation of habits, which requires simple updating of cached values, has been studied in great detail, and the reward prediction error theory of dopamine function has enjoyed prominent success in accounting for its neural bases. In contrast, the neural circuit mechanisms of goal-directed decision making, requiring extended iterative computations to estimate values online, are still unknown. Here we present a spiking neural network that provably solves the difficult online value estimation problem underlying goal-directed decision making in a near-optimal way and reproduces behavioral as well as neurophysiological experimental data on tasks ranging from simple binary choice to sequential decision making. Our model uses local plasticity rules to learn the synaptic weights of a simple neural network to achieve optimal performance and solves one-step decision-making tasks, commonly considered in neuroeconomics, as well as more challenging sequential decision-making tasks within 1 s. These decision times, and their parametric dependence on task parameters, as well as the final choice probabilities match behavioral data, whereas the evolution of neural activities in the network closely mimics neural responses recorded in frontal cortices during the execution of such tasks. Our theory provides a principled framework to understand the neural underpinning of goal-directed decision making and makes novel predictions for sequential decision-making tasks with multiple rewards. SIGNIFICANCE STATEMENT Goal-directed actions requiring prospective planning pervade decision making, but their circuit-level mechanisms remain elusive. We show how a model circuit of biologically realistic spiking neurons can solve this computationally challenging problem in a novel way. The synaptic weights of our network can be learned using local plasticity rules such that its dynamics devise a near-optimal plan of action. By systematically comparing our model results to experimental data, we show that it reproduces behavioral decision times and choice probabilities as well as neural responses in a rich set of tasks. Our results thus offer the first biologically realistic account for complex goal-directed decision making at a computational, algorithmic, and implementational level. PMID:26843636

Cognitive biases and heuristics in medical decision making: a critical review using a systematic search strategy.

PubMed

Blumenthal-Barby, J S; Krieger, Heather

2015-05-01

The role of cognitive biases and heuristics in medical decision making is of growing interest. The purpose of this study was to determine whether studies on cognitive biases and heuristics in medical decision making are based on actual or hypothetical decisions and are conducted with populations that are representative of those who typically make the medical decision; to categorize the types of cognitive biases and heuristics found and whether they are found in patients or in medical personnel; and to critically review the studies based on standard methodological quality criteria. Data sources were original, peer-reviewed, empirical studies on cognitive biases and heuristics in medical decision making found in Ovid Medline, PsycINFO, and the CINAHL databases published in 1980-2013. Predefined exclusion criteria were used to identify 213 studies. During data extraction, information was collected on type of bias or heuristic studied, respondent population, decision type, study type (actual or hypothetical), study method, and study conclusion. Of the 213 studies analyzed, 164 (77%) were based on hypothetical vignettes, and 175 (82%) were conducted with representative populations. Nineteen types of cognitive biases and heuristics were found. Only 34% of studies (n = 73) investigated medical personnel, and 68% (n = 145) confirmed the presence of a bias or heuristic. Each methodological quality criterion was satisfied by more than 50% of the studies, except for sample size and validated instruments/questions. Limitations are that existing terms were used to inform search terms, and study inclusion criteria focused strictly on decision making. Most of the studies on biases and heuristics in medical decision making are based on hypothetical vignettes, raising concerns about applicability of these findings to actual decision making. Biases and heuristics have been underinvestigated in medical personnel compared with patients. © The Author(s) 2014.

Differentiated Instruction in a Data-Based Decision-Making Context

ERIC Educational Resources Information Center

Faber, Janke M.; Glas, Cees A. W.; Visscher, Adrie J.

2018-01-01

In this study, the relationship between differentiated instruction, as an element of data-based decision making, and student achievement was examined. Classroom observations (n = 144) were used to measure teachers' differentiated instruction practices and to predict the mathematical achievement of 2nd- and 5th-grade students (n = 953). The…

An innovative approach to addressing childhood obesity: a knowledge-based infrastructure for supporting multi-stakeholder partnership decision-making in Quebec, Canada.

PubMed

Addy, Nii Antiaye; Shaban-Nejad, Arash; Buckeridge, David L; Dubé, Laurette

2015-01-23

Multi-stakeholder partnerships (MSPs) have become a widespread means for deploying policies in a whole of society strategy to address the complex problem of childhood obesity. However, decision-making in MSPs is fraught with challenges, as decision-makers are faced with complexity, and have to reconcile disparate conceptualizations of knowledge across multiple sectors with diverse sets of indicators and data. These challenges can be addressed by supporting MSPs with innovative tools for obtaining, organizing and using data to inform decision-making. The purpose of this paper is to describe and analyze the development of a knowledge-based infrastructure to support MSP decision-making processes. The paper emerged from a study to define specifications for a knowledge-based infrastructure to provide decision support for community-level MSPs in the Canadian province of Quebec. As part of the study, a process assessment was conducted to understand the needs of communities as they collect, organize, and analyze data to make decisions about their priorities. The result of this process is a "portrait", which is an epidemiological profile of health and nutrition in their community. Portraits inform strategic planning and development of interventions, and are used to assess the impact of interventions. Our key findings indicate ambiguities and disagreement among MSP decision-makers regarding causal relationships between actions and outcomes, and the relevant data needed for making decisions. MSP decision-makers expressed a desire for easy-to-use tools that facilitate the collection, organization, synthesis, and analysis of data, to enable decision-making in a timely manner. Findings inform conceptual modeling and ontological analysis to capture the domain knowledge and specify relationships between actions and outcomes. This modeling and analysis provide the foundation for an ontology, encoded using OWL 2 Web Ontology Language. The ontology is developed to provide semantic support for the MSP process, defining objectives, strategies, actions, indicators, and data sources. In the future, software interacting with the ontology can facilitate interactive browsing by decision-makers in the MSP in the form of concepts, instances, relationships, and axioms. Our ontology also facilitates the integration and interpretation of community data, and can help in managing semantic interoperability between different knowledge sources. Future work will focus on defining specifications for the development of a database of indicators and an information system to help decision-makers to view, analyze and organize indicators for their community. This work should improve MSP decision-making in the development of interventions to address childhood obesity.

An Innovative Approach to Addressing Childhood Obesity: A Knowledge-Based Infrastructure for Supporting Multi-Stakeholder Partnership Decision-Making in Quebec, Canada

PubMed Central

Addy, Nii Antiaye; Shaban-Nejad, Arash; Buckeridge, David L.; Dubé, Laurette

2015-01-01

Multi-stakeholder partnerships (MSPs) have become a widespread means for deploying policies in a whole of society strategy to address the complex problem of childhood obesity. However, decision-making in MSPs is fraught with challenges, as decision-makers are faced with complexity, and have to reconcile disparate conceptualizations of knowledge across multiple sectors with diverse sets of indicators and data. These challenges can be addressed by supporting MSPs with innovative tools for obtaining, organizing and using data to inform decision-making. The purpose of this paper is to describe and analyze the development of a knowledge-based infrastructure to support MSP decision-making processes. The paper emerged from a study to define specifications for a knowledge-based infrastructure to provide decision support for community-level MSPs in the Canadian province of Quebec. As part of the study, a process assessment was conducted to understand the needs of communities as they collect, organize, and analyze data to make decisions about their priorities. The result of this process is a “portrait”, which is an epidemiological profile of health and nutrition in their community. Portraits inform strategic planning and development of interventions, and are used to assess the impact of interventions. Our key findings indicate ambiguities and disagreement among MSP decision-makers regarding causal relationships between actions and outcomes, and the relevant data needed for making decisions. MSP decision-makers expressed a desire for easy-to-use tools that facilitate the collection, organization, synthesis, and analysis of data, to enable decision-making in a timely manner. Findings inform conceptual modeling and ontological analysis to capture the domain knowledge and specify relationships between actions and outcomes. This modeling and analysis provide the foundation for an ontology, encoded using OWL 2 Web Ontology Language. The ontology is developed to provide semantic support for the MSP process, defining objectives, strategies, actions, indicators, and data sources. In the future, software interacting with the ontology can facilitate interactive browsing by decision-makers in the MSP in the form of concepts, instances, relationships, and axioms. Our ontology also facilitates the integration and interpretation of community data, and can help in managing semantic interoperability between different knowledge sources. Future work will focus on defining specifications for the development of a database of indicators and an information system to help decision-makers to view, analyze and organize indicators for their community. This work should improve MSP decision-making in the development of interventions to address childhood obesity. PMID:25625409

The Adaptability of Career Decision-Making Profiles

ERIC Educational Resources Information Center

Gadassi, Reuma; Gati, Itamar; Dayan, Amira

2012-01-01

The Career Decision-Making Profiles questionnaire (CDMP; Gati, Landman, Davidovitch, Asulin-Peretz, & Gadassi, 2010) uses a new model for characterizing the way individuals make decisions based on the simultaneous use of 11 dimensions. The present study investigated which pole of each dimension is more adaptive. Using the data of 383 young…

A Novel Group Decision-Making Method Based on Sensor Data and Fuzzy Information.

PubMed

Bai, Yu-Ting; Zhang, Bai-Hai; Wang, Xiao-Yi; Jin, Xue-Bo; Xu, Ji-Ping; Su, Ting-Li; Wang, Zhao-Yang

2016-10-28

Algal bloom is a typical phenomenon of the eutrophication of rivers and lakes and makes the water dirty and smelly. It is a serious threat to water security and public health. Most scholars studying solutions for this pollution have studied the principles of remediation approaches, but few have studied the decision-making and selection of the approaches. Existing research uses simplex decision-making information which is highly subjective and uses little of the data from water quality sensors. To utilize these data and solve the rational decision-making problem, a novel group decision-making method is proposed using the sensor data with fuzzy evaluation information. Firstly, the optimal similarity aggregation model of group opinions is built based on the modified similarity measurement of Vague values. Secondly, the approaches' ability to improve the water quality indexes is expressed using Vague evaluation methods. Thirdly, the water quality sensor data are analyzed to match the features of the alternative approaches with grey relational degrees. This allows the best remediation approach to be selected to meet the current water status. Finally, the selection model is applied to the remediation of algal bloom in lakes. The results show this method's rationality and feasibility when using different data from different sources.

Housing decision making methods for initiation development phase process

NASA Astrophysics Data System (ADS)

Zainal, Rozlin; Kasim, Narimah; Sarpin, Norliana; Wee, Seow Ta; Shamsudin, Zarina

2017-10-01

Late delivery and sick housing project problems were attributed to poor decision making. These problems are the string of housing developer that prefers to create their own approach based on their experiences and expertise with the simplest approach by just applying the obtainable standards and rules in decision making. This paper seeks to identify the decision making methods for housing development at the initiation phase in Malaysia. The research involved Delphi method by using questionnaire survey which involved 50 numbers of developers as samples for the primary stage of collect data. However, only 34 developers contributed to the second stage of the information gathering process. At the last stage, only 12 developers were left for the final data collection process. Finding affirms that Malaysian developers prefer to make their investment decisions based on simple interpolation of historical data and using simple statistical or mathematical techniques in producing the required reports. It was suggested that they seemed to skip several important decision-making functions at the primary development stage. These shortcomings were mainly due to time and financial constraints and the lack of statistical or mathematical expertise among the professional and management groups in the developer organisations.

Gaze data reveal distinct choice processes underlying model-based and model-free reinforcement learning

PubMed Central

Konovalov, Arkady; Krajbich, Ian

2016-01-01

Organisms appear to learn and make decisions using different strategies known as model-free and model-based learning; the former is mere reinforcement of previously rewarded actions and the latter is a forward-looking strategy that involves evaluation of action-state transition probabilities. Prior work has used neural data to argue that both model-based and model-free learners implement a value comparison process at trial onset, but model-based learners assign more weight to forward-looking computations. Here using eye-tracking, we report evidence for a different interpretation of prior results: model-based subjects make their choices prior to trial onset. In contrast, model-free subjects tend to ignore model-based aspects of the task and instead seem to treat the decision problem as a simple comparison process between two differentially valued items, consistent with previous work on sequential-sampling models of decision making. These findings illustrate a problem with assuming that experimental subjects make their decisions at the same prescribed time. PMID:27511383

Decision making under uncertainty in a spiking neural network model of the basal ganglia.

PubMed

Héricé, Charlotte; Khalil, Radwa; Moftah, Marie; Boraud, Thomas; Guthrie, Martin; Garenne, André

2016-12-01

The mechanisms of decision-making and action selection are generally thought to be under the control of parallel cortico-subcortical loops connecting back to distinct areas of cortex through the basal ganglia and processing motor, cognitive and limbic modalities of decision-making. We have used these properties to develop and extend a connectionist model at a spiking neuron level based on a previous rate model approach. This model is demonstrated on decision-making tasks that have been studied in primates and the electrophysiology interpreted to show that the decision is made in two steps. To model this, we have used two parallel loops, each of which performs decision-making based on interactions between positive and negative feedback pathways. This model is able to perform two-level decision-making as in primates. We show here that, before learning, synaptic noise is sufficient to drive the decision-making process and that, after learning, the decision is based on the choice that has proven most likely to be rewarded. The model is then submitted to lesion tests, reversal learning and extinction protocols. We show that, under these conditions, it behaves in a consistent manner and provides predictions in accordance with observed experimental data.

Decision-making in nursing practice: An integrative literature review.

PubMed

Nibbelink, Christine W; Brewer, Barbara B

2018-03-01

To identify and summarise factors and processes related to registered nurses' patient care decision-making in medical-surgical environments. A secondary goal of this literature review was to determine whether medical-surgical decision-making literature included factors that appeared to be similar to concepts and factors in naturalistic decision making (NDM). Decision-making in acute care nursing requires an evaluation of many complex factors. While decision-making research in acute care nursing is prevalent, errors in decision-making continue to lead to poor patient outcomes. Naturalistic decision making may provide a framework for further exploring decision-making in acute care nursing practice. A better understanding of the literature is needed to guide future research to more effectively support acute care nurse decision-making. PubMed and CINAHL databases were searched, and research meeting criteria was included. Data were identified from all included articles, and themes were developed based on these data. Key findings in this review include nursing experience and associated factors; organisation and unit culture influences on decision-making; education; understanding patient status; situation awareness; and autonomy. Acute care nurses employ a variety of decision-making factors and processes and informally identify experienced nurses to be important resources for decision-making. Incorporation of evidence into acute care nursing practice continues to be a struggle for acute care nurses. This review indicates that naturalistic decision making may be applicable to decision-making nursing research. Experienced nurses bring a broad range of previous patient encounters to their practice influencing their intuitive, unconscious processes which facilitates decision-making. Using naturalistic decision making as a conceptual framework to guide research may help with understanding how to better support less experienced nurses' decision-making for enhanced patient outcomes. © 2017 John Wiley & Sons Ltd.

Demystifying Data: Designing and Implementing Data-Driven Systems and Practices for Continuous Quality Improvement

ERIC Educational Resources Information Center

Krugly, Andrew; Stein, Amanda; Centeno, Maribel G.

2014-01-01

Data-based decision making should be the driving force in any early care and education setting. Data usage compels early childhood practitioners and leaders to make decisions on the basis of more than just professional instinct. This article explores why early childhood schools should be using data for continuous quality improvement at various…

Comprehensible knowledge model creation for cancer treatment decision making.

PubMed

Afzal, Muhammad; Hussain, Maqbool; Ali Khan, Wajahat; Ali, Taqdir; Lee, Sungyoung; Huh, Eui-Nam; Farooq Ahmad, Hafiz; Jamshed, Arif; Iqbal, Hassan; Irfan, Muhammad; Abbas Hydari, Manzar

2017-03-01

A wealth of clinical data exists in clinical documents in the form of electronic health records (EHRs). This data can be used for developing knowledge-based recommendation systems that can assist clinicians in clinical decision making and education. One of the big hurdles in developing such systems is the lack of automated mechanisms for knowledge acquisition to enable and educate clinicians in informed decision making. An automated knowledge acquisition methodology with a comprehensible knowledge model for cancer treatment (CKM-CT) is proposed. With the CKM-CT, clinical data are acquired automatically from documents. Quality of data is ensured by correcting errors and transforming various formats into a standard data format. Data preprocessing involves dimensionality reduction and missing value imputation. Predictive algorithm selection is performed on the basis of the ranking score of the weighted sum model. The knowledge builder prepares knowledge for knowledge-based services: clinical decisions and education support. Data is acquired from 13,788 head and neck cancer (HNC) documents for 3447 patients, including 1526 patients of the oral cavity site. In the data quality task, 160 staging values are corrected. In the preprocessing task, 20 attributes and 106 records are eliminated from the dataset. The Classification and Regression Trees (CRT) algorithm is selected and provides 69.0% classification accuracy in predicting HNC treatment plans, consisting of 11 decision paths that yield 11 decision rules. Our proposed methodology, CKM-CT, is helpful to find hidden knowledge in clinical documents. In CKM-CT, the prediction models are developed to assist and educate clinicians for informed decision making. The proposed methodology is generalizable to apply to data of other domains such as breast cancer with a similar objective to assist clinicians in decision making and education. Copyright © 2017 Elsevier Ltd. All rights reserved.

Linking data to decision-making: applying qualitative data analysis methods and software to identify mechanisms for using outcomes data.

PubMed

Patel, Vaishali N; Riley, Anne W

2007-10-01

A multiple case study was conducted to examine how staff in child out-of-home care programs used data from an Outcomes Management System (OMS) and other sources to inform decision-making. Data collection consisted of thirty-seven semi-structured interviews with clinicians, managers, and directors from two treatment foster care programs and two residential treatment centers, and individuals involved with developing the OMS; and observations of clinical and quality management meetings. Case study and grounded theory methodology guided analyses. The application of qualitative data analysis software is described. Results show that although staff rarely used data from the OMS, they did rely on other sources of systematically collected information to inform clinical, quality management, and program decisions. Analyses of how staff used these data suggest that improving the utility of OMS will involve encouraging staff to participate in data-based decision-making, and designing and implementing OMS in a manner that reflects how decision-making processes operate.

Enhanced Requirements for Assessment in a Competency-Based, Time-Variable Medical Education System.

PubMed

Gruppen, Larry D; Ten Cate, Olle; Lingard, Lorelei A; Teunissen, Pim W; Kogan, Jennifer R

2018-03-01

Competency-based, time-variable medical education has reshaped the perceptions and practices of teachers, curriculum designers, faculty developers, clinician educators, and program administrators. This increasingly popular approach highlights the fact that learning among different individuals varies in duration, foundation, and goal. Time variability places particular demands on the assessment data that are so necessary for making decisions about learner progress. These decisions may be formative (e.g., feedback for improvement) or summative (e.g., decisions about advancing a student). This article identifies challenges to collecting assessment data and to making assessment decisions in a time-variable system. These challenges include managing assessment data, defining and making valid assessment decisions, innovating in assessment, and modeling the considerable complexity of assessment in real-world settings and richly interconnected social systems. There are hopeful signs of creativity in assessment both from researchers and practitioners, but the transition from a traditional to a competency-based medical education system will likely continue to create much controversy and offer opportunities for originality and innovation in assessment.

Decision-making in Swiss home-like childbirth: A grounded theory study.

PubMed

Meyer, Yvonne; Frank, Franziska; Schläppy Muntwyler, Franziska; Fleming, Valerie; Pehlke-Milde, Jessica

2017-12-01

Decision-making in midwifery, including a claim for shared decision-making between midwives and women, is of major significance for the health of mother and child. Midwives have little information about how to share decision-making responsibilities with women, especially when complications arise during birth. To increase understanding of decision-making in complex home-like birth settings by exploring midwives' and women's perspectives and to develop a dynamic model integrating participatory processes for making shared decisions. The study, based on grounded theory methodology, analysed 20 interviews of midwives and 20 women who had experienced complications in home-like births. The central phenomenon that arose from the data was "defining/redefining decision as a joint commitment to healthy childbirth". The sub-indicators that make up this phenomenon were safety, responsibility, mutual and personal commitments. These sub-indicators were also identified to influence temporal conditions of decision-making and to apply different strategies for shared decision-making. Women adopted strategies such as delegating a decision, making the midwife's decision her own, challenging a decision or taking a decision driven by the dynamics of childbirth. Midwives employed strategies such as remaining indecisive, approving a woman's decision, making an informed decision or taking the necessary decision. To respond to recommendations for shared responsibility for care, midwives need to strengthen their shared decision-making skills. The visual model of decision-making in childbirth derived from the data provides a framework for transferring clinical reasoning into practice. Copyright © 2017 Australian College of Midwives. Published by Elsevier Ltd. All rights reserved.

IBM's Health Analytics and Clinical Decision Support.

PubMed

Kohn, M S; Sun, J; Knoop, S; Shabo, A; Carmeli, B; Sow, D; Syed-Mahmood, T; Rapp, W

2014-08-15

This survey explores the role of big data and health analytics developed by IBM in supporting the transformation of healthcare by augmenting evidence-based decision-making. Some problems in healthcare and strategies for change are described. It is argued that change requires better decisions, which, in turn, require better use of the many kinds of healthcare information. Analytic resources that address each of the information challenges are described. Examples of the role of each of the resources are given. There are powerful analytic tools that utilize the various kinds of big data in healthcare to help clinicians make more personalized, evidenced-based decisions. Such resources can extract relevant information and provide insights that clinicians can use to make evidence-supported decisions. There are early suggestions that these resources have clinical value. As with all analytic tools, they are limited by the amount and quality of data. Big data is an inevitable part of the future of healthcare. There is a compelling need to manage and use big data to make better decisions to support the transformation of healthcare to the personalized, evidence-supported model of the future. Cognitive computing resources are necessary to manage the challenges in employing big data in healthcare. Such tools have been and are being developed. The analytic resources, themselves, do not drive, but support healthcare transformation.

Information and decision-making needs among people with mental disorders: a systematic review of the literature.

PubMed

Tlach, Lisa; Wüsten, Caroline; Daubmann, Anne; Liebherz, Sarah; Härter, Martin; Dirmaier, Jörg

2015-12-01

Assessment of users' information and decision-making needs is one key step in the development of decision-support interventions. To identify patients' information and decision-making needs as a pre-requisite for the development of high-quality web-based patient decision aids (PtDAs) for common mental disorders. A systematic MEDLINE search for papers published until December 2012 was conducted, and reference lists of included articles and relevant reviews were searched. Original studies containing data on information or decision-making needs of adults with depression, anxiety disorders, somatoform disorders, alcohol-related disorders and schizophrenia were included. Data extraction was performed using a standardized form, and data synthesis was conducted using a theory-based deductive approach by two independent reviewers. Studies were quality assessed using the Mixed Methods Appraisal Tool. Twelve studies were included focusing on information needs or the identification of decisions patients with depression and schizophrenia were facing. No studies were found for the other mental disorders. Overall, seven information needs categories were identified with the topics 'basic facts', 'treatment' and 'coping' being of major relevance. Six decision categories were identified of which decisions on 'medication' and 'treatment setting' were most often classified. This review reveals that patients with schizophrenia and depression show extensive information and decision-making needs. The identified needs can initially inform the design of PtDAs for schizophrenia and depression. However, there is an urgent need to investigate information and decision-making needs among patients with other mental disorders. © 2014 John Wiley & Sons Ltd.

Data-Based Decision-Making Teams in Middle School: Observations and Implications from the Middle School Intervention Project

ERIC Educational Resources Information Center

Crone, Deanne A.; Carlson, Sarah E.; Haack, Marcia K.; Kennedy, Patrick C.; Baker, Scott K.; Fien, Hank

2016-01-01

The use of data-based decision making (DBDM) in schools to drive educational improvement and success has been strongly promoted by educational experts and policymakers, yet very little is documented about the actual DBDM practices used in schools. This study examines DBDM practices in 25 middle schools through 80 standardized observations of data…

Teacher and Leader Perceptions Concerning the Implementation of a Web-Based Data Warehouse for Instructional Decision-Making

ERIC Educational Resources Information Center

Curtis, Jennifer Lee

2010-01-01

The purpose of this study was to identify, describe, and examine the perceptions of teachers and leaders when implementing a Web-based data warehouse (DW) for instructional decision-making in a K-12 public school setting. It identified the challenges and benefits of DW implementation by measuring teacher and leader concerns, studied teacher and…

Aging and the neuroeconomics of decision making: A review.

PubMed

Brown, Stephen B R E; Ridderinkhof, K Richard

2009-12-01

Neuroeconomics refers to a combination of paradigms derived from neuroscience, psychology, and economics for the study of decision making and is an area that has received considerable scientific attention in the recent literature. Using realistic laboratory tasks, researchers seek to study the neurocognitive processes underlying economic decision making and outcome-based decision learning, as well as individual differences in these processes and the social and affective factors that modulate them. To this point, one question has remained largely unanswered: What happens to decision-making processes and their neural substrates during aging? After all, aging is associated with neurocognitive change, which may affect outcome-based decision making. In our study, we use the subjective expected utility model-a well-established decision-making model in economics-as a descriptive framework. After a short survey of the brain areas and neurotransmitter systems associated with outcome-based decision making-and of the effects of aging thereon-we review a number of decision-making studies. Their general data pattern indicates that the decision-making process is changed by age: The elderly perform less efficiently than younger participants, as demonstrated, for instance, by the smaller total rewards that the elderly acquire in lab tasks. These findings are accounted for in terms of age-related deficiencies in the probability and value parameters of the subjective expected utility model. Finally, we discuss some implications and suggestions for future research.

The Risky Shift in Policy Decision Making: A Comparative Analysis

ERIC Educational Resources Information Center

Wilpert, B.; And Others

1976-01-01

Based on analysis of data on 432 decision-makers from around the world, this study examines the decision-making phenomenon that individuals tend to move toward riskier decisions after group discussion. Findings of the analysis contradicted earlier studies, showing a consistent shift toward greater risk avoidance. Available from Elsevier Scientific…

Disciplined Decision Making in an Interdisciplinary Environment: Some Implications for Clinical Applications of Statistical Process Control.

ERIC Educational Resources Information Center

Hantula, Donald A.

1995-01-01

Clinical applications of statistical process control (SPC) in human service organizations are considered. SPC is seen as providing a standard set of criteria that serves as a common interface for data-based decision making, which may bring decision making under the control of established contingencies rather than the immediate contingencies of…

An Autonomous Flight Safety System

DTIC Science & Technology

2008-11-01

are taken. AFSS can take vehicle navigation data from redundant onboard sensors and make flight termination decisions using software-based rules...implemented on redundant flight processors. By basing these decisions on actual Instantaneous Impact Predictions and by providing for an arbitrary...number of mission rules, it is the contention of the AFSS development team that the decision making process used by Missile Flight Control Officers

Moving data off the shelf and into action: an intervention to improve data-informed decision making in Côte d'Ivoire.

PubMed

Nutley, Tara; Gnassou, Léontine; Traore, Moussa; Bosso, Abitche Edwige; Mullen, Stephanie

2014-01-01

Improving a health system requires data, but too often they are unused or under-used by decision makers. Without interventions to improve the use of data in decision making, health systems cannot meet the needs of the populations they serve. In 2008, in Côte d'Ivoire, data were largely unused in health decision-making processes. To implement and evaluate an intervention to improve the use of data in decision making in Cote d'Ivoire. From 2008 to 2012, Cote d'Ivoire sought to improve the use of national health data through an intervention that broadens participation in and builds links between data collection and decision-making processes; identifies information needs; improves data quality; builds capacity to analyze, synthesize, and interpret data; and develops policies to support data use. To assess the results, a Performance of Routine Information System Management Assessment was conducted before and after the intervention using a combination of purposeful and random sampling. In 2008, the sample consisted of the central level, 12 districts, and 119 facilities, and in 2012, the sample consisted of the central level, 20 districts, and 190 health facilities. To assess data use, we developed dichotomous indicators: discussions of analysis findings, decisions taken based on the analysis, and decisions referred to upper management for action. We aggregated the indicators to generate a composite, continuous index of data use. From 2008 to 2012, the district data-use score increased from 40 to 70%; the facility score remained the same - 38%. The central score is not reported, because of a methodological difference in the two assessments. The intervention improved the use of data in decision making at the district level in Côte d'Ivoire. This study provides an example of, and guidance for, implementing a large-scale intervention to improve data-informed decision making.

Decision-Making, Information Communication Technology, and Data Analysis by School Leaders about Student Achievement

ERIC Educational Resources Information Center

Akoma, Ahunna Margaux

2012-01-01

This case study of one school district examined how school leaders use student performance data and technology-based data analysis tools to engage in data-informed decision-making for continuous improvement. School leaders in this context included leaders at the district, school, and classroom levels. An extensive literature review provided the…

Clinical data warehousing for evidence based decision making.

PubMed

Narra, Lekha; Sahama, Tony; Stapleton, Peta

2015-01-01

Large volumes of heterogeneous health data silos pose a big challenge when exploring for information to allow for evidence based decision making and ensuring quality outcomes. In this paper, we present a proof of concept for adopting data warehousing technology to aggregate and analyse disparate health data in order to understand the impact various lifestyle factors on obesity. We present a practical model for data warehousing with detailed explanation which can be adopted similarly for studying various other health issues.

A Decision-Making Method with Grey Multi-Source Heterogeneous Data and Its Application in Green Supplier Selection

PubMed Central

Dang, Yaoguo; Mao, Wenxin

2018-01-01

In view of the multi-attribute decision-making problem that the attribute values are grey multi-source heterogeneous data, a decision-making method based on kernel and greyness degree is proposed. The definitions of kernel and greyness degree of an extended grey number in a grey multi-source heterogeneous data sequence are given. On this basis, we construct the kernel vector and greyness degree vector of the sequence to whiten the multi-source heterogeneous information, then a grey relational bi-directional projection ranking method is presented. Considering the multi-attribute multi-level decision structure and the causalities between attributes in decision-making problem, the HG-DEMATEL method is proposed to determine the hierarchical attribute weights. A green supplier selection example is provided to demonstrate the rationality and validity of the proposed method. PMID:29510521

A Decision-Making Method with Grey Multi-Source Heterogeneous Data and Its Application in Green Supplier Selection.

PubMed

Sun, Huifang; Dang, Yaoguo; Mao, Wenxin

2018-03-03

In view of the multi-attribute decision-making problem that the attribute values are grey multi-source heterogeneous data, a decision-making method based on kernel and greyness degree is proposed. The definitions of kernel and greyness degree of an extended grey number in a grey multi-source heterogeneous data sequence are given. On this basis, we construct the kernel vector and greyness degree vector of the sequence to whiten the multi-source heterogeneous information, then a grey relational bi-directional projection ranking method is presented. Considering the multi-attribute multi-level decision structure and the causalities between attributes in decision-making problem, the HG-DEMATEL method is proposed to determine the hierarchical attribute weights. A green supplier selection example is provided to demonstrate the rationality and validity of the proposed method.

Middle Level Teachers' Perceptions of Interim Reading Assessments: An Exploratory Study of Data-Based Decision Making

ERIC Educational Resources Information Center

Reed, Deborah K.

2015-01-01

This study explored the data-based decision making of 12 teachers in grades 6-8 who were asked about their perceptions and use of three required interim measures of reading performance: oral reading fluency (ORF), retell, and a benchmark comprised of released state test items. Focus group participants reported they did not believe the benchmark or…

Evaluating the Intervention of an Ethics' Class in Students' Ethical Decision-Making: A Summative Review

ERIC Educational Resources Information Center

Walker, Marquita

2013-01-01

This summative evaluation is the result of two years' of data reflecting the impact of an ethics class in terms of students' ethical decision-making. The research compares aggregate responses from scenario-based pre- and post-survey open-ended survey questions designed to measure changes in ethical decision-making by comparing students' cognitive…

"People Can Go against the Government": Risk-Based Decision Making and High School Students' Concepts of Society

ERIC Educational Resources Information Center

Radakovic, Nenad

2015-01-01

Research in mathematics education stresses the importance of content knowledge in solving authentic tasks in statistics and in risk-based decision making. Existing research supports the claim that students rely on content knowledge and context expertise to make sense of data. In this article, however, I present evidence that the relationship…

District decision-making for health in low-income settings: a systematic literature review

PubMed Central

Avan, Bilal Iqbal

2016-01-01

Health management information systems (HMIS) produce large amounts of data about health service provision and population health, and provide opportunities for data-based decision-making in decentralized health systems. Yet the data are little-used locally. A well-defined approach to district-level decision-making using health data would help better meet the needs of the local population. In this second of four papers on district decision-making for health in low-income settings, our aim was to explore ways in which district administrators and health managers in low- and lower-middle-income countries use health data to make decisions, to describe the decision-making tools they used and identify challenges encountered when using these tools. A systematic literature review, following PRISMA guidelines, was undertaken. Experts were consulted about key sources of information. A search strategy was developed for 14 online databases of peer reviewed and grey literature. The resources were screened independently by two reviewers using pre-defined inclusion criteria. The 14 papers included were assessed for the quality of reported evidence and a descriptive evidence synthesis of the review findings was undertaken. We found 12 examples of tools to assist district-level decision-making, all of which included two key stages—identification of priorities, and development of an action plan to address them. Of those tools with more steps, four included steps to review or monitor the action plan agreed, suggesting the use of HMIS data. In eight papers HMIS data were used for prioritization. Challenges to decision-making processes fell into three main categories: the availability and quality of health and health facility data; human dynamics and financial constraints. Our findings suggest that evidence is available about a limited range of processes that include the use of data for decision-making at district level. Standardization and pre-testing in diverse settings would increase the potential that these tools could be used more widely. PMID:27591202

Decision-Making Accuracy of CBM Progress-Monitoring Data

ERIC Educational Resources Information Center

Hintze, John M.; Wells, Craig S.; Marcotte, Amanda M.; Solomon, Benjamin G.

2018-01-01

This study examined the diagnostic accuracy associated with decision making as is typically conducted with curriculum-based measurement (CBM) approaches to progress monitoring. Using previously published estimates of the standard errors of estimate associated with CBM, 20,000 progress-monitoring data sets were simulated to model student reading…

Balancing emotion and cognition: a case for decision aiding in conservation efforts.

PubMed

Wilson, Robyn S

2008-12-01

Despite advances in the quality of participatory decision making for conservation, many current efforts still suffer from an inability to bridge the gap between science and policy. Judgment and decision-making research suggests this gap may result from a person's reliance on affect-based shortcuts in complex decision contexts. I examined the results from 3 experiments that demonstrate how affect (i.e., the instantaneous reaction one has to a stimulus) influences individual judgments in these contexts and identified techniques from the decision-aiding literature that help encourage a balance between affect-based emotion and cognition in complex decision processes. In the first study, subjects displayed a lack of focus on their stated conservation objectives and made decisions that reflected their initial affective impressions. Value-focused approaches may help individuals incorporate all the decision-relevant objectives by making the technical and value-based objectives more salient. In the second study, subjects displayed a lack of focus on statistical risk and again made affect-based decisions. Trade-off techniques may help individuals incorporate relevant technical data, even when it conflicts with their initial affective impressions or other value-based objectives. In the third study, subjects displayed a lack of trust in decision-making authorities when the decision involved a negatively affect-rich outcome (i.e., a loss). Identifying shared salient values and increasing procedural fairness may help build social trust in both decision-making authorities and the decision process.

Fiscal Viability, Conjunctive and Compensatory Models, and Career-Ladder Decisions: An Empirical Investigation.

ERIC Educational Resources Information Center

Mehrens, William A.; And Others

A study was undertaken to explore cost-effective ways of making career ladder teacher evaluation system decisions based on fewer measures, assessing the relationship of observational variables to other data and final decisions, and comparison of compensatory and conjunctive decision models. Data included multiple scores from eight data sources in…

Decision-making based on emotional images.

PubMed

Katahira, Kentaro; Fujimura, Tomomi; Okanoya, Kazuo; Okada, Masato

2011-01-01

The emotional outcome of a choice affects subsequent decision making. While the relationship between decision making and emotion has attracted attention, studies on emotion and decision making have been independently developed. In this study, we investigated how the emotional valence of pictures, which was stochastically contingent on participants' choices, influenced subsequent decision making. In contrast to traditional value-based decision-making studies that used money or food as a reward, the "reward value" of the decision outcome, which guided the update of value for each choice, is unknown beforehand. To estimate the reward value of emotional pictures from participants' choice data, we used reinforcement learning models that have successfully been used in previous studies for modeling value-based decision making. Consequently, we found that the estimated reward value was asymmetric between positive and negative pictures. The negative reward value of negative pictures (relative to neutral pictures) was larger in magnitude than the positive reward value of positive pictures. This asymmetry was not observed in valence for an individual picture, which was rated by the participants regarding the emotion experienced upon viewing it. These results suggest that there may be a difference between experienced emotion and the effect of the experienced emotion on subsequent behavior. Our experimental and computational paradigm provides a novel way for quantifying how and what aspects of emotional events affect human behavior. The present study is a first step toward relating a large amount of knowledge in emotion science and in taking computational approaches to value-based decision making.

Use of cost-effectiveness data in priority setting decisions: experiences from the national guidelines for heart diseases in Sweden

PubMed Central

Eckard, Nathalie; Janzon, Magnus; Levin, Lars-Åke

2014-01-01

Background: The inclusion of cost-effectiveness data, as a basis for priority setting rankings, is a distinguishing feature in the formulation of the Swedish national guidelines. Guidelines are generated with the direct intent to influence health policy and support decisions about the efficient allocation of scarce healthcare resources. Certain medical conditions may be given higher priority rankings i.e. given more resources than others, depending on how serious the medical condition is. This study investigated how a decision-making group, the Priority Setting Group (PSG), used cost-effectiveness data in ranking priority setting decisions in the national guidelines for heart diseases. Methods: A qualitative case study methodology was used to explore the use of such data in ranking priority setting healthcare decisions. The study addressed availability of cost-effectiveness data, evidence understanding, interpretation difficulties, and the reliance on evidence. We were also interested in the explicit use of data in ranking decisions, especially in situations where economic arguments impacted the reasoning behind the decisions. Results: This study showed that cost-effectiveness data was an important and integrated part of the decision-making process. Involvement of a health economist and reliance on the data facilitated the use of cost-effectiveness data. Economic arguments were used both as a fine-tuning instrument and a counterweight for dichotomization. Cost-effectiveness data were used when the overall evidence base was weak and the decision-makers had trouble making decisions due to lack of clinical evidence and in times of uncertainty. Cost-effectiveness data were also used for decisions on the introduction of new expensive medical technologies. Conclusion: Cost-effectiveness data matters in decision-making processes and the results of this study could be applicable to other jurisdictions where health economics is implemented in decision-making. This study contributes to knowledge on how cost-effectiveness data is used in actual decision-making, to ensure that the decisions are offered on equal terms and that patients receive medical care according their needs in order achieve maximum benefit. PMID:25396208

Interactive Management and Updating of Spatial Data Bases

NASA Technical Reports Server (NTRS)

French, P.; Taylor, M.

1982-01-01

The decision making process, whether for power plant siting, load forecasting or energy resource planning, invariably involves a blend of analytical methods and judgement. Management decisions can be improved by the implementation of techniques which permit an increased comprehension of results from analytical models. Even where analytical procedures are not required, decisions can be aided by improving the methods used to examine spatially and temporally variant data. How the use of computer aided planning (CAP) programs and the selection of a predominant data structure, can improve the decision making process is discussed.

Facilitating Leadership: A Broader Look at Data Based Interventions.

ERIC Educational Resources Information Center

Mink, Oscar G.

Rational decision making by leaders in higher education and similar institutions suffers from both a lack of relevant data and the failure to use data when it is available. The purpose of this paper is to describe a process which when applied seems to facilitate the rational decision making processes of an institution's leadership. The process…

Teaching Decision-Making in Multiple Dimensions

ERIC Educational Resources Information Center

Barneva, Reneta P.; Brimkov, Valentin E.; Walters, Lisa M.

2018-01-01

In all areas of human activity, decision-making based on data analysis is very important. As the availability of data grows, it becomes critical to educate not only traditional students but also those individuals who are now in the workforce, as many of them are expected to manage the complex data streams and to provide evidence and guidance for…

IONIO Project: Computer-mediated Decision Support System and Communication in Ocean Science

NASA Astrophysics Data System (ADS)

Oddo, Paolo; Acierno, Arianna; Cuna, Daniela; Federico, Ivan; Galati, Maria Barbara; Awad, Esam; Korres, Gerasimos; Lecci, Rita; Manzella, Giuseppe M. R.; Merico, Walter; Perivoliotis, Leonidas; Pinardi, Nadia; Shchekinova, Elena; Mannarini, Gianandrea; Vamvakaki, Chrysa; Pecci, Leda; Reseghetti, Franco

2013-04-01

A decision Support System is composed by four main steps. The first one is the definition of the problem, the issue to be covered, decisions to be taken. Different causes can provoke different problems, for each of the causes or its effects it is necessary to define a list of information and/or data that are required in order to take the better decision. The second step is the determination of sources from where information/data needed for decision-making can be obtained and who has that information. Furthermore it must be possible to evaluate the quality of the sources to see which of them can provide the best information, and identify the mode and format in which the information is presented. The third step is relying on the processing of knowledge, i.e. if the information/data are fitting for purposes. It has to be decided which parts of the information/data need to be used, what additional data or information is necessary to access, how can information be best presented to be able to understand the situation and take decisions. Finally, the decision making process is an interactive and inclusive process involving all concerned parties, whose different views must be taken into consideration. A knowledge based discussion forum is necessary to reach a consensus. A decision making process need to be examined closely and refined, and modified to meet differing needs over time. The report is presenting legal framework and knowledge base for a scientific based decision support system and a brief exploration of some of the skills that enhances the quality of decisions taken.

IBM’s Health Analytics and Clinical Decision Support

PubMed Central

Sun, J.; Knoop, S.; Shabo, A.; Carmeli, B.; Sow, D.; Syed-Mahmood, T.; Rapp, W.

2014-01-01

Summary Objectives This survey explores the role of big data and health analytics developed by IBM in supporting the transformation of healthcare by augmenting evidence-based decision-making. Methods Some problems in healthcare and strategies for change are described. It is argued that change requires better decisions, which, in turn, require better use of the many kinds of healthcare information. Analytic resources that address each of the information challenges are described. Examples of the role of each of the resources are given. Results There are powerful analytic tools that utilize the various kinds of big data in healthcare to help clinicians make more personalized, evidenced-based decisions. Such resources can extract relevant information and provide insights that clinicians can use to make evidence-supported decisions. There are early suggestions that these resources have clinical value. As with all analytic tools, they are limited by the amount and quality of data. Conclusion Big data is an inevitable part of the future of healthcare. There is a compelling need to manage and use big data to make better decisions to support the transformation of healthcare to the personalized, evidence-supported model of the future. Cognitive computing resources are necessary to manage the challenges in employing big data in healthcare. Such tools have been and are being developed. The analytic resources, themselves, do not drive, but support healthcare transformation. PMID:25123736

Optimal decision making modeling for copper-matte Peirce-Smith converting process by means of data mining

NASA Astrophysics Data System (ADS)

Song, Yanpo; Peng, Xiaoqi; Tang, Ying; Hu, Zhikun

2013-07-01

To improve the operation level of copper converter, the approach to optimal decision making modeling for coppermatte converting process based on data mining is studied: in view of the characteristics of the process data, such as containing noise, small sample size and so on, a new robust improved ANN (artificial neural network) modeling method is proposed; taking into account the application purpose of decision making model, three new evaluation indexes named support, confidence and relative confidence are proposed; using real production data and the methods mentioned above, optimal decision making model for blowing time of S1 period (the 1st slag producing period) are developed. Simulation results show that this model can significantly improve the converting quality of S1 period, increase the optimal probability from about 70% to about 85%.

Artificial intelligence in cardiology.

PubMed

Bonderman, Diana

2017-12-01

Decision-making is complex in modern medicine and should ideally be based on available data, structured knowledge and proper interpretation in the context of an individual patient. Automated algorithms, also termed artificial intelligence that are able to extract meaningful patterns from data collections and build decisions upon identified patterns may be useful assistants in clinical decision-making processes. In this article, artificial intelligence-based studies in clinical cardiology are reviewed. The text also touches on the ethical issues and speculates on the future roles of automated algorithms versus clinicians in cardiology and medicine in general.

Knowledge Visualizations: A Tool to Achieve Optimized Operational Decision Making and Data Integration

DTIC Science & Technology

2015-06-01

Hadoop Distributed File System (HDFS) without any integration with Accumulo-based Knowledge Stores based on OWL/RDF. 4. Cloud Based The Apache Software...BTW, 7(12), pp. 227–241. Godin, A. & Akins, D. (2014). Extending DCGS-N naval tactical clouds from in-storage to in-memory for the integrated fires...VISUALIZATIONS: A TOOL TO ACHIEVE OPTIMIZED OPERATIONAL DECISION MAKING AND DATA INTEGRATION by Paul C. Hudson Jeffrey A. Rzasa June 2015 Thesis

Directional Slack-Based Measure for the Inverse Data Envelopment Analysis

PubMed Central

Abu Bakar, Mohd Rizam; Lee, Lai Soon; Jaafar, Azmi B.; Heydar, Maryam

2014-01-01

A novel technique has been introduced in this research which lends its basis to the Directional Slack-Based Measure for the inverse Data Envelopment Analysis. In practice, the current research endeavors to elucidate the inverse directional slack-based measure model within a new production possibility set. On one occasion, there is a modification imposed on the output (input) quantities of an efficient decision making unit. In detail, the efficient decision making unit in this method was omitted from the present production possibility set but substituted by the considered efficient decision making unit while its input and output quantities were subsequently modified. The efficiency score of the entire DMUs will be retained in this approach. Also, there would be an improvement in the efficiency score. The proposed approach was investigated in this study with reference to a resource allocation problem. It is possible to simultaneously consider any upsurges (declines) of certain outputs associated with the efficient decision making unit. The significance of the represented model is accentuated by presenting numerical examples. PMID:24883350

Digital technology and clinical decision making in depression treatment: Current findings and future opportunities.

PubMed

Hallgren, Kevin A; Bauer, Amy M; Atkins, David C

2017-06-01

Clinical decision making encompasses a broad set of processes that contribute to the effectiveness of depression treatments. There is emerging interest in using digital technologies to support effective and efficient clinical decision making. In this paper, we provide "snapshots" of research and current directions on ways that digital technologies can support clinical decision making in depression treatment. Practical facets of clinical decision making are reviewed, then research, design, and implementation opportunities where technology can potentially enhance clinical decision making are outlined. Discussions of these opportunities are organized around three established movements designed to enhance clinical decision making for depression treatment, including measurement-based care, integrated care, and personalized medicine. Research, design, and implementation efforts may support clinical decision making for depression by (1) improving tools to incorporate depression symptom data into existing electronic health record systems, (2) enhancing measurement of treatment fidelity and treatment processes, (3) harnessing smartphone and biosensor data to inform clinical decision making, (4) enhancing tools that support communication and care coordination between patients and providers and within provider teams, and (5) leveraging treatment and outcome data from electronic health record systems to support personalized depression treatment. The current climate of rapid changes in both healthcare and digital technologies facilitates an urgent need for research, design, and implementation of digital technologies that explicitly support clinical decision making. Ensuring that such tools are efficient, effective, and usable in frontline treatment settings will be essential for their success and will require engagement of stakeholders from multiple domains. © 2017 Wiley Periodicals, Inc.

An exploration of clinical decision making in mental health triage.

PubMed

Sands, Natisha

2009-08-01

Mental health (MH) triage is a specialist area of clinical nursing practice that involves complex decision making. The discussion in this article draws on the findings of a Ph.D. study that involved a statewide investigation of the scope of MH triage nursing practice in Victoria, Australia. Although the original Ph.D. study investigated a number of core practices in MH triage, the focus of the discussion in this article is specifically on the findings related to clinical decision making in MH triage, which have not previously been published. The study employed an exploratory descriptive research design that used mixed data collection methods including a survey questionnaire (n = 139) and semistructured interviews (n = 21). The study findings related to decision making revealed a lack of empirically tested evidence-based decision-making frameworks currently in use to support MH triage nursing practice. MH triage clinicians in Australia rely heavily on clinical experience to underpin decision making and have little of knowledge of theoretical models for practice, such as methodologies for rating urgency. A key recommendation arising from the study is the need to develop evidence-based decision-making frameworks such as clinical guidelines to inform and support MH triage clinical decision making.

Funding Based on Needs? A Study on the Use of Needs Assessment Data by a Major Humanitarian Health Assistance Donor in its Decisions to Allocate Funds

PubMed Central

Olin, Emma; von Schreeb, Johan

2014-01-01

Background: International humanitarian assistance is essential for disaster-affected populations, particularly in resource scarce settings. To target such assistance, needs assessments are required. According to internationally endorsed principles, donor governments should provide funding for humanitarian assistance based on need. Aim: The aim of this study is to explore a major donor’s use of needs assessment data in decision-making for allocations of funds for health-related humanitarian assistance contributions. Setting: This is a case study of the Swedish International Development Cooperation Agency (Sida), a major and respected international donor of humanitarian assistance. Methods: To explore Sida’s use of needs assessment data in practice for needs-based allocations, we reviewed all decision documents and assessment memoranda for humanitarian assistance contributions for 2012 using content analysis; this was followed by interviews with key personnel at Sida. Results: Our document analysis found that needs assessment data was not systematically included in Sida’s assessment memoranda and decision documents. In the interviews, we observed various descriptions of the concept of needs assessments, the importance of contextual influences as well as previous collaborations with implementing humanitarian assistance organizations. Our findings indicate that policies guiding funding decisions on humanitarian assistance need to be matched with available needs assessment data and that terminologies and concepts have to be clearly defined. Conclusion: Based on the document analysis and the interviews, it is unclear how well Sida used needs assessment data for decisions to allocate funds. However, although our observations show that needs assessments are seldom used in decision making, Sida’s use of needs assessments has improved compared to a previous study. To improve project funds allocations based on needs assessment data, it will be critical to develop distinct frameworks for allocation distributions based on needs assessment and clear definitions, measurements and interpretations of needs. Key words: Needs assessment, humanitarian assistance, disasters, donor decision-making PMID:24894417

[Patients' preferences and experience regarding participation in nursing care decisions in acute hospitals--an analysis of conformity of preferences and experience, and factors influencing different types of decision making].

PubMed

Smoliner, Andrea; Hantikainen, Virpi; Mayer, Hanna; Ponocny-Seliger, Elisabeth; Them, Christa

2009-12-01

Patients' preferences regarding their participation in nursing care decisions represent a key aspect of the concept of evidence-based nursing; nonetheless, very little quantitative research has been carried out in this area. The aim of the present study was to describe the patients' preferences and experience concerning their participation in nursing care decision-making processes in acute hospitals. A total of 967 patients in five hospitals in Vienna participated in this study by completing questionnaires. The results revealed that 38.5 % of patients preferred the paternalistic style of decision-making, 42.1 % wanted to make decisions together with the nursing staff and 5.7 % expressed a wish to make their own decisions. During their hospital stay, however, patients experienced paternalistic decision-making to a higher degree than they wished for. Age, sex, form of treatment and subjectively experienced health condition represented person-related characteristics that influenced preferences regarding the form of decision-making. The results of this study underline the importance of collecting data on patients' preferences in decision-making processes in order to meet the social, legal, and professional demands of patient-oriented nursing care based on the most recent scientific knowledge.

The effect of uncertainties in distance-based ranking methods for multi-criteria decision making

NASA Astrophysics Data System (ADS)

Jaini, Nor I.; Utyuzhnikov, Sergei V.

2017-08-01

Data in the multi-criteria decision making are often imprecise and changeable. Therefore, it is important to carry out sensitivity analysis test for the multi-criteria decision making problem. The paper aims to present a sensitivity analysis for some ranking techniques based on the distance measures in multi-criteria decision making. Two types of uncertainties are considered for the sensitivity analysis test. The first uncertainty is related to the input data, while the second uncertainty is towards the Decision Maker preferences (weights). The ranking techniques considered in this study are TOPSIS, the relative distance and trade-off ranking methods. TOPSIS and the relative distance method measure a distance from an alternative to the ideal and antiideal solutions. In turn, the trade-off ranking calculates a distance of an alternative to the extreme solutions and other alternatives. Several test cases are considered to study the performance of each ranking technique in both types of uncertainties.

A new web-based framework development for fuzzy multi-criteria group decision-making.

PubMed

Hanine, Mohamed; Boutkhoum, Omar; Tikniouine, Abdessadek; Agouti, Tarik

2016-01-01

Fuzzy multi-criteria group decision making (FMCGDM) process is usually used when a group of decision-makers faces imprecise data or linguistic variables to solve the problems. However, this process contains many methods that require many time-consuming calculations depending on the number of criteria, alternatives and decision-makers in order to reach the optimal solution. In this study, a web-based FMCGDM framework that offers decision-makers a fast and reliable response service is proposed. The proposed framework includes commonly used tools for multi-criteria decision-making problems such as fuzzy Delphi, fuzzy AHP and fuzzy TOPSIS methods. The integration of these methods enables taking advantages of the strengths and complements each method's weakness. Finally, a case study of location selection for landfill waste in Morocco is performed to demonstrate how this framework can facilitate decision-making process. The results demonstrate that the proposed framework can successfully accomplish the goal of this study.

Health technology assessment and primary data collection for reducing uncertainty in decision making.

PubMed

Goeree, Ron; Levin, Les; Chandra, Kiran; Bowen, James M; Blackhouse, Gord; Tarride, Jean-Eric; Burke, Natasha; Bischof, Matthias; Xie, Feng; O'Reilly, Daria

2009-05-01

Health care expenditures continue to escalate, and pressures for increased spending will continue. Health care decision makers from publicly financed systems, private insurance companies, or even from individual health care institutions, will continue to be faced with making difficult purchasing, access, and reimbursement decisions. As a result, decision makers are increasingly turning to evidence-based platforms to help control costs and make the most efficient use of existing resources. Most tools used to assist with evidence-based decision making focus on clinical outcomes. Health technology assessment (HTA) is increasing in popularity because it also considers other factors important for decision making, such as cost, social and ethical values, legal issues, and factors such as the feasibility of implementation. In some jurisdictions, HTAs have also been supplemented with primary data collection to help address uncertainty that may still exist after conducting a traditional HTA. The HTA process adopted in Ontario, Canada, is unique in that assessments are also made to determine what primary data research should be conducted and what should be collected in these studies. In this article, concerns with the traditional HTA process are discussed, followed by a description of the HTA process that has been established in Ontario, with a particular focus on the data collection program followed by the Programs for Assessment of Technology in Health Research Institute. An illustrative example is used to show how the Ontario HTA process works and the role value of information analyses plays in addressing decision uncertainty, determining research feasibility, and determining study data collection needs.

Vulnerable patients' perceptions of health care quality and quality data.

PubMed

Raven, Maria Catherine; Gillespie, Colleen C; DiBennardo, Rebecca; Van Busum, Kristin; Elbel, Brian

2012-01-01

Little is known about how patients served by safety-net hospitals utilize and respond to hospital quality data. To understand how vulnerable, lower income patients make health care decisions and define quality of care and whether hospital quality data factor into such decisions and definitions. Mixed quantitative and qualitative methods were used to gather primary data from patients at an urban, tertiary-care safety-net hospital. The study hospital is a member of the first public hospital system to voluntarily post hospital quality data online for public access. Patients were recruited from outpatient and inpatient clinics. Surveys were used to collect data on participants' sociodemographic characteristics, health literacy, health care experiences, and satisfaction variables. Focus groups were used to explore a representative sample of 24 patients' health care decision making and views of quality. Data from focus group transcripts were iteratively coded and analyzed by the authors. Focus group participants were similar to the broader diverse, low-income clinic. Participants reported exercising choice in making decisions about where to seek health care. Multiple sources influenced decision-making processes including participants' own beliefs and values, social influences, and prior experiences. Hospital quality data were notably absent as a source of influence in health care decision making for this population largely because participants were unaware of its existence. Participants' views of hospital quality were influenced by the quality and efficiency of services provided (with an emphasis on the doctor-patient relationship) and patient centeredness. When presented with it, patients appreciated the hospital quality data and, with guidance, were interested in incorporating it into health care decision making. Results suggest directions for optimizing the presentation, content, and availability of hospital quality data. Future research will explore how similar populations form and make choices based on presentation of hospital quality data.

Evidence based policy making in the European Union: the role of the scientific community.

PubMed

Majcen, Špela

2017-03-01

In the times when the acquis of the European Union (EU) has developed so far as to reach a high level of technical complexity, in particular in certain policy fields such as environmental legislation, it is important to look at what kind of information and data policy decisions are based on. This position paper looks at the extent to which evidence-based decision-making process is being considered in the EU institutions when it comes to adopting legislation in the field of environment at the EU level. The paper calls for closer collaboration between scientists and decision-makers in view of ensuring that correct data is understood and taken into consideration when drafting, amending, negotiating and adopting new legal texts at all levels of the EU decision-making process. It concludes that better awareness of the need for such collaboration among the decision-makers as well as the scientific community would benefit the process and quality of the final outcomes (legislation).

Factors affecting evidence-based decision making in local health departments.

PubMed

Sosnowy, Collette D; Weiss, Linda J; Maylahn, Christopher M; Pirani, Sylvia J; Katagiri, Nancy J

2013-12-01

Data indicating the extent to which evidence-based decision making (EBDM) is used in local health departments (LHDs) are limited. This study aims to determine use of decision-making processes by New York State LHD leaders and upper-level staff and identify facilitators and barriers to the use of EBDM in LHDs. The New York Public Health Practice-Based Research Network implemented a mixed-methods study in 31 LHDs. There were 20 individual interviews; five small-group interviews (two or three participants each); and two focus groups (eight participants each) conducted with people who had decision-making authority. Information was obtained about each person's background and position, decision-making responsibilities, how decisions are made within their LHD, knowledge and experience with EBDM, use of each step of the EBDM process, and barriers and facilitators to EBDM implementation. Data were collected from June to November 2010 and analyzed in 2011. Overall, participants supported EBDM and expressed a desire to increase their department's use of it. Although most people understood the concept, a relatively small number had substantial expertise and experience with its practice. Many indicated that they applied EBDM unevenly. Factors associated with use of EBDM included strong leadership; workforce capacity (number and skills); resources; funding and program mandates; political support; and access to data and program models suitable to community conditions. EBDM is used inconsistently in LHDs in New York. Despite knowledge and interest among LHD leadership, the LHD capacity, resources, appropriate programming, and other issues serve as impediments to EBDM and optimal implementation of evidence-based strategies. Published by Elsevier Inc.

New approaches for real time decision support systems

NASA Technical Reports Server (NTRS)

Hair, D. Charles; Pickslay, Kent

1994-01-01

NCCOSC RDT&E Division (NRaD) is conducting research into ways of improving decision support systems (DSS) that are used in tactical Navy decision making situations. The research has focused on the incorporation of findings about naturalistic decision-making processes into the design of the DSS. As part of that research, two computer tools were developed that model the two primary naturalistic decision-making strategies used by Navy experts in tactical settings. Current work is exploring how best to incorporate the information produced by those tools into an existing simulation of current Navy decision support systems. This work has implications for any applications involving the need to make decisions under time constraints, based on incomplete or ambiguous data.

Evidence-Based Library Management: The Leadership Challenge

ERIC Educational Resources Information Center

Lakos, Amos

2007-01-01

This paper is an extension of the author's earlier work on developing management information services and creating a culture of assessment in libraries. The author will focus observations on the use of data in decision-making in libraries, specifically on the role of leadership in making evidence-based decision a reality, and will review new…

Models based on value and probability in health improve shared decision making.

PubMed

Ortendahl, Monica

2008-10-01

Diagnostic reasoning and treatment decisions are a key competence of doctors. A model based on values and probability provides a conceptual framework for clinical judgments and decisions, and also facilitates the integration of clinical and biomedical knowledge into a diagnostic decision. Both value and probability are usually estimated values in clinical decision making. Therefore, model assumptions and parameter estimates should be continually assessed against data, and models should be revised accordingly. Introducing parameter estimates for both value and probability, which usually pertain in clinical work, gives the model labelled subjective expected utility. Estimated values and probabilities are involved sequentially for every step in the decision-making process. Introducing decision-analytic modelling gives a more complete picture of variables that influence the decisions carried out by the doctor and the patient. A model revised for perceived values and probabilities by both the doctor and the patient could be used as a tool for engaging in a mutual and shared decision-making process in clinical work.

Data quality system using reference dictionaries and edit distance algorithms

NASA Astrophysics Data System (ADS)

Karbarz, Radosław; Mulawka, Jan

2015-09-01

The real art of management it is important to make smart decisions, what in most of the cases is not a trivial task. Those decisions may lead to determination of production level, funds allocation for investments etc. Most of the parameters in decision-making process such as: interest rate, goods value or exchange rate may change. It is well know that these parameters in the decision-making are based on the data contained in datamarts or data warehouse. However, if the information derived from the processed data sets is the basis for the most important management decisions, it is required that the data is accurate, complete and current. In order to achieve high quality data and to gain from them measurable business benefits, data quality system should be used. The article describes the approach to the problem, shows the algorithms in details and their usage. Finally the test results are provide. Test results show the best algorithms (in terms of quality and quantity) for different parameters and data distribution.

Not a Humbug: the evolution of patient-centred medical decision-making.

PubMed

Trump, Benjamin D; Linkov, Faina; Edwards, Robert P; Linkov, Igor

2015-12-01

This 'Christmas Issue'-type paper uses the framework of 'A Christmas Carol' to tell about the evolution of decision-making in evidence-based medicine (EBM). The Ghost of the Past represents paternalistic medicine, the Ghost of the Present symbolises EBM, while the Ghost of the Future serves as a patient-centred system where research data and tools of decision science are jointly used to make optimal medical decisions for individual patients. We argue that this shift towards a patient-centred approach to EBM and medical care is the next step in the evolution of medical decision-making, which would help to empower patients with the capability to make educated decisions throughout the course of their medical treatment.

ENABLING SMART MANUFACTURING TECHNOLOGIES FOR DECISION-MAKING SUPPORT

PubMed Central

Helu, Moneer; Libes, Don; Lubell, Joshua; Lyons, Kevin; Morris, KC

2017-01-01

Smart manufacturing combines advanced manufacturing capabilities and digital technologies throughout the product lifecycle. These technologies can provide decision-making support to manufacturers through improved monitoring, analysis, modeling, and simulation that generate more and better intelligence about manufacturing systems. However, challenges and barriers have impeded the adoption of smart manufacturing technologies. To begin to address this need, this paper defines requirements for data-driven decision making in manufacturing based on a generalized description of decision making. Using these requirements, we then focus on identifying key barriers that prevent the development and use of data-driven decision making in industry as well as examples of technologies and standards that have the potential to overcome these barriers. The goal of this research is to promote a common understanding among the manufacturing community that can enable standardization efforts and innovation needed to continue adoption and use of smart manufacturing technologies. PMID:28649678

What is on your mind? Using the perceptual cycle model and critical decision method to understand the decision-making process in the cockpit.

PubMed

Plant, Katherine L; Stanton, Neville A

2013-01-01

Aeronautical decision-making is complex as there is not always a clear coupling between the decision made and decision outcome. As such, there is a call for process-orientated decision research in order to understand why a decision made sense at the time it was made. Schema theory explains how we interact with the world using stored mental representations and forms an integral part of the perceptual cycle model (PCM); proposed here as a way to understand the decision-making process. This paper qualitatively analyses data from the critical decision method (CDM) based on the principles of the PCM. It is demonstrated that the approach can be used to understand a decision-making process and highlights how influential schemata can be at informing decision-making. The reliability of this approach is established, the general applicability is discussed and directions for future work are considered. This paper introduces the PCM, and the associated schema theory, as a framework to structure and explain data collected from the CDM. The reliability of both the method and coding scheme is addressed.

Enhancing clinical decision making: development of a contiguous definition and conceptual framework.

PubMed

Tiffen, Jennifer; Corbridge, Susan J; Slimmer, Lynda

2014-01-01

Clinical decision making is a term frequently used to describe the fundamental role of the nurse practitioner; however, other terms have been used interchangeably. The purpose of this article is to begin the process of developing a definition and framework of clinical decision making. The developed definition was "Clinical decision making is a contextual, continuous, and evolving process, where data are gathered, interpreted, and evaluated in order to select an evidence-based choice of action." A contiguous framework for clinical decision making specific for nurse practitioners is also proposed. Having a clear and unique understanding of clinical decision making will allow for consistent use of the term, which is relevant given the changing educational requirements for nurse practitioners and broadening scope of practice. Copyright © 2014 Elsevier Inc. All rights reserved.

Health professionals' decision-making in wound management: a grounded theory.

PubMed

Gillespie, Brigid M; Chaboyer, Wendy; St John, Winsome; Morley, Nicola; Nieuwenhoven, Paul

2015-06-01

To develop a conceptual understanding of the decision-making processes used by healthcare professionals in wound care practice. With the global move towards using an evidence-base in standardizing wound care practices and the need to reduce hospital wound care costs, it is important to understand health professionals' decision-making in this important yet under-researched area. A grounded theory approach was used to explore clinical decision-making of healthcare professionals in wound care practice. Interviews were conducted with 20 multi-disciplinary participants from nursing, surgery, infection control and wound care who worked at a metropolitan hospital in Australia. Data were collected during 2012-2013. Constant comparative analysis underpinned by Strauss and Corbin's framework was used to identify clinical decision-making processes. The core category was 'balancing practice-based knowledge with evidence-based knowledge'. Participants' clinical practice and actions embedded the following processes: 'utilizing the best available information', 'using a consistent approach in wound assessment' and 'using a multidisciplinary approach'. The substantive theory explains how practice and evidence knowledge was balanced and the variation in use of intuitive practice-based knowledge versus evidence-based knowledge. Participants considered patients' needs and preferences, costs, outcomes, technologies, others' expertise and established practices. Participants' decision-making tended to be more heavily weighted towards intuitive practice-based processes. These findings offer a better understanding of the processes used by health professionals' in their decision-making in wound care. Such an understanding may inform the development of evidence-based interventions that lead to better patient outcomes. © 2014 John Wiley & Sons Ltd.

Spatial planning using probabilistic flood maps

NASA Astrophysics Data System (ADS)

Alfonso, Leonardo; Mukolwe, Micah; Di Baldassarre, Giuliano

2015-04-01

Probabilistic flood maps account for uncertainty in flood inundation modelling and convey a degree of certainty in the outputs. Major sources of uncertainty include input data, topographic data, model structure, observation data and parametric uncertainty. Decision makers prefer less ambiguous information from modellers; this implies that uncertainty is suppressed to yield binary flood maps. Though, suppressing information may potentially lead to either surprise or misleading decisions. Inclusion of uncertain information in the decision making process is therefore desirable and transparent. To this end, we utilise the Prospect theory and information from a probabilistic flood map to evaluate potential decisions. Consequences related to the decisions were evaluated using flood risk analysis. Prospect theory explains how choices are made given options for which probabilities of occurrence are known and accounts for decision makers' characteristics such as loss aversion and risk seeking. Our results show that decision making is pronounced when there are high gains and loss, implying higher payoffs and penalties, therefore a higher gamble. Thus the methodology may be appropriately considered when making decisions based on uncertain information.

Cost Analysis of Instructional Technology.

ERIC Educational Resources Information Center

Johnson, F. Craig; Dietrich, John E.

Although some serious limitations in the cost analysis technique do exist, the need for cost data in decision making is so great that every effort should be made to obtain accurate estimates. This paper discusses the several issues which arise when an attempt is made to make quality, trade-off, or scope decisions based on cost data. Three methods…

Data Clustering and Evolving Fuzzy Decision Tree for Data Base Classification Problems

NASA Astrophysics Data System (ADS)

Chang, Pei-Chann; Fan, Chin-Yuan; Wang, Yen-Wen

Data base classification suffers from two well known difficulties, i.e., the high dimensionality and non-stationary variations within the large historic data. This paper presents a hybrid classification model by integrating a case based reasoning technique, a Fuzzy Decision Tree (FDT), and Genetic Algorithms (GA) to construct a decision-making system for data classification in various data base applications. The model is major based on the idea that the historic data base can be transformed into a smaller case-base together with a group of fuzzy decision rules. As a result, the model can be more accurately respond to the current data under classifying from the inductions by these smaller cases based fuzzy decision trees. Hit rate is applied as a performance measure and the effectiveness of our proposed model is demonstrated by experimentally compared with other approaches on different data base classification applications. The average hit rate of our proposed model is the highest among others.

District decision-making for health in low-income settings: a systematic literature review.

PubMed

Wickremasinghe, Deepthi; Hashmi, Iram Ejaz; Schellenberg, Joanna; Avan, Bilal Iqbal

2016-09-01

Health management information systems (HMIS) produce large amounts of data about health service provision and population health, and provide opportunities for data-based decision-making in decentralized health systems. Yet the data are little-used locally. A well-defined approach to district-level decision-making using health data would help better meet the needs of the local population. In this second of four papers on district decision-making for health in low-income settings, our aim was to explore ways in which district administrators and health managers in low- and lower-middle-income countries use health data to make decisions, to describe the decision-making tools they used and identify challenges encountered when using these tools. A systematic literature review, following PRISMA guidelines, was undertaken. Experts were consulted about key sources of information. A search strategy was developed for 14 online databases of peer reviewed and grey literature. The resources were screened independently by two reviewers using pre-defined inclusion criteria. The 14 papers included were assessed for the quality of reported evidence and a descriptive evidence synthesis of the review findings was undertaken. We found 12 examples of tools to assist district-level decision-making, all of which included two key stages-identification of priorities, and development of an action plan to address them. Of those tools with more steps, four included steps to review or monitor the action plan agreed, suggesting the use of HMIS data. In eight papers HMIS data were used for prioritization. Challenges to decision-making processes fell into three main categories: the availability and quality of health and health facility data; human dynamics and financial constraints. Our findings suggest that evidence is available about a limited range of processes that include the use of data for decision-making at district level. Standardization and pre-testing in diverse settings would increase the potential that these tools could be used more widely. © The Author 2016. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine.

Medical Decision-Making for Adults Who Lack Decision-Making Capacity and a Surrogate: State of the Science.

PubMed

Kim, Hyejin; Song, Mi-Kyung

2018-01-01

Adults who lack decision-making capacity and a surrogate ("unbefriended" adults) are a vulnerable, voiceless population in health care. But little is known about this population, including how medical decisions are made for these individuals. This integrative review was to examine what is known about unbefriended adults and identify gaps in the literature. Six electronic databases were searched using 4 keywords: "unbefriended," "unrepresented patients," "adult orphans," and "incapacitated patients without surrogates." After screening, the final sample included 10 data-based articles for synthesis. Main findings include the following: (1) various terms were used to refer to adults who lack decision-making capacity and a surrogate; (2) the number of unbefriended adults was sizable and likely to grow; (3) approaches to medical decision-making for this population in health-care settings varied; and (4) professional guidelines and laws to address the issues related to this population were inconsistent. There have been no studies regarding the quality of medical decision-making and its outcomes for this population or societal impact. Extremely limited empirical data exist on unbefriended adults to develop strategies to improve how medical decisions are made for this population. There is an urgent need for research to examine the quality of medical decision-making and its outcomes for this vulnerable population.

Using health outcomes data to inform decision-making: formulary committee perspective.

PubMed

Janknegt, R

2001-01-01

When healthcare resources are limited, decisions about the treatments to fund can be complex and difficult to make, involving the careful balancing of multiple factors. The decisions taken may have far-reaching consequences affecting many people. Clearly, decisions such as the choice of products on a formulary must be taken using a selection process that is fully transparent and that can be justified to all parties concerned. Although everyone would agree that drug selection should be a rational process that follows the guidelines of evidence-based medicine, many other factors may play a role in decision-making. Although some of these are explicit and rational, others are less clearly defined, and decision-makers may be unaware of the influence exerted by some of these factors. In order to facilitate transparent decision-making that makes rational use of health outcomes information, the System of Objectified Judgement Analysis (SOJA) has been developed by the author. SOJA includes interactive software that combines the quality advantages of the 'top-down' approach to drug selection, based on a thorough literature review, with the compliance advantages of a 'bottom-up' approach, where the final decision is made by the individual formulary committee and not by the authors of the review. The SOJA method, based on decision-making processes in economics, ensures that health outcomes information is given appropriate weight. Such approaches are valuable tools in discussions about product selection for formularies.

Network-centric decision architecture for financial or 1/f data models

NASA Astrophysics Data System (ADS)

Jaenisch, Holger M.; Handley, James W.; Massey, Stoney; Case, Carl T.; Songy, Claude G.

2002-12-01

This paper presents a decision architecture algorithm for training neural equation based networks to make autonomous multi-goal oriented, multi-class decisions. These architectures make decisions based on their individual goals and draw from the same network centric feature set. Traditionally, these architectures are comprised of neural networks that offer marginal performance due to lack of convergence of the training set. We present an approach for autonomously extracting sample points as I/O exemplars for generation of multi-branch, multi-node decision architectures populated by adaptively derived neural equations. To test the robustness of this architecture, open source data sets in the form of financial time series were used, requiring a three-class decision space analogous to the lethal, non-lethal, and clutter discrimination problem. This algorithm and the results of its application are presented here.

Natural Resource Information System. Volume 1: Overall description

NASA Technical Reports Server (NTRS)

1972-01-01

A prototype computer-based Natural Resource Information System was designed which could store, process, and display data of maximum usefulness to land management decision making. The system includes graphic input and display, the use of remote sensing as a data source, and it is useful at multiple management levels. A survey established current decision making processes and functions, information requirements, and data collection and processing procedures. The applications of remote sensing data and processing requirements were established. Processing software was constructed and a data base established using high-altitude imagery and map coverage of selected areas of SE Arizona. Finally a demonstration of system processing functions was conducted utilizing material from the data base.

Decision-making when data and inferences are not conclusive: risk-benefit and acceptable regret approach.

PubMed

Hozo, Iztok; Schell, Michael J; Djulbegovic, Benjamin

2008-07-01

The absolute truth in research is unobtainable, as no evidence or research hypothesis is ever 100% conclusive. Therefore, all data and inferences can in principle be considered as "inconclusive." Scientific inference and decision-making need to take into account errors, which are unavoidable in the research enterprise. The errors can occur at the level of conclusions that aim to discern the truthfulness of research hypothesis based on the accuracy of research evidence and hypothesis, and decisions, the goal of which is to enable optimal decision-making under present and specific circumstances. To optimize the chance of both correct conclusions and correct decisions, the synthesis of all major statistical approaches to clinical research is needed. The integration of these approaches (frequentist, Bayesian, and decision-analytic) can be accomplished through formal risk:benefit (R:B) analysis. This chapter illustrates the rational choice of a research hypothesis using R:B analysis based on decision-theoretic expected utility theory framework and the concept of "acceptable regret" to calculate the threshold probability of the "truth" above which the benefit of accepting a research hypothesis outweighs its risks.

Discovering Decision Knowledge from Web Log Portfolio for Managing Classroom Processes by Applying Decision Tree and Data Cube Technology.

ERIC Educational Resources Information Center

Chen, Gwo-Dong; Liu, Chen-Chung; Ou, Kuo-Liang; Liu, Baw-Jhiune

2000-01-01

Discusses the use of Web logs to record student behavior that can assist teachers in assessing performance and making curriculum decisions for distance learning students who are using Web-based learning systems. Adopts decision tree and data cube information processing methodologies for developing more effective pedagogical strategies. (LRW)

Driving with roadmaps and dashboards: using information resources to structure the decision models in service organizations.

PubMed

Chorpita, Bruce F; Bernstein, Adam; Daleiden, Eric L

2008-03-01

This paper illustrates the application of design principles for tools that structure clinical decision-making. If the effort to implement evidence-based practices in community services organizations is to be effective, attention must be paid to the decision-making context in which such treatments are delivered. Clinical research trials commonly occur in an environment characterized by structured decision making and expert supports. Technology has great potential to serve mental health organizations by supporting these potentially important contextual features of the research environment, through organization and reporting of clinical data into interpretable information to support decisions and anchor decision-making procedures. This article describes one example of a behavioral health reporting system designed to facilitate clinical and administrative use of evidence-based practices. The design processes underlying this system-mapping of decision points and distillation of performance information at the individual, caseload, and organizational levels-can be implemented to support clinical practice in a wide variety of settings.

Application of the principles of evidence-based practice in decision making among senior management in Nova Scotia's addiction services agencies.

PubMed

Murphy, Matthew; MacCarthy, M Jayne; McAllister, Lynda; Gilbert, Robert

2014-12-05

Competency profiles for occupational clusters within Canada's substance abuse workforce (SAW) define the need for skill and knowledge in evidence-based practice (EBP) across all its members. Members of the Senior Management occupational cluster hold ultimate responsibility for decisions made within addiction services agencies and therefore must possess the highest level of proficiency in EBP. The objective of this study was to assess the knowledge of the principles of EBP, and use of the components of the evidence-based decision making (EBDM) process in members of this occupational cluster from selected addiction services agencies in Nova Scotia. A convenience sampling method was used to recruit participants from addiction services agencies. Semi-structured qualitative interviews were conducted with eighteen Senior Management. The interviews were audio-recorded, transcribed verbatim and checked by the participants. Interview transcripts were coded and analyzed for themes using content analysis and assisted by qualitative data analysis software (NVivo 9.0). Data analysis revealed four main themes: 1) Senior Management believe that addictions services agencies are evidence-based; 2) Consensus-based decision making is the norm; 3) Senior Management understand the principles of EBP and; 4) Senior Management do not themselves use all components of the EBDM process when making decisions, oftentimes delegating components of this process to decision support staff. Senior Management possess an understanding of the principles of EBP, however, when making decisions they often delegate components of the EBDM process to decision support staff. Decision support staff are not defined as an occupational cluster in Canada's SAW and have not been ascribed a competency profile. As such, there is no guarantee that this group possesses competency in EBDM. There is a need to advocate for the development of a defined occupational cluster and associated competency profile for this critical group.

Rational and experiential decision-making preferences of third-year student pharmacists.

PubMed

McLaughlin, Jacqueline E; Cox, Wendy C; Williams, Charlene R; Shepherd, Greene

2014-08-15

To examine the rational (systematic and rule-based) and experiential (fast and intuitive) decision-making preferences of student pharmacists, and to compare these preferences to the preferences of other health professionals and student populations. The Rational-Experiential Inventory (REI-40), a validated psychometric tool, was administered electronically to 114 third-year (P3) student pharmacists. Student demographics and preadmission data were collected. The REI-40 results were compared with student demographics and admissions data to identify possible correlations between these factors. Mean REI-40 rational scores were higher than experiential scores. Rational scores for younger students were significantly higher than students aged 30 years and older (p<0.05). No significant differences were found based on gender, race, or the presence of a prior degree. All correlations between REI-40 scores and incoming grade point average (GPA) and Pharmacy College Admission Test (PCAT) scores were weak. Student pharmacists favored rational decision making over experiential decision making, which was similar to results of studies done of other health professions.

Criminal decision making: the development of adolescent judgment, criminal responsibility, and culpability.

PubMed

Fried, C S; Reppucci, N D

2001-02-01

Theories of judgment in decision making hypothesize that throughout adolescence, judgment is impaired because the development of several psychosocial factors that are presumed to influence decision making lags behind the development of the cognitive capacities that are required to make mature decisions. This study uses an innovative video technique to examine the role of several psychosocial factors--temporal perspective, peer influence, and risk perception--in adolescent criminal decision making. Results based on data collected from 56 adolescents between the ages of 13 and 18 years revealed that detained youth were more likely to think of future-oriented consequences of engaging in the depicted delinquent act and less likely to anticipate pressure from their friends than nondetained youth. Examination of the developmental functions of the psychosocial factors indicates age-based differences on standardized measures of temporal perspective and resistance to peer influence and on measures of the role of risk perception in criminal decision making. Assessments of criminal responsibility and culpability were predicted by age and ethnicity. Implications for punishment in the juvenile justice system are discussed.

Strategic analytics: towards fully embedding evidence in healthcare decision-making.

PubMed

Garay, Jason; Cartagena, Rosario; Esensoy, Ali Vahit; Handa, Kiren; Kane, Eli; Kaw, Neal; Sadat, Somayeh

2015-01-01

Cancer Care Ontario (CCO) has implemented multiple information technology solutions and collected health-system data to support its programs. There is now an opportunity to leverage these data and perform advanced end-to-end analytics that inform decisions around improving health-system performance. In 2014, CCO engaged in an extensive assessment of its current data capacity and capability, with the intent to drive increased use of data for evidence-based decision-making. The breadth and volume of data at CCO uniquely places the organization to contribute to not only system-wide operational reporting, but more advanced modelling of current and future state system management and planning. In 2012, CCO established a strategic analytics practice to assist the agency's programs contextualize and inform key business decisions and to provide support through innovative predictive analytics solutions. This paper describes the organizational structure, services and supporting operations that have enabled progress to date, and discusses the next steps towards the vision of embedding evidence fully into healthcare decision-making. Copyright © 2014 Longwoods Publishing.

Making Instructional Decisions Based on Data: What, How, and Why

ERIC Educational Resources Information Center

Mokhtari, Kouider; Rosemary, Catherine A.; Edwards, Patricia A.

2007-01-01

A carefully coordinated literacy assessment and instruction framework implemented school-wide can support school teams in making sense of various types of data for instructional planning. Instruction that is data based and goal driven sets the stage for continuous reading and writing improvement. (Contains 2 figures.)

Big-Data Based Decision-Support Systems to Improve Clinicians' Cognition.

PubMed

Roosan, Don; Samore, Matthew; Jones, Makoto; Livnat, Yarden; Clutter, Justin

2016-01-01

Complex clinical decision-making could be facilitated by using population health data to inform clinicians. In two previous studies, we interviewed 16 infectious disease experts to understand complex clinical reasoning. For this study, we focused on answers from the experts on how clinical reasoning can be supported by population-based Big-Data. We found cognitive strategies such as trajectory tracking, perspective taking, and metacognition has the potential to improve clinicians' cognition to deal with complex problems. These cognitive strategies could be supported by population health data, and all have important implications for the design of Big-Data based decision-support tools that could be embedded in electronic health records. Our findings provide directions for task allocation and design of decision-support applications for health care industry development of Big data based decision-support systems.

Big-Data Based Decision-Support Systems to Improve Clinicians’ Cognition

PubMed Central

Roosan, Don; Samore, Matthew; Jones, Makoto; Livnat, Yarden; Clutter, Justin

2016-01-01

Complex clinical decision-making could be facilitated by using population health data to inform clinicians. In two previous studies, we interviewed 16 infectious disease experts to understand complex clinical reasoning. For this study, we focused on answers from the experts on how clinical reasoning can be supported by population-based Big-Data. We found cognitive strategies such as trajectory tracking, perspective taking, and metacognition has the potential to improve clinicians’ cognition to deal with complex problems. These cognitive strategies could be supported by population health data, and all have important implications for the design of Big-Data based decision-support tools that could be embedded in electronic health records. Our findings provide directions for task allocation and design of decision-support applications for health care industry development of Big data based decision-support systems. PMID:27990498

Data-Driven Decision Making in Out-of-School Time Programs. Part 6 in a Series on Implementing Evidence-Based Practices in Out-of-School Time Programs: The Role of Organization-Level Activities. Research-to-Results Brief. Publication #2009-34

ERIC Educational Resources Information Center

Bandy, Tawana; Burkhauser, Mary; Metz, Allison J. R.

2009-01-01

Although many program managers look to data to inform decision-making and manage their programs, high-quality program data may not always be available. Yet such data are necessary for effective program implementation. The use of high-quality data facilitates program management, reduces reliance on anecdotal information, and ensures that data are…

The Role of Evidence in the Decision-Making Process of Selecting Essential Medicines in Developing Countries: The Case of Tanzania

PubMed Central

Mori, Amani Thomas; Kaale, Eliangiringa Amos; Ngalesoni, Frida; Norheim, Ole Frithjof; Robberstad, Bjarne

2014-01-01

Background Insufficient access to essential medicines is a major health challenge in developing countries. Despite the importance of Standard Treatment Guidelines and National Essential Medicine Lists in facilitating access to medicines, little is known about how they are updated. This study aims to describe the process of updating the Standard Treatment Guidelines and National Essential Medicine List in Tanzania and further examines the criteria and the underlying evidence used in decision-making. Methods This is a qualitative study in which data were collected by in-depth interviews and document reviews. Interviews were conducted with 18 key informants who were involved in updating the Standard Treatment Guidelines and National Essential Medicine List. We used a thematic content approach to analyse the data. Findings The Standard Treatment Guidelines and National Essential Medicine List was updated by committees of experts who were recruited mostly from referral hospitals and the Ministry of Health and Social Welfare. Efficacy, safety, availability and affordability were the most frequently utilised criteria in decision-making, although these were largely based on experience rather than evidence. In addition, recommendations from international guidelines and medicine promotions also influenced decision-making. Cost-effectiveness, despite being an important criterion for formulary decisions, was not utilised. Conclusions Recent decisions about the selection of essential medicines in Tanzania were made by committees of experts who largely used experience and discretionary judgement, leaving evidence with only a limited role in decision-making process. There may be several reasons for the current limited use of evidence in decision-making, but one hypothesis that remains to be explored is whether training experts in evidence-based decision-making would lead to a better and more explicit use of evidence. PMID:24416293

The role of evidence in the decision-making process of selecting essential medicines in developing countries: the case of Tanzania.

PubMed

Mori, Amani Thomas; Kaale, Eliangiringa Amos; Ngalesoni, Frida; Norheim, Ole Frithjof; Robberstad, Bjarne

2014-01-01

Insufficient access to essential medicines is a major health challenge in developing countries. Despite the importance of Standard Treatment Guidelines and National Essential Medicine Lists in facilitating access to medicines, little is known about how they are updated. This study aims to describe the process of updating the Standard Treatment Guidelines and National Essential Medicine List in Tanzania and further examines the criteria and the underlying evidence used in decision-making. This is a qualitative study in which data were collected by in-depth interviews and document reviews. Interviews were conducted with 18 key informants who were involved in updating the Standard Treatment Guidelines and National Essential Medicine List. We used a thematic content approach to analyse the data. The Standard Treatment Guidelines and National Essential Medicine List was updated by committees of experts who were recruited mostly from referral hospitals and the Ministry of Health and Social Welfare. Efficacy, safety, availability and affordability were the most frequently utilised criteria in decision-making, although these were largely based on experience rather than evidence. In addition, recommendations from international guidelines and medicine promotions also influenced decision-making. Cost-effectiveness, despite being an important criterion for formulary decisions, was not utilised. Recent decisions about the selection of essential medicines in Tanzania were made by committees of experts who largely used experience and discretionary judgement, leaving evidence with only a limited role in decision-making process. There may be several reasons for the current limited use of evidence in decision-making, but one hypothesis that remains to be explored is whether training experts in evidence-based decision-making would lead to a better and more explicit use of evidence.

Distance-Based and Distributed Learning: A Decision Tool for Education Leaders.

ERIC Educational Resources Information Center

McGraw, Tammy M.; Ross, John D.

This decision tool presents a progression of data collection and decision-making strategies that can increase the effectiveness of distance-based or distributed learning instruction. A narrative and flow chart cover the following steps: (1) basic assumptions, including purpose of instruction, market scan, and financial resources; (2) needs…

Integrating HL7 RIM and ontology for unified knowledge and data representation in clinical decision support systems.

PubMed

Zhang, Yi-Fan; Tian, Yu; Zhou, Tian-Shu; Araki, Kenji; Li, Jing-Song

2016-01-01

The broad adoption of clinical decision support systems within clinical practice has been hampered mainly by the difficulty in expressing domain knowledge and patient data in a unified formalism. This paper presents a semantic-based approach to the unified representation of healthcare domain knowledge and patient data for practical clinical decision making applications. A four-phase knowledge engineering cycle is implemented to develop a semantic healthcare knowledge base based on an HL7 reference information model, including an ontology to model domain knowledge and patient data and an expression repository to encode clinical decision making rules and queries. A semantic clinical decision support system is designed to provide patient-specific healthcare recommendations based on the knowledge base and patient data. The proposed solution is evaluated in the case study of type 2 diabetes mellitus inpatient management. The knowledge base is successfully instantiated with relevant domain knowledge and testing patient data. Ontology-level evaluation confirms model validity. Application-level evaluation of diagnostic accuracy reaches a sensitivity of 97.5%, a specificity of 100%, and a precision of 98%; an acceptance rate of 97.3% is given by domain experts for the recommended care plan orders. The proposed solution has been successfully validated in the case study as providing clinical decision support at a high accuracy and acceptance rate. The evaluation results demonstrate the technical feasibility and application prospect of our approach. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Integrated Risk-Informed Decision-Making for an ALMR PRISM

DOE Office of Scientific and Technical Information (OSTI.GOV)

Muhlheim, Michael David; Belles, Randy; Denning, Richard S.

Decision-making is the process of identifying decision alternatives, assessing those alternatives based on predefined metrics, selecting an alternative (i.e., making a decision), and then implementing that alternative. The generation of decisions requires a structured, coherent process, or a decision-making process. The overall objective for this work is that the generalized framework is adopted into an autonomous decision-making framework and tailored to specific requirements for various applications. In this context, automation is the use of computing resources to make decisions and implement a structured decision-making process with limited or no human intervention. The overriding goal of automation is to replace ormore » supplement human decision makers with reconfigurable decision-making modules that can perform a given set of tasks rationally, consistently, and reliably. Risk-informed decision-making requires a probabilistic assessment of the likelihood of success given the status of the plant/systems and component health, and a deterministic assessment between plant operating parameters and reactor protection parameters to prevent unnecessary trips and challenges to plant safety systems. The probabilistic portion of the decision-making engine of the supervisory control system is based on the control actions associated with an ALMR PRISM. Newly incorporated into the probabilistic models are the prognostic/diagnostic models developed by Pacific Northwest National Laboratory. These allow decisions to incorporate the health of components into the decision–making process. Once the control options are identified and ranked based on the likelihood of success, the supervisory control system transmits the options to the deterministic portion of the platform. The deterministic portion of the decision-making engine uses thermal-hydraulic modeling and components for an advanced liquid-metal reactor Power Reactor Inherently Safe Module. The deterministic multi-attribute decision-making framework uses various sensor data (e.g., reactor outlet temperature, steam generator drum level) and calculates its position within the challenge state, its trajectory, and its margin within the controllable domain using utility functions to evaluate current and projected plant state space for different control decisions. The metrics that are evaluated are based on reactor trip set points. The integration of the deterministic calculations using multi-physics analyses and probabilistic safety calculations allows for the examination and quantification of margin recovery strategies. This also provides validation of the control options identified from the probabilistic assessment. Thus, the thermalhydraulics analyses are used to validate the control options identified from the probabilistic assessment. Future work includes evaluating other possible metrics and computational efficiencies, and developing a user interface to mimic display panels at a modern nuclear power plant.« less

Mapping Perceptions of Lupus Medication Decision-Making Facilitators: The Importance of Patient Context.

PubMed

Qu, Haiyan; Shewchuk, Richard M; Alarcón, Graciela; Fraenkel, Liana; Leong, Amye; Dall'Era, Maria; Yazdany, Jinoos; Singh, Jasvinder A

2016-12-01

Numerous factors can impede or facilitate patients' medication decision-making and adherence to physicians' recommendations. Little is known about how patients and physicians jointly view issues that affect the decision-making process. Our objective was to derive an empirical framework of patient-identified facilitators to lupus medication decision-making from key stakeholders (including 15 physicians, 5 patients/patient advocates, and 8 medical professionals) using a patient-centered cognitive mapping approach. We used nominal group patient panels to identify facilitators to lupus treatment decision-making. Stakeholders independently sorted the identified facilitators (n = 98) based on their similarities and rated the importance of each facilitator in patient decision-making. Data were analyzed using multidimensional scaling and hierarchical cluster analysis. A cognitive map was derived that represents an empirical framework of facilitators for lupus treatment decisions from multiple stakeholders' perspectives. The facilitator clusters were 1) hope for a normal/healthy life, 2) understand benefits and effectiveness of taking medications, 3) desire to minimize side effects, 4) medication-related data, 5) medication effectiveness for "me," 6) family focus, 7) confidence in physician, 8) medication research, 9) reassurance about medication, and 10) medication economics. Consideration of how different stakeholders perceive the relative importance of lupus medication decision-making clusters is an important step toward improving patient-physician communication and effective shared decision-making. The empirically derived framework of medication decision-making facilitators can be used as a guide to develop a lupus decision aid that focuses on improving physician-patient communication. © 2016, American College of Rheumatology.

The influence of evidence-based medicine training on decision-making in relation to over-the-counter medicines: a qualitative study.

PubMed

Hanna, Lezley-Anne; Hughes, Carmel

2012-12-01

To explore the role of evidence of effectiveness when making decisions about over-the-counter (OTC) medication and to ascertain whether evidence-based medicine training raised awareness in decision-making. Additionally, this work aimed to complement the findings of a previous study because all participants in this current study had received training in evidence-based medicine (unlike the previous participants). Following ethical approval and an e-mailed invitation, face-to-face, semi-structured interviews were conducted with newly registered pharmacists (who had received training in evidence-based medicine as part of their MPharm degree) to discuss the role of evidence of effectiveness with OTC medicines. Interviews were recorded and transcribed verbatim. Following transcription, all data were entered into the NVivo software package (version 8). Data were coded and analysed using a constant comparison approach. Twenty-five pharmacists (7 males and 18 females; registered for less than 4 months) were recruited and all participated in the study. Their primary focus with OTC medicines was safety; sales of products (including those that lack evidence of effectiveness) were justified provided they did no harm. Meeting patient expectation was also an important consideration and often superseded evidence. Despite knowledge of the concept, and an awareness of ethical requirements, an evidence-based approach was not routinely implemented by these pharmacists. Pharmacists did not routinely utilize evidence-based resources when making decisions about OTC medicines and some felt uncomfortable discussing the evidence-base for OTC products with patients. The evidence-based medicine training that these pharmacists received appeared to have limited influence on OTC decision-making. More work could be conducted to ensure that an evidence-based approach is routinely implemented in practice. © 2012 The Authors. IJPP © 2012 Royal Pharmaceutical Society.

How Reasoning, Judgment, and Decision Making are Colored by Gist-based Intuition: A Fuzzy-Trace Theory Approach

PubMed Central

Corbin, Jonathan C.; Reyna, Valerie F.; Weldon, Rebecca B.; Brainerd, Charles J.

2015-01-01

Fuzzy-trace theory distinguishes verbatim (literal, exact) from gist (meaningful) representations, predicting that reliance on gist increases with experience and expertise. Thus, many judgment-and-decision-making biases increase with development, such that cognition is colored by context in ways that violate logical coherence and probability theories. Nevertheless, this increase in gist-based intuition is adaptive: Gist is stable, less sensitive to interference, and easier to manipulate. Moreover, gist captures the functionally significant essence of information, supporting healthier and more robust decision processes. We describe how fuzzy-trace theory accounts for judgment-and-decision making phenomena, predicting the paradoxical arc of these processes with the development of experience and expertise. We present data linking gist memory processes to gist processing in decision making and provide illustrations of gist reliance in medicine, public health, and intelligence analysis. PMID:26664820

How Reasoning, Judgment, and Decision Making are Colored by Gist-based Intuition: A Fuzzy-Trace Theory Approach.

PubMed

Corbin, Jonathan C; Reyna, Valerie F; Weldon, Rebecca B; Brainerd, Charles J

2015-12-01

Fuzzy-trace theory distinguishes verbatim (literal, exact) from gist (meaningful) representations, predicting that reliance on gist increases with experience and expertise. Thus, many judgment-and-decision-making biases increase with development, such that cognition is colored by context in ways that violate logical coherence and probability theories. Nevertheless, this increase in gist-based intuition is adaptive: Gist is stable, less sensitive to interference, and easier to manipulate. Moreover, gist captures the functionally significant essence of information, supporting healthier and more robust decision processes. We describe how fuzzy-trace theory accounts for judgment-and-decision making phenomena, predicting the paradoxical arc of these processes with the development of experience and expertise. We present data linking gist memory processes to gist processing in decision making and provide illustrations of gist reliance in medicine, public health, and intelligence analysis.

Distributed decision making in action: diagnostic imaging investigations within the bigger picture.

PubMed

Makanjee, Chandra R; Bergh, Anne-Marie; Hoffmann, Willem A

2018-03-01

Decision making in the health care system - specifically with regard to diagnostic imaging investigations - occurs at multiple levels. Professional role players from various backgrounds are involved in making these decisions, from the point of referral to the outcomes of the imaging investigation. The aim of this study was to map the decision-making processes and pathways involved when patients are referred for diagnostic imaging investigations and to explore distributed decision-making events at the points of contact with patients within a health care system. A two-phased qualitative study was conducted in an academic public health complex with the district hospital as entry point. The first phase included case studies of 24 conveniently selected patients, and the second phase involved 12 focus group interviews with health care providers. Data analysis was based on Rapley's interpretation of decision making as being distributed across time, situations and actions, and including different role players and technologies. Clinical decisions incorporating imaging investigations are distributed across the three vital points of contact or decision-making events, namely the initial patient consultation, the diagnostic imaging investigation and the post-investigation consultation. Each of these decision-making events is made up of a sequence of discrete decision-making moments based on the transfer of retrospective, current and prospective information and its transformation into knowledge. This paper contributes to the understanding of the microstructural processes (the 'when' and 'where') involved in the distribution of decisions related to imaging investigations. It also highlights the interdependency in decision-making events of medical and non-medical providers within a single medical encounter. © 2017 The Authors. Journal of Medical Radiation Sciences published by John Wiley & Sons Australia, Ltd on behalf of Australian Society of Medical Imaging and Radiation Therapy and New Zealand Institute of Medical Radiation Technology.

How do small groups make decisions? : A theoretical framework to inform the implementation and study of clinical competency committees.

PubMed

Chahine, Saad; Cristancho, Sayra; Padgett, Jessica; Lingard, Lorelei

2017-06-01

In the competency-based medical education (CBME) approach, clinical competency committees are responsible for making decisions about trainees' competence. However, we currently lack a theoretical model for group decision-making to inform this emerging assessment phenomenon. This paper proposes an organizing framework to study and guide the decision-making processes of clinical competency committees.This is an explanatory, non-exhaustive review, tailored to identify relevant theoretical and evidence-based papers related to small group decision-making. The search was conducted using Google Scholar, Web of Science, MEDLINE, ERIC, and PsycINFO for relevant literature. Using a thematic analysis, two researchers (SC & JP) met four times between April-June 2016 to consolidate the literature included in this review.Three theoretical orientations towards group decision-making emerged from the review: schema, constructivist, and social influence. Schema orientations focus on how groups use algorithms for decision-making. Constructivist orientations focus on how groups construct their shared understanding. Social influence orientations focus on how individual members influence the group's perspective on a decision. Moderators of decision-making relevant to all orientations include: guidelines, stressors, authority, and leadership.Clinical competency committees are the mechanisms by which groups of clinicians will be in charge of interpreting multiple assessment data points and coming to a shared decision about trainee competence. The way in which these committees make decisions can have huge implications for trainee progression and, ultimately, patient care. Therefore, there is a pressing need to build the science of how such group decision-making works in practice. This synthesis suggests a preliminary organizing framework that can be used in the implementation and study of clinical competency committees.

CorRECTreatment: A Web-based Decision Support Tool for Rectal Cancer Treatment that Uses the Analytic Hierarchy Process and Decision Tree

PubMed Central

Karakülah, G.; Dicle, O.; Sökmen, S.; Çelikoğlu, C.C.

2015-01-01

Summary Background The selection of appropriate rectal cancer treatment is a complex multi-criteria decision making process, in which clinical decision support systems might be used to assist and enrich physicians’ decision making. Objective The objective of the study was to develop a web-based clinical decision support tool for physicians in the selection of potentially beneficial treatment options for patients with rectal cancer. Methods The updated decision model contained 8 and 10 criteria in the first and second steps respectively. The decision support model, developed in our previous study by combining the Analytic Hierarchy Process (AHP) method which determines the priority of criteria and decision tree that formed using these priorities, was updated and applied to 388 patients data collected retrospectively. Later, a web-based decision support tool named corRECTreatment was developed. The compatibility of the treatment recommendations by the expert opinion and the decision support tool was examined for its consistency. Two surgeons were requested to recommend a treatment and an overall survival value for the treatment among 20 different cases that we selected and turned into a scenario among the most common and rare treatment options in the patient data set. Results In the AHP analyses of the criteria, it was found that the matrices, generated for both decision steps, were consistent (consistency ratio<0.1). Depending on the decisions of experts, the consistency value for the most frequent cases was found to be 80% for the first decision step and 100% for the second decision step. Similarly, for rare cases consistency was 50% for the first decision step and 80% for the second decision step. Conclusions The decision model and corRECTreatment, developed by applying these on real patient data, are expected to provide potential users with decision support in rectal cancer treatment processes and facilitate them in making projections about treatment options. PMID:25848413

CorRECTreatment: a web-based decision support tool for rectal cancer treatment that uses the analytic hierarchy process and decision tree.

PubMed

Suner, A; Karakülah, G; Dicle, O; Sökmen, S; Çelikoğlu, C C

2015-01-01

The selection of appropriate rectal cancer treatment is a complex multi-criteria decision making process, in which clinical decision support systems might be used to assist and enrich physicians' decision making. The objective of the study was to develop a web-based clinical decision support tool for physicians in the selection of potentially beneficial treatment options for patients with rectal cancer. The updated decision model contained 8 and 10 criteria in the first and second steps respectively. The decision support model, developed in our previous study by combining the Analytic Hierarchy Process (AHP) method which determines the priority of criteria and decision tree that formed using these priorities, was updated and applied to 388 patients data collected retrospectively. Later, a web-based decision support tool named corRECTreatment was developed. The compatibility of the treatment recommendations by the expert opinion and the decision support tool was examined for its consistency. Two surgeons were requested to recommend a treatment and an overall survival value for the treatment among 20 different cases that we selected and turned into a scenario among the most common and rare treatment options in the patient data set. In the AHP analyses of the criteria, it was found that the matrices, generated for both decision steps, were consistent (consistency ratio<0.1). Depending on the decisions of experts, the consistency value for the most frequent cases was found to be 80% for the first decision step and 100% for the second decision step. Similarly, for rare cases consistency was 50% for the first decision step and 80% for the second decision step. The decision model and corRECTreatment, developed by applying these on real patient data, are expected to provide potential users with decision support in rectal cancer treatment processes and facilitate them in making projections about treatment options.

Factors influencing the clinical decision-making of midwives: a qualitative study.

PubMed

Daemers, Darie O A; van Limbeek, Evelien B M; Wijnen, Hennie A A; Nieuwenhuijze, Marianne J; de Vries, Raymond G

2017-10-06

Although midwives make clinical decisions that have an impact on the health and well-being of mothers and babies, little is known about how they make those decisions. Wide variation in intrapartum decisions to refer women to obstetrician-led care suggests that midwives' decisions are based on more than the evidence based medicine (EBM) model - i.e. clinical evidence, midwife's expertise, and woman's values - alone. With this study we aimed to explore the factors that influence clinical decision-making of midwives who work independently. We used a qualitative approach, conducting in-depth interviews with a purposive sample of 11 Dutch primary care midwives. Data collection took place between May and September 2015. The interviews were semi-structured, using written vignettes to solicit midwives' clinical decision-making processes (Think Aloud method). We performed thematic analysis on the transcripts. We identified five themes that influenced clinical decision-making: the pregnant woman as a whole person, sources of knowledge, the midwife as a whole person, the collaboration between maternity care professionals, and the organisation of care. Regarding the midwife, her decisions were shaped not only by her experience, intuition, and personal circumstances, but also by her attitudes about physiology, woman-centredness, shared decision-making, and collaboration with other professionals. The nature of the local collaboration between maternity care professionals and locally-developed protocols dominated midwives' clinical decision-making. When midwives and obstetricians had different philosophies of care and different practice styles, their collaborative efforts were challenged. Midwives' clinical decision-making is a more varied and complex process than the EBM framework suggests. If midwives are to succeed in their role as promoters and protectors of physiological pregnancy and birth, they need to understand how clinical decisions in a multidisciplinary context are actually made.

The Research of Spatial-Temporal Analysis and Decision-Making Assistant System for Disabled Person Affairs Based on Mapworld

NASA Astrophysics Data System (ADS)

Zhang, J. H.; Yang, J.; Sun, Y. S.

2015-06-01

This system combines the Mapworld platform and informationization of disabled person affairs, uses the basic information of disabled person as center frame. Based on the disabled person population database, the affairs management system and the statistical account system, the data were effectively integrated and the united information resource database was built. Though the data analysis and mining, the system provides powerful data support to the decision making, the affairs managing and the public serving. It finally realizes the rationalization, normalization and scientization of disabled person affairs management. It also makes significant contributions to the great-leap-forward development of the informationization of China Disabled Person's Federation.

Effect of training problem-solving skill on decision-making and critical thinking of personnel at medical emergencies

PubMed Central

Heidari, Mohammad; Shahbazi, Sara

2016-01-01

Background: The aim of this study was to determine the effect of problem-solving training on decision-making skill and critical thinking in emergency medical personnel. Materials and Methods: This study is an experimental study that performed in 95 emergency medical personnel in two groups of control (48) and experimental (47). Then, a short problem-solving course based on 8 sessions of 2 h during the term, was performed for the experimental group. Of data gathering was used demographic and researcher made decision-making and California critical thinking skills questionnaires. Data were analyzed using SPSS software. Results: The finding revealed that decision-making and critical thinking score in emergency medical personnel are low and problem-solving course, positively affected the personnel’ decision-making skill and critical thinking after the educational program (P < 0.05). Conclusions: Therefore, this kind of education on problem-solving in various emergency medicine domains such as education, research, and management, is recommended. PMID:28149823

The Importance Of Integrating Narrative Into Health Care Decision Making.

PubMed

Dohan, Daniel; Garrett, Sarah B; Rendle, Katharine A; Halley, Meghan; Abramson, Corey

2016-04-01

When making health care decisions, patients and consumers use data but also gather stories from family and friends. When advising patients, clinicians consult the medical evidence but also use professional judgment. These stories and judgments, as well as other forms of narrative, shape decision making but remain poorly understood. Furthermore, qualitative research methods to examine narrative are rarely included in health science research. We illustrate how narratives shape decision making and explain why it is difficult but necessary to integrate qualitative research on narrative into the health sciences. We draw on social-scientific insights on rigorous qualitative research and our ongoing studies of decision making by patients with cancer, and we describe new tools and approaches that link qualitative research findings with the predominantly quantitative health science scholarship. Finally, we highlight the benefits of more fully integrating qualitative research and narrative analysis into the medical evidence base and into evidence-based medical practice. Project HOPE—The People-to-People Health Foundation, Inc.

[Big data analysis and evidence-based medicine: controversy or cooperation].

PubMed

Chen, Xinzu; Hu, Jiankun

2016-01-01

The development of evidence-based medicince should be an important milestone from the empirical medicine to the evidence-driving modern medicine. With the outbreak in biomedical data, the rising big data analysis can efficiently solve exploratory questions or decision-making issues in biomedicine and healthcare activities. The current problem in China is that big data analysis is still not well conducted and applied to deal with problems such as clinical decision-making, public health policy, and should not be a debate whether big data analysis can replace evidence-based medicine or not. Therefore, we should clearly understand, no matter whether evidence-based medicine or big data analysis, the most critical infrastructure must be the substantial work in the design, constructure and collection of original database in China.

Investigating the Decision-Making of Response to Intervention (RtI) Teams within the School Setting

ERIC Educational Resources Information Center

Thur, Scott M.

2015-01-01

The purpose of this study was to measure decision-making influences within RtI teams. The study examined the factors that influence school personnel involved in three areas of RtI: determining which RtI measures and tools teams select and implement (i.e. Measures and Tools), evaluating the data-driven decisions that are made based on the…

Value-based attentional capture influences context-dependent decision-making

PubMed Central

Cha, Kexin; Rangsipat, Napat; Serences, John T.

2015-01-01

Normative theories posit that value-based decision-making is context independent. However, decisions between two high-value options can be suboptimally biased by the introduction of a third low-value option. This context-dependent modulation is consistent with the divisive normalization of the value of each stimulus by the total value of all stimuli. In addition, an independent line of research demonstrates that pairing a stimulus with a high-value outcome can lead to attentional capture that can mediate the efficiency of visual information processing. Here we tested the hypothesis that value-based attentional capture interacts with value-based normalization to influence the optimality of decision-making. We used a binary-choice paradigm in which observers selected between two targets and the color of each target indicated the magnitude of their reward potential. Observers also had to simultaneously ignore a task-irrelevant distractor rendered in a color that was previously associated with a specific reward magnitude. When the color of the task-irrelevant distractor was previously associated with a high reward, observers responded more slowly and less optimally. Moreover, as the learned value of the distractor increased, electrophysiological data revealed an attenuation of the lateralized N1 and N2Pc responses evoked by the relevant choice stimuli and an attenuation of the late positive deflection (LPD). Collectively, these behavioral and electrophysiological data suggest that value-based attentional capture and value-based normalization jointly mediate the influence of context on free-choice decision-making. PMID:25995350

Value-based attentional capture influences context-dependent decision-making.

PubMed

Itthipuripat, Sirawaj; Cha, Kexin; Rangsipat, Napat; Serences, John T

2015-07-01

Normative theories posit that value-based decision-making is context independent. However, decisions between two high-value options can be suboptimally biased by the introduction of a third low-value option. This context-dependent modulation is consistent with the divisive normalization of the value of each stimulus by the total value of all stimuli. In addition, an independent line of research demonstrates that pairing a stimulus with a high-value outcome can lead to attentional capture that can mediate the efficiency of visual information processing. Here we tested the hypothesis that value-based attentional capture interacts with value-based normalization to influence the optimality of decision-making. We used a binary-choice paradigm in which observers selected between two targets and the color of each target indicated the magnitude of their reward potential. Observers also had to simultaneously ignore a task-irrelevant distractor rendered in a color that was previously associated with a specific reward magnitude. When the color of the task-irrelevant distractor was previously associated with a high reward, observers responded more slowly and less optimally. Moreover, as the learned value of the distractor increased, electrophysiological data revealed an attenuation of the lateralized N1 and N2Pc responses evoked by the relevant choice stimuli and an attenuation of the late positive deflection (LPD). Collectively, these behavioral and electrophysiological data suggest that value-based attentional capture and value-based normalization jointly mediate the influence of context on free-choice decision-making. Copyright © 2015 the American Physiological Society.

Research-based-decision-making in Canadian health organizations: a behavioural approach.

PubMed

Jbilou, Jalila; Amara, Nabil; Landry, Réjean

2007-06-01

Decision making in Health sector is affected by a several elements such as economic constraints, political agendas, epidemiologic events, managers' values and environment... These competing elements create a complex environment for decision making. Research-Based-Decision-Making (RBDM) offers an opportunity to reduce the generated uncertainty and to ensure efficacy and efficiency in health administrations. We assume that RBDM is dependant on decision makers' behaviour and the identification of the determinants of this behaviour can help to enhance research results utilization in health sector decision making. This paper explores the determinants of RBDM as a personal behaviour among managers and professionals in health administrations in Canada. From the behavioural theories and the existing literature, we build a model measuring "RBDM" as an index based on five items. These items refer to the steps accomplished by a decision maker while developing a decision which is based on evidence. The determinants of RBDM behaviour are identified using data collected from 942 health care decision makers in Canadian health organizations. Linear regression is used to model the behaviour RBDM. Determinants of this behaviour are derived from Triandis Theory and Bandura's construct "self-efficacy." The results suggest that to improve research use among managers in Canadian governmental health organizations, strategies should focus on enhancing exposition to evidence through facilitating communication networks, partnerships and links between researchers and decision makers, with the key long-term objective of developing a culture that supports and values the contribution that research can make to decision making in governmental health organizations. Nevertheless, depending on the organizational level, determinants of RBDM are different. This difference has to be taken into account if RBDM adoption is desired. Decision makers in Canadian health organizations (CHO) can help to build networks, develop partnerships between professionals locally, regionally and nationally, and also act as change agents in the dissemination and adoption of knowledge and innovations in health services. However, the research focused on knowledge use as a support to decision-making, further research is needed to identify and evaluate effective incentives and strategies to implement so as to enhance RBDM adoption among health decision makers and more theoretical development are to complete in this perspective.

Social Capital in Data-Driven Community College Reform

ERIC Educational Resources Information Center

Kerrigan, Monica Reid

2015-01-01

The current rhetoric around using data to improve community college student outcomes with only limited research on data-driven decision-making (DDDM) within postsecondary education compels a more comprehensive understanding of colleges' capacity for using data to inform decisions. Based on an analysis of faculty and administrators' perceptions and…

Opioid Modulation of Value-Based Decision-Making in Healthy Humans.

PubMed

Eikemo, Marie; Biele, Guido; Willoch, Frode; Thomsen, Lotte; Leknes, Siri

2017-08-01

Modifying behavior to maximize reward is integral to adaptive decision-making. In rodents, the μ-opioid receptor (MOR) system encodes motivation and preference for high-value rewards. Yet it remains unclear whether and how human MORs contribute to value-based decision-making. We reasoned that if the human MOR system modulates value-based choice, this would be reflected by opposite effects of agonist and antagonist drugs. In a double-blind pharmacological cross-over study, 30 healthy men received morphine (10 mg), placebo, and the opioid antagonist naltrexone (50 mg). They completed a two-alternative decision-making task known to induce a considerable bias towards the most frequently rewarded response option. To quantify MOR involvement in this bias, we fitted accuracy and reaction time data with the drift-diffusion model (DDM) of decision-making. The DDM analysis revealed the expected bidirectional drug effects for two decision subprocesses. MOR stimulation with morphine increased the preference for the stimulus with high-reward probability (shift in starting point). Compared to placebo, morphine also increased, and naltrexone reduced, the efficiency of evidence accumulation. Since neither drug affected motor-coordination, speed-accuracy trade-off, or subjective state (indeed participants were still blinded after the third session), we interpret the MOR effects on evidence accumulation efficiency as a consequence of changes in effort exerted in the task. Together, these findings support a role for the human MOR system in value-based choice by tuning decision-making towards high-value rewards across stimulus domains.

Data Use by Teachers: The Impact of Motivation, Decision-Making Style, Supportive Relationships and Reflective Capacity

ERIC Educational Resources Information Center

Vanlommel, Kristin; Vanhoof, Jan; Van Petegem, Peter

2016-01-01

There is a growing expectation that schools should systematically collect and analyse data as a point of departure for decisions. However, research shows that teachers themselves are less convinced that they need to base their decisions on data, as they mainly rely on their intuition and experience. This article examines the extent to which…

The Impact of Multifaceted Osteoporosis Group Education on Patients' Decision-Making regarding Treatment Options and Lifestyle Changes.

PubMed

Jensen, Annesofie L; Wind, Gitte; Langdahl, Bente Lomholt; Lomborg, Kirsten

2018-01-01

Patients with chronic diseases like osteoporosis constantly have to make decisions related to their disease. Multifaceted osteoporosis group education (GE) may support patients' decision-making. This study investigated multifaceted osteoporosis GE focusing on the impact of GE on patients' decision-making related to treatment options and lifestyle. An interpretive description design using ethnographic methods was utilized with 14 women and three men diagnosed with osteoporosis who attended multifaceted GE. Data consisted of participant observation during GE and individual interviews. Attending GE had an impact on the patients' decision-making in all educational themes. Patients decided on new ways to manage osteoporosis and made decisions regarding bone health and how to implement a lifestyle ensuring bone health. During GE, teachers and patients shared evidence-based knowledge and personal experiences and preferences, respectively, leading to a two-way exchange of information and deliberation about recommendations. Though teachers and patients explored the implications of the decisions and shared their preferences, teachers stressed that the patients ultimately had to make the decision. Teachers therefore refrained from participating in the final step of the decision-making process. Attending GE has an impact on the patients' decision-making as it can initiate patient reflection and support decision-making.

[A study on participation in clinical decision making by home healthcare nurses].

PubMed

Kim, Se Young

2010-12-01

This study was done to identify participation by home healthcare nurses in clinical decision making and factors influencing clinical decision making. A descriptive survey was used to collect data from 68 home healthcare nurses in 22 hospital-based home healthcare services in Korea. To investigate participation, the researcher developed 3 scenarios through interviews with 5 home healthcare nurses. A self-report questionnaire composed of tools for characteristics, factors of clinical decision making, and participation was used. Participation was relatively high, but significantly lower in the design phase (F=3.51, p=.032). Competency in clinical decision making (r=.45, p<.001), perception of the decision maker role (r=.47, p<.001), and perception of the utility of clinical practice guidelines (r=.25, p=.043) were significantly correlated with participation. Competency in clinical decision making (Odds ratio [OR]=41.79, p=.007) and perception of the decision maker role (OR=15.09, p=.007) were significant factors predicting participation in clinical decision making by home healthcare nurses. In order to encourage participation in clinical decision making, education programs should be provided to home healthcare nurses. Official clinical practice guidelines should be used to support home healthcare nurses' participation in clinical decision making in cases where they can identify and solve the patient health problems.

Impaired decision-making and brain shrinkage in alcoholism.

PubMed

Le Berre, A-P; Rauchs, G; La Joie, R; Mézenge, F; Boudehent, C; Vabret, F; Segobin, S; Viader, F; Allain, P; Eustache, F; Pitel, A-L; Beaunieux, H

2014-03-01

Alcohol-dependent individuals usually favor instant gratification of alcohol use and ignore its long-term negative consequences, reflecting impaired decision-making. According to the somatic marker hypothesis, decision-making abilities are subtended by an extended brain network. As chronic alcohol consumption is known to be associated with brain shrinkage in this network, the present study investigated relationships between brain shrinkage and decision-making impairments in alcohol-dependent individuals early in abstinence using voxel-based morphometry. Thirty patients performed the Iowa Gambling Task and underwent a magnetic resonance imaging investigation (1.5T). Decision-making performances and brain data were compared with those of age-matched healthy controls. In the alcoholic group, a multiple regression analysis was conducted with two predictors (gray matter [GM] volume and decision-making measure) and two covariates (number of withdrawals and duration of alcoholism). Compared with controls, alcoholics had impaired decision-making and widespread reduced gray matter volume, especially in regions involved in decision-making. The regression analysis revealed links between high GM volume in the ventromedial prefrontal cortex, dorsal anterior cingulate cortex and right hippocampal formation, and high decision-making scores (P<0.001, uncorrected). Decision-making deficits in alcoholism may result from impairment of both emotional and cognitive networks. Copyright © 2012 Elsevier Masson SAS. All rights reserved.

The Impact of Health and Financial Literacy on Decision Making in Community-Based Older Adults

PubMed Central

James, Bryan D.; Boyle, Patricia A.; Bennett, Jarred S.; Bennett, David A.

2012-01-01

Background Health and financial literacy have been linked to the health and well-being of older adults, yet there are few data on how health and financial literacy actually impact decision making regarding healthcare and economic choices in advanced age. Objective To examine the association of health and financial literacy with decision making in older adults. Method Data came from 525 community-dwelling older persons without dementia from the Rush Memory and Aging Project, an ongoing longitudinal study of aging. Health and financial literacy were assessed via a series of questions designed to measure comprehension of health and financial information and concepts. The two scores were averaged to yield a total literacy score. A modified, 12-item version of the Decision-Making Competence Assessment Tool was used to measure financial and healthcare decision making (6 items each), using materials designed to approximate those used in real world settings. All 12 items were summed to yield a total decision-making score. Associations were tested via linear regression models adjusted for age, sex and education. Secondary models adjusted for global cognitive function, income, depression and chronic medical conditions. Results On average, participants correctly answered 67% of the literacy questions (health literacy = 61.6%, SD = 18.8% and financial literacy = 72.5%, SD = 16.0%). After adjustment for cognitive function, the total literacy score was positively associated with the decision-making total score (estimate = 0.64, SE = 0.08, p < 0.001), as well as healthcare (estimate = 0.37, SE = 0.5, p < 0.001) and financial decision making (estimate = 0.28, SE = 0.05, p < 0.001). Further, total literacy, health and financial literacy all were independently associated with decision making in models adjusted for covariates including income, depression, and chronic medical conditions (all p values < 0.001). Finally, there was evidence of effect modification such that the beneficial association between literacy and healthcare decision making was stronger among older persons, poorer persons and persons at the lower ranges of cognitive ability. Conclusion Among community based older persons without dementia, higher levels of health and financial literacy were associated with better decision making, suggesting that improvements in literacy could facilitate better decision making and lead to better health and quality of life in later years. PMID:22739454

The impact of health and financial literacy on decision making in community-based older adults.

PubMed

James, Bryan D; Boyle, Patricia A; Bennett, Jarred S; Bennett, David A

2012-01-01

Health and financial literacy have been linked to the health and well-being of older adults, yet there are few data on how health and financial literacy actually impact decision making regarding healthcare and economic choices in advanced age. To examine the association of health and financial literacy with decision making in older adults. Data came from 525 community-dwelling older persons without dementia from the Rush Memory and Aging Project, an ongoing longitudinal study of aging. Health and financial literacy were assessed via a series of questions designed to measure comprehension of health and financial information and concepts. The two scores were averaged to yield a total literacy score. A modified, 12-item version of the Decision-Making Competence Assessment Tool was used to measure financial and healthcare decision making (6 items each), using materials designed to approximate those used in real world settings. All 12 items were summed to yield a total decision-making score. Associations were tested via linear regression models adjusted for age, sex and education. Secondary models adjusted for global cognitive function, income, depression and chronic medical conditions. On average, participants correctly answered 67% of the literacy questions (health literacy = 61.6%, SD = 18.8% and financial literacy = 72.5%, SD = 16.0%). After adjustment for cognitive function, the total literacy score was positively associated with the decision-making total score (estimate = 0.64, SE = 0.08, p < 0.001), as well as healthcare (estimate = 0.37, SE = 0.5, p < 0.001) and financial decision making (estimate = 0.28, SE = 0.05, p < 0.001). Further, total literacy, health and financial literacy all were independently associated with decision making in models adjusted for covariates including income, depression, and chronic medical conditions (all p values < 0.001). Finally, there was evidence of effect modification such that the beneficial association between literacy and healthcare decision making was stronger among older persons, poorer persons and persons at the lower ranges of cognitive ability. Among community based older persons without dementia, higher levels of health and financial literacy were associated with better decision making, suggesting that improvements in literacy could facilitate better decision making and lead to better health and quality of life in later years. Copyright © 2012 S. Karger AG, Basel.

Toward Accountable Discrimination-Aware Data Mining: The Importance of Keeping the Human in the Loop-and Under the Looking Glass.

PubMed

Berendt, Bettina; Preibusch, Sören

2017-06-01

"Big Data" and data-mined inferences are affecting more and more of our lives, and concerns about their possible discriminatory effects are growing. Methods for discrimination-aware data mining and fairness-aware data mining aim at keeping decision processes supported by information technology free from unjust grounds. However, these formal approaches alone are not sufficient to solve the problem. In the present article, we describe reasons why discrimination with data can and typically does arise through the combined effects of human and machine-based reasoning, and argue that this requires a deeper understanding of the human side of decision-making with data mining. We describe results from a large-scale human-subjects experiment that investigated such decision-making, analyzing the reasoning that participants reported during their task to assess whether a loan request should or would be granted. We derive data protection by design strategies for making decision-making discrimination-aware in an accountable way, grounding these requirements in the accountability principle of the European Union General Data Protection Regulation, and outline how their implementations can integrate algorithmic, behavioral, and user interface factors.

Medical Decision-Making Among Adolescents with Neonatal Brachial Plexus Palsy and their Families: A Qualitative Study

PubMed Central

Squitieri, Lee; Larson, Bradley P.; Chang, Kate W-C; Yang, Lynda J-S.; Chung, Kevin C.

2016-01-01

Background Elective surgical management of neonatal brachial plexus palsy is complex, variable, and often individualized. Little is known about the medical decision-making process among adolescents with NBPP and their families faced with making complex treatment decisions. The experiences of these patients and their parents were analyzed to identify key factors in the decision-making process. Patients and Methods Eighteen adolescents with residual NBPP deficits between the ages of 10 to 17 years along with their parents were included in the present study. A qualitative research design was employed involving the use of separate one hour, in person, semi-structured interviews, which were audio recorded and transcribed. Grounded theory was applied by two independent members of the research team to identify recurrent themes and ultimately create a codebook that was then applied to the data. Results Medical decision-making among adolescents with NBPP and their families is multifaceted and individualized, comprised of both patient and system dependent factors. Four codes pertaining to the medical decision-making process were identified: 1) knowledge acquisition, 2) multidisciplinary care, 3) adolescent autonomy, and 4) patient expectations and treatment desires. Overall, parental decision-making was heavily influenced by system dependent factors, while adolescents largely based their medical decision-making on individual treatment desires to improve function and/or aesthetics. Conclusions There are many areas for improving the delivery of information and health care organization among adolescents with NBPP and their families. We recommend the development of educational interdisciplinary programs and decision aids containing evidence-based management guidelines targeted toward primary care providers and patients. We believe that a computer-based learning module may provide the best avenue to achieve maximum penetrance and convenience of information sharing. PMID:23714810

Understanding decision-making towards housework among women with upper limb repetitive strain injury.

PubMed

Cheung, Therma W C; Clemson, Lindy; O'Loughlin, Kate; Shuttleworth, Russell

2016-02-01

Among women with upper limb repetitive strain injury (RSI), occupational therapy interventions include education to facilitate ergonomic practices in housework. From a client-centred perspective, an understanding of women's decision-making about housework is needed to design effective occupational therapy programmes. This study addresses a gap in research in this area by exploring women's views about changing housework habits. The aim was to construct a conceptual representation to explain decision-making in housework by drawing on experiences of a sample of Singapore Chinese women with upper limb RSI from one hand therapy clinic. Based on a constructivist grounded theory methodology, data were collected through in-depth interviewing with 15 women. Interviews were audiotaped and transcribed. Data were analysed with line by line coding, focussed coding and axial coding with constant comparison throughout data collection. Decision-making in housework among these women involved three main themes: (i) emotional attachment to housework; (ii) cognitively informed decision; and (iii) emotionally influenced decision. Women with upper limb RSI had to make cognitive decisions for or against a change in housework to manage their condition. However, the women's cognitively informed decisions were shaped by their emotional attachment to housework. As such, they experienced strong emotional barriers to changing their housework practices even when they had cognitively accepted the necessity and possibility of making a change. Therapists need to be aware that counselling to address the emotional barriers experienced by women is important during ergonomic education. © 2016 Occupational Therapy Australia.

The decision-making matrix of propensity to outsourcing hospital services in Bandar Abbas, Iran.

PubMed

Hayati, Ramin; Setoodehzadeh, Fateme; Heydarvand, Sanaz; Khammarnia, Mohammad; Ravangard, Ramin; Sadeghi, Ahmad; Sobhani, Ghasem

2015-12-01

To determine the level of managers' propensity for outsourcing the services in hospitals using decision-making matrix. The applied, cross-sectional study was conducted at three hospitals affiliated to Bandar Abbas University of Medical Sciences, Iran, in 2013, and comprised managers and employees of four service units: radiology, laboratory, nursing, and nutrition services. Data was collected using two questionnaires and face-to-face interviews. Data was analysed using SPSS 16 and by using decision-making matrix. Of the 122 subjects in the study, 12(9.8%) were managers and 110(90.2%) were other employees. The highest and lowest propensities for outsourcing were related to nutrition (66.6%) and nursing services one (8.33%). The decision-making matrix showed low outsourcing of the nursing, radiology, and laboratory services based on the services' features. However, there were difference between the results obtained from laboratory service decision-making matrix and the propensity for laboratory service outsourcing. The difference between the results obtained from the matrix and managers' viewpoint can be due to the lack of managers' sufficient attention to the features of hospital services when making decisions on outsourcing them.

An Analysis of the Associations among Cognitive Impulsiveness, Reasoning Process, and Rational Decision Making

PubMed Central

Jelihovschi, Ana P. G.; Cardoso, Ricardo L.; Linhares, Alexandre

2018-01-01

Impulsivity may lead to several unfortunate consequences and maladaptive behaviors for both clinical and nonclinical people. It has a key role in many forms of psychopathology. Although literature has discussed the negative impact of impulsivity, few have emphasized the relationship between cognitive impulsiveness and decision making. The aim of this study is to investigate the effects of cognitive impulsiveness on decision making and explore the strategies used by participants to solve problems. For this purpose, we apply two measures of impulsivity: the self-report Barratt Impulsiveness Scale (BIS-11) and the performance based Cognitive Reflection Test (CRT). Moreover, we evaluate participants' reasoning processes employed to answer CRT questions based on the calculation expressions, data organization, and erasures they made while answering the CRT (note that we utilized the instruments using pen and paper). These reasoning processes are related to the role of executive functions in decision making, and its relationship with impulsiveness. The sample consists of 191 adults, who were either professionals or undergraduate students from the fields of business, management, or accounting. The results show that cognitive impulsiveness may negatively affect decision making, and that those who presented the calculation to answer the CRT questions made better decisions. Moreover, there was no difference in the strategies used by impulsive vs. nonimpulsive participants during decision making. Finally, people who inhibited their immediate answers to CRT questions performed better during decision making. PMID:29375440

An Analysis of the Associations among Cognitive Impulsiveness, Reasoning Process, and Rational Decision Making.

PubMed

Jelihovschi, Ana P G; Cardoso, Ricardo L; Linhares, Alexandre

2017-01-01

Impulsivity may lead to several unfortunate consequences and maladaptive behaviors for both clinical and nonclinical people. It has a key role in many forms of psychopathology. Although literature has discussed the negative impact of impulsivity, few have emphasized the relationship between cognitive impulsiveness and decision making. The aim of this study is to investigate the effects of cognitive impulsiveness on decision making and explore the strategies used by participants to solve problems. For this purpose, we apply two measures of impulsivity: the self-report Barratt Impulsiveness Scale (BIS-11) and the performance based Cognitive Reflection Test (CRT). Moreover, we evaluate participants' reasoning processes employed to answer CRT questions based on the calculation expressions, data organization, and erasures they made while answering the CRT (note that we utilized the instruments using pen and paper). These reasoning processes are related to the role of executive functions in decision making, and its relationship with impulsiveness. The sample consists of 191 adults, who were either professionals or undergraduate students from the fields of business, management, or accounting. The results show that cognitive impulsiveness may negatively affect decision making, and that those who presented the calculation to answer the CRT questions made better decisions. Moreover, there was no difference in the strategies used by impulsive vs. nonimpulsive participants during decision making. Finally, people who inhibited their immediate answers to CRT questions performed better during decision making.

Development of an evidence-based decision pathway for vestibular schwannoma treatment options.

PubMed

Linkov, Faina; Valappil, Benita; McAfee, Jacob; Goughnour, Sharon L; Hildrew, Douglas M; McCall, Andrew A; Linkov, Igor; Hirsch, Barry; Snyderman, Carl

To integrate multiple sources of clinical information with patient feedback to build evidence-based decision support model to facilitate treatment selection for patients suffering from vestibular schwannomas (VS). This was a mixed methods study utilizing focus group and survey methodology to solicit feedback on factors important for making treatment decisions among patients. Two 90-minute focus groups were conducted by an experienced facilitator. Previously diagnosed VS patients were recruited by clinical investigators at the University of Pittsburgh Medical Center (UPMC). Classical content analysis was used for focus group data analysis. Providers were recruited from practices within the UPMC system and were surveyed using Delphi methods. This information can provide a basis for multi-criteria decision analysis (MCDA) framework to develop a treatment decision support system for patients with VS. Eight themes were derived from these data (focus group + surveys): doctor/health care system, side effects, effectiveness of treatment, anxiety, mortality, family/other people, quality of life, and post-operative symptoms. These data, as well as feedback from physicians were utilized in building a multi-criteria decision model. The study illustrated steps involved in the development of a decision support model that integrates evidence-based data and patient values to select treatment alternatives. Studies focusing on the actual development of the decision support technology for this group of patients are needed, as decisions are highly multifactorial. Such tools have the potential to improve decision making for complex medical problems with alternate treatment pathways. Copyright © 2016 Elsevier Inc. All rights reserved.

Real-Time Analysis of a Sensor's Data for Automated Decision Making in an IoT-Based Smart Home.

PubMed

Khan, Nida Saddaf; Ghani, Sayeed; Haider, Sajjad

2018-05-25

IoT devices frequently generate large volumes of streaming data and in order to take advantage of this data, their temporal patterns must be learned and identified. Streaming data analysis has become popular after being successfully used in many applications including forecasting electricity load, stock market prices, weather conditions, etc. Artificial Neural Networks (ANNs) have been successfully utilized in understanding the embedded interesting patterns/behaviors in the data and forecasting the future values based on it. One such pattern is modelled and learned in the present study to identify the occurrence of a specific pattern in a Water Management System (WMS). This prediction aids in making an automatic decision support system, to switch OFF a hydraulic suction pump at the appropriate time. Three types of ANN, namely Multi-Input Multi-Output (MIMO), Multi-Input Single-Output (MISO), and Recurrent Neural Network (RNN) have been compared, for multi-step-ahead forecasting, on a sensor's streaming data. Experiments have shown that RNN has the best performance among three models and based on its prediction, a system can be implemented to make the best decision with 86% accuracy.

Launching a virtual decision lab: development and field-testing of a web-based patient decision support research platform.

PubMed

Hoffman, Aubri S; Llewellyn-Thomas, Hilary A; Tosteson, Anna N A; O'Connor, Annette M; Volk, Robert J; Tomek, Ivan M; Andrews, Steven B; Bartels, Stephen J

2014-12-12

Over 100 trials show that patient decision aids effectively improve patients' information comprehension and values-based decision making. However, gaps remain in our understanding of several fundamental and applied questions, particularly related to the design of interactive, personalized decision aids. This paper describes an interdisciplinary development process for, and early field testing of, a web-based patient decision support research platform, or virtual decision lab, to address these questions. An interdisciplinary stakeholder panel designed the web-based research platform with three components: a) an introduction to shared decision making, b) a web-based patient decision aid, and c) interactive data collection items. Iterative focus groups provided feedback on paper drafts and online prototypes. A field test assessed a) feasibility for using the research platform, in terms of recruitment, usage, and acceptability; and b) feasibility of using the web-based decision aid component, compared to performance of a videobooklet decision aid in clinical care. This interdisciplinary, theory-based, patient-centered design approach produced a prototype for field-testing in six months. Participants (n = 126) reported that: the decision aid component was easy to use (98%), information was clear (90%), the length was appropriate (100%), it was appropriately detailed (90%), and it held their interest (97%). They spent a mean of 36 minutes using the decision aid and 100% preferred using their home/library computer. Participants scored a mean of 75% correct on the Decision Quality, Knowledge Subscale, and 74 out of 100 on the Preparation for Decision Making Scale. Completing the web-based decision aid reduced mean Decisional Conflict scores from 31.1 to 19.5 (p < 0.01). Combining decision science and health informatics approaches facilitated rapid development of a web-based patient decision support research platform that was feasible for use in research studies in terms of recruitment, acceptability, and usage. Within this platform, the web-based decision aid component performed comparably with the videobooklet decision aid used in clinical practice. Future studies may use this interactive research platform to study patients' decision making processes in real-time, explore interdisciplinary approaches to designing web-based decision aids, and test strategies for tailoring decision support to meet patients' needs and preferences.

Using Office Discipline Referral Data for Decision Making about Student Behavior in Elementary and Middle Schools: An Empirical Evaluation of Validity

ERIC Educational Resources Information Center

Irvin, Larry K.; Horner, Robert H.; Ingram, Kimberly; Todd, Anne W.; Sugai, George; Sampson, Nadia Katul; Boland, Joseph B.

2006-01-01

In this evaluation we used Messick's construct validity as a conceptual framework for an empirical study assessing the validity of use, utility, and impact of office discipline referral (ODR) measures for data-based decision making about student behavior in schools. The Messick approach provided a rubric for testing the fit of our theory of use of…

Teachers' Experiences with the Data-Driven Decision Making Process in Increasing Students' Reading Achievement in a Title I Elementary Public School

ERIC Educational Resources Information Center

Atkinson, Linton

2015-01-01

This paper is a research dissertation based on a qualitative case study conducted on Teachers' Experiences within a Data-Driven Decision Making (DDDM) process. The study site was a Title I elementary school in a large school district in Central Florida. Background information is given in relation to the need for research that was conducted on the…

Using Visualization in Cockpit Decision Support Systems

NASA Technical Reports Server (NTRS)

Aragon, Cecilia R.

2005-01-01

In order to safely operate their aircraft, pilots must make rapid decisions based on integrating and processing large amounts of heterogeneous information. Visual displays are often the most efficient method of presenting safety-critical data to pilots in real time. However, care must be taken to ensure the pilot is provided with the appropriate amount of information to make effective decisions and not become cognitively overloaded. The results of two usability studies of a prototype airflow hazard visualization cockpit decision support system are summarized. The studies demonstrate that such a system significantly improves the performance of helicopter pilots landing under turbulent conditions. Based on these results, design principles and implications for cockpit decision support systems using visualization are presented.

Event-based knowledge elicitation of operating room management decision-making using scenarios adapted from information systems data

PubMed Central

2011-01-01

Background No systematic process has previously been described for a needs assessment that identifies the operating room (OR) management decisions made by the anesthesiologists and nurse managers at a facility that do not maximize the efficiency of use of OR time. We evaluated whether event-based knowledge elicitation can be used practically for rapid assessment of OR management decision-making at facilities, whether scenarios can be adapted automatically from information systems data, and the usefulness of the approach. Methods A process of event-based knowledge elicitation was developed to assess OR management decision-making that may reduce the efficiency of use of OR time. Hypothetical scenarios addressing every OR management decision influencing OR efficiency were created from published examples. Scenarios are adapted, so that cues about conditions are accurate and appropriate for each facility (e.g., if OR 1 is used as an example in a scenario, the listed procedure is a type of procedure performed at the facility in OR 1). Adaptation is performed automatically using the facility's OR information system or anesthesia information management system (AIMS) data for most scenarios (43 of 45). Performing the needs assessment takes approximately 1 hour of local managers' time while they decide if their decisions are consistent with the described scenarios. A table of contents of the indexed scenarios is created automatically, providing a simple version of problem solving using case-based reasoning. For example, a new OR manager wanting to know the best way to decide whether to move a case can look in the chapter on "Moving Cases on the Day of Surgery" to find a scenario that describes the situation being encountered. Results Scenarios have been adapted and used at 22 hospitals. Few changes in decisions were needed to increase the efficiency of use of OR time. The few changes were heterogeneous among hospitals, showing the usefulness of individualized assessments. Conclusions Our technical advance is the development and use of automated event-based knowledge elicitation to identify suboptimal OR management decisions that decrease the efficiency of use of OR time. The adapted scenarios can be used in future decision-making. PMID:21214905

Event-based knowledge elicitation of operating room management decision-making using scenarios adapted from information systems data.

PubMed

Dexter, Franklin; Wachtel, Ruth E; Epstein, Richard H

2011-01-07

No systematic process has previously been described for a needs assessment that identifies the operating room (OR) management decisions made by the anesthesiologists and nurse managers at a facility that do not maximize the efficiency of use of OR time. We evaluated whether event-based knowledge elicitation can be used practically for rapid assessment of OR management decision-making at facilities, whether scenarios can be adapted automatically from information systems data, and the usefulness of the approach. A process of event-based knowledge elicitation was developed to assess OR management decision-making that may reduce the efficiency of use of OR time. Hypothetical scenarios addressing every OR management decision influencing OR efficiency were created from published examples. Scenarios are adapted, so that cues about conditions are accurate and appropriate for each facility (e.g., if OR 1 is used as an example in a scenario, the listed procedure is a type of procedure performed at the facility in OR 1). Adaptation is performed automatically using the facility's OR information system or anesthesia information management system (AIMS) data for most scenarios (43 of 45). Performing the needs assessment takes approximately 1 hour of local managers' time while they decide if their decisions are consistent with the described scenarios. A table of contents of the indexed scenarios is created automatically, providing a simple version of problem solving using case-based reasoning. For example, a new OR manager wanting to know the best way to decide whether to move a case can look in the chapter on "Moving Cases on the Day of Surgery" to find a scenario that describes the situation being encountered. Scenarios have been adapted and used at 22 hospitals. Few changes in decisions were needed to increase the efficiency of use of OR time. The few changes were heterogeneous among hospitals, showing the usefulness of individualized assessments. Our technical advance is the development and use of automated event-based knowledge elicitation to identify suboptimal OR management decisions that decrease the efficiency of use of OR time. The adapted scenarios can be used in future decision-making.

Facilitators and constraints at each stage of the migration decision process.

PubMed

Kley, Stefanie

2017-10-01

Behavioural models of migration emphasize the importance of migration decision-making for the explanation of subsequent behaviour. But empirical migration research regularly finds considerable gaps between those who intend to migrate and those who actually realize their intention. This paper applies the Theory of Planned Behaviour, enriched by the Rubicon model, to test specific hypotheses about distinct effects of facilitators and constraints on specific stages of migration decision-making and behaviour. The data come from a tailor-made panel survey based on random samples of people drawn from two German cities in 2006-07. The results show that in conventional models the effects of facilitators and constraints on migration decision-making are likely to be underestimated. Splitting the process of migration decision-making into a pre-decisional and a pre-actional phase helps to avoid bias in the estimated effects of facilitators and constraints on both migration decision-making and migration behaviour.

The Evidential Basis of Decision Making in Plant Disease Management.

PubMed

Hughes, Gareth

2017-08-04

The evidential basis for disease management decision making is provided by data relating to risk factors. The decision process involves an assessment of the evidence leading to taking (or refraining from) action on the basis of a prediction. The primary objective of the decision process is to identify-at the time the decision is made-the control action that provides the best predicted end-of-season outcome, calculated in terms of revenue or another appropriate metric. Data relating to disease risk factors may take a variety of forms (e.g., continuous, discrete, categorical) on measurement scales in a variety of units. Log 10 -likelihood ratios provide a principled basis for the accumulation of evidence based on such data and allow predictions to be made via Bayesian updating of prior probabilities.

Controlling Chronic Diseases Through Evidence-Based Decision Making: A Group-Randomized Trial.

PubMed

Brownson, Ross C; Allen, Peg; Jacob, Rebekah R; deRuyter, Anna; Lakshman, Meenakshi; Reis, Rodrigo S; Yan, Yan

2017-11-30

Although practitioners in state health departments are ideally positioned to implement evidence-based interventions, few studies have examined how to build their capacity to do so. The objective of this study was to explore how to increase the use of evidence-based decision-making processes at both the individual and organization levels. We conducted a 2-arm, group-randomized trial with baseline data collection and follow-up at 18 to 24 months. Twelve state health departments were paired and randomly assigned to intervention or control condition. In the 6 intervention states, a multiday training on evidence-based decision making was conducted from March 2014 through March 2015 along with a set of supplemental capacity-building activities. Individual-level outcomes were evidence-based decision making skills of public health practitioners; organization-level outcomes were access to research evidence and participatory decision making. Mixed analysis of covariance models was used to evaluate the intervention effect by accounting for the cluster randomized trial design. Analysis was performed from March through May 2017. Participation 18 to 24 months after initial training was 73.5%. In mixed models adjusted for participant and state characteristics, the intervention group improved significantly in the overall skill gap (P = .01) and in 6 skill areas. Among the 4 organizational variables, only access to evidence and skilled staff showed an intervention effect (P = .04). Tailored and active strategies are needed to build capacity at the individual and organization levels for evidence-based decision making. Our study suggests several dissemination interventions for consideration by leaders seeking to improve public health practice.

ACTIVITIES TO DEVELOP AN INTERIM GUIDANCE FOR MICROARRAY-BASED ASSAYS FOR REGULATORY AND RISK ASSESSMENT APPLICATIONS AT EPA

EPA Science Inventory

Abstract for presentation. Advances in genomics will have significant implications for risk assessment policies and regulatory decision making. In 2002, EPA issued its lnterim Policy on Genomics which stated that such data may be considered in the decision making process, but tha...

Retirement and Marital Decision Making: Effects on Retirement Satisfaction

ERIC Educational Resources Information Center

Szinovacz, Maximiliane E.; Davey, Adam

2005-01-01

This study explores how partner's employment and pre-retirement decision-making structures affect retirement satisfaction, using pooled data from Waves 1 to 4 of the Health and Retirement Surveys. Based on resource theory, the analyses indicate that retired husbands are least satisfied if their wives remain employed and had more say in decisions…

Improving Decision Making Skill Using an Online Volcanic Crisis Simulation: Impact of Data Presentation Format

ERIC Educational Resources Information Center

Barclay, Elizabeth J.; Renshaw, Carl E.; Taylor, Holly A.; Bilge, A. Reyan

2011-01-01

Creating effective computer-based learning exercises requires an understanding of optimal user interface designs for improving higher order cognitive skills. Using an online volcanic crisis simulation previously shown to improve decision making skill, we find that a user interface using a graphical presentation of the volcano monitoring data…

Errors in statistical decision making Chapter 2 in Applied Statistics in Agricultural, Biological, and Environmental Sciences

USDA-ARS?s Scientific Manuscript database

Agronomic and Environmental research experiments result in data that are analyzed using statistical methods. These data are unavoidably accompanied by uncertainty. Decisions about hypotheses, based on statistical analyses of these data are therefore subject to error. This error is of three types,...

Rational and Experiential Decision-Making Preferences of Third-Year Student Pharmacists

PubMed Central

McLaughlin, Jacqueline E.; Cox, Wendy C.; Williams, Charlene R.

2014-01-01

Objective. To examine the rational (systematic and rule-based) and experiential (fast and intuitive) decision-making preferences of student pharmacists, and to compare these preferences to the preferences of other health professionals and student populations. Methods. The Rational-Experiential Inventory (REI-40), a validated psychometric tool, was administered electronically to 114 third-year (P3) student pharmacists. Student demographics and preadmission data were collected. The REI-40 results were compared with student demographics and admissions data to identify possible correlations between these factors. Results. Mean REI-40 rational scores were higher than experiential scores. Rational scores for younger students were significantly higher than students aged 30 years and older (p<0.05). No significant differences were found based on gender, race, or the presence of a prior degree. All correlations between REI-40 scores and incoming grade point average (GPA) and Pharmacy College Admission Test (PCAT) scores were weak. Conclusion. Student pharmacists favored rational decision making over experiential decision making, which was similar to results of studies done of other health professions. PMID:25147392

Veterinary decision making in relation to metritis--a qualitative approach to understand the background for variation and bias in veterinary medical records.

PubMed

Lastein, Dorte B; Vaarst, Mette; Enevoldsen, Carsten

2009-08-30

Results of analyses based on veterinary records of animal disease may be prone to variation and bias, because data collection for these registers relies on different observers in different settings as well as different treatment criteria. Understanding the human influence on data collection and the decisions related to this process may help veterinary and agricultural scientists motivate observers (veterinarians and farmers) to work more systematically, which may improve data quality. This study investigates qualitative relations between two types of records: 1) 'diagnostic data' as recordings of metritis scores and 2) 'intervention data' as recordings of medical treatment for metritis and the potential influence on quality of the data. The study is based on observations in veterinary dairy practice combined with semi-structured research interviews of veterinarians working within a herd health concept where metritis diagnosis was described in detail. The observations and interviews were analysed by qualitative research methods to describe differences in the veterinarians' perceptions of metritis diagnosis (scores) and their own decisions related to diagnosis, treatment, and recording. The analysis demonstrates how data quality can be affected during the diagnostic procedures, as interaction occurs between diagnostics and decisions about medical treatments. Important findings were when scores lacked consistency within and between observers (variation) and when scores were adjusted to the treatment decision already made by the veterinarian (bias). The study further demonstrates that veterinarians made their decisions at 3 different levels of focus (cow, farm, population). Data quality was influenced by the veterinarians' perceptions of collection procedures, decision making and their different motivations to collect data systematically. Both variation and bias were introduced into the data because of veterinarians' different perceptions of and motivations for decision making. Acknowledgement of these findings by researchers, educational institutions and veterinarians in practice may stimulate an effort to improve the quality of field data, as well as raise awareness about the importance of including knowledge about human perceptions when interpreting studies based on field data. Both recognitions may increase the usefulness of both within-herd and between-herd epidemiological analyses.

Veterinary decision making in relation to metritis - a qualitative approach to understand the background for variation and bias in veterinary medical records

PubMed Central

Lastein, Dorte B; Vaarst, Mette; Enevoldsen, Carsten

2009-01-01

Background Results of analyses based on veterinary records of animal disease may be prone to variation and bias, because data collection for these registers relies on different observers in different settings as well as different treatment criteria. Understanding the human influence on data collection and the decisions related to this process may help veterinary and agricultural scientists motivate observers (veterinarians and farmers) to work more systematically, which may improve data quality. This study investigates qualitative relations between two types of records: 1) 'diagnostic data' as recordings of metritis scores and 2) 'intervention data' as recordings of medical treatment for metritis and the potential influence on quality of the data. Methods The study is based on observations in veterinary dairy practice combined with semi-structured research interviews of veterinarians working within a herd health concept where metritis diagnosis was described in detail. The observations and interviews were analysed by qualitative research methods to describe differences in the veterinarians' perceptions of metritis diagnosis (scores) and their own decisions related to diagnosis, treatment, and recording. Results The analysis demonstrates how data quality can be affected during the diagnostic procedures, as interaction occurs between diagnostics and decisions about medical treatments. Important findings were when scores lacked consistency within and between observers (variation) and when scores were adjusted to the treatment decision already made by the veterinarian (bias). The study further demonstrates that veterinarians made their decisions at 3 different levels of focus (cow, farm, population). Data quality was influenced by the veterinarians' perceptions of collection procedures, decision making and their different motivations to collect data systematically. Conclusion Both variation and bias were introduced into the data because of veterinarians' different perceptions of and motivations for decision making. Acknowledgement of these findings by researchers, educational institutions and veterinarians in practice may stimulate an effort to improve the quality of field data, as well as raise awareness about the importance of including knowledge about human perceptions when interpreting studies based on field data. Both recognitions may increase the usefulness of both within-herd and between-herd epidemiological analyses. PMID:19715614

Reducing Subjectivity in Geothermal Exploration Decision Making (Presentation); NREL(National Renewable Energy Laboratory)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Akar, S.; Young, K.

Geothermal exploration projects have a significant amount of risk associated with uncertainties encountered in the discovery of the geothermal resource. Two of the largest challenges for increased geothermal deployment are 1) understanding when and how to proceed in an exploration program, and 2) when to walk away from a site. Current methodologies for exploration decision-making are formulatedby subjective expert opinion which can be incorrectly biased by expertise (e.g. geochemistry, geophysics), geographic location of focus, and the assumed conceptual model. The aim of this project is to develop a methodology for more objective geothermal exploration decision making at a given location,more » including go/no-go decision points to help developers and investors decide when to give up on alocation. In this scope, two different approaches are investigated: 1) value of information analysis (VOIA) which is used for evaluating and quantifying the value of a data before they are purchased, and 2) enthalpy-based exploration targeting based on reservoir size, temperature gradient estimates, and internal rate of return (IRR). The first approach, VOIA, aims to identify the value of aparticular data when making decisions with an uncertain outcome. This approach targets the pre-drilling phase of exploration. These estimated VOIs are highly affected by the size of the project and still have a high degree of subjectivity in assignment of probabilities. The second approach, exploration targeting, is focused on decision making during the drilling phase. It starts with a basicgeothermal project definition that includes target and minimum required production capacity and initial budgeting for exploration phases. Then, it uses average temperature gradient, reservoir temperature estimates, and production capacity to define targets and go/no-go limits. The decision analysis in this approach is based on achieving a minimum IRR at each phase of the project. This secondapproach was determined to be less subjective, since numerical inputs come from the collected data. And it helps to facilitate communication between project managers and exploration geologists in making objective go/no-go decisions throughout the different project phases.« less

Advanced Computational Framework for Environmental Management ZEM, Version 1.x

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vesselinov, Velimir V.; O'Malley, Daniel; Pandey, Sachin

2016-11-04

Typically environmental management problems require analysis of large and complex data sets originating from concurrent data streams with different data collection frequencies and pedigree. These big data sets require on-the-fly integration into a series of models with different complexity for various types of model analyses where the data are applied as soft and hard model constraints. This is needed to provide fast iterative model analyses based on the latest available data to guide decision-making. Furthermore, the data and model are associated with uncertainties. The uncertainties are probabilistic (e.g. measurement errors) and non-probabilistic (unknowns, e.g. alternative conceptual models characterizing site conditions).more » To address all of these issues, we have developed an integrated framework for real-time data and model analyses for environmental decision-making called ZEM. The framework allows for seamless and on-the-fly integration of data and modeling results for robust and scientifically-defensible decision-making applying advanced decision analyses tools such as Bayesian- Information-Gap Decision Theory (BIG-DT). The framework also includes advanced methods for optimization that are capable of dealing with a large number of unknown model parameters, and surrogate (reduced order) modeling capabilities based on support vector regression techniques. The framework is coded in Julia, a state-of-the-art high-performance programing language (http://julialang.org). The ZEM framework is open-source and can be applied to any environmental management site. The framework will be open-source and released under GPL V3 license.« less

Choosing an Advanced Therapy in Parkinson's Disease; is it an Evidence-Based Decision in Current Practice?

PubMed

Nijhuis, Frouke A P; van Heek, Jolien; Bloem, Bastiaan R; Post, Bart; Faber, Marjan J

2016-07-25

In advanced Parkinson's disease (PD), neurologists and patients face a complex decision for an advanced therapy. When choosing a treatment, the best available evidence should be combined with the professional's expertise and the patient's preferences. The objective of this study was to explore current decision-making in advanced PD. We conducted focus group discussions and individual interviews with patients (N = 20) who had received deep brain stimulation, Levodopa-Carbidopa intestinal gel, or subcutaneous apomorphine infusion, and with their caregivers (N = 16). Furthermore, we conducted semi-structured interviews with neurologists (N = 7) and PD nurse specialists (N = 3) to include the perspectives of all key players in this decision-making process. Data were analyzed by two researchers using a qualitative thematic analysis approach. Four themes representing current experiences with the decision-making process were identified: 1) information and information needs, 2) factors influencing treatment choice and individual decision strategies, 3) decision-making roles, and 4) barriers and facilitators to shared decision-making (SDM). Patient preferences were taken into account, however patients were not always provided with adequate information. The professional's expertise influenced the decision-making process in both positive and negative ways. Although professionals and patients considered SDM essential for the decision of an advanced treatment, they mentioned several barriers for the implementation in current practice. In this study we found several factors explaining why in current practice, evidence-based decision-making in advanced PD is not optimal. An important first step would be to develop objective information on all treatment options.

Geospatial Data Fusion and Multigroup Decision Support for Surface Water Quality Management

NASA Astrophysics Data System (ADS)

Sun, A. Y.; Osidele, O.; Green, R. T.; Xie, H.

2010-12-01

Social networking and social media have gained significant popularity and brought fundamental changes to many facets of our everyday life. With the ever-increasing adoption of GPS-enabled gadgets and technology, location-based content is likely to play a central role in social networking sites. While location-based content is not new to the geoscience community, where geographic information systems (GIS) are extensively used, the delivery of useful geospatial data to targeted user groups for decision support is new. Decision makers and modelers ought to make more effective use of the new web-based tools to expand the scope of environmental awareness education, public outreach, and stakeholder interaction. Environmental decision processes are often rife with uncertainty and controversy, requiring integration of multiple sources of information and compromises between diverse interests. Fusing of multisource, multiscale environmental data for multigroup decision support is a challenging task. Toward this goal, a multigroup decision support platform should strive to achieve transparency, impartiality, and timely synthesis of information. The latter criterion often constitutes a major technical bottleneck to traditional GIS-based media, featuring large file or image sizes and requiring special processing before web deployment. Many tools and design patterns have appeared in recent years to ease the situation somewhat. In this project, we explore the use of Web 2.0 technologies for “pushing” location-based content to multigroups involved in surface water quality management and decision making. In particular, our granular bottom-up approach facilitates effective delivery of information to most relevant user groups. Our location-based content includes in-situ and remotely sensed data disseminated by NASA and other national and local agencies. Our project is demonstrated for managing the total maximum daily load (TMDL) program in the Arroyo Colorado coastal river basin in Texas. The overall design focuses on assigning spatial information to decision support elements and on efficiently using Web 2.0 technologies to relay scientific information to the nonscientific community. We conclude that (i) social networking, if appropriately used, has great potential for mitigating difficulty associated with multigroup decision making; (ii) all potential stakeholder groups should be involved in creating a useful decision support system; and (iii) environmental decision support systems should be considered a must-have, instead of an optional component of TMDL decision support projects. Acknowledgment: This project was supported by NASA grant NNX09AR63G.

Ability Grouping and Differentiated Instruction in an Era of Data-Driven Decision Making

ERIC Educational Resources Information Center

Park, Vicki; Datnow, Amanda

2017-01-01

Despite data-driven decision making being a ubiquitous part of policy and school reform efforts, little is known about how teachers use data for instructional decision making. Drawing on data from a qualitative case study of four elementary schools, we examine the logic and patterns of teacher decision making about differentiation and ability…

A management-oriented framework for selecting metrics used to assess habitat- and path-specific quality in spatially structured populations

USGS Publications Warehouse

Nicol, Sam; Wiederholt, Ruscena; Diffendorfer, James E.; Mattsson, Brady; Thogmartin, Wayne E.; Semmens, Darius J.; Laura Lopez-Hoffman,; Norris, Ryan

2016-01-01

Mobile species with complex spatial dynamics can be difficult to manage because their population distributions vary across space and time, and because the consequences of managing particular habitats are uncertain when evaluated at the level of the entire population. Metrics to assess the importance of habitats and pathways connecting habitats in a network are necessary to guide a variety of management decisions. Given the many metrics developed for spatially structured models, it can be challenging to select the most appropriate one for a particular decision. To guide the management of spatially structured populations, we define three classes of metrics describing habitat and pathway quality based on their data requirements (graph-based, occupancy-based, and demographic-based metrics) and synopsize the ecological literature relating to these classes. Applying the first steps of a formal decision-making approach (problem framing, objectives, and management actions), we assess the utility of metrics for particular types of management decisions. Our framework can help managers with problem framing, choosing metrics of habitat and pathway quality, and to elucidate the data needs for a particular metric. Our goal is to help managers to narrow the range of suitable metrics for a management project, and aid in decision-making to make the best use of limited resources.

Analysis of decision fusion algorithms in handling uncertainties for integrated health monitoring systems

NASA Astrophysics Data System (ADS)

Zein-Sabatto, Saleh; Mikhail, Maged; Bodruzzaman, Mohammad; DeSimio, Martin; Derriso, Mark; Behbahani, Alireza

2012-06-01

It has been widely accepted that data fusion and information fusion methods can improve the accuracy and robustness of decision-making in structural health monitoring systems. It is arguably true nonetheless, that decision-level is equally beneficial when applied to integrated health monitoring systems. Several decisions at low-levels of abstraction may be produced by different decision-makers; however, decision-level fusion is required at the final stage of the process to provide accurate assessment about the health of the monitored system as a whole. An example of such integrated systems with complex decision-making scenarios is the integrated health monitoring of aircraft. Thorough understanding of the characteristics of the decision-fusion methodologies is a crucial step for successful implementation of such decision-fusion systems. In this paper, we have presented the major information fusion methodologies reported in the literature, i.e., probabilistic, evidential, and artificial intelligent based methods. The theoretical basis and characteristics of these methodologies are explained and their performances are analyzed. Second, candidate methods from the above fusion methodologies, i.e., Bayesian, Dempster-Shafer, and fuzzy logic algorithms are selected and their applications are extended to decisions fusion. Finally, fusion algorithms are developed based on the selected fusion methods and their performance are tested on decisions generated from synthetic data and from experimental data. Also in this paper, a modeling methodology, i.e. cloud model, for generating synthetic decisions is presented and used. Using the cloud model, both types of uncertainties; randomness and fuzziness, involved in real decision-making are modeled. Synthetic decisions are generated with an unbiased process and varying interaction complexities among decisions to provide for fair performance comparison of the selected decision-fusion algorithms. For verification purposes, implementation results of the developed fusion algorithms on structural health monitoring data collected from experimental tests are reported in this paper.

A Cognitive Modeling Approach to Strategy Formation in Dynamic Decision Making.

PubMed

Prezenski, Sabine; Brechmann, André; Wolff, Susann; Russwinkel, Nele

2017-01-01

Decision-making is a high-level cognitive process based on cognitive processes like perception, attention, and memory. Real-life situations require series of decisions to be made, with each decision depending on previous feedback from a potentially changing environment. To gain a better understanding of the underlying processes of dynamic decision-making, we applied the method of cognitive modeling on a complex rule-based category learning task. Here, participants first needed to identify the conjunction of two rules that defined a target category and later adapt to a reversal of feedback contingencies. We developed an ACT-R model for the core aspects of this dynamic decision-making task. An important aim of our model was that it provides a general account of how such tasks are solved and, with minor changes, is applicable to other stimulus materials. The model was implemented as a mixture of an exemplar-based and a rule-based approach which incorporates perceptual-motor and metacognitive aspects as well. The model solves the categorization task by first trying out one-feature strategies and then, as a result of repeated negative feedback, switching to two-feature strategies. Overall, this model solves the task in a similar way as participants do, including generally successful initial learning as well as reversal learning after the change of feedback contingencies. Moreover, the fact that not all participants were successful in the two learning phases is also reflected in the modeling data. However, we found a larger variance and a lower overall performance of the modeling data as compared to the human data which may relate to perceptual preferences or additional knowledge and rules applied by the participants. In a next step, these aspects could be implemented in the model for a better overall fit. In view of the large interindividual differences in decision performance between participants, additional information about the underlying cognitive processes from behavioral, psychobiological and neurophysiological data may help to optimize future applications of this model such that it can be transferred to other domains of comparable dynamic decision tasks.

A Cognitive Modeling Approach to Strategy Formation in Dynamic Decision Making

PubMed Central

Prezenski, Sabine; Brechmann, André; Wolff, Susann; Russwinkel, Nele

2017-01-01

Decision-making is a high-level cognitive process based on cognitive processes like perception, attention, and memory. Real-life situations require series of decisions to be made, with each decision depending on previous feedback from a potentially changing environment. To gain a better understanding of the underlying processes of dynamic decision-making, we applied the method of cognitive modeling on a complex rule-based category learning task. Here, participants first needed to identify the conjunction of two rules that defined a target category and later adapt to a reversal of feedback contingencies. We developed an ACT-R model for the core aspects of this dynamic decision-making task. An important aim of our model was that it provides a general account of how such tasks are solved and, with minor changes, is applicable to other stimulus materials. The model was implemented as a mixture of an exemplar-based and a rule-based approach which incorporates perceptual-motor and metacognitive aspects as well. The model solves the categorization task by first trying out one-feature strategies and then, as a result of repeated negative feedback, switching to two-feature strategies. Overall, this model solves the task in a similar way as participants do, including generally successful initial learning as well as reversal learning after the change of feedback contingencies. Moreover, the fact that not all participants were successful in the two learning phases is also reflected in the modeling data. However, we found a larger variance and a lower overall performance of the modeling data as compared to the human data which may relate to perceptual preferences or additional knowledge and rules applied by the participants. In a next step, these aspects could be implemented in the model for a better overall fit. In view of the large interindividual differences in decision performance between participants, additional information about the underlying cognitive processes from behavioral, psychobiological and neurophysiological data may help to optimize future applications of this model such that it can be transferred to other domains of comparable dynamic decision tasks. PMID:28824512

Distinction between Externally vs. Internally Guided Decision-Making: Operational Differences, Meta-Analytical Comparisons and Their Theoretical Implications

PubMed Central

Nakao, Takashi; Ohira, Hideki; Northoff, Georg

2012-01-01

Most experimental studies of decision-making have specifically examined situations in which a single less-predictable correct answer exists (externally guided decision-making under uncertainty). Along with such externally guided decision-making, there are instances of decision-making in which no correct answer based on external circumstances is available for the subject (internally guided decision-making). Such decisions are usually made in the context of moral decision-making as well as in preference judgment, where the answer depends on the subject’s own, i.e., internal, preferences rather than on external, i.e., circumstantial, criteria. The neuronal and psychological mechanisms that allow guidance of decisions based on more internally oriented criteria in the absence of external ones remain unclear. This study was undertaken to compare decision-making of these two kinds empirically and theoretically. First, we reviewed studies of decision-making to clarify experimental–operational differences between externally guided and internally guided decision-making. Second, using multi-level kernel density analysis, a whole-brain-based quantitative meta-analysis of neuroimaging studies was performed. Our meta-analysis revealed that the neural network used predominantly for internally guided decision-making differs from that for externally guided decision-making under uncertainty. This result suggests that studying only externally guided decision-making under uncertainty is insufficient to account for decision-making processes in the brain. Finally, based on the review and results of the meta-analysis, we discuss the differences and relations between decision-making of these two types in terms of their operational, neuronal, and theoretical characteristics. PMID:22403525

A novel framework for improvement of road accidents considering decision-making styles of drivers in a large metropolitan area.

PubMed

Azadeh, Ali; Zarrin, Mansour; Hamid, Mehdi

2016-02-01

Road accidents can be caused by different factors such as human factors. Quality of the decision-making process of drivers could have a considerable impact on preventing disasters. The main objective of this study is the analysis of factors affecting road accidents by considering the severity of accidents and decision-making styles of drivers. To this end, a novel framework is proposed based on data envelopment analysis (DEA) and statistical methods (SMs) to assess the factors affecting road accidents. In this study, for the first time, dominant decision-making styles of drivers with respect to severity of injuries are identified. To show the applicability of the proposed framework, this research employs actual data of more than 500 samples in Tehran, Iran. The empirical results indicate that the flexible decision style is the dominant style for both minor and severe levels of accident injuries. Copyright © 2015 Elsevier Ltd. All rights reserved.

Physics-based and human-derived information fusion for analysts

NASA Astrophysics Data System (ADS)

Blasch, Erik; Nagy, James; Scott, Steve; Okoth, Joshua; Hinman, Michael

2017-05-01

Recent trends in physics-based and human-derived information fusion (PHIF) have amplified the capabilities of analysts; however with the big data opportunities there is a need for open architecture designs, methods of distributed team collaboration, and visualizations. In this paper, we explore recent trends in the information fusion to support user interaction and machine analytics. Challenging scenarios requiring PHIF include combing physics-based video data with human-derived text data for enhanced simultaneous tracking and identification. A driving effort would be to provide analysts with applications, tools, and interfaces that afford effective and affordable solutions for timely decision making. Fusion at scale should be developed to allow analysts to access data, call analytics routines, enter solutions, update models, and store results for distributed decision making.

Family Communication about End-of-Life Decisions and the Enactment of the Decision-Maker Role.

PubMed

Trees, April R; Ohs, Jennifer E; Murray, Meghan C

2017-06-07

End-of-life (EOL) decisions in families are complex and emotional sites of family interaction necessitating family members coordinate roles in the EOL decision-making process. How family members in the United States enact the decision-maker role in EOL decision situations was examined through in-depth interviews with 22 individuals who participated in EOL decision-making for a family member. A number of themes emerged from the data with regard to the enactment of the decision-maker role. Families varied in how decision makers enacted the role in relation to collective family input, with consulting, informing and collaborating as different patterns of behavior. Formal family roles along with gender- and age-based roles shaped who took on the decision-maker role. Additionally, both family members and medical professionals facilitated or undermined the decision-maker's role enactment. Understanding the structure and enactment of the decision-maker role in family interaction provides insight into how individuals and/or family members perform the decision-making role within a cultural context that values autonomy and self-determination in combination with collective family action in EOL decision-making.

Critical thinking by nurses on ethical issues like the termination of pregnancies.

PubMed

Botes, A

2000-09-01

This research forms part of a larger interdisciplinary research project on the termination of pregnancies. The focus of this part of the project is on the ethical issues related to termination of pregnancies. The practice of the professional nurse is confronted with ethical dilemmas and disputes. Whether the nurse chooses to participate in the termination of pregnancies or not, the core function of the nurse is that of counseling and ethical decision-making. Effective counseling requires empathy, respect for human rights and unconditional acceptance of a person. Making ethical decisions implies making critical decisions. It is self-evident, therefore, that such decisions should be based on sound arguments and logical reasoning. It is of vital importance that ethical decisions can be justified on rational ground. Decision-making is a critical thinking approach process for choosing the best action to meet a desired goal. The research question that is relevant for this paper is: Are nurses thinking critically about ethical issues like the termination of pregnancies? To answer the research question a qualitative, exploratory, descriptive design was used (Mouton, 1996:103-169). Registered nurses were selected purposively (Creswell, 1994:15). 1200 registered nurses completed the open-ended questionnaires. Focus group interviews were conducted with 22 registered nurses from a public hospital for women and child health services. Data analysis, using secondary data from open-ended questionnaires and transcribed focus group interviews, were based on the approach of Morse and Field (1994:25-34) and Strauss and Corbin (1990). The themes and categories from open coding were compared, conceptualized and linked with theories on critical thinking (Paul, 1994; Watson & Glaser, 1991 and the American Philosophical Association, 1990). The measures of Lincoln and Guba (1985) and Morse (1994) related to secondary data analysis were employed to ensure trustworthiness. Based on these findings the researcher concluded that nurses are not thinking critically when making ethical decisions concerning the termination of pregnancies. Recommendations are made as a possible solution for this problem.

Strategies to facilitate shared decision-making about pediatric oncology clinical trial enrollment: A systematic review.

PubMed

Robertson, Eden G; Wakefield, Claire E; Signorelli, Christina; Cohn, Richard J; Patenaude, Andrea; Foster, Claire; Pettit, Tristan; Fardell, Joanna E

2018-07-01

We conducted a systematic review to identify the strategies that have been recommended in the literature to facilitate shared decision-making regarding enrolment in pediatric oncology clinical trials. We searched seven databases for peer-reviewed literature, published 1990-2017. Of 924 articles identified, 17 studies were eligible for the review. We assessed study quality using the 'Mixed-Methods Appraisal Tool'. We coded the results and discussions of papers line-by-line using nVivo software. We categorized strategies thematically. Five main themes emerged: 1) decision-making as a process, 2) individuality of the process; 3) information provision, 4) the role of communication, or 5) decision and psychosocial support. Families should have adequate time to make a decision. HCPs should elicit parents' and patients' preferences for level of information and decision involvement. Information should be clear and provided in multiple modalities. Articles also recommended providing training for healthcare professionals and access to psychosocial support for families. High quality, individually-tailored information, open communication and psychosocial support appear vital in supporting decision-making regarding enrollment in clinical trials. These data will usefully inform future decision-making interventions/tools to support families making clinical trial decisions. A solid evidence-base for effective strategies which facilitate shared decision-making is needed. Copyright © 2018 Elsevier B.V. All rights reserved.

Evidence-based decision making in health care settings: from theory to practice.

PubMed

Kohn, Melanie Kazman; Berta, Whitney; Langley, Ann; Davis, David

2011-01-01

The relatively recent attention that evidence-based decision making has received in health care management has been at least in part due to the profound influence of evidence-based medicine. The result has been several comparisons in the literature between the use of evidence in health care management decisions and the use of evidence in medical decision making. Direct comparison, however, may be problematic, given the differences between medicine and management as they relate to (1) the nature of evidence that is brought to bear on decision making; (2) the maturity of empirical research in each field (in particular, studies that have substantiated whether or not and how evidence-based decision making is enacted); and (3) the context within which evidence-based decisions are made. By simultaneously reviewing evidence-based medicine and management, this chapter aims to inform future theorizing and empirical research on evidence-based decision making in health care settings.

Shared decision making in chronic care in the context of evidence based practice in nursing.

PubMed

Friesen-Storms, Jolanda H H M; Bours, Gerrie J J W; van der Weijden, Trudy; Beurskens, Anna J H M

2015-01-01

In the decision-making environment of evidence-based practice, the following three sources of information must be integrated: research evidence of the intervention, clinical expertise, and the patient's values. In reality, evidence-based practice usually focuses on research evidence (which may be translated into clinical practice guidelines) and clinical expertise without considering the individual patient's values. The shared decision-making model seems to be helpful in the integration of the individual patient's values in evidence-based practice. We aim to discuss the relevance of shared decision making in chronic care and to suggest how it can be integrated with evidence-based practice in nursing. We start by describing the following three possible approaches to guide the decision-making process: the paternalistic approach, the informed approach, and the shared decision-making approach. Implementation of shared decision making has gained considerable interest in cases lacking a strong best-treatment recommendation, and when the available treatment options are equivalent to some extent. We discuss that in chronic care it is important to always invite the patient to participate in the decision-making process. We delineate the following six attributes of health care interventions in chronic care that influence the degree of shared decision making: the level of research evidence, the number of available intervention options, the burden of side effects, the impact on lifestyle, the patient group values, and the impact on resources. Furthermore, the patient's willingness to participate in shared decision making, the clinical expertise of the nurse, and the context in which the decision making takes place affect the shared decision-making process. A knowledgeable and skilled nurse with a positive attitude towards shared decision making—integrated with evidence-based practice—can facilitate the shared decision-making process. We conclude that nurses as well as other health care professionals in chronic care should integrate shared decision making with evidence-based practice to deliver patient-centred care. Copyright © 2014 Elsevier Ltd. All rights reserved.

78 FR 43926 - Solicitation for a Cooperative Agreement-Evidence-Based Decision Making in State and Local...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-07-22

...--Evidence-Based Decision Making in State and Local Criminal Justice Systems: Planning and Development for... Evidence-Based Decision Making (EBDM) in Local Criminal Justice Systems initiative. It will require the... will also revise ``A Framework for Evidence- Based Decision Making in Local Criminal Justice Systems...

A conversation-based process tracing method for use with naturalistic decisions: an evaluation study.

PubMed

Williamson, J; Ranyard, R; Cuthbert, L

2000-05-01

This study is an evaluation of a process tracing method developed for naturalistic decisions, in this case a consumer choice task. The method is based on Huber et al.'s (1997) Active Information Search (AIS) technique, but develops it by providing spoken rather than written answers to respondents' questions, and by including think aloud instructions. The technique is used within a conversation-based situation, rather than the respondent thinking aloud 'into an empty space', as is conventionally the case in think aloud techniques. The method results in a concurrent verbal protocol as respondents make their decisions, and a retrospective report in the form of a post-decision summary. The method was found to be virtually non-reactive in relation to think aloud, although the variable of Preliminary Attribute Elicitation showed some evidence of reactivity. This was a methodological evaluation, and as such the data reported are essentially descriptive. Nevertheless, the data obtained indicate that the method is capable of producing information about decision processes which could have theoretical importance in terms of evaluating models of decision-making.

Smart algorithms and adaptive methods in computational fluid dynamics

NASA Astrophysics Data System (ADS)

Tinsley Oden, J.

1989-05-01

A review is presented of the use of smart algorithms which employ adaptive methods in processing large amounts of data in computational fluid dynamics (CFD). Smart algorithms use a rationally based set of criteria for automatic decision making in an attempt to produce optimal simulations of complex fluid dynamics problems. The information needed to make these decisions is not known beforehand and evolves in structure and form during the numerical solution of flow problems. Once the code makes a decision based on the available data, the structure of the data may change, and criteria may be reapplied in order to direct the analysis toward an acceptable end. Intelligent decisions are made by processing vast amounts of data that evolve unpredictably during the calculation. The basic components of adaptive methods and their application to complex problems of fluid dynamics are reviewed. The basic components of adaptive methods are: (1) data structures, that is what approaches are available for modifying data structures of an approximation so as to reduce errors; (2) error estimation, that is what techniques exist for estimating error evolution in a CFD calculation; and (3) solvers, what algorithms are available which can function in changing meshes. Numerical examples which demonstrate the viability of these approaches are presented.

Parents' information needs and influential factors when making decisions about TNF-α inhibitors.

PubMed

Lipstein, Ellen A; Lovell, Daniel J; Denson, Lee A; Kim, Sandra C; Spencer, Charles; Britto, Maria T

2016-09-15

Parents struggle when making treatment decisions for children with arthritis or other chronic conditions. Understanding their decision-making process is an essential step towards improving the decision-making experience. The objective of this study was to describe parents' information needs and the influences on their decision making about treatment with TNF-α inhibitors. Survey domains were developed based on qualitative data and cognitive interviewing. We mailed the survey to parents of children with juvenile idiopathic arthritis or inflammatory bowel disease who had initiated treatment with TNF-α inhibitors in the prior 2 years. Data were analyzed using descriptive and non-parametric statistics. Survey response rate was 54.9 %. Each item had <2 % missing responses. Parents used an array of information sources when deciding about treatment with TNF-α inhibitors. Resources other than their child's specialist were most often used to increase confidence in parents' decisions or because they wanted to know more about other people's experiences being treated with TNF-α inhibitors, rather than due to a lack of understanding. All but two (cost and route of administration) of the influential decision factors were very or extremely important to the majority of participants with factors related to long-term side effects, treatment efficacy, and disease impact being most important. This study describes parents' information needs and influential factors in treatment decision making. Results suggest that future work should be aimed at helping families weigh risks and benefits, such as through decision support interventions, as well as developing opportunities to include people beyond the family and physician in the decision-making process.

Prognostic categories and timing of negative prognostic communication from critical care physicians to family members at end-of-life in an intensive care unit.

PubMed

Gutierrez, Karen M

2013-09-01

Negative prognostic communication is often delayed in intensive care units, which limits time for families to prepare for end-of-life. This descriptive study, informed by ethnographic methods, was focused on exploring critical care physician communication of negative prognoses to families and identifying timing influences. Prognostic communication of critical care physicians to nurses and family members was observed and physicians and family members were interviewed. Physician perception of prognostic certainty, based on an accumulation of empirical data, and the perceived need for decision-making, drove the timing of prognostic communication, rather than family needs. Although prognoses were initially identified using intuitive knowledge for patients in one of the six identified prognostic categories, utilizing decision-making to drive prognostic communication resulted in delayed prognostic communication to families until end-of-life (EOL) decisions could be justified with empirical data. Providers will better meet the needs of families who desire earlier prognostic information by separating prognostic communication from decision-making and communicating the possibility of a poor prognosis based on intuitive knowledge, while acknowledging the uncertainty inherent in prognostication. This sets the stage for later prognostic discussions focused on EOL decisions, including limiting or withdrawing treatment, which can be timed when empirical data substantiate intuitive prognoses. This allows additional time for families to anticipate and prepare for end-of-life decision-making. © 2012 John Wiley & Sons Ltd.

Including values in evidence-based policy making for breast screening: An empirically grounded tool to assist expert decision makers.

PubMed

Parker, Lisa

2017-07-01

Values are an important part of evidence-based decision making for health policy: they guide the type of evidence that is collected, how it is interpreted, and how important the conclusions are considered to be. Experts in breast screening (including clinicians, researchers, consumer advocates and senior administrators) hold differing values in relation to what is important in breast screening policy and practice, and committees may find it difficult to incorporate the complexity and variety of values into policy decisions. The decision making tool provided here is intended to assist with this process. The tool is modified from more general frameworks that are intended to assist with ethical decision making in public health, and informed by data drawn from previous empirical studies on values amongst Australian breast screening experts. It provides a structured format for breast screening committees to consider and discuss the values of themselves and others, suggests relevant topics for further inquiry and highlights areas of need for future research into the values of the public. It enables committees to publicly explain and justify their decisions with reference to values, improving transparency and accountability. It is intended to act alongside practices that seek to accommodate the values of individual women in the informed decision making process for personal decision making about participation in breast screening. Copyright © 2017 Elsevier B.V. All rights reserved.

Decision-making in schizophrenia: A predictive-coding perspective.

PubMed

Sterzer, Philipp; Voss, Martin; Schlagenhauf, Florian; Heinz, Andreas

2018-05-31

Dysfunctional decision-making has been implicated in the positive and negative symptoms of schizophrenia. Decision-making can be conceptualized within the framework of hierarchical predictive coding as the result of a Bayesian inference process that uses prior beliefs to infer states of the world. According to this idea, prior beliefs encoded at higher levels in the brain are fed back as predictive signals to lower levels. Whenever these predictions are violated by the incoming sensory data, a prediction error is generated and fed forward to update beliefs encoded at higher levels. Well-documented impairments in cognitive decision-making support the view that these neural inference mechanisms are altered in schizophrenia. There is also extensive evidence relating the symptoms of schizophrenia to aberrant signaling of prediction errors, especially in the domain of reward and value-based decision-making. Moreover, the idea of altered predictive coding is supported by evidence for impaired low-level sensory mechanisms and motor processes. We review behavioral and neural findings from these research areas and provide an integrated view suggesting that schizophrenia may be related to a pervasive alteration in predictive coding at multiple hierarchical levels, including cognitive and value-based decision-making processes as well as sensory and motor systems. We relate these findings to decision-making processes and propose that varying degrees of impairment in the implicated brain areas contribute to the variety of psychotic experiences. Copyright © 2018 Elsevier Inc. All rights reserved.

Arriba-lib: association of an evidence-based electronic library of decision aids with communication and decision-making in patients and primary care physicians.

PubMed

Hirsch, Oliver; Keller, Heidemarie; Krones, Tanja; Donner-Banzhoff, Norbert

2012-03-01

In shared decision-making, patients are empowered to actively ask questions and participate in decisions about their healthcare based on their preferences and values. Decision aids should help patients make informed choices among diagnostic or treatment options by delivering evidence-based information on options and outcomes; however, they have rarely been field tested, especially in the primary care context. We therefore evaluated associations between the use of an interactive, transactional and evidence-based library of decision aids (arriba-lib) and communication and decision-making in patients and physicians in the primary care context. Our electronic library of decision aids ('arriba-lib') includes evidence-based modules for cardiovascular prevention, diabetes, coronary heart disease, atrial fibrillation and depression. Twenty-nine primary care physicians recruited 192 patients. We used questionnaires to ask patients and physicians about their experiences with and attitudes towards the programme. Patients were interviewed via telephone 2 months after the consultation. Data were analysed by general estimation equations, cross tab analyses and by using effect sizes. Only a minority (8.9%) of the consultations were felt to be too long because physicians said consultations were unacceptably extended by arriba-lib. We found a negative association between the detailedness of the discussion of the clinical problem's definition and the age of the patients. Physicians discuss therapeutic options in less detail with patients who have a formal education of less than 8 years. Patients who were counselled by a physician with no experience in using a decision aid more often reported that they do not remember being counselled with the help of a decision aid or do not wish to be counselled again with a decision aid. Arriba-lib has positive associations to the decision-making process in patients and physicians. It can also be used with older age groups and patients with less formal education. Physicians seem to adapt their counselling strategy to different patient groups. Prior experience with the use of decision aids has an influence on the acceptance of arriba-lib in patients but not on their decision-making or decision implementation. © 2012 The Authors. International Journal of Evidence-Based Healthcare © 2012 The Joanna Briggs Institute.

Making the Case for Evidence-Based Practice

ERIC Educational Resources Information Center

Bates, Joanne; McClure, Janelle; Spinks, Andy

2010-01-01

Evidence-based practice is the collection, interpretation, and use of data, such as collection statistics or assessment results, that measure the effectiveness of a library media program. In this article, the authors will present various forms of evidence and show that any library media specialist can use data to make informed decisions that…

Evidence-informed decision-making by professionals working in addiction agencies serving women: a descriptive qualitative study.

PubMed

Jack, Susan M; Dobbins, Maureen; Sword, Wendy; Novotna, Gabriela; Brooks, Sandy; Lipman, Ellen L; Niccols, Alison

2011-11-07

Effective approaches to the prevention and treatment of substance abuse among mothers have been developed but not widely implemented. Implementation studies suggest that the adoption of evidence-based practices in the field of addictions remains low. There is a need, therefore, to better understand decision making processes in addiction agencies in order to develop more effective approaches to promote the translation of knowledge gained from addictions research into clinical practice. A descriptive qualitative study was conducted to explore: 1) the types and sources of evidence used to inform practice-related decisions within Canadian addiction agencies serving women; 2) how decision makers at different levels report using research evidence; and 3) factors that influence evidence-informed decision making. A purposeful sample of 26 decision-makers providing addiction treatment services to women completed in-depth qualitative interviews. Interview data were coded and analyzed using directed and summative content analysis strategies as well as constant comparison techniques. Across all groups, individuals reported locating and using multiple types of evidence to inform decisions. Some decision-makers rely on their experiential knowledge of addiction and recovery in decision-making. Research evidence is often used directly in decision-making at program management and senior administrative levels. Information for decision-making is accessed from a range of sources, including web-based resources and experts in the field. Individual and organizational facilitators and barriers to using research evidence in decision making were identified. There is support at administrative levels for integrating EIDM in addiction agencies. Knowledge transfer and exchange strategies should be focussed towards program managers and administrators and include capacity building for locating, appraising and using research evidence, knowledge brokering, and for partnering with universities. Resources are required to maintain web-based databases of searchable evidence to facilitate access to research evidence. A need exists to address the perception that there is a paucity of research evidence available to inform program decisions. Finally, there is a need to consider how experiential knowledge influences decision-making and what guidance research evidence has to offer regarding the implementation of different treatment approaches within the field of addictions.

Evidence-informed decision-making by professionals working in addiction agencies serving women: a descriptive qualitative study

PubMed Central

2011-01-01

Background Effective approaches to the prevention and treatment of substance abuse among mothers have been developed but not widely implemented. Implementation studies suggest that the adoption of evidence-based practices in the field of addictions remains low. There is a need, therefore, to better understand decision making processes in addiction agencies in order to develop more effective approaches to promote the translation of knowledge gained from addictions research into clinical practice. Methods A descriptive qualitative study was conducted to explore: 1) the types and sources of evidence used to inform practice-related decisions within Canadian addiction agencies serving women; 2) how decision makers at different levels report using research evidence; and 3) factors that influence evidence-informed decision making. A purposeful sample of 26 decision-makers providing addiction treatment services to women completed in-depth qualitative interviews. Interview data were coded and analyzed using directed and summative content analysis strategies as well as constant comparison techniques. Results Across all groups, individuals reported locating and using multiple types of evidence to inform decisions. Some decision-makers rely on their experiential knowledge of addiction and recovery in decision-making. Research evidence is often used directly in decision-making at program management and senior administrative levels. Information for decision-making is accessed from a range of sources, including web-based resources and experts in the field. Individual and organizational facilitators and barriers to using research evidence in decision making were identified. Conclusions There is support at administrative levels for integrating EIDM in addiction agencies. Knowledge transfer and exchange strategies should be focussed towards program managers and administrators and include capacity building for locating, appraising and using research evidence, knowledge brokering, and for partnering with universities. Resources are required to maintain web-based databases of searchable evidence to facilitate access to research evidence. A need exists to address the perception that there is a paucity of research evidence available to inform program decisions. Finally, there is a need to consider how experiential knowledge influences decision-making and what guidance research evidence has to offer regarding the implementation of different treatment approaches within the field of addictions. PMID:22059528

Communicating with the coroner: how religion, culture, and family concerns may influence autopsy decision making.

PubMed

Carpenter, Belinda; Adkins, Glenda; Barnes, Michael; Naylor, Charles; Begum, Nelufa

2011-04-01

Based on coronial data gathered in the state of Queensland in 2004, this article reviews how a change in legislation may have impacted autopsy decision making by coroners. More specifically, the authors evaluated whether the requirement that coronial autopsy orders specify the level of invasiveness of an autopsy to be performed by a pathologist was affected by the further requirement that coroners take into consideration a known religion, culture, and/or raised family concern before making such an order. Preliminary data reveal that the cultural status of the deceased did not affect coronial autopsy decision making. However, a known religion with a proscription against autopsy and a raised family concern appeared to be taken into account by coroners when making autopsy decisions and tended to decrease the invasiveness of the autopsy ordered from a full internal examination to either a partial internal examination or an external-only examination of the body. The impact of these findings is briefly discussed.

Core domains of shared decision-making during psychiatric visits: scientific and preference-based discussions.

PubMed

Fukui, Sadaaki; Matthias, Marianne S; Salyers, Michelle P

2015-01-01

Shared decision-making (SDM) is imperative to person-centered care, yet little is known about what aspects of SDM are targeted during psychiatric visits. This secondary data analysis (191 psychiatric visits with 11 providers, coded with a validated SDM coding system) revealed two factors (scientific and preference-based discussions) underlying SDM communication. Preference-based discussion occurred less. Both provider and consumer initiation of SDM elements and decision complexity were associated with greater discussions in both factors, but were more strongly associated with scientific discussion. Longer visit length correlated with only scientific discussion. Providers' understanding of core domains could facilitate engaging consumers in SDM.

Next generation data systems and knowledge products to support agricultural producers and science-based policy decision making.

PubMed

Capalbo, Susan M; Antle, John M; Seavert, Clark

2017-07-01

Research on next generation agricultural systems models shows that the most important current limitation is data, both for on-farm decision support and for research investment and policy decision making. One of the greatest data challenges is to obtain reliable data on farm management decision making, both for current conditions and under scenarios of changed bio-physical and socio-economic conditions. This paper presents a framework for the use of farm-level and landscape-scale models and data to provide analysis that could be used in NextGen knowledge products, such as mobile applications or personal computer data analysis and visualization software. We describe two analytical tools - AgBiz Logic and TOA-MD - that demonstrate the current capability of farmlevel and landscape-scale models. The use of these tools is explored with a case study of an oilseed crop, Camelina sativa , which could be used to produce jet aviation fuel. We conclude with a discussion of innovations needed to facilitate the use of farm and policy-level models to generate data and analysis for improved knowledge products.

The Role of Dysfunctional Myths in a Decision-Making Process under Bounded Rationality: A Complex Dynamical Systems Perspective.

PubMed

Stamovlasis, Dimitrios; Vaiopoulou, Julie

2017-07-01

The present study examines the factors influencing a decision-making process, with specific focus on the role of dysfunctional myths (DM). DM are thoughts or beliefs that are rather irrational, however influential to people's decisions. In this paper a decision-making process regarding the career choice of university students majoring in natural sciences and education (N=496) is examined by analyzing survey data taken via Career Decision Making Difficulties Questionnaire (CDDQ). The difficulty of making the choice and the certainty about one's decision were the state variables, while the independent variables were factors related to the lack of information or knowledge needed, which actually reflect a bounded rationality. Cusp catastrophe analysis, based on both least squares and maximum likelihood procedures, showed that the nonlinear models predicting the two state variables were superior to linear alternatives. Factors related to lack of knowledge about the steps involved in the process of career decision-making, lack of information about the various occupations, lack of information about self and lack of motivation acted as asymmetry, while dysfunctional myths acted as bifurcation factor for both state variables. The catastrophe model, grounded in empirical data, revealed a unique role for DM and a better interpretation within the context of complexity and the notion of bounded rationality. The analysis opens the nonlinear dynamical systems (NDS) perspective in studying decision-making processes. Theoretical and practical implications are discussed.

Uncovering the decision-making work of transferring dying patients home from critical care units: An integrative review.

PubMed

Lin, Yanxia; Myall, Michelle; Jarrett, Nikki

2017-12-01

To understand how decisions are made to transfer dying patients home from critical care units. Many people prefer a home death, but a high proportion die in critical care units. Transferring dying patients home is recognized to be complex but transfer decision-making itself remains unclear. Integrative review. Seven bibliographic databases (origin-2015), grey literature and reference lists were searched. An integrative review method was used to synthesize data from diverse sources. Papers were selected through title and abstract screening and full-text reviewing, using inclusion and exclusion criteria derived from review questions. Following quality appraisal, data were extracted and synthesized using normalization process theory as a framework. The number of patients transferred home ranged from 1-346, with most papers reporting on the transfer of one or two patients. Four themes regarding transfer decision-making work were generated: divergent views and practice, multiple stakeholders' involvement in decision-making, collective work and limited understanding of individuals' experiences. The practice of transferring patients home to die and its decision-making varies internationally and is usually influenced by the care system, culture or religion. It is less common to transfer patients home to die from critical care units in western societies. A better understanding of the decision-making work was obtained but mainly from the perspective of hospital-based healthcare professionals. Further research is needed to develop decision-making practice guidance to facilitate patients' wishes to die at home. © 2017 John Wiley & Sons Ltd.

Linking Theoretical Decision-making Mechanisms in the Simon Task with Electrophysiological Data: A Model-based Neuroscience Study in Humans.

PubMed

Servant, Mathieu; White, Corey; Montagnini, Anna; Burle, Borís

2016-10-01

A current challenge for decision-making research is in extending models of simple decisions to more complex and ecological choice situations. Conflict tasks (e.g., Simon, Stroop, Eriksen flanker) have been the focus of much interest, because they provide a decision-making context representative of everyday life experiences. Modeling efforts have led to an elaborated drift diffusion model for conflict tasks (DMC), which implements a superimposition of automatic and controlled decision activations. The DMC has proven to capture the diversity of behavioral conflict effects across various task contexts. This study combined DMC predictions with EEG and EMG measurements to test a set of linking propositions that specify the relationship between theoretical decision-making mechanisms involved in the Simon task and brain activity. Our results are consistent with a representation of the superimposed decision variable in the primary motor cortices. The decision variable was also observed in the EMG activity of response agonist muscles. These findings provide new insight into the neurophysiology of human decision-making. In return, they provide support for the DMC model framework.

How do persons with dementia participate in decision making related to health and daily care? A multi-case study

PubMed Central

2012-01-01

Background Many countries have passed laws giving patients the right to participate in decisions about health care. People with dementia cannot be assumed to be incapable of making decisions on their diagnosis alone as they may have retained cognitive abilities. The purpose of this study was to gain a better understanding of how persons with dementia participated in making decisions about health care and how their family carers and professional caregivers influenced decision making. Methods This Norwegian study had a qualitative multi-case design. The triad in each of the ten cases consisted of the person with dementia, the family carer and the professional caregiver, in all 30 participants. Inclusion criteria for the persons with dementia were: (1) 67 years or older (2) diagnosed with dementia (3) Clinical Dementia Rating score 2, moderate dementia; (3) able to communicate verbally. The family carers and professional caregivers were then asked to participate. A semi-structured interview guide was used in interviews with family carers and professional caregivers. Field notes were written after participant observation of interactions between persons with dementia and professional caregivers during morning care or activities at a day centre. How the professional caregivers facilitated decision making was the focus of the observations that varied in length from 30 to 90 minutes. The data were analyzed using framework analysis combined with a hermeneutical interpretive approach. Results Professional caregivers based their assessment of mental competence on experience and not on standardized tests. Persons with dementia demonstrated variability in how they participated in decision making. Pseudo-autonomous decision making and delegating decision making were new categories that emerged. Autonomous decision making did occur but shared decision making was the most typical pattern. Reduced mental capacity, lack of available choices or not being given the opportunity to participate led to non-involvement. Not all decisions were based on logic; personal values and relationships were also considered. Conclusions Persons with moderate dementia demonstrated variability in how they participated in decision making. Optimal involvement was facilitated by positioning them as capable of influencing decisions, assessing decision-specific competence, clarifying values and understanding the significance of relationships and context. PMID:22870952

Certainty, leaps of faith, and tradition: rethinking clinical interventions.

PubMed

Dzurec, L C

1998-12-01

Clinical decision making requires that clinicians think quickly and in ways that will foster optimal, safe client care. Tradition influences clinical decision making, enhancing efficiency of resulting nursing action; however, since many decisions must be based on data that are either uncertain, incomplete, or indirect, clinicians are readily ensnared in processes involving potentially faulty logic associated with tradition. The author addresses the tenacity of tradition and then focuses on three processes--consensus formation, the grounding of certainty in inductive reasoning, and affirming the consequent--that have affected clinical decision making. For some recipients of care, tradition has had a substantial and invalid influence on their ability to access care.

Prevention of and Early Intervention for Students with Emotional and Behavioral Disorders: Systems to Support Data-Based Decision Making

ERIC Educational Resources Information Center

Lewis, Timothy J.; Mitchell, Barbara S.

2012-01-01

Students with emotional and behavioral disorders are at great risk for long-term negative outcomes. Researchers and practitioners alike acknowledge the need for evidence-based, preventive, and early intervention strategies. Accordingly, in this chapter an expanded view of prevention is presented as a series of data driven decisions to guide…

Breast cancer patients' use of health information in decision making and coping.

PubMed

Radina, M Elise; Ginter, Amanda C; Brandt, Julie; Swaney, Jan; Longo, Daniel R

2011-01-01

Breast cancer patients are some of today's most proactive healthcare consumers. Given how the media has highlighted the many issues involved in breast cancer, the unprecedented rise of consumerism in general, and the rise of healthcare consumerism specifically, a plethora of information on breast cancer has emerged in both scientific and popular media. It is timely and appropriate to consider breast cancer patients' perspectives regarding their search for health-related information and its use for treatment decision making and coping. The present study explores health information-seeking behaviors (passive and active), use of health information, sources of health information, and how such information is or is not used in patients' decision making about their treatment. This study used a secondary analysis of data regarding health information-seeking behaviors and treatment decisions from 2 separate but compatible qualitative data sets based on in-depth interviews with a total of 35 breast cancer survivors. Data were analyzed using thematic analysis. The majority of participating women were active information seekers (n = 26). Of the subsets of women who described their level of involvement in treatment decision making, the largest number (n = 13) reported a shared responsibility for decision making with their physician, and the next largest subset (n = 9) reported making the final decision themselves. These findings provide an enhanced understanding of the preferred source and method of delivery of information given health information-seeking behaviors and decision-making strategies. How health information is delivered in the future given these findings is discussed with specific attention to matching patient preferences with delivery methods to potentially enhance patients' sense of agency with regard to treatment, which has been shown to improve patients' psychosocial outcomes.

An Information Theoretic Approach for Measuring Data Discovery and Utilization During Analytical and Decision Making Processes

DTIC Science & Technology

2015-07-31

and make the expected decision outcomes. The scenario is based around a scripted storyboard where an organized crime network is operating in a city to...interdicted by law enforcement to disrupt the network. The scenario storyboard was used to develop a probabilistic vehicle traffic model in order to

Supporting Valid Decision Making: Uses and Misuses of Assessment Data within the Context of RtI

ERIC Educational Resources Information Center

Ball, Carrie R.; Christ, Theodore J.

2012-01-01

Within an RtI problem-solving context, assessment and decision making generally center around the tasks of problem identification, problem analysis, progress monitoring, and program evaluation. We use this framework to discuss the current state of the literature regarding curriculum based measurement, its technical properties, and its utility for…

Parent Decision-Making When Selecting Schools: The Case of Nepal

ERIC Educational Resources Information Center

Joshi, Priyadarshani

2014-01-01

This paper analyzes the parent decision-making processes underlying school selection in Nepal. The analysis is based on primary survey and focus group data collected from parent meetings in diverse local education markets in two districts of Nepal in 2011. It highlights three main arguments that are less frequently discussed in the context of…

Using a model and forecasted weather to predict forage and livestock production for making stocking decisions in the coming growing season

USDA-ARS?s Scientific Manuscript database

Forecasting peak standing crop (PSC) for the coming grazing season can help ranchers make appropriate stocking decisions to reduce enterprise risks. Previously developed PSC predictors were based on short-term experimental data (<15 yr) and limited stocking rates (SR) without including the effect of...

Potential for Improved Crop Yield Prediction Through Assimilation of Satellite-Derived Soil Moisture Data

USDA-ARS?s Scientific Manuscript database

Crop yield estimates have a strong impact on dealing with food shortages and on market demand and supply; these estimates are critical for decision-making processes by the U.S. Government, policy makers, stakeholders, etc. Most of the decision making is based on forecasts provided by the U.S. Depart...

32 CFR Appendix E to Part 806b - Privacy Impact Assessment

Code of Federal Regulations, 2010 CFR

2010-07-01

... in order to assure fairness to the individual in making decisions based on the data. Maintenance of.... The process consists of privacy training, gathering data from a project on privacy issues, and... analyzed and decisions are being made about data usage and system design. This applies to all of the...

Hands-On Learning: A Problem-Based Approach to Teaching Microsoft Excel

ERIC Educational Resources Information Center

Slayter, Erik; Higgins, Lindsey M.

2018-01-01

The development of a student's ability to make data-driven decisions has become a focus in higher education (Schield 1999; Stephenson and Caravello 2007). Data literacy, the ability to understand and use data to effectively inform decisions, is a fundamental component of information competence (Mandinach and Gummer 2013; Stephenson and Caravello,…

An Investigation of Data Overload in Team-Based Distributed Cognition Systems

ERIC Educational Resources Information Center

Hellar, David Benjamin

2009-01-01

The modern military command center is a hybrid system of computer automated surveillance and human oriented decision making. In these distributed cognition systems, data overload refers simultaneously to the glut of raw data processed by information technology systems and the dearth of actionable knowledge useful to human decision makers.…

A Multicriteria Decision Making Approach for Estimating the Number of Clusters in a Data Set

PubMed Central

Peng, Yi; Zhang, Yong; Kou, Gang; Shi, Yong

2012-01-01

Determining the number of clusters in a data set is an essential yet difficult step in cluster analysis. Since this task involves more than one criterion, it can be modeled as a multiple criteria decision making (MCDM) problem. This paper proposes a multiple criteria decision making (MCDM)-based approach to estimate the number of clusters for a given data set. In this approach, MCDM methods consider different numbers of clusters as alternatives and the outputs of any clustering algorithm on validity measures as criteria. The proposed method is examined by an experimental study using three MCDM methods, the well-known clustering algorithm–k-means, ten relative measures, and fifteen public-domain UCI machine learning data sets. The results show that MCDM methods work fairly well in estimating the number of clusters in the data and outperform the ten relative measures considered in the study. PMID:22870181

Pain relief in labour: a qualitative study to determine how to support women to make decisions about pain relief in labour

PubMed Central

2014-01-01

Background Engagement in decision making is a key priority of modern healthcare. Women are encouraged to make decisions about pain relief in labour in the ante-natal period based upon their expectations of what labour pain will be like. Many women find this planning difficult. The aim of this qualitative study was to explore how women can be better supported in preparing for, and making, decisions during pregnancy and labour regarding pain management. Methods Semi-structured interviews were conducted with 13 primiparous and 10 multiparous women at 36 weeks of pregnancy and again within six weeks postnatally. Data collection and analysis occurred concurrently to identify key themes. Results Three main themes emerged from the data. Firstly, during pregnancy women expressed a degree of uncertainty about the level of pain they would experience in labour and the effect of different methods of pain relief. Secondly, women reflected on how decisions had been made regarding pain management in labour and the degree to which they had felt comfortable making these decisions. Finally, women discussed their perceived levels of control, both desired and experienced, over both their bodies and the decisions they were making. Conclusion This study suggests that the current approach of antenatal preparation in the NHS, of asking women to make decisions antenatally for pain relief in labour, needs reviewing. It would be more beneficial to concentrate efforts on better informing women and on engaging them in discussions around their values, expectations and preferences and how these affect each specific choice rather than expecting them to make to make firm decisions in advance of such an unpredictable event as labour. PMID:24397421

Leadership of risk decision making in a complex, technology organization: The deliberative decision making model

NASA Astrophysics Data System (ADS)

Flaming, Susan C.

2007-12-01

The continuing saga of satellite technology development is as much a story of successful risk management as of innovative engineering. How do program leaders on complex, technology projects manage high stakes risks that threaten business success and satellite performance? This grounded theory study of risk decision making portrays decision leadership practices at one communication satellite company. Integrated product team (IPT) leaders of multi-million dollar programs were interviewed and observed to develop an extensive description of the leadership skills required to navigate organizational influences and drive challenging risk decisions to closure. Based on the study's findings the researcher proposes a new decision making model, Deliberative Decision Making, to describe the program leaders' cognitive and organizational leadership practices. This Deliberative Model extends the insights of prominent decision making models including the rational (or classical) and the naturalistic and qualifies claims made by bounded rationality theory. The Deliberative Model describes how leaders proactively engage resources to play a variety of decision leadership roles. The Model incorporates six distinct types of leadership decision activities, undertaken in varying sequence based on the challenges posed by specific risks. Novel features of the Deliberative Decision Model include: an inventory of leadership methods for managing task challenges, potential stakeholder bias and debates; four types of leadership meta-decisions that guide decision processes, and aligned organizational culture. Both supporting and constraining organizational influences were observed as leaders managed major risks, requiring active leadership on the most difficult decisions. Although the company's engineering culture emphasized the importance of data-based decisions, the uncertainties intrinsic to satellite risks required expert engineering judgment to be exercised throughout. An investigation into the co-variation of decision methods with uncertainty suggests that perceived risk severity may serve as a robust indicator for choices about decision practices. The Deliberative Decision processes incorporate multiple organizational and cultural controls as cross-checks to mitigate potential parochial bias of individuals, stakeholder groups, or leaders. Overall the Deliberative Decision framework describes how expert leadership practices, supportive organizational systems along with aligned cultural values and behavioral norms help leaders drive high stakes risk decisions to closure in this complex, advanced-technology setting.

Patients’ priorities for treatment decision making during periods of incapacity: quantitative survey

PubMed Central

RID, ANNETTE; WESLEY, ROBERT; PAVLICK, MARK; MAYNARD, SHARON; ROTH, KATALIN; WENDLER, DAVID

2017-01-01

Objective Clinical practice aims to respect patient autonomy by basing treatment decisions for incapacitated patients on their own preferences. Yet many patients do not complete an advance directive, and those who do frequently just designate a family member to make decisions for them. This finding raises the concern that clinical practice may be based on a mistaken understanding of patient priorities. The present study aimed to collect systematic data on how patients prioritize the goals of treatment decision making. Method We employed a self-administered, quantitative survey of patients in a tertiary care center. Results Some 80% or more of the 1169 respondents (response rate = 59.8%) ranked six of eight listed goals for treatment decision making as important. When asked which goal was most important, 38.8% identified obtaining desired or avoiding unwanted treatments, 20.0% identified minimizing stress or financial burden on their family, and 14.6% identified having their family help to make treatment decisions. No single goal was designated as most important by 25.0% of participants. Significance of Results Patients endorsed three primary goals with respect to decision making during periods of incapacity: being treated consistent with their own preferences; minimizing the burden on their family; and involving their family in the decision-making process. However, no single goal was prioritized by a clear majority of patients. These findings suggest that advance care planning should not be limited to documenting patients’ treatment preferences. Clinicians should also discuss and document patients’ priorities for how decisions are to be made. Moreover, future research should evaluate ways to modify current practice to promote all three of patients primary goals for treatment decision making. PMID:25273677

Patients' priorities for treatment decision making during periods of incapacity: quantitative survey.

PubMed

Rid, Annette; Wesley, Robert; Pavlick, Mark; Maynard, Sharon; Roth, Katalin; Wendler, David

2015-10-01

Clinical practice aims to respect patient autonomy by basing treatment decisions for incapacitated patients on their own preferences. Yet many patients do not complete an advance directive, and those who do frequently just designate a family member to make decisions for them. This finding raises the concern that clinical practice may be based on a mistaken understanding of patient priorities. The present study aimed to collect systematic data on how patients prioritize the goals of treatment decision making. We employed a self-administered, quantitative survey of patients in a tertiary care center. Some 80% or more of the 1169 respondents (response rate = 59.8%) ranked six of eight listed goals for treatment decision making as important. When asked which goal was most important, 38.8% identified obtaining desired or avoiding unwanted treatments, 20.0% identified minimizing stress or financial burden on their family, and 14.6% identified having their family help to make treatment decisions. No single goal was designated as most important by 25.0% of participants. Patients endorsed three primary goals with respect to decision making during periods of incapacity: being treated consistent with their own preferences; minimizing the burden on their family; and involving their family in the decision-making process. However, no single goal was prioritized by a clear majority of patients. These findings suggest that advance care planning should not be limited to documenting patients' treatment preferences. Clinicians should also discuss and document patients' priorities for how decisions are to be made. Moreover, future research should evaluate ways to modify current practice to promote all three of patients primary goals for treatment decision making.

An integrated experiment for identification of best decision styles and teamworks with respect to HSE and ergonomics program: The case of a large oil refinery.

PubMed

Azadeh, A; Mokhtari, Z; Sharahi, Z Jiryaei; Zarrin, M

2015-12-01

Decision making failure is a predominant human error in emergency situations. To demonstrate the subject model, operators of an oil refinery were asked to answer a health, safety and environment HSE-decision styles (DS) questionnaire. In order to achieve this purpose, qualitative indicators in HSE and ergonomics domain have been collected. Decision styles, related to the questions, have been selected based on Driver taxonomy of human decision making approach. Teamwork efficiency has been assessed based on different decision style combinations. The efficiency has been ranked based on HSE performance. Results revealed that efficient decision styles resulted from data envelopment analysis (DEA) optimization model is consistent with the plant's dominant styles. Therefore, improvement in system performance could be achieved using the best operator for critical posts or in team arrangements. This is the first study that identifies the best decision styles with respect to HSE and ergonomics factors. Copyright © 2015 Elsevier Ltd. All rights reserved.

Factual Approach in Decision Making - the Prerequisite of Success in Quality Management

NASA Astrophysics Data System (ADS)

Kučerová, Marta; Škůrková Lestyánszka, Katarína

2013-12-01

In quality management system as well as in other managerial systems, effective decisions must be always based on the data and information analysis, i.e. based on facts, in accordance with the factual approach principle in quality management. It is therefore necessary to measure and collect the data and information about processes. The article presents the results of a conducted survey, which was focused on application of factual approach in decision making. It also offers suggestions for improvements of application of the principle in business practice. This article was prepared using the research results of VEGA project No. 1/0229/08 "Perspectives of the quality management development in relation to the requirements of market in the Slovak Republic".

Communication-based behaviour support for adults with intellectual disabilities receiving dental care: A focus group study exploring dentists' decision-making and communication.

PubMed

Phadraig, Caoimhin Mac Giolla; Griffiths, Colin; McCallion, Philip; McCarron, Mary; Nunn, June

2017-01-01

A better understanding of how communication-based behaviour supports are applied with adults with intellectual disabilities may reduce reliance on restrictive practices such as holding, sedation and anaesthesia in dentistry. In this study, we explore how communication is used by dentists who provide treatment for adults with intellectual disabilities. A descriptive qualitative study, adopting synchronous online focus groups, was undertaken with six expert dentists in Ireland. Members were contacted again in pairs or individually for further data collection, analysed using thematic content analysis. Two relevant categories emerged from the data, relating to the selection and application of communication-based behaviour support for adults with intellectual disabilities. Decision-making processes were explored. Building on these categories, a co-regulating process of communication emerged as the means by which dentists iteratively apply and adapt communicative strategies. This exploration revealed rationalist and intuitive decision-making. Implications for education, practice and research are identified.

[The role of information in public health decision-making].

PubMed

Cecchi, Catherine

2008-01-01

Public health, prevention, health education and health promotion are inseparable from the concepts of information and communication. Information should respond as much as possible to the needs of professionals, decision-makers, and consumers who are more and more concerned and conscious of its importance in light of "information overload", various dissemination channels and the multiplicity of its sources. There are numerous issues at stake ranging from comprehension, to the validation of health information, health education, health promotion, prevention, decision-making, as well as issues related to knowledge and power. Irrespective of the type of choice to be made, the need for information, knowledge, and know-how is inseparable from that of other tools or regulatory measures required for decision-making. Information is the same as competence, epidemiological and population data, health data, scientific opinion, and expert conferences--all are needed to assist in decision-making. Based on the principle of precaution, information must increasingly take into account the rejection of a society which often reasons on the basis of a presumption of zero-risk, in an idealistic manner, and which also excludes the possibility of new risks. The consumer positions himself as the regulator of decisions, specifically those with regard to the notion of acceptable level of risk. All of the actors involved in the health system are or become at one moment or another public health decision-makers. Their decision might be based either on an analytical approach, or on an intuitive approach. Although the act of decision-making is the least visible part of public health policy, it is certainly the driving force. This process should integrate the perspective of all of the relevant players, including consumers, who are currently situated more and more frequently at the heart of the health system. Public health decision-making is conducted as a function of political, strategic and environmental issues; of lobbies and their power; and of social maturation. Decision-making is a necessity. Making the right choice at the right time requires high quality information, and it is often necessary to respect a certain amount of time for reflection and ripening of an issue in order to make the best possible decision. The media and consumers play an increasingly significant role in public health decision-making and in the ensuing legislative consequences and debates which come as a result. Access to information is changing, especially thanks to the Internet which is completely modifying the global scenery of knowledge and know-how. Information supports decision-making with calculated risk, and it offers the opportunity to make choices and decisions, recognising that "to choose, is sometimes to relinquish".

The Effects of Safety Information on Aeronautical Decision Making

NASA Technical Reports Server (NTRS)

Lee, Jang R.; Fanjoy, Richard O.; Dillman, Brian G.

2005-01-01

The importance of aeronautical decision making (ADM) has been considered one of the most critical issues of flight education for future professional pilots. Researchers have suggested that a safety information system based on information from incidents and near misses is an important tool to improve the intelligence and readiness of pilots. This paper describes a study that examines the effect of safety information on aeronautical decision making for students in a collegiate flight program. Data was collected from study participants who were exposed to periodic information about local aircraft malfunctions. Participants were then evaluated using a flight simulator profile and a pen and pencil test of situational judgment. Findings suggest that regular access to the described safety information program significantly improves decision making of student pilots.

Making the case for evidence-based design in healthcare: a descriptive case study of organizational decision making.

PubMed

Shoemaker, Lorie K; Kazley, Abby Swanson; White, Andrea

2010-01-01

The aim of this study was to describe the organizational decision-making process used in the selection of evidence-based design (EBD) concepts, the criteria used to make these decisions, and the extent to which leadership style may have influenced the decision-making process. Five research questions were formulated to frame the direction of this study, including: (1) How did healthcare leaders learn of innovations in design? (2) How did healthcare leaders make decisions in the selection of healthcare design concepts? (3) What criteria did healthcare leaders use in the decision-making process? (4) How did healthcare leaders consider input from the staff in design decisions? and (5) To what extent did the leadership style of administrators affect the outcomes of the decision-making process? Current issues affecting healthcare in the community led the principal investigator's organization to undertake an ambitious facilities expansion project. As part of its planning process, the organization learned of EBD principles that seemingly had a positive impact on patient care and safety and staff working conditions. Although promising, a paucity of empirical research addressed the cost/benefit of incorporating many EBD concepts into one hospital setting, and there was no research that articulated the organizational decision-making process used by healthcare administrators when considering the use of EBD in expansion projects. A mixed-method, descriptive, qualitative, single-case study and quantitative design were used to address the five research questions. The Systems Research Organizing Model provided the theoretical framework. A variety of data collection methods was used, including interviews of key respondents, the review of documentary evidence, and the Multifactor Leadership Questionnaire. A participatory process was used throughout the design decision phases, involving staff at all levels of the organization. The Internet and architects facilitated learning about EBD. Financial considerations were a factor in decision making. The prevalence of the transformational leadership style among the organization's administrators exceeded the U.S. mean.

Decision Support Systems and the Conflict Model of Decision Making: A Stimulus for New Computer-Assisted Careers Guidance Systems.

ERIC Educational Resources Information Center

Ballantine, R. Malcolm

Decision Support Systems (DSSs) are computer-based decision aids to use when making decisions which are partially amenable to rational decision-making procedures but contain elements where intuitive judgment is an essential component. In such situations, DSSs are used to improve the quality of decision-making. The DSS approach is based on Simon's…

Evidence-based management - healthcare manager viewpoints.

PubMed

Janati, Ali; Hasanpoor, Edris; Hajebrahimi, Sakineh; Sadeghi-Bazargani, Homayoun

2018-06-11

Purpose Hospital manager decisions can have a significant impact on service effectiveness and hospital success, so using an evidence-based approach can improve hospital management. The purpose of this paper is to identify evidence-based management (EBMgt) components and challenges. Consequently, the authors provide an improving evidence-based decision-making framework. Design/methodology/approach A total of 45 semi-structured interviews were conducted in 2016. The authors also established three focus group discussions with health service managers. Data analysis followed deductive qualitative analysis guidelines. Findings Four basic themes emerged from the interviews, including EBMgt evidence sources (including sub-themes: scientific and research evidence, facts and information, political-social development plans, managers' professional expertise and ethical-moral evidence); predictors (sub-themes: stakeholder values and expectations, functional behavior, knowledge, key competencies and skill, evidence sources, evidence levels, uses and benefits and government programs); EBMgt barriers (sub-themes: managers' personal characteristics, decision-making environment, training and research system and organizational issues); and evidence-based hospital management processes (sub-themes: asking, acquiring, appraising, aggregating, applying and assessing). Originality/value Findings suggest that most participants have positive EBMgt attitudes. A full evidence-based hospital manager is a person who uses all evidence sources in a six-step decision-making process. EBMgt frameworks are a good tool to manage healthcare organizations. The authors found factors affecting hospital EBMgt and identified six evidence sources that healthcare managers can use in evidence-based decision-making processes.

Using statistical process control to make data-based clinical decisions.

PubMed

Pfadt, A; Wheeler, D J

1995-01-01

Applied behavior analysis is based on an investigation of variability due to interrelationships among antecedents, behavior, and consequences. This permits testable hypotheses about the causes of behavior as well as for the course of treatment to be evaluated empirically. Such information provides corrective feedback for making data-based clinical decisions. This paper considers how a different approach to the analysis of variability based on the writings of Walter Shewart and W. Edwards Deming in the area of industrial quality control helps to achieve similar objectives. Statistical process control (SPC) was developed to implement a process of continual product improvement while achieving compliance with production standards and other requirements for promoting customer satisfaction. SPC involves the use of simple statistical tools, such as histograms and control charts, as well as problem-solving techniques, such as flow charts, cause-and-effect diagrams, and Pareto charts, to implement Deming's management philosophy. These data-analytic procedures can be incorporated into a human service organization to help to achieve its stated objectives in a manner that leads to continuous improvement in the functioning of the clients who are its customers. Examples are provided to illustrate how SPC procedures can be used to analyze behavioral data. Issues related to the application of these tools for making data-based clinical decisions and for creating an organizational climate that promotes their routine use in applied settings are also considered.

Understandings of the nature of science and decision making on science and technology-based issues

NASA Astrophysics Data System (ADS)

Bell, Randy Lee

Current reforms emphasize the development of scientific literacy as the principal goal of science education. The nature of science is considered a critical component of scientific literacy and is assumed to be an important factor in decision making on science and technology based issues. However, little research exists that delineates the role of the nature of science in decision making. The purpose of this investigation was to explicate the role of the nature of science in decision making on science and technology based issues and to delineate the reasoning and factors associated with these types of decisions. The 15-item, open-ended "Decision Making Questionnaire" (DMQ) based on four different scenarios concerning science and technology issues was developed to assess decision making. Twenty-one volunteer participants purposively selected from the faculty of geographically diverse universities completed the questionnaire and follow-up interviews. Participants were subsequently grouped according to their understandings of the nature of science, based on responses to a second open-ended questionnaire and follow-up interview. Profiles of each group's decision making were constructed, based on their previous responses to the DMQ and follow-up interviews. Finally, the two groups' decisions, decision making factors, and decision making strategies were compared. No differences were found between the decisions of the two groups, despite their disparate views of the nature of science. While their reasoning did not follow formal lines of argumentation, several influencing factors and general reasoning patterns were identified. Participants in both groups based their decisions primarily on personal values, morals/ethics, and social concerns. While all participants said they considered scientific evidence in their decision making, most did not require absolute "proof," even though Group B participants held more absolute conceptions of the nature of science. Overall, the nature of science did not figure prominently in either group's decisions. These findings contrast with the assumptions of the science education community and current reform efforts and call for a reexamination of the goals of nature of science instruction. Developing better decision making skills---even on science and technology based issues---may involve other factors, including more values-based instruction and attention to intellectual/moral development.

Rationality versus reality: the challenges of evidence-based decision making for health policy makers

PubMed Central

2010-01-01

Background Current healthcare systems have extended the evidence-based medicine (EBM) approach to health policy and delivery decisions, such as access-to-care, healthcare funding and health program continuance, through attempts to integrate valid and reliable evidence into the decision making process. These policy decisions have major impacts on society and have high personal and financial costs associated with those decisions. Decision models such as these function under a shared assumption of rational choice and utility maximization in the decision-making process. Discussion We contend that health policy decision makers are generally unable to attain the basic goals of evidence-based decision making (EBDM) and evidence-based policy making (EBPM) because humans make decisions with their naturally limited, faulty, and biased decision-making processes. A cognitive information processing framework is presented to support this argument, and subtle cognitive processing mechanisms are introduced to support the focal thesis: health policy makers' decisions are influenced by the subjective manner in which they individually process decision-relevant information rather than on the objective merits of the evidence alone. As such, subsequent health policy decisions do not necessarily achieve the goals of evidence-based policy making, such as maximizing health outcomes for society based on valid and reliable research evidence. Summary In this era of increasing adoption of evidence-based healthcare models, the rational choice, utility maximizing assumptions in EBDM and EBPM, must be critically evaluated to ensure effective and high-quality health policy decisions. The cognitive information processing framework presented here will aid health policy decision makers by identifying how their decisions might be subtly influenced by non-rational factors. In this paper, we identify some of the biases and potential intervention points and provide some initial suggestions about how the EBDM/EBPM process can be improved. PMID:20504357

Rationality versus reality: the challenges of evidence-based decision making for health policy makers.

PubMed

McCaughey, Deirdre; Bruning, Nealia S

2010-05-26

Current healthcare systems have extended the evidence-based medicine (EBM) approach to health policy and delivery decisions, such as access-to-care, healthcare funding and health program continuance, through attempts to integrate valid and reliable evidence into the decision making process. These policy decisions have major impacts on society and have high personal and financial costs associated with those decisions. Decision models such as these function under a shared assumption of rational choice and utility maximization in the decision-making process. We contend that health policy decision makers are generally unable to attain the basic goals of evidence-based decision making (EBDM) and evidence-based policy making (EBPM) because humans make decisions with their naturally limited, faulty, and biased decision-making processes. A cognitive information processing framework is presented to support this argument, and subtle cognitive processing mechanisms are introduced to support the focal thesis: health policy makers' decisions are influenced by the subjective manner in which they individually process decision-relevant information rather than on the objective merits of the evidence alone. As such, subsequent health policy decisions do not necessarily achieve the goals of evidence-based policy making, such as maximizing health outcomes for society based on valid and reliable research evidence. In this era of increasing adoption of evidence-based healthcare models, the rational choice, utility maximizing assumptions in EBDM and EBPM, must be critically evaluated to ensure effective and high-quality health policy decisions. The cognitive information processing framework presented here will aid health policy decision makers by identifying how their decisions might be subtly influenced by non-rational factors. In this paper, we identify some of the biases and potential intervention points and provide some initial suggestions about how the EBDM/EBPM process can be improved.

Multi-criteria clinical decision support: A primer on the use of multiple criteria decision making methods to promote evidence-based, patient-centered healthcare

PubMed Central

Dolan, James G.

2010-01-01

Current models of healthcare quality recommend that patient management decisions be evidence-based and patient-centered. Evidence-based decisions require a thorough understanding of current information regarding the natural history of disease and the anticipated outcomes of different management options. Patient-centered decisions incorporate patient preferences, values, and unique personal circumstances into the decision making process and actively involve both patients along with health care providers as much as possible. Fundamentally, therefore, evidence-based, patient-centered decisions are multi-dimensional and typically involve multiple decision makers. Advances in the decision sciences have led to the development of a number of multiple criteria decision making methods. These multi-criteria methods are designed to help people make better choices when faced with complex decisions involving several dimensions. They are especially helpful when there is a need to combine “hard data” with subjective preferences, to make trade-offs between desired outcomes, and to involve multiple decision makers. Evidence-based, patient-centered clinical decision making has all of these characteristics. This close match suggests that clinical decision support systems based on multi-criteria decision making techniques have the potential to enable patients and providers to carry out the tasks required to implement evidence-based, patient-centered care effectively and efficiently in clinical settings. The goal of this paper is to give readers a general introduction to the range of multi-criteria methods available and show how they could be used to support clinical decision-making. Methods discussed include the balance sheet, the even swap method, ordinal ranking methods, direct weighting methods, multi-attribute decision analysis, and the analytic hierarchy process (AHP) PMID:21394218

A Briefing on Metrics and Risks for Autonomous Decision-Making in Aerospace Applications

NASA Technical Reports Server (NTRS)

Frost, Susan; Goebel, Kai Frank; Galvan, Jose Ramon

2012-01-01

Significant technology advances will enable future aerospace systems to safely and reliably make decisions autonomously, or without human interaction. The decision-making may result in actions that enable an aircraft or spacecraft in an off-nominal state or with slightly degraded components to achieve mission performance and safety goals while reducing or avoiding damage to the aircraft or spacecraft. Some key technology enablers for autonomous decision-making include: a continuous state awareness through the maturation of the prognostics health management field, novel sensor development, and the considerable gains made in computation power and data processing bandwidth versus system size. Sophisticated algorithms and physics based models coupled with these technological advances allow reliable assessment of a system, subsystem, or components. Decisions that balance mission objectives and constraints with remaining useful life predictions can be made autonomously to maintain safety requirements, optimal performance, and ensure mission objectives. This autonomous approach to decision-making will come with new risks and benefits, some of which will be examined in this paper. To start, an account of previous work to categorize or quantify autonomy in aerospace systems will be presented. In addition, a survey of perceived risks in autonomous decision-making in the context of piloted aircraft and remotely piloted or completely autonomous unmanned autonomous systems (UAS) will be presented based on interviews that were conducted with individuals from industry, academia, and government.

Initiating decision-making conversations in palliative care: an ethnographic discourse analysis.

PubMed

Bélanger, Emmanuelle; Rodríguez, Charo; Groleau, Danielle; Légaré, France; Macdonald, Mary Ellen; Marchand, Robert

2014-01-01

Conversations about end-of-life care remain challenging for health care providers. The tendency to delay conversations about care options represents a barrier that impedes the ability of terminally-ill patients to participate in decision-making. Family physicians with a palliative care practice are often responsible for discussing end-of-life care preferences with patients, yet there is a paucity of research directly observing these interactions. In this study, we sought to explore how patients and family physicians initiated decision-making conversations in the context of a community hospital-based palliative care service. This qualitative study combined discourse analysis with ethnographic methods. The field research lasted one year, and data were generated through participant observation and audio-recordings of consultations. A total of 101 consultations were observed longitudinally between 18 patients, 6 family physicians and 2 pivot nurses. Data analysis consisted in exploring the different types of discourses initiating decision-making conversations and how these discourses were affected by the organizational context in which they took place. The organization of care had an impact on decision-making conversations. The timing and origin of referrals to palliative care shaped whether patients were still able to participate in decision-making, and the decisions that remained to be made. The type of decisions to be made also shaped how conversations were initiated. Family physicians introduced decision-making conversations about issues needing immediate attention, such as symptom management, by directly addressing or eliciting patients' complaints. When decisions involved discussing impending death, decision-making conversations were initiated either indirectly, by prompting the patients to express their understanding of the disease and its progression, or directly, by providing a justification for broaching a difficult topic. Decision-making conversations and the initiation thereof were framed by the organization of care and the referral process prior to initial encounters. While symptom management was taken for granted as part of health care professionals' expected role, engaging in decisions regarding preparation for death implicitly remained under patients' control. This work makes important clinical contributions by exposing the rhetorical function of family physicians' discourse when introducing palliative care decisions.

What Do the Stats Tell Us? Engaging Elementary Children in Probabilistic Reasoning Based on Data Analysis

ERIC Educational Resources Information Center

Hourigan, Mairéad; Leavy, Aisling

2016-01-01

As part of Japanese Lesson study research focusing on "comparing and describing likelihoods", fifth grade elementary students used real-world data in decision-making. Sporting statistics facilitated opportunities for informal inference, where data were used to make and justify predictions.

Podium: Ranking Data Using Mixed-Initiative Visual Analytics.

PubMed

Wall, Emily; Das, Subhajit; Chawla, Ravish; Kalidindi, Bharath; Brown, Eli T; Endert, Alex

2018-01-01

People often rank and order data points as a vital part of making decisions. Multi-attribute ranking systems are a common tool used to make these data-driven decisions. Such systems often take the form of a table-based visualization in which users assign weights to the attributes representing the quantifiable importance of each attribute to a decision, which the system then uses to compute a ranking of the data. However, these systems assume that users are able to quantify their conceptual understanding of how important particular attributes are to a decision. This is not always easy or even possible for users to do. Rather, people often have a more holistic understanding of the data. They form opinions that data point A is better than data point B but do not necessarily know which attributes are important. To address these challenges, we present a visual analytic application to help people rank multi-variate data points. We developed a prototype system, Podium, that allows users to drag rows in the table to rank order data points based on their perception of the relative value of the data. Podium then infers a weighting model using Ranking SVM that satisfies the user's data preferences as closely as possible. Whereas past systems help users understand the relationships between data points based on changes to attribute weights, our approach helps users to understand the attributes that might inform their understanding of the data. We present two usage scenarios to describe some of the potential uses of our proposed technique: (1) understanding which attributes contribute to a user's subjective preferences for data, and (2) deconstructing attributes of importance for existing rankings. Our proposed approach makes powerful machine learning techniques more usable to those who may not have expertise in these areas.

Current Use of Evidence-Based Medicine in Pediatric Spine Surgery.

PubMed

Oetgen, Matthew E

2018-04-01

Evidence-based medicine (EBM) is a process of decision-making aimed at making the best clinical decisions as they relate to patients' health. The current use of EBM in pediatric spine surgery is varied, based mainly on the availability of high-quality data. The use of EBM is limited in idiopathic scoliosis, whereas EBM has been used to investigate the treatment of pediatric spondylolysis. Studies on early onset scoliosis are of low quality, making EBM difficult in this condition. Future focus and commitment to study quality in pediatric spinal surgery will likely increase the role of EBM in these conditions. Copyright © 2017 Elsevier Inc. All rights reserved.

Wishful Thinking? Inside the Black Box of Exposure Assessment.

PubMed

Money, Annemarie; Robinson, Christine; Agius, Raymond; de Vocht, Frank

2016-05-01

Decision-making processes used by experts when undertaking occupational exposure assessment are relatively unknown, but it is often assumed that there is a common underlying method that experts employ. However, differences in training and experience of assessors make it unlikely that one general method for expert assessment would exist. Therefore, there are concerns about formalizing, validating, and comparing expert estimates within and between studies that are difficult, if not impossible, to characterize. Heuristics on the other hand (the processes involved in decision making) have been extensively studied. Heuristics are deployed by everyone as short-cuts to make the often complex process of decision-making simpler, quicker, and less burdensome. Experts' assessments are often subject to various simplifying heuristics as a way to reach a decision in the absence of sufficient data. Therefore, investigating the underlying heuristics or decision-making processes involved may help to shed light on the 'black box' of exposure assessment. A mixed method study was conducted utilizing both a web-based exposure assessment exercise incorporating quantitative and semiqualitative elements of data collection, and qualitative semi-structured interviews with exposure assessors. Qualitative data were analyzed using thematic analysis. Twenty-five experts completed the web-based exposure assessment exercise and 8 of these 25 were randomly selected to participate in the follow-up interview. Familiar key themes relating to the exposure assessment exercise emerged; 'intensity'; 'probability'; 'agent'; 'process'; and 'duration' of exposure. However, an important aspect of the detailed follow-up interviews revealed a lack of structure and order with which participants described their decision making. Participants mostly described some form of an iterative process, heavily relying on the anchoring and adjustment heuristic, which differed between experts. In spite of having undertaken comparable training (in occupational hygiene or exposure assessment), experts use different methods to assess exposure. Decision making appears to be an iterative process with heavy reliance on the key heuristic of anchoring and adjustment. Using multiple experts to assess exposure while providing some form of anchoring scenario to build from, and additional training in understanding the impact of simple heuristics on the process of decision making, is likely to produce a more methodical approach to assessment; thereby improving consistency and transparency in expert exposure assessment. © The Author 2016. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.

Wishful Thinking? Inside the Black Box of Exposure Assessment

PubMed Central

Money, Annemarie; Robinson, Christine; Agius, Raymond; de Vocht, Frank

2016-01-01

Background: Decision-making processes used by experts when undertaking occupational exposure assessment are relatively unknown, but it is often assumed that there is a common underlying method that experts employ. However, differences in training and experience of assessors make it unlikely that one general method for expert assessment would exist. Therefore, there are concerns about formalizing, validating, and comparing expert estimates within and between studies that are difficult, if not impossible, to characterize. Heuristics on the other hand (the processes involved in decision making) have been extensively studied. Heuristics are deployed by everyone as short-cuts to make the often complex process of decision-making simpler, quicker, and less burdensome. Experts’ assessments are often subject to various simplifying heuristics as a way to reach a decision in the absence of sufficient data. Therefore, investigating the underlying heuristics or decision-making processes involved may help to shed light on the ‘black box’ of exposure assessment. Methods: A mixed method study was conducted utilizing both a web-based exposure assessment exercise incorporating quantitative and semiqualitative elements of data collection, and qualitative semi-structured interviews with exposure assessors. Qualitative data were analyzed using thematic analysis. Results: Twenty-five experts completed the web-based exposure assessment exercise and 8 of these 25 were randomly selected to participate in the follow-up interview. Familiar key themes relating to the exposure assessment exercise emerged; ‘intensity’; ‘probability’; ‘agent’; ‘process’; and ‘duration’ of exposure. However, an important aspect of the detailed follow-up interviews revealed a lack of structure and order with which participants described their decision making. Participants mostly described some form of an iterative process, heavily relying on the anchoring and adjustment heuristic, which differed between experts. Conclusion: In spite of having undertaken comparable training (in occupational hygiene or exposure assessment), experts use different methods to assess exposure. Decision making appears to be an iterative process with heavy reliance on the key heuristic of anchoring and adjustment. Using multiple experts to assess exposure while providing some form of anchoring scenario to build from, and additional training in understanding the impact of simple heuristics on the process of decision making, is likely to produce a more methodical approach to assessment; thereby improving consistency and transparency in expert exposure assessment. PMID:26764244

The Two-Communities Theory and Knowledge Utilization.

ERIC Educational Resources Information Center

Caplan, Nathan

1979-01-01

Discusses strategies to improve policy makers' utilization of research based on the "two-communities" theory that social scientists and policy makers live in two different worlds. Notes that for high level decision making, collaboration must involve more general problems and a decision to use either data-based or nonresearch knowledge for solving…

Limits to relational autonomy--the Singaporean experience.

PubMed

Krishna, Lalit Kumar Radha; Watkinson, Deborah S; Beng, Ng Lee

2015-05-01

Recognition that the Principle of Respect for Autonomy fails to work in family-centric societies such as Singapore has recently led to the promotion of relational autonomy as a suitable framework within which to place healthcare decision making. However, empirical data, relating to patient and family opinions and the practices of healthcare professionals in Confucian-inspired Singapore, demonstrate clear limitations on the ability of a relational autonomy framework to provide the anticipated compromise between prevailing family decision-making norms and adopted Western led atomistic concepts of autonomy. Evidence suggests that despite a growing infusion of Western influence, there is still little to indicate any major shift to individual decision making, particularly in light of the way society and healthcare are structured. Similarly, the lack of employing a shared decision-making model and data that discredit the notion that the complex psychosocial and cultural factors that affect the decision making may be considered "content neutral" not only prevents the application of relational autonomy but questions the viability of the values behind the Principle of Respect for Autonomy. Taking into account local data and drawing upon a wider concept of personhood that extends beyond prevailing family-centric ideals along with the complex interests that are focused upon the preservation of the unique nature of personhood that arises from the Ring Theory of Personhood, we propose and "operationalize" the employing of an authoritative welfare-based approach, within the confines of best interest decision making, to better meet the current care needs within Singapore. © The Author(s) 2014.

"If It Feels Right, Do It": Intuitive Decision Making in a Sample of High-Level Sport Coaches.

PubMed

Collins, Dave; Collins, Loel; Carson, Howie J

2016-01-01

Comprehensive understanding and application of decision making is important for the professional practice and status of sports coaches. Accordingly, building on a strong work base exploring the use of professional judgment and decision making (PJDM) in sport, we report a preliminary investigation into uses of intuition by high-level coaches. Two contrasting groups of high-level coaches from adventure sports (n = 10) and rugby union (n = 8), were interviewed on their experiences of using intuitive and deliberative decision making styles, the source of these skills, and the interaction between the two. Participants reported similarly high levels of usage to other professions. Interaction between the two styles was apparent to varying degrees, while the role of experience was seen as an important precursor to greater intuitive practice and employment. Initially intuitive then deliberate decision making was a particular feature, offering participants an immediate check on the accuracy and validity of the decision. Integration of these data with the extant literature and implications for practice are discussed.

A Web-based graphical user interface for evidence-based decision making for health care allocations in rural areas

PubMed Central

Schuurman, Nadine; Leight, Margo; Berube, Myriam

2008-01-01

Background The creation of successful health policy and location of resources increasingly relies on evidence-based decision-making. The development of intuitive, accessible tools to analyse, display and disseminate spatial data potentially provides the basis for sound policy and resource allocation decisions. As health services are rationalized, the development of tools such graphical user interfaces (GUIs) is especially valuable at they assist decision makers in allocating resources such that the maximum number of people are served. GIS can used to develop GUIs that enable spatial decision making. Results We have created a Web-based GUI (wGUI) to assist health policy makers and administrators in the Canadian province of British Columbia make well-informed decisions about the location and allocation of time-sensitive service capacities in rural regions of the province. This tool integrates datasets for existing hospitals and services, regional populations and road networks to allow users to ascertain the percentage of population in any given service catchment who are served by a specific health service, or baskets of linked services. The wGUI allows policy makers to map trauma and obstetric services against rural populations within pre-specified travel distances, illustrating service capacity by region. Conclusion The wGUI can be used by health policy makers and administrators with little or no formal GIS training to visualize multiple health resource allocation scenarios. The GUI is poised to become a critical decision-making tool especially as evidence is increasingly required for distribution of health services. PMID:18793428

Communicating with the Coroner: How Religion, Culture, and Family Concerns May Influence Autopsy Decision Making

ERIC Educational Resources Information Center

Carpenter, Belinda; Tait, Gordon; Adkins, Glenda; Barnes, Michael; Naylor, Charles; Begum, Nelufa

2011-01-01

Based on coronial data gathered in the state of Queensland in 2004, this article reviews how a change in legislation may have impacted autopsy decision making by coroners. More specifically, the authors evaluated whether the requirement that coronial autopsy orders specify the level of invasiveness of an autopsy to be performed by a pathologist…

Big Data & Learning Analytics: A Potential Way to Optimize eLearning Technological Tools

ERIC Educational Resources Information Center

García, Olga Arranz; Secades, Vidal Alonso

2013-01-01

In the information age, one of the most influential institutions is education. The recent emergence of MOOCS [Massively Open Online Courses] is a sample of the new expectations that are offered to university students. Basing decisions on data and evidence seems obvious, and indeed, research indicates that data-driven decision-making improves…

Nurses' decision-making process in cases of physical restraint in acute elderly care: a qualitative study.

PubMed

Goethals, S; Dierckx de Casterlé, B; Gastmans, C

2013-05-01

The increasing vulnerability of patients in acute elderly care requires constant critical reflection in ethically charged situations such as when employing physical restraint. Qualitative evidence concerning nurses' decision making in cases of physical restraint is limited and fragmented. A thorough understanding of nurses' decision-making process could be useful to understand how nurses reason and make decisions in ethically laden situations. The aims of this study were to explore and describe nurses' decision-making process in cases of physical restraint. We used a qualitative interview design inspired by the Grounded Theory approach. Data analysis was guided by the Qualitative Analysis Guide of Leuven. Twelve hospitals geographically spread throughout the five provinces of Flanders, Belgium. Twenty-one acute geriatric nurses interviewed between October 2009 and April 2011 were purposively and theoretically selected, with the aim of including nurses having a variety of characteristics and experiences concerning decisions on using physical restraint. In cases of physical restraint in acute elderly care, nurses' decision making was never experienced as a fixed decision but rather as a series of decisions. Decision making was mostly reasoned upon and based on rational arguments; however, decisions were also made routinely and intuitively. Some nurses felt very certain about their decisions, while others experienced feelings of uncertainty regarding their decisions. Nurses' decision making is an independent process that requires nurses to obtain a good picture of the patient, to be constantly observant, and to assess and reassess the patient's situation. Coming to thoughtful and individualized decisions requires major commitment and constant critical reflection. Copyright © 2012 Elsevier Ltd. All rights reserved.

Prospective Analysis of Decision Making During Joint Cardiology Cardiothoracic Conference in Treatment of 107 Consecutive Children with Congenital Heart Disease.

PubMed

Duignan, Sophie; Ryan, Aedin; O'Keeffe, Dara; Kenny, Damien; McMahon, Colin J

2018-05-12

The complexity and potential biases involved in decision making have long been recognised and examined in both the aviation and business industries. More recently, the medical community have started to explore this concept and its particular importance in our field. Paediatric cardiology is a rapidly expanding field and for many of the conditions we treat, there is limited evidence available to support our decision-making. Variability exists within decision-making in paediatric cardiology and this may influence outcomes. There are no validated tools available to support and examine consistent decision-making for various treatment strategies in children with congenital heart disease in a multidisciplinary cardiology and cardiothoracic institution. Our primary objective was to analyse the complexity of decision-making for children with cardiac conditions in the context of our joint cardiology and cardiothoracic conference (JCC). Two paediatric cardiologists acted as investigators by observing the weekly joint cardiology-cardiothoracic surgery conference and prospectively evaluating the degree of complexity of decision-making in the management of 107 sequential children with congenital heart disease discussed. Additionally, the group consensus on the same patients was prospectively assessed to compare this to the independent observers. Of 107 consecutive children discussed at our JCC conference 32 (27%) went on to receive surgical intervention, 20 (17%) underwent catheterisation and 65 (56%) received medical treatment. There were 53 (50%) cases rated as simple by one senior observer, while 54 (50%) were rated as complex to some degree. There was high inter-observer agreement with a Krippendorff's alpha of ≥ 0.8 between 2 observers and between 2 observers and the group consensus as a whole for grading of the complexity of decision-making. Different decisions were occasionally made on patients with the same data set. Discussions revisiting the same patient, in complex cases, resulted in different management decisions being reached in this series. Anchoring of decision-making was witnessed in certain cases. Potential application of decision making algorithms is discussed in making decisions in paediatric cardiology patients. Decision-making in our institution's joint cardiology-cardiothoracic conference proved to be complex in approximately half of our patients. Inconsistency in decision-making for patients with the same diagnosis, and different decisions made for the same complex patient at different time points confounds the reliability of the decision-making process. These novel data highlight the absence of evidence-based medicine for many decisions, occasional lack of consistency and the impact of anchoring, heuristics and other biases in complex cases. Validated decision-making algorithms may assist in providing consistency to decision-making in this setting.

Consumer Decision-Making Abilities and Long-Term Care Insurance Purchase.

PubMed

McGarry, Brian E; Tempkin-Greener, Helena; Grabowski, David C; Chapman, Benjamin P; Li, Yue

2018-04-16

To determine the impact of consumer decision-making abilities on making a long-term care insurance (LTCi) purchasing decision that is consistent with normative economic predictions regarding policy ownership. Using data from the Health and Retirement Study, multivariate analyses are implemented to estimate the effect of decision-making ability factors on owning LTCi. Stratified multivariate analyses are used to examine the effect of decision-making abilities on the likelihood of adhering to economic predictions of LTCi ownership. In the full sample, better cognitive capacity was found to significantly increase the odds of ownership. When the sample was stratified based on expected LTCi ownership status, cognitive capacity was positively associated with ownership among those predicted to own and negatively associated with ownership among those predicted not to own who could likely afford a policy. Consumer decision-making abilities, specifically cognitive capacity, are an important determinant of LTCi decision outcomes. Deficits in this ability may prevent individuals from successfully preparing for future long-term care expenses. Policy makers should consider changes that reduce the cognitive burden of this choice, including the standardization of the LTCi market, the provision of consumer decision aids, and alternatives to voluntary and private insuring mechanisms.

Scrutinizing screening: a critical interpretive review of primary care provider perspectives on mammography decision-making with average-risk women.

PubMed

Siedlikowski, Sophia; Ells, Carolyn; Bartlett, Gillian

2018-01-01

A decision to undertake screening for breast cancer often takes place within the primary care setting, but current controversies such as overdiagnosis and inconsistent screening recommendations based on evolving evidence render this a challenging process, particularly for average-risk women. Given the responsibility of primary care providers in counseling women in this decision-making process, it is important to understand their thoughts on these controversies and how they manage uncertainty in their practice. To review the perspectives and approaches of primary care providers regarding mammography decision-making with average-risk women. This study is a critical interpretive review of peer-review literature that reports primary care provider perspectives on mammography screening decision-making. Ovid MEDLINE®, Ovid PsycInfo, and Scopus databases were searched with dates from 2002 to 2017 using search terms related to mammography screening, uncertainty, counseling, decision-making, and primary health care providers. Nine articles were included following a review process involving the three authors. Using an inductive and iterative approach, data were grouped into four thematic categories: (1) perceptions on the effectiveness of screening, screening initiation age, and screening frequency; (2) factors guiding primary care providers in the screening decision-making process, including both provider and patient-related factors, (3) uncertainty faced by primary care providers regarding guidelines and screening discussions with their patients; and (4) informed decision-making with average-risk women, including factors that facilitate and hinder this process. The discussion of results addresses several factors about the diversity of perspectives and practices of physicians counseling average-risk women regarding breast cancer screening. This has implications for the challenge of understanding and explaining evidence, what should be shared with average-risk women considering screening, the forms of knowledge that physicians value to guide screening decision-making, and the consent process for population-based screening initiatives. Within the data, there was little attention placed on how physicians coped with uncertainty in practice. Given the dual responsibility of physicians in caring for both individuals and the larger population, further research should probe more deeply into how they balance their duties to individual patients with those to the larger population they serve.

Dysfunctional representation of expected value is associated with reinforcement-based decision-making deficits in adolescents with conduct problems.

PubMed

White, Stuart F; Tyler, Patrick M; Erway, Anna K; Botkin, Mary L; Kolli, Venkata; Meffert, Harma; Pope, Kayla; Blair, James R

2016-08-01

Previous work has shown that patients with conduct problems (CP) show impairments in reinforcement-based decision-making. However, studies with patients have not previously demonstrated any relationships between impairment in any of the neurocomputations underpinning reinforcement-based decision-making and specific symptom sets [e.g. level of CP and/or callous-unemotional (CU) traits]. Seventy-two youths [20 female, mean age = 13.81 (SD = 2.14), mean IQ = 102.34 (SD = 10.99)] from a residential treatment program and the community completed a passive avoidance task while undergoing functional MRI. Greater levels of CP were associated with poorer task performance. Reduced representation of expected values (EV) when making avoidance responses within bilateral anterior insula cortex/inferior frontal gyrus (AIC/iFG) and striatum was associated with greater levels of CP but not CU traits. The current data indicate that difficulties in the use of value information to motivate decisions to avoid suboptimal choices are associated with increased levels of CP (though not severity of CU traits). Moreover, they account for the behavioral deficits observed during reinforcement-based decision-making in youth with CP. In short, an individual's relative failure to utilize value information within AIC/iFG to avoid bad choices is associated with elevated levels of CP. © 2016 Association for Child and Adolescent Mental Health.

Data collection and information presentation for optimal decision making by clinical managers--the Autocontrol Project.

PubMed Central

Grant, A. M.; Richard, Y.; Deland, E.; Després, N.; de Lorenzi, F.; Dagenais, A.; Buteau, M.

1997-01-01

The Autocontrol methodology has been developed in order to support the optimisation of decision-making and the use of resources in the context of a clinical unit. The theoretical basis relates to quality assurance and information systems and is influenced by management and cognitive research in the health domain. The methodology uses population rather than individual decision making and because of its dynamic feedback design promises to have rapid and profound effect on practice. Most importantly the health care professional is the principle user of the Autocontrol system. In this methodology we distinguish three types of evidence necessary for practice change: practice based or internal evidence, best evidence derived from the literature or external evidence concerning the practice in question, and process based evidence on how to optimise the process of practice change. The software used by the system is of the executive decision support type which facilitates interrogation of large databases. The Autocontrol system is designed to interrogate the data of the patient medical record however the latter often lacks data on concomitant resource use and this must be supplemented. This paper reviews the Autocontrol methodology and gives examples from current studies. PMID:9357733

Data collection and information presentation for optimal decision making by clinical managers--the Autocontrol Project.

PubMed

Grant, A M; Richard, Y; Deland, E; Després, N; de Lorenzi, F; Dagenais, A; Buteau, M

1997-01-01

The Autocontrol methodology has been developed in order to support the optimisation of decision-making and the use of resources in the context of a clinical unit. The theoretical basis relates to quality assurance and information systems and is influenced by management and cognitive research in the health domain. The methodology uses population rather than individual decision making and because of its dynamic feedback design promises to have rapid and profound effect on practice. Most importantly the health care professional is the principle user of the Autocontrol system. In this methodology we distinguish three types of evidence necessary for practice change: practice based or internal evidence, best evidence derived from the literature or external evidence concerning the practice in question, and process based evidence on how to optimise the process of practice change. The software used by the system is of the executive decision support type which facilitates interrogation of large databases. The Autocontrol system is designed to interrogate the data of the patient medical record however the latter often lacks data on concomitant resource use and this must be supplemented. This paper reviews the Autocontrol methodology and gives examples from current studies.

Understandings of the nature of science and decision making on science and technology based issues

NASA Astrophysics Data System (ADS)

Bell, Randy L.; Lederman, Norman G.

2003-05-01

The purpose of this investigation was to explicate the role of the nature of science in decision making on science and technology based issues and to delineate factors and reasoning associated with these types of decisions. Twenty-one volunteer participants purposively selected from the faculty of geographically diverse universities completed an open-ended questionnaire and follow-up interview designed to assess their decision making on science and technology based issues. Participants were subsequently placed in one of two groups based upon their divergent views of the nature of science as assessed by a second open-ended questionnaire and follow-up interview. Profiles of each group's decision making were then constructed, based on participants' previous responses to the decision making questionnaire and follow-up interviews. Finally, the two groups' decisions, decision influencing factors, and decision making strategies were compared. No differences were found between the decisions of the two groups, despite their disparate views of the nature of science. Participants in both groups based their decisions primarily on personal values, morals/ethics, and social concerns. While all participants considered scientific evidence in their decision making, most did not require absolute proof, even though many participants held absolute conceptions of the nature of science. Overall, the nature of science did not figure prominently in either group's decisions. These findings contrast with basic assumptions of current science education reform efforts and call for a re-examination of the goals of nature of science instruction. Developing better decision making skills - even on science and technology based issues - may involve other factors, including more value-based instruction and attention to intellectual/moral development.

The alcoholic brain: neural bases of impaired reward-based decision-making in alcohol use disorders.

PubMed

Galandra, Caterina; Basso, Gianpaolo; Cappa, Stefano; Canessa, Nicola

2018-03-01

Neuroeconomics is providing insights into the neural bases of decision-making in normal and pathological conditions. In the neuropsychiatric domain, this discipline investigates how abnormal functioning of neural systems associated with reward processing and cognitive control promotes different disorders, and whether such evidence may inform treatments. This endeavor is crucial when studying different types of addiction, which share a core promoting mechanism in the imbalance between impulsive subcortical neural signals associated with immediate pleasurable outcomes and inhibitory signals mediated by a prefrontal reflective system. The resulting impairment in behavioral control represents a hallmark of alcohol use disorders (AUDs), a chronic relapsing disorder characterized by excessive alcohol consumption despite devastating consequences. This review aims to summarize available magnetic resonance imaging (MRI) evidence on reward-related decision-making alterations in AUDs, and to envision possible future research directions. We review functional MRI (fMRI) studies using tasks involving monetary rewards, as well as MRI studies relating decision-making parameters to neurostructural gray- or white-matter metrics. The available data suggest that excessive alcohol exposure affects neural signaling within brain networks underlying adaptive behavioral learning via the implementation of prediction errors. Namely, weaker ventromedial prefrontal cortex activity and altered connectivity between ventral striatum and dorsolateral prefrontal cortex likely underpin a shift from goal-directed to habitual actions which, in turn, might underpin compulsive alcohol consumption and relapsing episodes despite adverse consequences. Overall, these data highlight abnormal fronto-striatal connectivity as a candidate neurobiological marker of impaired choice in AUDs. Further studies are needed, however, to unveil its implications in the multiple facets of decision-making.

Parental decision-making after ultrasound diagnosis of a serious foetal abnormality.

PubMed

Bijma, Hilmar H; Wildschut, Hajo I J; van der Heide, Agnes; Passchier, Jan; Wladimiroff, Juriy W; van der Maas, Paul J

2005-01-01

The purpose of this article is to provide clinicians who are involved in the field of foetal medicine with a comprehensive overview of theories that are relevant for the parental decision-making process after ultrasound diagnosis of a serious foetal abnormality. Since little data are available of parental decision-making after ultrasound diagnosis of foetal abnormality, we reviewed the literature on parental decision-making in genetic counselling of couples at increased genetic risk together with the literature on general decision-making theories. The findings were linked to the specific situation of parental decision-making after an ultrasound diagnosis of foetal abnormality. Based on genetic counselling studies, several cognitive mechanisms play a role in parental decision-making regarding future pregnancies. Parents often have a binary perception of risk. Probabilistic information is translated into two options: the child will or will not be affected. The graduality of chance seems to be of little importance in this process. Instead, the focus shifts to the possible consequences for future family life. General decision-making theories often focus on rationality and coherence of the decision-making process. However, studies of both the influence of framing and the influence of stress indicate that emotional mechanisms can have an important and beneficial function in the decision-making process. Cognitive mechanisms that are elicited by emotions and that are not necessarily rational can have an important and beneficial function in parental decision-making after ultrasound diagnosis of a foetal abnormality. Consequently, the process of parental decision-making should not solely be assessed on the basis of its rationality, but also on the basis of the parental emotional outcome. Copyright (c) 2005 S. Karger AG, Basel.

Big data and high-performance analytics in structural health monitoring for bridge management

NASA Astrophysics Data System (ADS)

Alampalli, Sharada; Alampalli, Sandeep; Ettouney, Mohammed

2016-04-01

Structural Health Monitoring (SHM) can be a vital tool for effective bridge management. Combining large data sets from multiple sources to create a data-driven decision-making framework is crucial for the success of SHM. This paper presents a big data analytics framework that combines multiple data sets correlated with functional relatedness to convert data into actionable information that empowers risk-based decision-making. The integrated data environment incorporates near real-time streams of semi-structured data from remote sensors, historical visual inspection data, and observations from structural analysis models to monitor, assess, and manage risks associated with the aging bridge inventories. Accelerated processing of dataset is made possible by four technologies: cloud computing, relational database processing, support from NOSQL database, and in-memory analytics. The framework is being validated on a railroad corridor that can be subjected to multiple hazards. The framework enables to compute reliability indices for critical bridge components and individual bridge spans. In addition, framework includes a risk-based decision-making process that enumerate costs and consequences of poor bridge performance at span- and network-levels when rail networks are exposed to natural hazard events such as floods and earthquakes. Big data and high-performance analytics enable insights to assist bridge owners to address problems faster.

The effect of four user interface concepts on visual scan pattern similarity and information foraging in a complex decision making task.

PubMed

Starke, Sandra D; Baber, Chris

2018-07-01

User interface (UI) design can affect the quality of decision making, where decisions based on digitally presented content are commonly informed by visually sampling information through eye movements. Analysis of the resulting scan patterns - the order in which people visually attend to different regions of interest (ROIs) - gives an insight into information foraging strategies. In this study, we quantified scan pattern characteristics for participants engaging with conceptually different user interface designs. Four interfaces were modified along two dimensions relating to effort in accessing information: data presentation (either alpha-numerical data or colour blocks), and information access time (all information sources readily available or sequential revealing of information required). The aim of the study was to investigate whether a) people develop repeatable scan patterns and b) different UI concepts affect information foraging and task performance. Thirty-two participants (eight for each UI concept) were given the task to correctly classify 100 credit card transactions as normal or fraudulent based on nine transaction attributes. Attributes varied in their usefulness of predicting the correct outcome. Conventional and more recent (network analysis- and bioinformatics-based) eye tracking metrics were used to quantify visual search. Empirical findings were evaluated in context of random data and possible accuracy for theoretical decision making strategies. Results showed short repeating sequence fragments within longer scan patterns across participants and conditions, comprising a systematic and a random search component. The UI design concept showing alpha-numerical data in full view resulted in most complete data foraging, while the design concept showing colour blocks in full view resulted in the fastest task completion time. Decision accuracy was not significantly affected by UI design. Theoretical calculations showed that the difference in achievable accuracy between very complex and simple decision making strategies was small. We conclude that goal-directed search of familiar information results in repeatable scan pattern fragments (often corresponding to information sources considered particularly important), but no repeatable complete scan pattern. The underlying concept of the UI affects how visual search is performed, and a decision making strategy develops. This should be taken in consideration when designing for applied domains. Copyright © 2018 Elsevier Ltd. All rights reserved.

Development and field testing of a decision support tool to facilitate shared decision making in contraceptive counseling.

PubMed

Dehlendorf, Christine; Fitzpatrick, Judith; Steinauer, Jody; Swiader, Lawrence; Grumbach, Kevin; Hall, Cara; Kuppermann, Miriam

2017-07-01

We developed and formatively evaluated a tablet-based decision support tool for use by women prior to a contraceptive counseling visit to help them engage in shared decision making regarding method selection. Drawing upon formative work around women's preferences for contraceptive counseling and conceptual understanding of health care decision making, we iteratively developed a storyboard and then digital prototypes, based on best practices for decision support tool development. Pilot testing using both quantitative and qualitative data and cognitive testing was conducted. We obtained feedback from patient and provider advisory groups throughout the development process. Ninety-six percent of women who used the tool in pilot testing reported that it helped them choose a method, and qualitative interviews indicated acceptability of the tool's content and presentation. Compared to the control group, women who used the tool demonstrated trends toward increased likelihood of complete satisfaction with their method. Participant responses to cognitive testing were used in tool refinement. Our decision support tool appears acceptable to women in the family planning setting. Formative evaluation of the tool supports its utility among patients making contraceptive decisions, which can be further evaluated in a randomized controlled trial. Copyright © 2017 Elsevier B.V. All rights reserved.

Information and Decision-Making Needs Among People with Anxiety Disorders: Results of an Online Survey.

PubMed

Liebherz, Sarah; Härter, Martin; Dirmaier, Jörg; Tlach, Lisa

2015-12-01

People with anxiety disorders are faced with treatment decisions considerably affecting their life. Patient decision aids are aimed at enabling patients to deliberate treatment options based on individual values and to participate in medical decisions. This is the first study to determine patients' information and decision-making needs as a pre-requisite for the development of patient decision aids for anxiety disorders. An online cross-sectional survey was conducted between January and April 2013 on the e-health portal http://www.psychenet.de by using a self-administered questionnaire with items on internet use, online health information needs, role in decision making and important treatment decisions. Descriptive and inferential statistical as well as qualitative data analyses were performed. A total of 60 people with anxiety disorders with a mean age of 33.3 years (SD 10.5) participated in the survey. The most prevalent reasons for online health information search were the need for general information on anxiety disorders, the search for a physician or psychiatrist and the insufficiency of information given by the healthcare provider. Respondents experienced less shared and more autonomous decisions than they preferred. They assessed decisions on psychotherapy, medication, and treatment setting (inpatient or outpatient) as the most difficult decisions. Our results confirm the importance of offering patient decision aids for people with anxiety disorders that encourage patients to participate in decision making by providing information about the pros and cons of evidence-based treatment options.

Experimental Evaluation of Suitability of Selected Multi-Criteria Decision-Making Methods for Large-Scale Agent-Based Simulations.

PubMed

Tučník, Petr; Bureš, Vladimír

2016-01-01

Multi-criteria decision-making (MCDM) can be formally implemented by various methods. This study compares suitability of four selected MCDM methods, namely WPM, TOPSIS, VIKOR, and PROMETHEE, for future applications in agent-based computational economic (ACE) models of larger scale (i.e., over 10 000 agents in one geographical region). These four MCDM methods were selected according to their appropriateness for computational processing in ACE applications. Tests of the selected methods were conducted on four hardware configurations. For each method, 100 tests were performed, which represented one testing iteration. With four testing iterations conducted on each hardware setting and separated testing of all configurations with the-server parameter de/activated, altogether, 12800 data points were collected and consequently analyzed. An illustrational decision-making scenario was used which allows the mutual comparison of all of the selected decision making methods. Our test results suggest that although all methods are convenient and can be used in practice, the VIKOR method accomplished the tests with the best results and thus can be recommended as the most suitable for simulations of large-scale agent-based models.

Considering Information Up-to-Dateness to Increase the Accuracy of Therapy Decision Support Systems.

PubMed

Gaebel, Jan; Cypko, Mario A; Oeltze-Jafra, Steffen

2017-01-01

During the diagnostic process a lot of information is generated. All this information is assessed when making a final diagnosis and planning the therapy. While some patient information is stable, e.g., gender, others may become outdated, e.g., tumor size derived from CT data. Quantifying this information up-to-dateness and deriving consequences are difficult. Especially for the implementation in clinical decision support systems, this has not been studied. When information entities tend to become outdated, in practice, clinicians intuitively reduce their impact when making decisions. Therefore, in a system's calculations their impact should be reduced as well. We propose a method of decreasing the certainty of information entities based on their up-to-dateness. The method is tested in a decision support system for TNM staging based on Bayesian networks. We compared the actual N-state in records of 39 patients to the N-state calculated with and without decreasing data certainty. The results under decreased certainty correlated better with the actual states (r=0.958, p=0.008). We conclude that the up-to-dateness must be considered when processing clinical information to enhance decision making and ensure more patient safety.

Integration of Dynamic Models in Range Operations

NASA Technical Reports Server (NTRS)

Bardina, Jorge; Thirumalainambi, Rajkumar

2004-01-01

This work addresses the various model interactions in real-time to make an efficient internet based decision making tool for Shuttle launch. The decision making tool depends on the launch commit criteria coupled with physical models. Dynamic interaction between a wide variety of simulation applications and techniques, embedded algorithms, and data visualizations are needed to exploit the full potential of modeling and simulation. This paper also discusses in depth details of web based 3-D graphics and applications to range safety. The advantages of this dynamic model integration are secure accessibility and distribution of real time information to other NASA centers.

Continuous track paths reveal additive evidence integration in multistep decision making.

PubMed

Buc Calderon, Cristian; Dewulf, Myrtille; Gevers, Wim; Verguts, Tom

2017-10-03

Multistep decision making pervades daily life, but its underlying mechanisms remain obscure. We distinguish four prominent models of multistep decision making, namely serial stage, hierarchical evidence integration, hierarchical leaky competing accumulation (HLCA), and probabilistic evidence integration (PEI). To empirically disentangle these models, we design a two-step reward-based decision paradigm and implement it in a reaching task experiment. In a first step, participants choose between two potential upcoming choices, each associated with two rewards. In a second step, participants choose between the two rewards selected in the first step. Strikingly, as predicted by the HLCA and PEI models, the first-step decision dynamics were initially biased toward the choice representing the highest sum/mean before being redirected toward the choice representing the maximal reward (i.e., initial dip). Only HLCA and PEI predicted this initial dip, suggesting that first-step decision dynamics depend on additive integration of competing second-step choices. Our data suggest that potential future outcomes are progressively unraveled during multistep decision making.

Risk assessment and decision making about in-labour transfer from rural maternity care: a social judgment and signal detection analysis

PubMed Central

2012-01-01

Background The importance of respecting women’s wishes to give birth close to their local community is supported by policy in many developed countries. However, persistent concerns about the quality and safety of maternity care in rural communities have been expressed. Safe childbirth in rural communities depends on good risk assessment and decision making as to whether and when the transfer of a woman in labour to an obstetric led unit is required. This is a difficult decision. Wide variation in transfer rates between rural maternity units have been reported suggesting different decision making criteria may be involved; furthermore, rural midwives and family doctors report feeling isolated in making these decisions and that staff in urban centres do not understand the difficulties they face. In order to develop more evidence based decision making strategies greater understanding of the way in which maternity care providers currently make decisions is required. This study aimed to examine how midwives working in urban and rural settings and obstetricians make intrapartum transfer decisions, and describe sources of variation in decision making. Methods The study was conducted in three stages. 1. 20 midwives and four obstetricians described factors influencing transfer decisions. 2. Vignettes depicting an intrapartum scenario were developed based on stage one data. 3. Vignettes were presented to 122 midwives and 12 obstetricians who were asked to assess the level of risk in each case and decide whether to transfer or not. Social judgment analysis was used to identify the factors and factor weights used in assessment. Signal detection analysis was used to identify participants’ ability to distinguish high and low risk cases and personal decision thresholds. Results When reviewing the same case information in vignettes midwives in different settings and obstetricians made very similar risk assessments. Despite this, a wide range of transfer decisions were still made, suggesting that the main source of variation in decision making and transfer rates is not in the assessment but the personal decision thresholds of clinicians. Conclusions Currently health care practice focuses on supporting or improving decision making through skills training and clinical guidelines. However, these methods alone are unlikely to be effective in improving consistency of decision making. PMID:23114289

Modelling elderly cardiac patients decision making using Cognitive Work Analysis: identifying requirements for patient decision aids.

PubMed

Dhukaram, Anandhi Vivekanandan; Baber, Chris

2015-06-01

Patients make various healthcare decisions on a daily basis. Such day-to-day decision making can have significant consequences on their own health, treatment, care, and costs. While decision aids (DAs) provide effective support in enhancing patient's decision making, to date there have been few studies examining patient's decision making process or exploring how the understanding of such decision processes can aid in extracting requirements for the design of DAs. This paper applies Cognitive Work Analysis (CWA) to analyse patient's decision making in order to inform requirements for supporting self-care decision making. This study uses focus groups to elicit information from elderly cardiovascular disease (CVD) patients concerning a range of decision situations they face on a daily basis. Specifically, the focus groups addressed issues related to the decision making of CVD in terms of medication compliance, pain, diet and exercise. The results of these focus groups are used to develop high level views using CWA. CWA framework decomposes the complex decision making problem to inform three approaches to DA design: one design based on high level requirements; one based on a normative model of decision-making for patients; and the third based on a range of heuristics that patients seem to use. CWA helps in extracting and synthesising decision making from different perspectives: decision processes, work organisation, patient competencies and strategies used in decision making. As decision making can be influenced by human behaviour like skills, rules and knowledge, it is argued that patients require support to different types of decision making. This paper also provides insights for designers in using CWA framework for the design of effective DAs to support patients in self-management. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Development of spatial density maps based on geoprocessing web services: application to tuberculosis incidence in Barcelona, Spain.

PubMed

Dominkovics, Pau; Granell, Carlos; Pérez-Navarro, Antoni; Casals, Martí; Orcau, Angels; Caylà, Joan A

2011-11-29

Health professionals and authorities strive to cope with heterogeneous data, services, and statistical models to support decision making on public health. Sophisticated analysis and distributed processing capabilities over geocoded epidemiological data are seen as driving factors to speed up control and decision making in these health risk situations. In this context, recent Web technologies and standards-based web services deployed on geospatial information infrastructures have rapidly become an efficient way to access, share, process, and visualize geocoded health-related information. Data used on this study is based on Tuberculosis (TB) cases registered in Barcelona city during 2009. Residential addresses are geocoded and loaded into a spatial database that acts as a backend database. The web-based application architecture and geoprocessing web services are designed according to the Representational State Transfer (REST) principles. These web processing services produce spatial density maps against the backend database. The results are focused on the use of the proposed web-based application to the analysis of TB cases in Barcelona. The application produces spatial density maps to ease the monitoring and decision making process by health professionals. We also include a discussion of how spatial density maps may be useful for health practitioners in such contexts. In this paper, we developed web-based client application and a set of geoprocessing web services to support specific health-spatial requirements. Spatial density maps of TB incidence were generated to help health professionals in analysis and decision-making tasks. The combined use of geographic information tools, map viewers, and geoprocessing services leads to interesting possibilities in handling health data in a spatial manner. In particular, the use of spatial density maps has been effective to identify the most affected areas and its spatial impact. This study is an attempt to demonstrate how web processing services together with web-based mapping capabilities suit the needs of health practitioners in epidemiological analysis scenarios.

Development of spatial density maps based on geoprocessing web services: application to tuberculosis incidence in Barcelona, Spain

PubMed Central

2011-01-01

Background Health professionals and authorities strive to cope with heterogeneous data, services, and statistical models to support decision making on public health. Sophisticated analysis and distributed processing capabilities over geocoded epidemiological data are seen as driving factors to speed up control and decision making in these health risk situations. In this context, recent Web technologies and standards-based web services deployed on geospatial information infrastructures have rapidly become an efficient way to access, share, process, and visualize geocoded health-related information. Methods Data used on this study is based on Tuberculosis (TB) cases registered in Barcelona city during 2009. Residential addresses are geocoded and loaded into a spatial database that acts as a backend database. The web-based application architecture and geoprocessing web services are designed according to the Representational State Transfer (REST) principles. These web processing services produce spatial density maps against the backend database. Results The results are focused on the use of the proposed web-based application to the analysis of TB cases in Barcelona. The application produces spatial density maps to ease the monitoring and decision making process by health professionals. We also include a discussion of how spatial density maps may be useful for health practitioners in such contexts. Conclusions In this paper, we developed web-based client application and a set of geoprocessing web services to support specific health-spatial requirements. Spatial density maps of TB incidence were generated to help health professionals in analysis and decision-making tasks. The combined use of geographic information tools, map viewers, and geoprocessing services leads to interesting possibilities in handling health data in a spatial manner. In particular, the use of spatial density maps has been effective to identify the most affected areas and its spatial impact. This study is an attempt to demonstrate how web processing services together with web-based mapping capabilities suit the needs of health practitioners in epidemiological analysis scenarios. PMID:22126392

Risk Aversion is Associated with Decision Making among Community-Based Older Persons

PubMed Central

Boyle, Patricia A.; Yu, Lei; Buchman, Aron S.; Bennett, David A.

2012-01-01

Background: Risk aversion is associated with many important decisions among younger and middle aged persons, but the association of risk aversion with decision making has not been well studied among older persons who face some of the most significant decisions of their lives. Method: Using data from 606 community-dwelling older persons without dementia from the Rush Memory and Aging Project, an ongoing longitudinal epidemiologic study of aging, we examined the association of risk aversion with decision making. Risk aversion was measured using standard behavioral economics questions in which participants were asked to choose between a certain monetary payment ($15) versus a gamble in which they could gain more than $15 or gain nothing; potential gamble gains ranged from $20 to $300 with the gain amounts varied randomly over questions. Decision making was measured using a 12 item version of the Decision Making Competence Assessment Tool. Findings: In a linear regression model adjusted for age, sex, education, and income, greater risk aversion was associated with poorer decision making [estimate = −1.03, standard error (SE) = 0.35, p = 0.003]. Subsequent analyses showed that the association of risk aversion with decision making persisted after adjustment for global cognitive function as well as executive and non-executive cognitive abilities. Conclusion: Similar to findings from studies of younger persons, risk aversion is associated with poorer decision making among older persons who face a myriad of complex and influential decisions. PMID:22754545

Risk Aversion is Associated with Decision Making among Community-Based Older Persons.

PubMed

Boyle, Patricia A; Yu, Lei; Buchman, Aron S; Bennett, David A

2012-01-01

Risk aversion is associated with many important decisions among younger and middle aged persons, but the association of risk aversion with decision making has not been well studied among older persons who face some of the most significant decisions of their lives. Using data from 606 community-dwelling older persons without dementia from the Rush Memory and Aging Project, an ongoing longitudinal epidemiologic study of aging, we examined the association of risk aversion with decision making. Risk aversion was measured using standard behavioral economics questions in which participants were asked to choose between a certain monetary payment ($15) versus a gamble in which they could gain more than $15 or gain nothing; potential gamble gains ranged from $20 to $300 with the gain amounts varied randomly over questions. Decision making was measured using a 12 item version of the Decision Making Competence Assessment Tool. In a linear regression model adjusted for age, sex, education, and income, greater risk aversion was associated with poorer decision making [estimate = -1.03, standard error (SE) = 0.35, p = 0.003]. Subsequent analyses showed that the association of risk aversion with decision making persisted after adjustment for global cognitive function as well as executive and non-executive cognitive abilities. Similar to findings from studies of younger persons, risk aversion is associated with poorer decision making among older persons who face a myriad of complex and influential decisions.

Decision-making about complementary and alternative medicine by cancer patients: integrative literature review.

PubMed

Weeks, Laura; Balneaves, Lynda G; Paterson, Charlotte; Verhoef, Marja

2014-01-01

Patients with cancer consistently report conflict and anxiety when making decisions about complementary and alternative medicine (CAM) treatment. To design evidence-informed decision-support strategies, a better understanding is needed of how the decision-making process unfolds for these patients during their experience with cancer. We undertook this study to review the research literature regarding CAM-related decision-making by patients with cancer within the context of treatment, survivorship, and palliation. We also aimed to summarize emergent concepts within a preliminary conceptual framework. We conducted an integrative literature review, searching 12 electronic databases for articles published in English that described studies of the process, context, or outcomes of CAM-related decision-making. We summarized descriptive data using frequencies and used a descriptive constant comparative method to analyze statements about original qualitative results, with the goal of identifying distinct concepts pertaining to CAM-related decision-making by patients with cancer and the relationships among these concepts. Of 425 articles initially identified, 35 met our inclusion criteria. Seven unique concepts related to CAM and cancer decision-making emerged: decision-making phases, information-seeking and evaluation, decision-making roles, beliefs, contextual factors, decision-making outcomes, and the relationship between CAM and conventional medical decision-making. CAM decision-making begins with the diagnosis of cancer and encompasses 3 distinct phases (early, mid, and late), each marked by unique aims for CAM treatment and distinct patterns of information-seeking and evaluation. Phase transitions correspond to changes in health status or other milestones within the cancer trajectory. An emergent conceptual framework illustrating relationships among the 7 central concepts is presented. CAM-related decision-making by patients with cancer occurs as a nonlinear, complex, dynamic process. The conceptual framework presented here identifies influential factors within that process, as well as patients' unique needs during different phases. The framework can guide the development and evaluation of theory-based decision-support programs that are responsive to patients' beliefs and preferences.

Beyond pain: modeling decision-making deficits in chronic pain

PubMed Central

Hess, Leonardo Emanuel; Haimovici, Ariel; Muñoz, Miguel Angel; Montoya, Pedro

2014-01-01

Risky decision-making seems to be markedly disrupted in patients with chronic pain, probably due to the high cost that impose pain and negative mood on executive control functions. Patients’ behavioral performance on decision-making tasks such as the Iowa Gambling Task (IGT) is characterized by selecting cards more frequently from disadvantageous than from advantageous decks, and by switching often between competing responses in comparison with healthy controls (HCs). In the present study, we developed a simple heuristic model to simulate individuals’ choice behavior by varying the level of decision randomness and the importance given to gains and losses. The findings revealed that the model was able to differentiate the behavioral performance of patients with chronic pain and HCs at the group, as well as at the individual level. The best fit of the model in patients with chronic pain was yielded when decisions were not based on previous choices and when gains were considered more relevant than losses. By contrast, the best account of the available data in HCs was obtained when decisions were based on previous experiences and losses loomed larger than gains. In conclusion, our model seems to provide useful information to measure each individual participant extensively, and to deal with the data on a participant-by-participant basis. PMID:25136301

Beyond pain: modeling decision-making deficits in chronic pain.

PubMed

Hess, Leonardo Emanuel; Haimovici, Ariel; Muñoz, Miguel Angel; Montoya, Pedro

2014-01-01

Risky decision-making seems to be markedly disrupted in patients with chronic pain, probably due to the high cost that impose pain and negative mood on executive control functions. Patients' behavioral performance on decision-making tasks such as the Iowa Gambling Task (IGT) is characterized by selecting cards more frequently from disadvantageous than from advantageous decks, and by switching often between competing responses in comparison with healthy controls (HCs). In the present study, we developed a simple heuristic model to simulate individuals' choice behavior by varying the level of decision randomness and the importance given to gains and losses. The findings revealed that the model was able to differentiate the behavioral performance of patients with chronic pain and HCs at the group, as well as at the individual level. The best fit of the model in patients with chronic pain was yielded when decisions were not based on previous choices and when gains were considered more relevant than losses. By contrast, the best account of the available data in HCs was obtained when decisions were based on previous experiences and losses loomed larger than gains. In conclusion, our model seems to provide useful information to measure each individual participant extensively, and to deal with the data on a participant-by-participant basis.

Electrophysiological correlates reflect the integration of model-based and model-free decision information.

PubMed

Eppinger, Ben; Walter, Maik; Li, Shu-Chen

2017-04-01

In this study, we investigated the interplay of habitual (model-free) and goal-directed (model-based) decision processes by using a two-stage Markov decision task in combination with event-related potentials (ERPs) and computational modeling. To manipulate the demands on model-based decision making, we applied two experimental conditions with different probabilities of transitioning from the first to the second stage of the task. As we expected, when the stage transitions were more predictable, participants showed greater model-based (planning) behavior. Consistent with this result, we found that stimulus-evoked parietal (P300) activity at the second stage of the task increased with the predictability of the state transitions. However, the parietal activity also reflected model-free information about the expected values of the stimuli, indicating that at this stage of the task both types of information are integrated to guide decision making. Outcome-related ERP components only reflected reward-related processes: Specifically, a medial prefrontal ERP component (the feedback-related negativity) was sensitive to negative outcomes, whereas a component that is elicited by reward (the feedback-related positivity) increased as a function of positive prediction errors. Taken together, our data indicate that stimulus-locked parietal activity reflects the integration of model-based and model-free information during decision making, whereas feedback-related medial prefrontal signals primarily reflect reward-related decision processes.

[Which research is needed to support clinical decision-making on integrative medicine? Can comparative effectiveness research close the gap?].

PubMed

Witt, Claudia M; Huang, Wen-jing; Lao, Lixing; Berman, Brian M

2013-08-01

In clinical research on complementary and integrative medicine, experts and scientists have often pursued a research agenda in spite of an incomplete understanding of the needs of end users. Consequently, the majority of previous clinical trials have mainly assessed the efficacy of interventions. Scant data is available on their effectiveness. Comparative effectiveness research (CER) promises to support decision makers by generating evidence that compares the benefits and harms of best care options. This evidence, more generalizable than evidence generated by traditional randomized clinical trials (RCTs), is better suited to inform real-world care decisions. An emphasis on CER supports the development of the evidence base for clinical and policy decision-making. Whereas in most areas of complementary and integrative medicine data on CER is scarce, available acupuncture research already contributes to CER evidence. This paper will introduce CER and make suggestions for future research.

Which research is needed to support clinical decision-making on integrative medicine?- Can comparative effectiveness research close the gap?

PubMed

Witt, Claudia M; Huang, Wen-jing; Lao, Lixing; Bm, Berman

2012-10-01

In clinical research on complementary and integrative medicine, experts and scientists have often pursued a research agenda in spite of an incomplete understanding of the needs of end users. Consequently, the majority of previous clinical trials have mainly assessed the efficacy of interventions. Scant data is available on their effectiveness. Comparative effectiveness research (CER) promises to support decision makers by generating evidence that compares the benefits and harms of the best care options. This evidence, more generalizable than the evidence generated by traditional randomized controlled trials (RCTs), is better suited to inform real-world care decisions. An emphasis on CER supports the development of the evidence base for clinical and policy decision-making. Whereas in most areas of complementary and integrative medicine data on comparative effectiveness is scarce, available acupuncture research already contributes to CER evidence. This paper will introduce CER and make suggestions for future research.

Intelligent data management for real-time spacecraft monitoring

NASA Technical Reports Server (NTRS)

Schwuttke, Ursula M.; Gasser, Les; Abramson, Bruce

1992-01-01

Real-time AI systems have begun to address the challenge of restructuring problem solving to meet real-time constraints by making key trade-offs that pursue less than optimal strategies with minimal impact on system goals. Several approaches for adapting to dynamic changes in system operating conditions are known. However, simultaneously adapting system decision criteria in a principled way has been difficult. Towards this end, a general technique for dynamically making such trade-offs using a combination of decision theory and domain knowledge has been developed. Multi-attribute utility theory (MAUT), a decision theoretic approach for making one-time decisions is discussed and dynamic trade-off evaluation is described as a knowledge-based extension of MAUT that is suitable for highly dynamic real-time environments, and provides an example of dynamic trade-off evaluation applied to a specific data management trade-off in a real-world spacecraft monitoring application.

A Conceptual Model of the Role of Communication in Surrogate Decision Making for Hospitalized Adults

PubMed Central

Torke, Alexia M.; Petronio, Sandra; Sachs, Greg A.; Helft, Paul R.; Purnell, Christianna

2011-01-01

Objective To build a conceptual model of the role of communication in decision making, based on literature from medicine, communication studies and medical ethics. Methods We propose a model and describe each construct in detail. We review what is known about interpersonal and patient-physician communication, describe literature about surrogate-clinician communication, and discuss implications for our developing model. Results The communication literature proposes two major elements of interpersonal communication: information processing and relationship building. These elements are composed of constructs such as information disclosure and emotional support that are likely to be relevant to decision making. We propose these elements of communication impact decision making, which in turn affects outcomes for both patients and surrogates. Decision making quality may also mediate the relationship between communication and outcomes. Conclusion Although many elements of the model have been studied in relation to patient-clinician communication, there is limited data about surrogate decision making. There is evidence of high surrogate distress associated with decision making that may be alleviated by communication–focused interventions. More research is needed to test the relationships proposed in the model. Practice Implications Good communication with surrogates may improve both the quality of medical decisions and outcomes for the patient and surrogate. PMID:21889865

A conceptual model of the role of communication in surrogate decision making for hospitalized adults.

PubMed

Torke, Alexia M; Petronio, Sandra; Sachs, Greg A; Helft, Paul R; Purnell, Christianna

2012-04-01

To build a conceptual model of the role of communication in decision making, based on literature from medicine, communication studies and medical ethics. We proposed a model and described each construct in detail. We review what is known about interpersonal and patient-physician communication, described literature about surrogate-clinician communication, and discussed implications for our developing model. The communication literature proposes two major elements of interpersonal communication: information processing and relationship building. These elements are composed of constructs such as information disclosure and emotional support that are likely to be relevant to decision making. We propose these elements of communication impact decision making, which in turn affects outcomes for both patients and surrogates. Decision making quality may also mediate the relationship between communication and outcomes. Although many elements of the model have been studied in relation to patient-clinician communication, there is limited data about surrogate decision making. There is evidence of high surrogate distress associated with decision making that may be alleviated by communication-focused interventions. More research is needed to test the relationships proposed in the model. Good communication with surrogates may improve both the quality of medical decisions and outcomes for the patient and surrogate. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Controlling equine influenza: policy networks and decision-making during the 2007 Australian equine influenza outbreak.

PubMed

Schemann, K; Gillespie, J A; Toribio, J-A L M L; Ward, M P; Dhand, N K

2014-10-01

Rapid, evidence-based decision-making is critical during a disease outbreak response; however, compliance by stakeholders is necessary to ensure that such decisions are effective - especially if the response depends on voluntary action. This mixed method study evaluated technical policy decision-making processes during the 2007 outbreak of equine influenza in Australia by identifying and analysing the stakeholder network involved and the factors driving policy decision-making. The study started with a review of the outbreak literature and published policy documents. This identified six policy issues regarding policy modifications or differing interpretations by different state agencies. Data on factors influencing the decision-making process for these six issues and on stakeholder interaction were collected using a pre-tested, semi-structured questionnaire. Face-to-face interviews were conducted with 24 individuals representing 12 industry and government organizations. Quantitative data were analysed using social network analysis. Qualitative data were coded and patterns matched to test a pre-determined general theory using a method called theory-oriented process-tracing. Results revealed that technical policy decisions were framed by social, political, financial, strategic and operational considerations. Industry stakeholders had influence through formal pre-existing channels, yet specific gaps in stakeholder interaction were overcome by reactive alliances formed during the outbreak response but outside the established system. Overall, the crisis management system and response were seen as positive, and 75-100% of individuals interviewed were supportive of, had interest in and considered the outcome as good for the majority of policy decisions, yet only 46-75% of those interviewed considered that they had influence on these decisions. Training to increase awareness and knowledge of emergency animal diseases (EADs) and response systems will improve stakeholder participation in emergency disease management and preparedness for future EAD incursions. © 2012 Blackwell Verlag GmbH.

GUIDED TOUR OF A WEB-BASED ENVIRONMENTAL DECISION TOOLKIT

EPA Science Inventory

Decision-making regarding the targeting of vulnerable resources and prioritization of actions requires synthesis of data on condition, vulnerability, and feasibility of risk management alternatives. EP A's Regional Vulnerability Assessment (ReV A) Program has evaluated existing a...

Effects of reflection on clinical decision-making of intensive care unit nurses.

PubMed

Razieh, Shahrokhi; Somayeh, Ghafari; Fariba, Haghani

2018-07-01

Nurses are one of the most influential factors in overcoming the main challenges faced by health systems throughout the world. Every health system should, hence, empower nurses in clinical judgment and decision-making skills. This study evaluated the effects of implementing Tanner's reflection method on clinical decision-making of nurses working in an intensive care unit (ICU). This study used an experimental, pretest, posttest design. The setting was the intensive care unit of Amin Hospital Isfahan, Iran. The convenience sample included 60 nurses working in the ICU of Amin Hospital (Isfahan, Iran). This clinical trial was performed on 60 nurses working in the ICU of Amin Hospital (Isfahan, Iran). The nurses were selected by census sampling and randomly allocated to either the case or the control group. Data were collected using a questionnaire containing demographic characteristics and the clinical decision-making scale developed by Laurie and Salantera (NDMI-14). The questionnaire was completed before and one week after the intervention. The data were analyzed using SPSS 21.0. The two groups were not significantly different in terms of the level and mean scores of clinical decision-making before the intervention (P = 0.786). Based on the results of independent t-test, the mean score of clinical decision-making one week after the intervention was significantly higher in the case group than in the control group (P = 0.009; t = -2.69). The results of Mann Whitney test showed that one week after the intervention, the nurses' level of clinical decision-making in the case group rose to the next level (P = 0.001). Reflection could improve the clinical decision-making of ICU nurses. It is, thus, recommended to incorporate this method into the nursing curriculum and care practices. Copyright © 2018. Published by Elsevier Ltd.

A decision technology system for health care electronic commerce.

PubMed

Forgionne, G A; Gangopadhyay, A; Klein, J A; Eckhardt, R

1999-08-01

Mounting costs have escalated the pressure on health care providers and payers to improve decision making and control expenses. Transactions to form the needed decision data will routinely flow, often electronically, between the affected parties. Conventional health care information systems facilitate flow, process transactions, and generate useful decision information. Typically, such support is offered through a series of stand-alone systems that lose much useful decision knowledge and wisdom during health care electronic commerce (e-commerce). Integrating the stand-alone functions can enhance the quality and efficiency of the segmented support, create synergistic effects, and augment decision-making performance and value for both providers and payers. This article presents an information system that can provide complete and integrated support for e-commerce-based health care decision making. The article describes health care e-commerce, presents the system, examines the system's potential use and benefits, and draws implications for health care management and practice.

Decision Making in the Airplane

NASA Technical Reports Server (NTRS)

Orasanu, Judith; Shafto, Michael G. (Technical Monitor)

1995-01-01

The Importance of decision-making to safety in complex, dynamic environments like mission control centers, aviation, and offshore installations has been well established. NASA-ARC has a program of research dedicated to fostering safe and effective decision-making in the manned spaceflight environment. Because access to spaceflight is limited, environments with similar characteristics, including aviation and nuclear power plants, serve as analogs from which space-relevant data can be gathered and theories developed. Analyses of aviation accidents cite crew judgement and decision making as causes or contributing factors in over half of all accidents. Yet laboratory research on decision making has not proven especially helpful In improving the quality of decisions in these kinds of environments. One reason is that the traditional, analytic decision models are inappropriate to multi-dimensional, high-risk environments, and do not accurately describe what expert human decision makers do when they make decisions that have consequences. A new model of dynamic, naturalistic decision making is offered that may prove useful for improving decision making in complex, isolated, confined and high-risk environments. Based on analyses of crew performance in full-mission simulators and accident reports, features that define effective decision strategies in abnormal or emergency situations have been identified. These include accurate situation assessment (including time and risk assessment), appreciation of the complexity of the problem, sensitivity to constraints on the decision, timeliness of the response, and use of adequate information. More effective crews also manage their workload to provide themselves with time and resources to make good decisions. In brief, good decisions are appropriate to the demands of the situation. Effective crew decision making and overall performance are mediated by crew communication. Communication contributes to performance because it assures that all crew members have essential information, but it also regulates and coordinates crew actions and is the medium of collective thinking In response to a problem, This presentation will examine the relations between leadership, communication, decision making and overall crew performance. Implications of these findings for training will be discussed.

Basic physiological systems indicator's informative assessment for children and adolescents obesity diagnosis tasks

NASA Astrophysics Data System (ADS)

Marukhina, O. V.; Berestneva, O. G.; Emelyanova, Yu A.; Romanchukov, S. V.; Petrova, L.; Lombardo, C.; Kozlova, N. V.

2018-05-01

The healthcare computerization creates opportunities to the clinical decision support system development. In the course of diagnosis, doctor manipulates a considerable amount of data and makes a decision in the context of uncertainty basing upon the first-hand experience and knowledge. The situation is exacerbated by the fact that the knowledge scope in medicine is incrementally growing, but the decision-making time does not increase. The amount of medical malpractice is growing and it leads to various negative effects, even the mortality rate increase. IT-solution's development for clinical purposes is one of the most promising and efficient ways to prevent these effects. That is why the efforts of many IT specialists are directed to the doctor's heuristics simulating software or expert-based medical decision-making algorithms development. Thus, the objective of this study is to develop techniques and approaches for the body physiological system's informative value assessment index for the obesity degree evaluation based on the diagnostic findings.

Using sense-making theory to aid understanding of the recognition, assessment and management of pain in patients with dementia in acute hospital settings.

PubMed

Dowding, Dawn; Lichtner, Valentina; Allcock, Nick; Briggs, Michelle; James, Kirstin; Keady, John; Lasrado, Reena; Sampson, Elizabeth L; Swarbrick, Caroline; José Closs, S

2016-01-01

The recognition, assessment and management of pain in hospital settings is suboptimal, and is a particular challenge in patients with dementia. The existing process guiding pain assessment and management in clinical settings is based on the assumption that nurses follow a sequential linear approach to decision making. In this paper we re-evaluate this theoretical assumption drawing on findings from a study of pain recognition, assessment and management in patients with dementia. To provide a revised conceptual model of pain recognition, assessment and management based on sense-making theories of decision making. The research we refer to is an exploratory ethnographic study using nested case sites. Patients with dementia (n=31) were the unit of data collection, nested in 11 wards (vascular, continuing care, stroke rehabilitation, orthopaedic, acute medicine, care of the elderly, elective and emergency surgery), located in four NHS hospital organizations in the UK. Data consisted of observations of patients at bedside (170h in total); observations of the context of care; audits of patient hospital records; documentary analysis of artefacts; semi-structured interviews (n=56) and informal open conversations with staff and carers (family members). Existing conceptualizations of pain recognition, assessment and management do not fully explain how the decision process occurs in clinical practice. Our research indicates that pain recognition, assessment and management is not an individual cognitive activity; rather it is carried out by groups of individuals over time and within a specific organizational culture or climate, which influences both health care professional and patient behaviour. We propose a revised theoretical model of decision making related to pain assessment and management for patients with dementia based on theories of sense-making, which is reflective of the reality of clinical decision making in acute hospital wards. The revised model recognizes the salience of individual cognition as well as acknowledging that decisions are constructed through social interaction and organizational context. The model will be used in further research to develop decision support interventions to assist with the assessment and management of patients with dementia in acute hospital settings. Copyright © 2015. Published by Elsevier Ltd.

Use of GIS-Based Sampling to Inform Food Security Assessments and Decision Making in Kenya

NASA Astrophysics Data System (ADS)

Wahome, A.; Ndubi, A. O.; Ndungu, L. W.; Mugo, R. M.; Flores Cordova, A. I.

2017-12-01

Kenya relies on agricultural production for supporting local consumption and other processing value chains. With changing climate in a rain-fed dependent agricultural production system, cropping zones are shifting and proper decision making will require updated data. Where up-to-date data is not available it is important that it is generated and passed over to relevant stakeholders to inform their decision making. The process of generating this data should be cost effective and less time consuming. The Kenyan State Department of Agriculture (SDA) runs an insurance programme for maize farmers in a number of counties in Kenya. Previously, SDA was using a list of farmers to identify the crop fields for this insurance programme. However, the process of listing of all farmers in each Unit Area of Insurance (UAI) proved to be tedious and very costly, hence need for an alternative approach, but acceptable sampling methodology. Building on the existing cropland maps, SERVIR, a joint NASA-USAID initiative that brings Earth observations (EO) for improved environmental decision making in developing countries, specifically its hub in Eastern and Soutehrn Africa developed a High Resolution Map based on 10m Sentinel satellite images from which a GIS based sampling frame for identifying maize fields was developed. Sampling points were randomly generated in each UAI and navigated to using hand-held GPS units for identification of maize farmers. In the GIS-based identification of farmers SDA uses 1 day to cover an area covered in 1 week by list identification of farmers. Similarly, SDA spends approximately 3,000 USD per sub-county to locate maize fields using GIS-based sampling as compared 10,000 USD they used to spend before. This has resulted in 70% cost reduction.

A Multi-layer Dynamic Model for Coordination Based Group Decision Making in Water Resource Allocation and Scheduling

NASA Astrophysics Data System (ADS)

Huang, Wei; Zhang, Xingnan; Li, Chenming; Wang, Jianying

Management of group decision-making is an important issue in water source management development. In order to overcome the defects in lacking of effective communication and cooperation in the existing decision-making models, this paper proposes a multi-layer dynamic model for coordination in water resource allocation and scheduling based group decision making. By introducing the scheme-recognized cooperative satisfaction index and scheme-adjusted rationality index, the proposed model can solve the problem of poor convergence of multi-round decision-making process in water resource allocation and scheduling. Furthermore, the problem about coordination of limited resources-based group decision-making process can be solved based on the effectiveness of distance-based group of conflict resolution. The simulation results show that the proposed model has better convergence than the existing models.

Innovation Need Survey: Implementing a Technology Tool to Improve Early Data-Based Decisions to Address and Prevent Learning Disabilities. Technical Report #1602

ERIC Educational Resources Information Center

Irvin, P. Shawn; Pilger, Marissa; Sáez, Leilani; Alonzo, Julie

2016-01-01

Identifying and measuring indicators of learning difficulties among young children and implementing effective instructional approaches are complicated, particularly during the transition to kindergarten. Purposeful school-based transition policies and practices support teacher and school decision-making and, thus, can ease the…

The Utility of Curriculum-Based Measurement and Performance Assessment as Alternatives to Traditional Intelligence and Achievement Tests.

ERIC Educational Resources Information Center

Elliott, Stephen N.; Fuchs, Lynn S.

1997-01-01

Curriculum-based measurement and performance assessments can provide valuable data for making special-education eligibility decisions. Reviews applied research on these assessment approaches and discusses the practical context of treatment validation and decisions about instructional services for students with diverse academic needs. (Author/JDM)

Personalized Clinical Diagnosis in Data Bases for Treatment Support in Phthisiology.

PubMed

Lugovkina, T K; Skornyakov, S N; Golubev, D N; Egorov, E A; Medvinsky, I D

2016-01-01

The decision-making is a key event in the clinical practice. The program products with clinical decision support models in electronic data-base as well as with fixed decision moments of the real clinical practice and treatment results are very actual instruments for improving phthisiological practice and may be useful in the severe cases caused by the resistant strains of Mycobacterium tuberculosis. The methodology for gathering and structuring of useful information (critical clinical signals for decisions) is described. Additional coding of clinical diagnosis characteristics was implemented for numeric reflection of the personal situations. The created methodology for systematization and coding Clinical Events allowed to improve the clinical decision models for better clinical results.

Web-Based Versus Usual Care and Other Formats of Decision Aids to Support Prostate Cancer Screening Decisions: Systematic Review and Meta-Analysis.

PubMed

Baptista, Sofia; Teles Sampaio, Elvira; Heleno, Bruno; Azevedo, Luís Filipe; Martins, Carlos

2018-06-26

Prostate cancer is a leading cause of cancer among men. Because screening for prostate cancer is a controversial issue, many experts in the field have defended the use of shared decision making using validated decision aids, which can be presented in different formats (eg, written, multimedia, Web). Recent studies have concluded that decision aids improve knowledge and reduce decisional conflict. This meta-analysis aimed to investigate the impact of using Web-based decision aids to support men's prostate cancer screening decisions in comparison with usual care and other formats of decision aids. We searched PubMed, CINAHL, PsycINFO, and Cochrane CENTRAL databases up to November 2016. This search identified randomized controlled trials, which assessed Web-based decision aids for men making a prostate cancer screening decision and reported quality of decision-making outcomes. Two reviewers independently screened citations for inclusion criteria, extracted data, and assessed risk of bias. Using a random-effects model, meta-analyses were conducted pooling results using mean differences (MD), standardized mean differences (SMD), and relative risks (RR). Of 2406 unique citations, 7 randomized controlled trials met the inclusion criteria. For risk of bias, selective outcome reporting and participant/personnel blinding were mostly rated as unclear due to inadequate reporting. Based on seven items, two studies had high risk of bias for one item. Compared to usual care, Web-based decision aids increased knowledge (SMD 0.46; 95% CI 0.18-0.75), reduced decisional conflict (MD -7.07%; 95% CI -9.44 to -4.71), and reduced the practitioner control role in the decision-making process (RR 0.50; 95% CI 0.31-0.81). Web-based decision aids compared to printed decision aids yielded no differences in knowledge, decisional conflict, and participation in decision or screening behaviors. Compared to video decision aids, Web-based decision aids showed lower average knowledge scores (SMD -0.50; 95% CI -0.88 to -0.12) and a slight decrease in prostate-specific antigen screening (RR 1.12; 95% CI 1.01-1.25). According to this analysis, Web-based decision aids performed similarly to alternative formats (ie, printed, video) for the assessed decision-quality outcomes. The low cost, readiness, availability, and anonymity of the Web can be an advantage for increasing access to decision aids that support prostate cancer screening decisions among men. ©Sofia Baptista, Elvira Teles Sampaio, Bruno Heleno, Luís Filipe Azevedo, Carlos Martins. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 26.06.2018.

Decision Making in Action: Applying Research to Practice

NASA Technical Reports Server (NTRS)

Orasanu, Judith; Hart, Sandra G. (Technical Monitor)

1994-01-01

The importance of decision-making to safety in complex, dynamic environments like mission control centers, aviation, and offshore installations has been well established. NASA-ARC has a program of research dedicated to fostering safe and effective decision-making in the manned spaceflight environment: Because access to spaceflight is limited, environments with similar characteristics, including aviation and nuclear power plants, serve as analogs from which space-relevant data can be gathered and theories developed. Analyses of aviation accidents cite crew judgement and decision making as causes or contributing factors in over half of all accidents. Yet laboratory research on decision making has not proven especially helpful in improving the quality of decisions in these kinds of environments. One reason is that the traditional, analytic decision models are inappropriate to multi-dimensional, high-risk environments, and do not accurately describe what expert human decision makers do when they make decisions that have consequences. A new model of dynamic, naturalistic decision making is offered that may prove useful for improving decision making in complex, isolated, confined and high-risk environments. Based on analyses of crew performance in full-mission simulators and accident reports, features that define effective decision strategies in abnormal or emergency situations have been identified. These include accurate situation assessment (including time and risk assessment), appreciation of the complexity of the problem, sensitivity to constraints on the decision, timeliness of the response, and use of adequate information. More effective crews also manage their workload to provide themselves with time and resources to make good good decisions are appropriate to the demands of the situation. Effective crew decision making and overall performance are mediated by crew communication. Communication contributes to performance because it assures that all crew members have essential information, but it also regulates and coordinates crew actions and is the medium of collective thinking in response to a problem. This presentation will examine the relations between leadership, communication, decision making and overall crew performance. Implications of these findings for training will be discussed.

DECISION-MAKING ALIGNED WITH RAPID-CYCLE EVALUATION IN HEALTH CARE.

PubMed

Schneeweiss, Sebastian; Shrank, William H; Ruhl, Michael; Maclure, Malcolm

2015-01-01

Availability of real-time electronic healthcare data provides new opportunities for rapid-cycle evaluation (RCE) of health technologies, including healthcare delivery and payment programs. We aim to align decision-making processes with stages of RCE to optimize the usefulness and impact of rapid results. Rational decisions about program adoption depend on program effect size in relation to externalities, including implementation cost, sustainability, and likelihood of broad adoption. Drawing on case studies and experience from drug safety monitoring, we examine how decision makers have used scientific evidence on complex interventions in the past. We clarify how RCE alters the nature of policy decisions; develop the RAPID framework for synchronizing decision-maker activities with stages of RCE; and provide guidelines on evidence thresholds for incremental decision-making. In contrast to traditional evaluations, RCE provides early evidence on effectiveness and facilitates a stepped approach to decision making in expectation of future regularly updated evidence. RCE allows for identification of trends in adjusted effect size. It supports adapting a program in midstream in response to interim findings, or adapting the evaluation strategy to identify true improvements earlier. The 5-step RAPID approach that utilizes the cumulating evidence of program effectiveness over time could increase policy-makers' confidence in expediting decisions. RCE enables a step-wise approach to HTA decision-making, based on gradually emerging evidence, reducing delays in decision-making processes after traditional one-time evaluations.

Assessment of New Approaches in Geothermal Exploration Decision Making: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Akar, S.; Young, K. R.

Geothermal exploration projects have significant amount of risk associated with uncertainties encountered in the discovery of the geothermal resource. Understanding when and how to proceed in an exploration program, and when to walk away from a site, are two of the largest challenges for increased geothermal deployment. Current methodologies for exploration decision making is left to subjective by subjective expert opinion which can be incorrectly biased by expertise (e.g. geochemistry, geophysics), geographic location of focus, and the assumed conceptual model. The aim of this project is to develop a methodology for more objective geothermal exploration decision making at a givenmore » location, including go-no-go decision points to help developers and investors decide when to give up on a location. In this scope, two different approaches are investigated: 1) value of information analysis (VOIA) which is used for evaluating and quantifying the value of a data before they are purchased, and 2) enthalpy-based exploration targeting based on reservoir size, temperature gradient estimates, and internal rate of return (IRR). The first approach, VOIA, aims to identify the value of a particular data when making decisions with an uncertain outcome. This approach targets the pre-drilling phase of exploration. These estimated VOIs are highly affected by the size of the project and still have a high degree of subjectivity in assignment of probabilities. The second approach, exploration targeting, is focused on decision making during the drilling phase. It starts with a basic geothermal project definition that includes target and minimum required production capacity and initial budgeting for exploration phases. Then, it uses average temperature gradient, reservoir temperature estimates, and production capacity to define targets and go/no-go limits. The decision analysis in this approach is based on achieving a minimum IRR at each phase of the project. This second approach was determined to be less subjective, since it requires less subjectivity in the input values.« less

Sustainability in Health care by Allocating Resources Effectively (SHARE) 7: supporting staff in evidence-based decision-making, implementation and evaluation in a local healthcare setting.

PubMed

Harris, Claire; Allen, Kelly; Waller, Cara; Dyer, Tim; Brooke, Vanessa; Garrubba, Marie; Melder, Angela; Voutier, Catherine; Gust, Anthony; Farjou, Dina

2017-06-21

This is the seventh in a series of papers reporting Sustainability in Health care by Allocating Resources Effectively (SHARE) in a local healthcare setting. The SHARE Program was a systematic, integrated, evidence-based program for resource allocation within a large Australian health service. It aimed to facilitate proactive use of evidence from research and local data; evidence-based decision-making for resource allocation including disinvestment; and development, implementation and evaluation of disinvestment projects. From the literature and responses of local stakeholders it was clear that provision of expertise and education, training and support of health service staff would be required to achieve these aims. Four support services were proposed. This paper is a detailed case report of the development, implementation and evaluation of a Data Service, Capacity Building Service and Project Support Service. An Evidence Service is reported separately. Literature reviews, surveys, interviews, consultation and workshops were used to capture and process the relevant information. Existing theoretical frameworks were adapted for evaluation and explication of processes and outcomes. Surveys and interviews identified current practice in use of evidence in decision-making, implementation and evaluation; staff needs for evidence-based practice; nature, type and availability of local health service data; and preferred formats for education and training. The Capacity Building and Project Support Services were successful in achieving short term objectives; but long term outcomes were not evaluated due to reduced funding. The Data Service was not implemented at all. Factors influencing the processes and outcomes are discussed. Health service staff need access to education, training, expertise and support to enable evidence-based decision-making and to implement and evaluate the changes arising from those decisions. Three support services were proposed based on research evidence and local findings. Local factors, some unanticipated and some unavoidable, were the main barriers to successful implementation. All three proposed support services hold promise as facilitators of EBP in the local healthcare setting. The findings from this study will inform further exploration.

Geospatial decision support systems for societal decision making

USGS Publications Warehouse

Bernknopf, R.L.

2005-01-01

While science provides reliable information to describe and understand the earth and its natural processes, it can contribute more. There are many important societal issues in which scientific information can play a critical role. Science can add greatly to policy and management decisions to minimize loss of life and property from natural and man-made disasters, to manage water, biological, energy, and mineral resources, and in general, to enhance and protect our quality of life. However, the link between science and decision-making is often complicated and imperfect. Technical language and methods surround scientific research and the dissemination of its results. Scientific investigations often are conducted under different conditions, with different spatial boundaries, and in different timeframes than those needed to support specific policy and societal decisions. Uncertainty is not uniformly reported in scientific investigations. If society does not know that data exist, what the data mean, where to use the data, or how to include uncertainty when a decision has to be made, then science gets left out -or misused- in a decision making process. This paper is about using Geospatial Decision Support Systems (GDSS) for quantitative policy analysis. Integrated natural -social science methods and tools in a Geographic Information System that respond to decision-making needs can be used to close the gap between science and society. The GDSS has been developed so that nonscientists can pose "what if" scenarios to evaluate hypothetical outcomes of policy and management choices. In this approach decision makers can evaluate the financial and geographic distribution of potential policy options and their societal implications. Actions, based on scientific information, can be taken to mitigate hazards, protect our air and water quality, preserve the planet's biodiversity, promote balanced land use planning, and judiciously exploit natural resources. Applications using the GDSS have demonstrated the benefits of utilizing science for policy decisions. Investment in science reduces decision-making uncertainty and reducing that uncertainty has economic value.

The impact of health technology assessment reports on decision making in Austria.

PubMed

Zechmeister, Ingrid; Schumacher, Ines

2012-01-01

Health technology assessment (HTA) was established in Austria in the 1990s and, since then, it has gained considerable importance. In this study, we aim to analyze whether the HTA reports that have been produced at the Institute for Technology Assessment (ITA) and at the Ludwig Boltzmann Institute for HTA (LBI-HTA) have had an impact on decision making within the Austrian health care system. We selected all reports that were intended for supporting (i) reimbursement/investment or (ii) disinvestment decisions. Eleven full HTA reports and fifty-eight rapid assessments fulfilled the inclusion criteria. We used interview data and administrative data on volumes, tariffs and expenditure of products/services to analyze whether and how reports were in reality used in decision making and what the consequences for health care expenditure and resource distribution have been. Five full HTA reports and fifty-six rapid technology assessments were used for reimbursement decisions. Four full HTA reports and two rapid assessments were used for disinvestment decisions and resulted in reduced volumes and expenditure. Two full HTA reports showed no impact on decision making. Impact was most evident for hospital technologies. HTA has played some role in reducing volumes of over-supplied hospital technologies, resulting in reduced expenditure for several hospital providers. Additionally, it has been increasingly included in prospective planning and reimbursement decisions of late, indicating re-distribution of resources toward evidence-based technologies. However, further factors may have influenced the decisions, and the impact could be considerably increased by systematically incorporating HTA into the decision-making process in Austria.

Exploring Data-Driven Decision-Making in the Field: How Faculty Use Data and Other Forms of Information to Guide Instructional Decision-Making. WCER Working Paper No. 2014-3

ERIC Educational Resources Information Center

Hora, Matthew T.; Bouwma-Gearhart, Jana; Park, Hyoung Joon

2014-01-01

A defining characteristic of current U.S. educational policy is the use of data to inform decisions about resource allocation, teacher hiring, and curriculum and instruction. Perhaps the biggest challenge to data-driven decision making (DDDM) is that data use alone does not automatically result in improved teaching and learning. Research indicates…

Evaluation of EMERGE, a Medical Decision Making Aid for Analysis of Chest Pain

PubMed Central

Hudson, Donna L.; Cohen, Moses E.; Deedwania, Prakash C.; Watson, Patricia E.

1983-01-01

EMERGE, a rule-based medical decision making aid for analysis of chest pain in the emergency room, was evaluated using retrospective patient data. The analysis consisted of two phases. In the initial phase, patient cases were run in order to make minor modifications and adjustments in the criteria used for determination of admission. In the second phase, patient cases were analyzed to determine the effectiveness of the EMERGE system in arriving at the proper conclusion.

Distributed Cognition in Cancer Treatment Decision Making: An Application of the DECIDE Decision-Making Styles Typology.

PubMed

Krieger, Janice L; Krok-Schoen, Jessica L; Dailey, Phokeng M; Palmer-Wackerly, Angela L; Schoenberg, Nancy; Paskett, Electra D; Dignan, Mark

2017-07-01

Distributed cognition occurs when cognitive and affective schemas are shared between two or more people during interpersonal discussion. Although extant research focuses on distributed cognition in decision making between health care providers and patients, studies show that caregivers are also highly influential in the treatment decisions of patients. However, there are little empirical data describing how and when families exert influence. The current article addresses this gap by examining decisional support in the context of cancer randomized clinical trial (RCT) decision making. Data are drawn from in-depth interviews with rural, Appalachian cancer patients ( N = 46). Analysis of transcript data yielded empirical support for four distinct models of health decision making. The implications of these findings for developing interventions to improve the quality of treatment decision making and overall well-being are discussed.

Decision-making impairments in the context of intact reward sensitivity in schizophrenia.

PubMed

Heerey, Erin A; Bell-Warren, Kimberly R; Gold, James M

2008-07-01

Deficits in motivated behavior and decision-making figure prominently in the behavioral syndrome that characterizes schizophrenia and are difficult both to treat and to understand. One explanation for these deficits is that schizophrenia decreases sensitivity to rewards in the environment. An alternate explanation is that sensitivity to rewards is intact but that poor integration of affective with cognitive information impairs the ability to use this information to guide behavior. We tested reward sensitivity with a modified version of an existing signal detection task with asymmetric reinforcement and decision-making with a probabilistic decision-making task in 40 participants with schizophrenia and 26 healthy participants. Results showed normal sensitivity to reward in participants with schizophrenia but differences in choice patterns on the decision-making task. A logistic regression model of the decision-making data showed that participants with schizophrenia differed from healthy participants in the ability to weigh potential outcomes, specifically potential losses, when choosing between competing response options. Deficits in working memory ability accounted for group differences in ability to use potential outcomes during decision-making. These results suggest that the implicit mechanisms that drive reward-based learning are surprisingly intact in schizophrenia but that poor ability to integrate cognitive and affective information when calculating the value of possible choices might hamper the ability to use such information during explicit decision-making.

Understanding How Principals Use Data Dashboards to Inform Systemic School Improvement

ERIC Educational Resources Information Center

Marker, Kathryn Christner

2016-01-01

Because data access may be perceived by principals as overwhelming or irrelevant rather than helpful (Wayman, Spikes, & Volonnino, 2013), data access does not guarantee effective data use. The data-based decision making literature has largely focused on teacher use of data, considering less often data-based organizational improvements for the…

A critical narrative analysis of shared decision-making in acute inpatient mental health care.

PubMed

Stacey, Gemma; Felton, Anne; Morgan, Alastair; Stickley, Theo; Willis, Martin; Diamond, Bob; Houghton, Philip; Johnson, Beverley; Dumenya, John

2016-01-01

Shared decision-making (SDM) is a high priority in healthcare policy and is complementary to the recovery philosophy in mental health care. This agenda has been operationalised within the Values-Based Practice (VBP) framework, which offers a theoretical and practical model to promote democratic interprofessional approaches to decision-making. However, these are limited by a lack of recognition of the implications of power implicit within the mental health system. This study considers issues of power within the context of decision-making and examines to what extent decisions about patients' care on acute in-patient wards are perceived to be shared. Focus groups were conducted with 46 mental health professionals, service users, and carers. The data were analysed using the framework of critical narrative analysis (CNA). The findings of the study suggested each group constructed different identity positions, which placed them as inside or outside of the decision-making process. This reflected their view of themselves as best placed to influence a decision on behalf of the service user. In conclusion, the discourse of VBP and SDM needs to take account of how differentials of power and the positioning of speakers affect the context in which decisions take place.

[The role of research-based evidence in health system policy decision-making].

PubMed

Patiño, Daniel; Lavis, John N; Moat, Kaelan

2013-01-01

Different models may be used for explaining how research-based evidence is used in healthcare system policy-making. It is argued that models arising from a clinical setting (i.e. evidence-based policy-making model) could be useful regarding some types of healthcare system decision-making. However, such models are "silent" concerning the influence of political contextual factors on healthcare policy-making and are thus inconsistent with decision-making regarding the modification of healthcare system arrangements. Other political science-based models would seem to be more useful for understanding that research is just one factor affecting decision-making and that different types of research-based evidence can be used instrumentally, conceptual or strategically during different policy-making stages.

The emergent relevance of care staff decision-making and situation awareness to mobility care in nursing homes: an ethnographic study.

PubMed

Taylor, Janice; Sims, Jane; Haines, Terry P

2014-12-01

To explore mobility care as provided by care staff in nursing homes. Care staff regularly assist residents with their mobility. Nurses are increasingly reliant on such staff to provide safe and quality mobility care. However, the nature of care staff decision-making when providing assistance has not been fully addressed in the literature. A focused ethnography. The study was conducted in four nursing homes in Melbourne, Australia. Non-participant observations of residents and staff in 2011. Focus groups with 18 nurses, care and lifestyle staff were conducted at three facilities in 2012. Thematic analysis was employed for focus groups and content analysis for observation data. Cognitive Continuum Theory and the notion of 'situation awareness' assisted data interpretation. Decision-making during mobility care emerged as a major theme. Using Cognitive Continuum Theory as a guide, nursing home staff's decision-making was described as ranging from system-aided, through resident- and peer-aided, to reflective and intuitive. Staff seemed aware of the need for resident-aided decision-making consistent with person-centred care. Habitual mobility care based on shared mental models occurred. It was noted that levels of situation awareness may vary among staff. Care staff may benefit from support via collaborative and reflective practice to develop decision-making skills, situation awareness and person-centred mobility care. Further research is required to explore the connection between staff's skills in mobility care and their decision-making competence as well as how these factors link to quality mobility care. © 2014 John Wiley & Sons Ltd.

Decision making based on data analysis and optimization algorithm applied for cogeneration systems integration into a grid

NASA Astrophysics Data System (ADS)

Asmar, Joseph Al; Lahoud, Chawki; Brouche, Marwan

2018-05-01

Cogeneration and trigeneration systems can contribute to the reduction of primary energy consumption and greenhouse gas emissions in residential and tertiary sectors, by reducing fossil fuels demand and grid losses with respect to conventional systems. The cogeneration systems are characterized by a very high energy efficiency (80 to 90%) as well as a less polluting aspect compared to the conventional energy production. The integration of these systems into the energy network must simultaneously take into account their economic and environmental challenges. In this paper, a decision-making strategy will be introduced and is divided into two parts. The first one is a strategy based on a multi-objective optimization tool with data analysis and the second part is based on an optimization algorithm. The power dispatching of the Lebanese electricity grid is then simulated and considered as a case study in order to prove the compatibility of the cogeneration power calculated by our decision-making technique. In addition, the thermal energy produced by the cogeneration systems which capacity is selected by our technique shows compatibility with the thermal demand for district heating.

Risk-taking and decision-making in youth: relationships to addiction vulnerability.

PubMed

Balogh, Kornelia N; Mayes, Linda C; Potenza, Marc N

2013-03-01

Decision-making and risk-taking behavior undergo developmental changes during adolescence. Disadvantageous decision-making and increased risk-taking may lead to problematic behaviors such as substance use and abuse, pathological gambling and excessive internet use. Based on MEDLINE searches, this article reviews the literature on decision-making and risk-taking and their relationship to addiction vulnerability in youth. Decision-making and risk-taking behaviors involve brain areas that undergoing developmental changes during puberty and young adulthood. Individual differences and peer pressure also relate importantly to decision-making and risk-taking. Brain-based changes in emotional, motivational and cognitive processing may underlie risk-taking and decision-making propensities in adolescence, making this period a time of heightened vulnerability for engagement in additive behaviors.

Policy, practice and decision making for zoonotic disease management: water and Cryptosporidium.

PubMed

Austin, Zoë; Alcock, Ruth E; Christley, Robert M; Haygarth, Philip M; Heathwaite, A Louise; Latham, Sophia M; Mort, Maggie; Oliver, David M; Pickup, Roger; Wastling, Jonathan M; Wynne, Brian

2012-04-01

Decision making for zoonotic disease management should be based on many forms of appropriate data and sources of evidence. However, the criteria and timing for policy response and the resulting management decisions are often altered when a disease outbreak occurs and captures full media attention. In the case of waterborne disease, such as the robust protozoa, Cryptosporidium spp, exposure can cause significant human health risks and preventing exposure by maintaining high standards of biological and chemical water quality remains a priority for water companies in the UK. Little has been documented on how knowledge and information is translated between the many stakeholders involved in the management of Cryptosporidium, which is surprising given the different drivers that have shaped management decisions. Such information, coupled with the uncertainties that surround these data is essential for improving future management strategies that minimise disease outbreaks. Here, we examine the interplay between scientific information, the media, and emergent government and company policies to examine these issues using qualitative and quantitative data relating to Cryptosporidium management decisions by a water company in the North West of England. Our results show that political and media influences are powerful drivers of management decisions if fuelled by high profile outbreaks. Furthermore, the strength of the scientific evidence is often constrained by uncertainties in the data, and in the way knowledge is translated between policy levels during established risk management procedures. In particular, under or over-estimating risk during risk assessment procedures together with uncertainty regarding risk factors within the wider environment, was found to restrict the knowledge-base for decision-making in Cryptosporidium management. Our findings highlight some key current and future challenges facing the management of such diseases that are widely applicable to other risk management situations. Copyright © 2011 Elsevier Ltd. All rights reserved.

Discrete event simulation for healthcare organizations: a tool for decision making.

PubMed

Hamrock, Eric; Paige, Kerrie; Parks, Jennifer; Scheulen, James; Levin, Scott

2013-01-01

Healthcare organizations face challenges in efficiently accommodating increased patient demand with limited resources and capacity. The modern reimbursement environment prioritizes the maximization of operational efficiency and the reduction of unnecessary costs (i.e., waste) while maintaining or improving quality. As healthcare organizations adapt, significant pressures are placed on leaders to make difficult operational and budgetary decisions. In lieu of hard data, decision makers often base these decisions on subjective information. Discrete event simulation (DES), a computerized method of imitating the operation of a real-world system (e.g., healthcare delivery facility) over time, can provide decision makers with an evidence-based tool to develop and objectively vet operational solutions prior to implementation. DES in healthcare commonly focuses on (1) improving patient flow, (2) managing bed capacity, (3) scheduling staff, (4) managing patient admission and scheduling procedures, and (5) using ancillary resources (e.g., labs, pharmacies). This article describes applicable scenarios, outlines DES concepts, and describes the steps required for development. An original DES model developed to examine crowding and patient flow for staffing decision making at an urban academic emergency department serves as a practical example.

Drug pricing and reimbursement decision making systems in Mongolia.

PubMed

Dorj, Gereltuya; Sunderland, Bruce; Sanjjav, Tsetsegmaa; Dorj, Gantuya; Gendenragchaa, Byambatsogt

2017-01-01

It is essential to allocate available resources equitably in order to ensure accessibility and affordability of essential medicines, especially in less fortunate nations with limited health funding. Currently, transparent and evidence based research is required to evaluate decision making regarding drug registration, drug pricing and reimbursement processes in Mongolia. To assess the drug reimbursement system and discuss challenges faced by policy-makers and stakeholders. The study has examined Mongolian administrative documents and directives for stakeholders and analysed published statistics. Experts and decision-makers were interviewed about the drug pricing and reimbursement processes in Mongolia. Decisions regarding Mongolian drug registration were based on commonly used criteria of quality, safety, efficacy plus some economic considerations. A total of 11.32 billion Mongolian National Tugrugs (MNT) [5.6 million United States Dollars (USD)] or 12.1% of total health expenditure was spent on patient reimbursement of essential drugs. The highest reimbursed drugs with respect to cost in 2014 were the cardiovascular drug group. Health insurance is compulsory for all citizens; in addition all insured patients have access to reimbursed drugs. However, the decision making process, in particular the level of reimbursement was limited by various barriers, including lack of evidence based data regarding efficacy and comparative cost-effectiveness analysis of drugs and decisions regarding reimbursement. Drug registration, pricing and reimbursement process in Mongolia show an increasing trend of drug registration and reimbursement rates, along with lack of transparency. Limited available data indicate that more evidence-based research studies are required in Mongolia to evaluate and improve the effectiveness of drug pricing and reimbursement policies.

Foundations for context-aware information retrieval for proactive decision support

NASA Astrophysics Data System (ADS)

Mittu, Ranjeev; Lin, Jessica; Li, Qingzhe; Gao, Yifeng; Rangwala, Huzefa; Shargo, Peter; Robinson, Joshua; Rose, Carolyn; Tunison, Paul; Turek, Matt; Thomas, Stephen; Hanselman, Phil

2016-05-01

Intelligence analysts and military decision makers are faced with an onslaught of information. From the now ubiquitous presence of intelligence, surveillance, and reconnaissance (ISR) platforms providing large volumes of sensor data, to vast amounts of open source data in the form of news reports, blog postings, or social media postings, the amount of information available to a modern decision maker is staggering. Whether tasked with leading a military campaign or providing support for a humanitarian mission, being able to make sense of all the information available is a challenge. Due to the volume and velocity of this data, automated tools are required to help support reasoned, human decisions. In this paper we describe several automated techniques that are targeted at supporting decision making. Our approaches include modeling the kinematics of moving targets as motifs; developing normalcy models and detecting anomalies in kinematic data; automatically classifying the roles of users in social media; and modeling geo-spatial regions based on the behavior that takes place in them. These techniques cover a wide-range of potential decision maker needs.

Watson will see you now: a supercomputer to help clinicians make informed treatment decisions.

PubMed

Doyle-Lindrud, Susan

2015-02-01

IBM has collaborated with several cancer care providers to develop and train the IBM supercomputer Watson to help clinicians make informed treatment decisions. When a patient is seen in clinic, the oncologist can input all of the clinical information into the computer system. Watson will then review all of the data and recommend treatment options based on the latest evidence and guidelines. Once the oncologist makes the treatment decision, this information can be sent directly to the insurance company for approval. Watson has the ability to standardize care and accelerate the approval process, a benefit to the healthcare provider and the patient.

Consumer Product Data for Exposure Screening, Modeling and Prioritization, and Risk-based Decision Making

EPA Science Inventory

This presentation will provide an overview of the research efforts underway in EPA ORD's Chemicals for Safety and Sustainability research program which relate to providing information to prioritize chemicals in consumer products based on risk. It also describes effort to make dat...

A novel computer based expert decision making model for prostate cancer disease management.

PubMed

Richman, Martin B; Forman, Ernest H; Bayazit, Yildirim; Einstein, Douglas B; Resnick, Martin I; Stovsky, Mark D

2005-12-01

We propose a strategic, computer based, prostate cancer decision making model based on the analytic hierarchy process. We developed a model that improves physician-patient joint decision making and enhances the treatment selection process by making this critical decision rational and evidence based. Two groups (patient and physician-expert) completed a clinical study comparing an initial disease management choice with the highest ranked option generated by the computer model. Participants made pairwise comparisons to derive priorities for the objectives and subobjectives related to the disease management decision. The weighted comparisons were then applied to treatment options to yield prioritized rank lists that reflect the likelihood that a given alternative will achieve the participant treatment goal. Aggregate data were evaluated by inconsistency ratio analysis and sensitivity analysis, which assessed the influence of individual objectives and subobjectives on the final rank list of treatment options. Inconsistency ratios less than 0.05 were reliably generated, indicating that judgments made within the model were mathematically rational. The aggregate prioritized list of treatment options was tabulated for the patient and physician groups with similar outcomes for the 2 groups. Analysis of the major defining objectives in the treatment selection decision demonstrated the same rank order for the patient and physician groups with cure, survival and quality of life being more important than controlling cancer, preventing major complications of treatment, preventing blood transfusion complications and limiting treatment cost. Analysis of subobjectives, including quality of life and sexual dysfunction, produced similar priority rankings for the patient and physician groups. Concordance between initial treatment choice and the highest weighted model option differed between the groups with the patient group having 59% concordance and the physician group having only 42% concordance. This study successfully validated the usefulness of a computer based prostate cancer management decision making model to produce individualized, rational, clinically appropriate disease management decisions without physician bias.

Advances in the Application of Decision Theory to Test-Based Decision Making.

ERIC Educational Resources Information Center

van der Linden, Wim J.

This paper reviews recent research in the Netherlands on the application of decision theory to test-based decision making about personnel selection and student placement. The review is based on an earlier model proposed for the classification of decision problems, and emphasizes an empirical Bayesian framework. Classification decisions with…

Dynamic fluctuations in dopamine efflux in the prefrontal cortex and nucleus accumbens during risk-based decision making.

PubMed

St Onge, Jennifer R; Ahn, Soyon; Phillips, Anthony G; Floresco, Stan B

2012-11-21

Mesocorticolimbic dopamine (DA) has been implicated in cost/benefit decision making about risks and rewards. The prefrontal cortex (PFC) and nucleus accumbens (NAc) are two DA terminal regions that contribute to decision making in distinct manners. However, how fluctuations of tonic DA levels may relate to different aspects of decision making remains to be determined. The present study measured DA efflux in the PFC and NAc with microdialysis in well trained rats performing a probabilistic discounting task. Selection of a small/certain option always delivered one pellet, whereas another, large/risky option yielded four pellets, with probabilities that decreased (100-12.5%) or increased (12.5-100%) across four blocks of trials. Yoked-reward groups were also included to control for reward delivery. PFC DA efflux during decision making decreased or increased over a session, corresponding to changes in large/risky reward probabilities. Similar profiles were observed from yoked-rewarded rats, suggesting that fluctuations in PFC DA reflect changes in the relative rate of reward received. NAc DA efflux also showed decreasing/increasing trends over the session during both tasks. However, DA efflux was higher during decision making on free- versus forced-choice trials and during periods of greater reward uncertainty. Moreover, changes in NAc DA closely tracked shifts in choice biases. These data reveal dynamic and dissociable fluctuations in PFC and NAc DA transmission associated with different aspects of risk-based decision making. PFC DA may signal changes in reward availability that facilitates modification of choice biases, whereas NAc DA encodes integrated signals about reward rates, uncertainty, and choice, reflecting implementation of decision policies.

An Educator's Guide to Questionnaire Development. REL 2016-108

ERIC Educational Resources Information Center

Harlacher, Jason

2016-01-01

Educators have many decisions to make and it's important that they have the right data to inform those decisions and access to questionnaires that can gather that data. This guide, developed by REL Central and based on work done through separate projects with the Wyoming Office of Public Instruction and the Nebraska Department of Education,…

Keeping Teachers in the Center: A Framework of Data-Driven Decision-Making

ERIC Educational Resources Information Center

Light, Daniel; Wexler, Dara H.; Heinze, Juliette

2004-01-01

The Education Development Center's Center for Children and Technology (CCT) conducted a three year study of a large-scale data reporting system, developed by the Grow Network for New York City's Department of Education. This paper presents a framework based on two years of research exploring the intersection of decision-support technologies,…

Poor Decision Making Is a Consequence of Cognitive Decline among Older Persons without Alzheimer’s Disease or Mild Cognitive Impairment

PubMed Central

Boyle, Patricia A.; Yu, Lei; Wilson, Robert S.; Gamble, Keith; Buchman, Aron S.; Bennett, David A.

2012-01-01

Objective Decision making is an important determinant of health and well-being across the lifespan but is critical in aging, when many influential decisions are made just as cognitive function declines. Increasing evidence suggests that older adults, even those without dementia, often make poor decisions and are selectively vulnerable to scams. To date, however, the factors associated with poor decision making in old age are unknown. The objective of this study was to test the hypothesis that poor decision making is a consequence of cognitive decline among older persons without Alzheimer’s disease or mild cognitive impairment. Methods Participants were 420 non-demented persons from the Memory and Aging Project, a longitudinal, clinical-pathologic cohort study of aging in the Chicago metropolitan area. All underwent repeated cognitive evaluations and subsequently completed assessments of decision making and susceptibility to scams. Decision making was measured using 12 items from a previously established performance-based measure and a self-report measure of susceptibility to scams. Results Cognitive function data were collected over an average of 5.5 years prior to the decision making assessment. Regression analyses were used to examine whether the prior rate of cognitive decline predicted the level of decision making and susceptibility to scams; analyses controlled for age, sex, education, and starting level of cognition. Among 420 persons without dementia, more rapid cognitive decline predicted poorer decision making and increased susceptibility to scams (p’s<0.001). Further, the relations between cognitive decline, decision making and scams persisted in analyses restricted to persons without any cognitive impairment (i.e., no dementia or even mild cognitive impairment). Conclusions Poor decision making is a consequence of cognitive decline among older persons without Alzheimer’s disease or mild cognitive impairment, those widely considered “cognitively healthy.” These findings suggest that even very subtle age-related changes in cognition have detrimental effects on judgment. PMID:22916287

Incentives for Optimal Multi-level Allocation of HIV Prevention Resources

PubMed Central

Malvankar, Monali M.; Zaric, Gregory S.

2013-01-01

HIV/AIDS prevention funds are often allocated at multiple levels of decision-making. Optimal allocation of HIV prevention funds maximizes the number of HIV infections averted. However, decision makers often allocate using simple heuristics such as proportional allocation. We evaluate the impact of using incentives to encourage optimal allocation in a two-level decision-making process. We model an incentive based decision-making process consisting of an upper-level decision maker allocating funds to a single lower-level decision maker who then distributes funds to local programs. We assume that the lower-level utility function is linear in the amount of the budget received from the upper-level, the fraction of funds reserved for proportional allocation, and the number of infections averted. We assume that the upper level objective is to maximize the number of infections averted. We illustrate with an example using data from California, U.S. PMID:23766551

Probabilistic Reward- and Punishment-based Learning in Opioid Addiction: Experimental and Computational Data

PubMed Central

Myers, Catherine E.; Sheynin, Jony; Baldson, Tarryn; Luzardo, Andre; Beck, Kevin D.; Hogarth, Lee; Haber, Paul; Moustafa, Ahmed A.

2016-01-01

Addiction is the continuation of a habit in spite of negative consequences. A vast literature gives evidence that this poor decision-making behavior in individuals addicted to drugs also generalizes to laboratory decision making tasks, suggesting that the impairment in decision-making is not limited to decisions about taking drugs. In the current experiment, opioid-addicted individuals and matched controls with no history of illicit drug use were administered a probabilistic classification task that embeds both reward-based and punishment-based learning trials, and a computational model of decision making was applied to understand the mechanisms describing individuals’ performance on the task. Although behavioral results showed thatopioid-addicted individuals performed as well as controls on both reward- and punishment-based learning, the modeling results suggested subtle differences in how decisions were made between the two groups. Specifically, the opioid-addicted group showed decreased tendency to repeat prior responses, meaning that they were more likely to “chase reward” when expectancies were violated, whereas controls were more likely to stick with a previously-successful response rule, despite occasional expectancy violations. This tendency to chase short-term reward, potentially at the expense of developing rules that maximize reward over the long term, may be a contributing factor to opioid addiction. Further work is indicated to better understand whether this tendency arises as a result of brain changes in the wake of continued opioid use/abuse, or might be a pre-existing factor that may contribute to risk for addiction. PMID:26381438

"Moneyball" for Education Using Data, Evidence, and Evaluation to Improve Federal Education Policy

ERIC Educational Resources Information Center

Hess, Frederick M.; Little, Bethany

2015-01-01

More than a decade ago, Michael Lewis penned the influential book "Moneyball." An examination of how Oakland Athletics General Manager Billy Beane used data to make his franchise competitive with wealthier baseball teams, the book struck a chord. Beane's strategy of making decisions based on data had a powerful and positive impact on the…

Young People's Decision-Making: The Importance of High Quality School-Based Careers Education, Information, Advice and Guidance

ERIC Educational Resources Information Center

Haynes, Gill; McCrone, Tami; Wade, Pauline

2013-01-01

This paper explores the decision-making processes of young people aged 13-14?years in 30 consortia across England as they chose their options for Key Stage 4 at a time when a new qualification, the 14-19 Diploma, was being introduced. It draws on data collected as part of a longitudinal national study (January 2008-August 2011) of the introduction…

Evolutionary Algorithm Based Automated Reverse Engineering and Defect Discovery

DTIC Science & Technology

2007-09-21

a previous application of a GP as a data mining function to evolve fuzzy decision trees symbolically [3-5], the terminal set consisted of fuzzy...of input and output information is required. In the case of fuzzy decision trees, the database represented a collection of scenarios about which the...fuzzy decision tree to be evolved would make decisions . The database also had entries created by experts representing decisions about the scenarios

A behavioural and neural evaluation of prospective decision-making under risk

PubMed Central

Symmonds, Mkael; Bossaerts, Peter; Dolan, Raymond J.

2010-01-01

Making the best choice when faced with a chain of decisions requires a person to judge both anticipated outcomes and future actions. Although economic decision-making models account for both risk and reward in single choice contexts there is a dearth of similar knowledge about sequential choice. Classical utility-based models assume that decision-makers select and follow an optimal pre-determined strategy, irrespective of the particular order in which options are presented. An alternative model involves continuously re-evaluating decision utilities, without prescribing a specific future set of choices. Here, using behavioral and functional magnetic resonance imaging (fMRI) data, we studied human subjects in a sequential choice task and use these data to compare alternative decision models of valuation and strategy selection. We provide evidence that subjects adopt a model of re-evaluating decision utilities, where available strategies are continuously updated and combined in assessing action values. We validate this model by using simultaneously-acquired fMRI data to show that sequential choice evokes a pattern of neural response consistent with a tracking of anticipated distribution of future reward, as expected in such a model. Thus, brain activity evoked at each decision point reflects the expected mean, variance and skewness of possible payoffs, consistent with the idea that sequential choice evokes a prospective evaluation of both available strategies and possible outcomes. PMID:20980595

A behavioral and neural evaluation of prospective decision-making under risk.

PubMed

Symmonds, Mkael; Bossaerts, Peter; Dolan, Raymond J

2010-10-27

Making the best choice when faced with a chain of decisions requires a person to judge both anticipated outcomes and future actions. Although economic decision-making models account for both risk and reward in single-choice contexts, there is a dearth of similar knowledge about sequential choice. Classical utility-based models assume that decision-makers select and follow an optimal predetermined strategy, regardless of the particular order in which options are presented. An alternative model involves continuously reevaluating decision utilities, without prescribing a specific future set of choices. Here, using behavioral and functional magnetic resonance imaging (fMRI) data, we studied human subjects in a sequential choice task and use these data to compare alternative decision models of valuation and strategy selection. We provide evidence that subjects adopt a model of reevaluating decision utilities, in which available strategies are continuously updated and combined in assessing action values. We validate this model by using simultaneously acquired fMRI data to show that sequential choice evokes a pattern of neural response consistent with a tracking of anticipated distribution of future reward, as expected in such a model. Thus, brain activity evoked at each decision point reflects the expected mean, variance, and skewness of possible payoffs, consistent with the idea that sequential choice evokes a prospective evaluation of both available strategies and possible outcomes.

Multialternative drift-diffusion model predicts the relationship between visual fixations and choice in value-based decisions.

PubMed

Krajbich, Ian; Rangel, Antonio

2011-08-16

How do we make decisions when confronted with several alternatives (e.g., on a supermarket shelf)? Previous work has shown that accumulator models, such as the drift-diffusion model, can provide accurate descriptions of the psychometric data for binary value-based choices, and that the choice process is guided by visual attention. However, the computational processes used to make choices in more complicated situations involving three or more options are unknown. We propose a model of trinary value-based choice that generalizes what is known about binary choice, and test it using an eye-tracking experiment. We find that the model provides a quantitatively accurate description of the relationship between choice, reaction time, and visual fixation data using the same parameters that were estimated in previous work on binary choice. Our findings suggest that the brain uses similar computational processes to make binary and trinary choices.

Multiple attribute decision making model and application to food safety risk evaluation.

PubMed

Ma, Lihua; Chen, Hong; Yan, Huizhe; Yang, Lifeng; Wu, Lifeng

2017-01-01

Decision making for supermarket food purchase decisions are characterized by network relationships. This paper analyzed factors that influence supermarket food selection and proposes a supplier evaluation index system based on the whole process of food production. The author established the intuitive interval value fuzzy set evaluation model based on characteristics of the network relationship among decision makers, and validated for a multiple attribute decision making case study. Thus, the proposed model provides a reliable, accurate method for multiple attribute decision making.

Operationalising uncertainty in data and models for integrated water resources management.

PubMed

Blind, M W; Refsgaard, J C

2007-01-01

Key sources of uncertainty of importance for water resources management are (1) uncertainty in data; (2) uncertainty related to hydrological models (parameter values, model technique, model structure); and (3) uncertainty related to the context and the framing of the decision-making process. The European funded project 'Harmonised techniques and representative river basin data for assessment and use of uncertainty information in integrated water management (HarmoniRiB)' has resulted in a range of tools and methods to assess such uncertainties, focusing on items (1) and (2). The project also engaged in a number of discussions surrounding uncertainty and risk assessment in support of decision-making in water management. Based on the project's results and experiences, and on the subsequent discussions a number of conclusions can be drawn on the future needs for successful adoption of uncertainty analysis in decision support. These conclusions range from additional scientific research on specific uncertainties, dedicated guidelines for operational use to capacity building at all levels. The purpose of this paper is to elaborate on these conclusions and anchoring them in the broad objective of making uncertainty and risk assessment an essential and natural part in future decision-making processes.

NASA Wrangler: Automated Cloud-Based Data Assembly in the RECOVER Wildfire Decision Support System

NASA Technical Reports Server (NTRS)

Schnase, John; Carroll, Mark; Gill, Roger; Wooten, Margaret; Weber, Keith; Blair, Kindra; May, Jeffrey; Toombs, William

2017-01-01

NASA Wrangler is a loosely-coupled, event driven, highly parallel data aggregation service designed to take advantageof the elastic resource capabilities of cloud computing. Wrangler automatically collects Earth observational data, climate model outputs, derived remote sensing data products, and historic biophysical data for pre-, active-, and post-wildfire decision making. It is a core service of the RECOVER decision support system, which is providing rapid-response GIS analytic capabilities to state and local government agencies. Wrangler reduces to minutes the time needed to assemble and deliver crucial wildfire-related data.

Risk-taking and decision-making in youth: relationships to addiction vulnerability

PubMed Central

Balogh, Kornelia N.; Mayes, Linda C.; Potenza, Marc N.

2013-01-01

Background Decision-making and risk-taking behavior undergo developmental changes during adolescence. Disadvantageous decision-making and increased risk-taking may lead to problematic behaviors such as substance use and abuse, pathological gambling and excessive internet use. Methods Based on MEDLINE searches, this article reviews the literature on decision-making and risk-taking and their relationship to addiction vulnerability in youth. Results Decision-making and risk-taking behaviors involve brain areas that undergoing developmental changes during puberty and young adulthood. Individual differences and peer pressure also relate importantly to decision-making and risk-taking. Conclusions Brain-based changes in emotional, motivational and cognitive processing may underlie risk-taking and decision-making propensities in adolescence, making this period a time of heightened vulnerability for engagement in additive behaviors. PMID:24294500

City-Level Energy Decision Making. Data Use in Energy Planning, Implementation, and Evaluation in U.S. Cities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aznar, Alexandra; Day, Megan; Doris, Elizabeth

2015-07-08

The Cities-LEAP technical report, City-Level Energy Decision Making: Data Use in Energy Planning, Implementation, and Evaluation in U.S. Cities, explores how a sample of cities incorporates data into making energy-related decisions. This report provides the foundation for forthcoming components of the Cities-LEAP project that will help cities improve energy decision making by mapping specific city energy or climate policies and actions to measurable impacts and results.

Stakeholders apply the GRADE evidence-to-decision framework to facilitate coverage decisions.

PubMed

Dahm, Philipp; Oxman, Andrew D; Djulbegovic, Benjamin; Guyatt, Gordon H; Murad, M Hassan; Amato, Laura; Parmelli, Elena; Davoli, Marina; Morgan, Rebecca L; Mustafa, Reem A; Sultan, Shahnaz; Falck-Ytter, Yngve; Akl, Elie A; Schünemann, Holger J

2017-06-01

Coverage decisions are complex and require the consideration of many factors. A well-defined, transparent process could improve decision-making and facilitate decision-maker accountability. We surveyed key US-based stakeholders regarding their current approaches for coverage decisions. Then, we held a workshop to test an evidence-to-decision (EtD) framework for coverage based on the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) criteria. A total of 42 individuals (including 19 US stakeholders as well as international health policymakers and GRADE working group members) attended the workshop. Of the 19 stakeholders, 14 (74%) completed the survey before the workshop. Almost all of their organizations (13 of 14; 93%) used systematic reviews for coverage decision-making; few (2 of 14; 14%) developed their own evidence synthesis; a majority (9 of 14; 64%) rated the certainty of evidence (using various systems); almost all (13 of 14; 93%) denied formal consideration of resource use; and half (7 of 14; 50%) reported explicit criteria for decision-making. At the workshop, stakeholders successfully applied the EtD framework to four case studies and provided narrative feedback, which centered on contextual factors affecting coverage decisions in the United States, the need for reliable data on subgroups of patients, and the challenge of decision-making without formal consideration of resource use. Stakeholders successfully applied the EtD framework to four case studies and highlighted contextual factors affecting coverage decisions and affirmed its value. Their input informed the further development of a revised EtD framework, now publicly available (http://gradepro.org/). Published by Elsevier Inc.

Collaborative mining and interpretation of large-scale data for biomedical research insights.

PubMed

Tsiliki, Georgia; Karacapilidis, Nikos; Christodoulou, Spyros; Tzagarakis, Manolis

2014-01-01

Biomedical research becomes increasingly interdisciplinary and collaborative in nature. Researchers need to efficiently and effectively collaborate and make decisions by meaningfully assembling, mining and analyzing available large-scale volumes of complex multi-faceted data residing in different sources. In line with related research directives revealing that, in spite of the recent advances in data mining and computational analysis, humans can easily detect patterns which computer algorithms may have difficulty in finding, this paper reports on the practical use of an innovative web-based collaboration support platform in a biomedical research context. Arguing that dealing with data-intensive and cognitively complex settings is not a technical problem alone, the proposed platform adopts a hybrid approach that builds on the synergy between machine and human intelligence to facilitate the underlying sense-making and decision making processes. User experience shows that the platform enables more informed and quicker decisions, by displaying the aggregated information according to their needs, while also exploiting the associated human intelligence.

Collaborative Mining and Interpretation of Large-Scale Data for Biomedical Research Insights

PubMed Central

Tsiliki, Georgia; Karacapilidis, Nikos; Christodoulou, Spyros; Tzagarakis, Manolis

2014-01-01

Biomedical research becomes increasingly interdisciplinary and collaborative in nature. Researchers need to efficiently and effectively collaborate and make decisions by meaningfully assembling, mining and analyzing available large-scale volumes of complex multi-faceted data residing in different sources. In line with related research directives revealing that, in spite of the recent advances in data mining and computational analysis, humans can easily detect patterns which computer algorithms may have difficulty in finding, this paper reports on the practical use of an innovative web-based collaboration support platform in a biomedical research context. Arguing that dealing with data-intensive and cognitively complex settings is not a technical problem alone, the proposed platform adopts a hybrid approach that builds on the synergy between machine and human intelligence to facilitate the underlying sense-making and decision making processes. User experience shows that the platform enables more informed and quicker decisions, by displaying the aggregated information according to their needs, while also exploiting the associated human intelligence. PMID:25268270

Error-associated behaviors and error rates for robotic geology

NASA Technical Reports Server (NTRS)

Anderson, Robert C.; Thomas, Geb; Wagner, Jacob; Glasgow, Justin

2004-01-01

This study explores human error as a function of the decision-making process. One of many models for human decision-making is Rasmussen's decision ladder [9]. The decision ladder identifies the multiple tasks and states of knowledge involved in decision-making. The tasks and states of knowledge can be classified by the level of cognitive effort required to make the decision, leading to the skill, rule, and knowledge taxonomy (Rasmussen, 1987). Skill based decisions require the least cognitive effort and knowledge based decisions require the greatest cognitive effort. Errors can occur at any of the cognitive levels.

Teaching critical thinking.

PubMed

Holmes, N G; Wieman, Carl E; Bonn, D A

2015-09-08

The ability to make decisions based on data, with its inherent uncertainties and variability, is a complex and vital skill in the modern world. The need for such quantitative critical thinking occurs in many different contexts, and although it is an important goal of education, that goal is seldom being achieved. We argue that the key element for developing this ability is repeated practice in making decisions based on data, with feedback on those decisions. We demonstrate a structure for providing suitable practice that can be applied in any instructional setting that involves the acquisition of data and relating that data to scientific models. This study reports the results of applying that structure in an introductory physics laboratory course. Students in an experimental condition were repeatedly instructed to make and act on quantitative comparisons between datasets, and between data and models, an approach that is common to all science disciplines. These instructions were slowly faded across the course. After the instructions had been removed, students in the experimental condition were 12 times more likely to spontaneously propose or make changes to improve their experimental methods than a control group, who performed traditional experimental activities. The students in the experimental condition were also four times more likely to identify and explain a limitation of a physical model using their data. Students in the experimental condition also showed much more sophisticated reasoning about their data. These differences between the groups were seen to persist into a subsequent course taken the following year.

Teaching critical thinking

PubMed Central

Holmes, N. G.; Wieman, Carl E.; Bonn, D. A.

2015-01-01

The ability to make decisions based on data, with its inherent uncertainties and variability, is a complex and vital skill in the modern world. The need for such quantitative critical thinking occurs in many different contexts, and although it is an important goal of education, that goal is seldom being achieved. We argue that the key element for developing this ability is repeated practice in making decisions based on data, with feedback on those decisions. We demonstrate a structure for providing suitable practice that can be applied in any instructional setting that involves the acquisition of data and relating that data to scientific models. This study reports the results of applying that structure in an introductory physics laboratory course. Students in an experimental condition were repeatedly instructed to make and act on quantitative comparisons between datasets, and between data and models, an approach that is common to all science disciplines. These instructions were slowly faded across the course. After the instructions had been removed, students in the experimental condition were 12 times more likely to spontaneously propose or make changes to improve their experimental methods than a control group, who performed traditional experimental activities. The students in the experimental condition were also four times more likely to identify and explain a limitation of a physical model using their data. Students in the experimental condition also showed much more sophisticated reasoning about their data. These differences between the groups were seen to persist into a subsequent course taken the following year. PMID:26283351

Assessing Generalisability in Model-Based Economic Evaluation Studies: A Structured Review in Osteoporosis

PubMed Central

Urdahl, Hege; Manca, Andrea; Sculpher, Mark J

2008-01-01

Background To support decision making many countries have now introduced some formal assessment process to evaluate whether health technologies represent good ‘value for money’. These often take the form of decision models which can be used to explore elements of importance to generalisability of study results across clinical settings and jurisdictions. The objectives of the present review were to assess: (i) whether the published studies clearly defined the decision-making audience for the model; (ii) the transparency of the reporting in terms of study question, structure and data inputs; (iii) the relevance of the data inputs used in the model to the stated decision-maker or jurisdiction; and (iv) how fully the robustness of the model's results to variation in data inputs between locations was assessed. Methods Articles reporting decision-analytic models in the area of osteoporosis were assessed to establish the extent to which the information provided enabled decision makers in different countries/jurisdictions to fully appreciate the variability of results according to location, and the relevance to their own. Results Of the 18 articles included in the review, only three explicitly stated the decision-making audience. It was not possible to infer a decision-making audience in eight studies. Target population was well reported, as was resource and cost data, and clinical data used for estimates of relative risk reduction. However, baseline risk was rarely adapted to the relevant jurisdiction, and when no decision-maker was explicit it was difficult to assess whether the reported cost and resource use data was in fact relevant. A few studies used sensitivity analysis to explore elements of generalisability, such as compliance rates and baseline fracture risk rates, although such analyses were generally restricted to evaluating parameter uncertainty. Conclusion This review found that variability in cost-effectiveness across locations is addressed to a varying extent in modelling studies in the field of osteoporosis, limiting their use for decision-makers across different locations. Transparency of reporting is expected to increase as methodology develops, and decision-makers publish “reference case” type guidance. PMID:17129074

Integrated System of Structural Health Monitoring and Intelligent Management for a Cable-Stayed Bridge

PubMed Central

Chen, Bin; Wang, Xu; Sun, Dezhang; Xie, Xu

2014-01-01

It is essential to construct structural health monitoring systems for large important bridges. Zhijiang Bridge is a cable-stayed bridge that was built recently over the Hangzhou Qiantang River (the largest river in Zhejiang Province). The length of Zhijiang Bridge is 478 m, which comprises an arched twin-tower space and a twin-cable plane structure. As an example, the present study describes the integrated system of structural health monitoring and intelligent management for Zhijiang Bridge, which comprises an information acquisition system, data management system, evaluation and decision-making system, and application service system. The monitoring components include the working environment of the bridge and various factors that affect bridge safety, such as the stress and strain of the main bridge structure, vibration, cable force, temperature, and wind speed. In addition, the integrated system includes a forecasting and decision-making module for real-time online evaluation, which provides warnings and makes decisions based on the monitoring information. From this, the monitoring information, evaluation results, maintenance decisions, and warning information can be input simultaneously into the bridge monitoring center and traffic emergency center to share the monitoring data, thereby facilitating evaluations and decision making using the system. PMID:25140342

Integrated system of structural health monitoring and intelligent management for a cable-stayed bridge.

PubMed

Chen, Bin; Wang, Xu; Sun, Dezhang; Xie, Xu

2014-01-01

It is essential to construct structural health monitoring systems for large important bridges. Zhijiang Bridge is a cable-stayed bridge that was built recently over the Hangzhou Qiantang River (the largest river in Zhejiang Province). The length of Zhijiang Bridge is 478 m, which comprises an arched twin-tower space and a twin-cable plane structure. As an example, the present study describes the integrated system of structural health monitoring and intelligent management for Zhijiang Bridge, which comprises an information acquisition system, data management system, evaluation and decision-making system, and application service system. The monitoring components include the working environment of the bridge and various factors that affect bridge safety, such as the stress and strain of the main bridge structure, vibration, cable force, temperature, and wind speed. In addition, the integrated system includes a forecasting and decision-making module for real-time online evaluation, which provides warnings and makes decisions based on the monitoring information. From this, the monitoring information, evaluation results, maintenance decisions, and warning information can be input simultaneously into the bridge monitoring center and traffic emergency center to share the monitoring data, thereby facilitating evaluations and decision making using the system.

Changes of mind in an attractor network of decision-making.

PubMed

Albantakis, Larissa; Deco, Gustavo

2011-06-01

Attractor networks successfully account for psychophysical and neurophysiological data in various decision-making tasks. Especially their ability to model persistent activity, a property of many neurons involved in decision-making, distinguishes them from other approaches. Stable decision attractors are, however, counterintuitive to changes of mind. Here we demonstrate that a biophysically-realistic attractor network with spiking neurons, in its itinerant transients towards the choice attractors, can replicate changes of mind observed recently during a two-alternative random-dot motion (RDM) task. Based on the assumption that the brain continues to evaluate available evidence after the initiation of a decision, the network predicts neural activity during changes of mind and accurately simulates reaction times, performance and percentage of changes dependent on difficulty. Moreover, the model suggests a low decision threshold and high incoming activity that drives the brain region involved in the decision-making process into a dynamical regime close to a bifurcation, which up to now lacked evidence for physiological relevance. Thereby, we further affirmed the general conformance of attractor networks with higher level neural processes and offer experimental predictions to distinguish nonlinear attractor from linear diffusion models.

Exploring decision-making for environmental health services: perspectives from four cities.

PubMed

Hunt, C; Lewin, S

2000-01-01

Increasing resources are being allocated to environmental health monitoring, especially for developing methods and collecting data to construct environmental health indicators (EHIs). Yet, little research has focused on understanding how communities and service providers make decisions with regard to environmental health priorities and the role of indicators in this process. This paper presents insights regarding local decision-making that arose from a project to test the feasibility of using community-based EHIs to facilitate communication between the providers and the recipients of environmental services in four developing-country cities. The results of the study indicate that decision-making for environmental health services is complex and iterative rather than rational and linear. Contextual and process factors play an important role. These factors include the morale of service providers, the extent of collaboration between service agencies, the priorities of different community groups and relations between service providers and communities. Scientific information, in the form of EHIs, did not appear to be a key element of decision-making in the settings studied. As tools, EHIs are unlikely to become part of the decision-making process unless they are integrated with local agendas and backed by strong local representation.

Experimental Evaluation of Suitability of Selected Multi-Criteria Decision-Making Methods for Large-Scale Agent-Based Simulations

PubMed Central

2016-01-01

Multi-criteria decision-making (MCDM) can be formally implemented by various methods. This study compares suitability of four selected MCDM methods, namely WPM, TOPSIS, VIKOR, and PROMETHEE, for future applications in agent-based computational economic (ACE) models of larger scale (i.e., over 10 000 agents in one geographical region). These four MCDM methods were selected according to their appropriateness for computational processing in ACE applications. Tests of the selected methods were conducted on four hardware configurations. For each method, 100 tests were performed, which represented one testing iteration. With four testing iterations conducted on each hardware setting and separated testing of all configurations with the–server parameter de/activated, altogether, 12800 data points were collected and consequently analyzed. An illustrational decision-making scenario was used which allows the mutual comparison of all of the selected decision making methods. Our test results suggest that although all methods are convenient and can be used in practice, the VIKOR method accomplished the tests with the best results and thus can be recommended as the most suitable for simulations of large-scale agent-based models. PMID:27806061

The Implementation of Kentucky's School-Based Decision Making Program.

ERIC Educational Resources Information Center

Kentucky Univ., Lexington. Inst. on Education Reform.

This report describes what schools and educators across Kentucky are doing to implement school reform in school-based decision-making based on the Kentucky Education Reform Act of 1990 (KERA). The School-Based Decision Making (SBDM) component of KERA is a decentralized governance structure that vests great authority in SBDM councils operating at…

Identifying Non-Sustainable Courses of Action: A Prerequisite for Decision-Making in Education for Sustainable Development

NASA Astrophysics Data System (ADS)

Gresch, Helge; Bögeholz, Susanne

2013-04-01

Students are faced with a multitude of decisions as consumers and in societal debates. Because of the scarcity of resources, the destruction of ecosystems and social injustice in a globalized world, it is vital that students are able to identify non-sustainable courses of action when involved in decision-making. The application of decision-making strategies is one approach to enhancing the quality of decisions. Options that do not meet ecological, social or economic standards should be excluded using non-compensatory strategies whereas other tasks may require a complete trade-off of all the evidence, following a compensatory approach. To enhance decision-making competence, a computer-based intervention study was conducted that focused on the use of decision-making strategies. While the results of the summative evaluation are reported by Gresch et al. (International Journal of Science Education, 2011), in-depth analyses of process-related data collected during the information processing are presented in this paper to reveal insights into the mechanisms of the intervention. The quality of high school students' ( n = 120) metadecision skills when selecting a decision-making strategy was investigated using qualitative content analyses combined with inferential statistics. The results reveal that the students offered elaborate reflections on the sustainability of options. However, the characteristics that were declared non-sustainable differed among the students because societal norms and personal values were intertwined. One implication for education for sustainable development is that students are capable of reflecting on decision-making tasks and on corresponding favorable decision-making strategies at a metadecision level. From these results, we offer suggestions for improving learning environments and constructing test instruments for decision-making competence.

Motivational deficits in effort-based decision making in individuals with subsyndromal depression, first-episode and remitted depression patients.

PubMed

Yang, Xin-Hua; Huang, Jia; Zhu, Cui-Ying; Wang, Ye-Fei; Cheung, Eric F C; Chan, Raymond C K; Xie, Guang-Rong

2014-12-30

Anhedonia is a hallmark symptom of major depressive disorder (MDD). Preliminary findings suggest that anhedonia is characterized by reduced reward anticipation and motivation of obtaining reward. However, relatively little is known about reward-based decision-making in depression. We tested the hypothesis that anhedonia in MDD may reflect specific impairments in motivation on reward-based decision-making and the deficits might be associated with depressive symptoms severity. In study 1, individuals with and without depressive symptoms performed the modified version of the Effort Expenditure for Rewards Task (EEfRT), a behavioral measure of cost/benefit decision-making. In study 2, MDD patients, remitted MDD patients and healthy controls were recruited for the same procedures. We found evidence for decreased willingness to make effort for rewards among individuals with subsyndromal depression; the effect was amplified in MDD patients, but dissipated in patients with remitted depression. We also found that reduced anticipatory and consummatory pleasure predicted decreased willingness to expend efforts to obtain rewards in MDD patients. For individuals with subsyndromal depression, the impairments were correlated with anticipatory anhedonia but not consummatory anhedonia. These data offer novel evidence that motivational deficits in MDD are correlated with depression severity and predicted by self-reported anhedonia. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

On Decision-Making Among Multiple Rule-Bases in Fuzzy Control Systems

NASA Technical Reports Server (NTRS)

Tunstel, Edward; Jamshidi, Mo

1997-01-01

Intelligent control of complex multi-variable systems can be a challenge for single fuzzy rule-based controllers. This class of problems cam often be managed with less difficulty by distributing intelligent decision-making amongst a collection of rule-bases. Such an approach requires that a mechanism be chosen to ensure goal-oriented interaction between the multiple rule-bases. In this paper, a hierarchical rule-based approach is described. Decision-making mechanisms based on generalized concepts from single-rule-based fuzzy control are described. Finally, the effects of different aggregation operators on multi-rule-base decision-making are examined in a navigation control problem for mobile robots.

A Hybrid Backward-Forward Iterative Model for Improving Capacity Building of Earth Observations for Sustainable Societal Application

NASA Astrophysics Data System (ADS)

Hossain, F.; Iqbal, N.; Lee, H.; Muhammad, A.

2015-12-01

When it comes to building durable capacity for implementing state of the art technology and earth observation (EO) data for improved decision making, it has been long recognized that a unidirectional approach (from research to application) often does not work. Co-design of capacity building effort has recently been recommended as a better alternative. This approach is a two-way street where scientists and stakeholders engage intimately along the entire chain of actions from design of research experiments to packaging of decision making tools and each party provides an equal amount of input. Scientists execute research experiments based on boundary conditions and outputs that are defined as tangible by stakeholders for decision making. On the other hand, decision making tools are packaged by stakeholders with scientists ensuring the application-specific science is relevant. In this talk, we will overview one such iterative capacity building approach that we have implemented for gravimetry-based satellite (GRACE) EO data for improved groundwater management in Pakistan. We call our approach a hybrid approach where the initial step is a forward model involving a conventional short-term (3 day) capacity building workshop in the stakeholder environment addressing a very large audience. In this forward model, the net is cast wide to 'shortlist' a set of highly motivated stakeholder agency staffs who are then engaged more directly in 1-1 training. In the next step (the backward model), these short listed staffs are then brought back in the research environment of the scientists (supply) for 1-1 and long-term (6 months) intense brainstorming, training, and design of decision making tools. The advantage of this backward model is that it allows for a much better understanding for scientists of the ground conditions and hurdles of making a EO-based scientific innovation work for a specific decision making problem that is otherwise fundamentally impossible in conventional training workshops. We demonstrate here our experience of implementing this hybrid model for capacity building for groundwater management for Pakistan Council for Research on Water Resources (PCRWR) with the ultimate goal of empowering naitonal agencies in their ability to monitor groundwater storage changes independently from satellites.

History matching through dynamic decision-making

PubMed Central

Maschio, Célio; Santos, Antonio Alberto; Schiozer, Denis; Rocha, Anderson

2017-01-01

History matching is the process of modifying the uncertain attributes of a reservoir model to reproduce the real reservoir performance. It is a classical reservoir engineering problem and plays an important role in reservoir management since the resulting models are used to support decisions in other tasks such as economic analysis and production strategy. This work introduces a dynamic decision-making optimization framework for history matching problems in which new models are generated based on, and guided by, the dynamic analysis of the data of available solutions. The optimization framework follows a ‘learning-from-data’ approach, and includes two optimizer components that use machine learning techniques, such as unsupervised learning and statistical analysis, to uncover patterns of input attributes that lead to good output responses. These patterns are used to support the decision-making process while generating new, and better, history matched solutions. The proposed framework is applied to a benchmark model (UNISIM-I-H) based on the Namorado field in Brazil. Results show the potential the dynamic decision-making optimization framework has for improving the quality of history matching solutions using a substantial smaller number of simulations when compared with a previous work on the same benchmark. PMID:28582413

Cancer Counseling of Low-Income Limited English Proficient Latina Women Using Medical Interpreters: Implications for Shared Decision-Making.

PubMed

Kamara, Daniella; Weil, Jon; Youngblom, Janey; Guerra, Claudia; Joseph, Galen

2018-02-01

In cancer genetic counseling (CGC), communication across language and culture challenges the model of practice based on shared decision-making. To date, little research has examined the decision-making process of low-income, limited English proficiency (LEP) patients in CGC. This study identified communication patterns in CGC sessions with this population and assessed how these patterns facilitate or inhibit the decision-making process during the sessions. We analyzed 24 audio recordings of CGC sessions conducted in Spanish via telephone interpreters at two public hospitals. Patients were referred for risk of hereditary breast and ovarian cancer; all were offered genetic testing. Audio files were coded by two bilingual English-Spanish researchers and analyzed using conventional content analysis through an iterative process. The 24 sessions included 13 patients, 6 counselors, and 18 interpreters. Qualitative data analyses identified three key domains - Challenges Posed by Hypothetical Explanations, Misinterpretation by the Medical Interpreter, and Communication Facilitators - that reflect communication patterns and their impact on the counselor's ability to facilitate shared decision-making. Overall, we found an absence of patient participation in the decision-making process. Our data suggest that when counseling LEP Latina patients via medical interpreter, prioritizing information with direct utility for the patient and organizing information into short- and long-term goals may reduce information overload and improve comprehension for patient and interpreter. Further research is needed to test the proposed counseling strategies with this population and to assess how applicable our findings are to other populations.

Role of scientific data in health decisions.

PubMed Central

Samuels, S W

1979-01-01

The distinction between reality and models or methodological assumptions is necessary for an understanding of the use of data--economic, technical or biological--in decision-making. The traditional modes of analysis used in decisions are discussed historically and analytically. Utilitarian-based concepts such as cost-benefit analysis and cannibalistic concepts such as "acceptable risk" are rejected on logical and moral grounds. Historical reality suggests the concept of socially necessary risk determined through the dialectic process in democracy. PMID:120251

Tools to Promote Shared Decision Making in Serious Illness: A Systematic Review.

PubMed

Austin, C Adrian; Mohottige, Dinushika; Sudore, Rebecca L; Smith, Alexander K; Hanson, Laura C

2015-07-01

Serious illness impairs function and threatens survival. Patients facing serious illness value shared decision making, yet few decision aids address the needs of this population. To perform a systematic review of evidence about decision aids and other exportable tools that promote shared decision making in serious illness, thereby (1) identifying tools relevant to the treatment decisions of seriously ill patients and their caregivers, (2) evaluating the quality of evidence for these tools, and (3) summarizing their effect on outcomes and accessibility for clinicians. We searched PubMed, CINAHL, and PsychInfo from January 1, 1995, through October 31, 2014, and identified additional studies from reference lists and other systematic reviews. Clinical trials with random or nonrandom controls were included if they tested print, video, or web-based tools for advance care planning (ACP) or decision aids for serious illness. We extracted data on the study population, design, results, and risk for bias using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) criteria. Each tool was evaluated for its effect on patient outcomes and accessibility. Seventeen randomized clinical trials tested decision tools in serious illness. Nearly all the trials were of moderate or high quality and showed that decision tools improve patient knowledge and awareness of treatment choices. The available tools address ACP, palliative care and goals of care communication, feeding options in dementia, lung transplant in cystic fibrosis, and truth telling in terminal cancer. Five randomized clinical trials provided further evidence that decision tools improve ACP documentation, clinical decisions, and treatment received. Clinicians can access and use evidence-based tools to engage seriously ill patients in shared decision making. This field of research is in an early stage; future research is needed to develop novel decision aids for other serious diagnoses and key decisions. Health care delivery organizations should prioritize the use of currently available tools that are evidence based and effective.

Multiobjective Decision Making Policies and Coordination Mechanisms in Hierarchical Organizations: Results of an Agent-Based Simulation

PubMed Central

2014-01-01

This paper analyses how different coordination modes and different multiobjective decision making approaches interfere with each other in hierarchical organizations. The investigation is based on an agent-based simulation. We apply a modified NK-model in which we map multiobjective decision making as adaptive walk on multiple performance landscapes, whereby each landscape represents one objective. We find that the impact of the coordination mode on the performance and the speed of performance improvement is critically affected by the selected multiobjective decision making approach. In certain setups, the performances achieved with the more complex multiobjective decision making approaches turn out to be less sensitive to the coordination mode than the performances achieved with the less complex multiobjective decision making approaches. Furthermore, we present results on the impact of the nature of interactions among decisions on the achieved performance in multiobjective setups. Our results give guidance on how to control the performance contribution of objectives to overall performance and answer the question how effective certain multiobjective decision making approaches perform under certain circumstances (coordination mode and interdependencies among decisions). PMID:25152926

Cancer multidisciplinary team meetings in practice: Results from a multi-institutional quantitative survey and implications for policy change.

PubMed

Rankin, Nicole M; Lai, Michelle; Miller, Danielle; Beale, Philip; Spigelman, Allan; Prest, Gabrielle; Turley, Kim; Simes, John

2018-02-01

Multidisciplinary care is advocated as best practice in cancer care. Relatively little is documented about multidisciplinary team (MDT) meeting functioning, decision making and the use of evidence to support decision making in Australia. This descriptive study aimed to examine team functioning, the role of team meetings and evidence use in MDTs whose institutions are members of Sydney Catalyst Translational Cancer Research Centre. We designed a structured 40-item survey instrument about topics that included meeting purpose, organization, resources and documentation; caseload estimates; use of evidence and quality assurance; patient involvement and supportive care needs; and open-ended items about the MDTs strengths and weaknesses. Participants were invited to participate via email and the survey was administered online. Data were analyzed using descriptive and comparative statistics. Thirty-seven MDTs from seven hospitals participated (100% response) and represented common (70%) and rare tumor groups (30%). MDT meeting purpose was reported as treatment (100%) or diagnostic decision making (88%), or for education purposes (70%). Most MDTs based treatment decisions on group consensus (92%), adherence to clinical practice guidelines (57%) or other evidence-based medicine sources (33%). The majority of MDTs discussed only a proportion of new patients at each meeting emphasizing the importance of educational aspects for other cases. Barriers exist in the availability of data to enable audit and reflection on evidence-based practice. MDT strengths included collaboration and quality discussion about patients. MDT meetings focus on treatment decision making, with group consensus playing a significant role in translating research evidence from guidelines into clinical decision making. With a varying proportion of patients discussed in each MDT meeting, a wider audit of multidisciplinary care would enable more accurate assessments of whether treatment recommendations are in accordance with best-practice evidence. © 2017 John Wiley & Sons Australia, Ltd.

Understanding the Association Between Negative Symptoms and Performance on Effort-Based Decision-Making Tasks: The Importance of Defeatist Performance Beliefs.

PubMed

Reddy, L Felice; Horan, William P; Barch, Deanna M; Buchanan, Robert W; Gold, James M; Marder, Stephen R; Wynn, Jonathan K; Young, Jared; Green, Michael F

2017-11-13

Effort-based decision-making paradigms are increasingly utilized to gain insight into the nature of motivation deficits. Research has shown associations between effort-based decision making and experiential negative symptoms; however, the associations are not consistent. The current study had two primary goals. First, we aimed to replicate previous findings of a deficit in effort-based decision making among individuals with schizophrenia on a test of cognitive effort. Second, in a large sample combined from the current and a previous study, we sought to examine the association between negative symptoms and effort by including the related construct of defeatist beliefs. The results replicated previous findings of impaired cognitive effort-based decision making in schizophrenia. Defeatist beliefs significantly moderated the association between negative symptoms and effort-based decision making such that there was a strong association between high negative symptoms and deficits in effort-based decision making, but only among participants with high levels of defeatist beliefs. Thus, our findings suggest the relationship between negative symptoms and effort performance may be understood by taking into account the role of defeatist beliefs, and finding that might explain discrepancies in previous studies. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center 2017.

Decision Making in Action

NASA Technical Reports Server (NTRS)

Orasanu, Judith; Statler, Irving C. (Technical Monitor)

1994-01-01

The importance of decision-making to safety in complex, dynamic environments like mission control centers and offshore installations has been well established. NASA-ARC has a program of research dedicated to fostering safe and effective decision-making in the manned spaceflight environment. Because access to spaceflight is limited, environments with similar characteristics, including aviation and nuclear power plants, serve as analogs from which space-relevant data can be gathered and theories developed. Analyses of aviation accidents cite crew judgement and decision making as causes or contributing factors in over half of all accidents. A similar observation has been made in nuclear power plants. Yet laboratory research on decision making has not proven especially helpful in improving the quality of decisions in these kinds of environments. One reason is that the traditional, analytic decision models are inappropriate to multidimensional, high-risk environments, and do not accurately describe what expert human decision makers do when they make decisions that have consequences. A new model of dynamic, naturalistic decision making is offered that may prove useful for improving decision making in complex, isolated, confined and high-risk environments. Based on analyses of crew performance in full-mission simulators and accident reports, features that define effective decision strategies in abnormal or emergency situations have been identified. These include accurate situation assessment (including time and risk assessment), appreciation of the complexity of the problem, sensitivity to constraints on the decision, timeliness of the response, and use of adequate information. More effective crews also manage their workload to provide themselves with time and resources to make good decisions. In brief, good decisions are appropriate to the demands of the situation. Effective crew decision making and overall performance are mediated by crew communication. Communication contributes to performance because it assures that all crew members have essential information, but it also regulates and coordinates crew actions and is the medium of collective thinking in response to a problem. This presentation will examine the relations between leadership, communication, decision making and overall crew performance. Implications of these findings for spaceflight and training for offshore installations will be discussed.

Decision Making in Action: Applying Research to Practice

NASA Technical Reports Server (NTRS)

Orasanu, Judith; Statler, Irving C. (Technical Monitor)

1994-01-01

The importance of decision-making to safety in complex, dynamic environments like mission control centers and offshore installations has been well established. NASA-ARC has a program of research dedicated to fostering safe and effective decision-making in the manned spaceflight environment. Because access to spaceflight is limited, environments with similar characteristics, including aviation and nuclear power plants, serve as analogs from which space-relevant data can be gathered and theories developed. Analyses of aviation accidents cite crew judgement and decision making as causes or contributing factors in over half of all accidents. A similar observation has been made in nuclear power plants. Yet laboratory research on decision making has not proven especially helpful in improving the quality of decisions in these kinds of environments. One reason is that the traditional, analytic decision models are inappropriate to multidimensional, high-risk environments, and do not accurately describe what expert human decision makers do when they make decisions that have consequences. A new model of dynamic, naturalistic decision making is offered that may prove useful for improving decision making in complex, isolated, confined and high-risk environments. Based on analyses of crew performance in full-mission simulators and accident reports, features that define effective decision strategies in abnormal or emergency situations have been identified. These include accurate situation assessment (including time and risk assessment), appreciation of the complexity of the problem, sensitivity to constraints on the decision, timeliness of the response, and use of adequate information. More effective crews also manage their workload to provide themselves with time and resources to make good decisions. In brief, good decisions are appropriate to the demands of the situation. Effective crew decision making and overall performance are mediated by crew communication. Communication contributes to performance because it assures that all crew members have essential information, but it also regulates and coordinates crew actions and is the medium of collective thinking in response to a problem. This presentation will examine the relations between leadership, communication, decision making and overall crew performance. Implications of these findings for spaceflight and training for offshore installations will be discussed.

Using Data to Advance Learning Outcomes in Schools

ERIC Educational Resources Information Center

VanDerHeyden, Amanda; Harvey, Mark

2013-01-01

This article describes the emergence and influence of evidence-based practice and data-based decision making in educational systems. Increasingly, educators and consumers want to know that resources allocated to educational efforts yield strong effects for all learners. This trend is reflected by the widespread influence of evidence-based practice…

Reaching a Consensus: Terminology and Concepts Used in Coordination and Decision-Making Research.

PubMed

Pyritz, Lennart W; King, Andrew J; Sueur, Cédric; Fichtel, Claudia

2011-12-01

Research on coordination and decision-making in humans and nonhuman primates has increased considerably throughout the last decade. However, terminology has been used inconsistently, hampering the broader integration of results from different studies. In this short article, we provide a glossary containing the central terms of coordination and decision-making research. The glossary is based on previous definitions that have been critically revised and annotated by the participants of the symposium "Where next? Coordination and decision-making in primate groups" at the XXIIIth Congress of the International Primatological Society (IPS) in Kyoto, Japan. We discuss a number of conceptual and methodological issues and highlight consequences for their implementation. In summary, we recommend that future studies on coordination and decision-making in animal groups do not use the terms "combined decision" and "democratic/despotic decision-making." This will avoid ambiguity as well as anthropocentric connotations. Further, we demonstrate the importance of 1) taxon-specific definitions of coordination parameters (initiation, leadership, followership, termination), 2) differentiation between coordination research on individual-level process and group-level outcome, 3) analyses of collective action processes including initiation and termination, and 4) operationalization of successful group movements in the field to collect meaningful and comparable data across different species.

Improving family satisfaction and participation in decision making in an intensive care unit.

PubMed

Huffines, Meredith; Johnson, Karen L; Smitz Naranjo, Linda L; Lissauer, Matthew E; Fishel, Marmie Ann-Michelle; D'Angelo Howes, Susan M; Pannullo, Diane; Ralls, Mindy; Smith, Ruth

2013-10-01

Background Survey data revealed that families of patients in a surgical intensive care unit were not satisfied with their participation in decision making or with how well the multidisciplinary team worked together. Objectives To develop and implement an evidence-based communication algorithm and evaluate its effect in improving satisfaction among patients' families. Methods A multidisciplinary team developed an algorithm that included bundles of communication interventions at 24, 72, and 96 hours after admission to the unit. The algorithm included clinical triggers, which if present escalated the algorithm. A pre-post design using process improvement methods was used to compare families' satisfaction scores before and after implementation of the algorithm. Results Satisfaction scores for participation in decision making (45% vs 68%; z = -2.62, P = .009) and how well the health care team worked together (64% vs 83%; z = -2.10, P = .04) improved significantly after implementation. Conclusions Use of an evidence-based structured communication algorithm may be a way to improve satisfaction of families of intensive care patients with their participation in decision making and their perception of how well the unit's team works together.

The Effect of Conflict Theory Based Decision-Making Skill Training Psycho-Educational Group Experience on Decision Making Styles of Adolescents

ERIC Educational Resources Information Center

Colakkadioglu, Oguzhan; Gucray, S. Sonay

2012-01-01

In this study, the effect of conflict theory based decision making skill training group applications on decision making styles of adolescents was investigated. A total of 36 students, including 18 students in experimental group and 18 students in control group, participated in the research. When assigning students to experimental group or control…

Belief Function Based Decision Fusion for Decentralized Target Classification in Wireless Sensor Networks

PubMed Central

Zhang, Wenyu; Zhang, Zhenjiang

2015-01-01

Decision fusion in sensor networks enables sensors to improve classification accuracy while reducing the energy consumption and bandwidth demand for data transmission. In this paper, we focus on the decentralized multi-class classification fusion problem in wireless sensor networks (WSNs) and a new simple but effective decision fusion rule based on belief function theory is proposed. Unlike existing belief function based decision fusion schemes, the proposed approach is compatible with any type of classifier because the basic belief assignments (BBAs) of each sensor are constructed on the basis of the classifier’s training output confusion matrix and real-time observations. We also derive explicit global BBA in the fusion center under Dempster’s combinational rule, making the decision making operation in the fusion center greatly simplified. Also, sending the whole BBA structure to the fusion center is avoided. Experimental results demonstrate that the proposed fusion rule has better performance in fusion accuracy compared with the naïve Bayes rule and weighted majority voting rule. PMID:26295399

Shared Decision-Making for Nursing Practice: An Integrative Review.

PubMed

Truglio-Londrigan, Marie; Slyer, Jason T

2018-01-01

Shared decision-making has received national and international interest by providers, educators, researchers, and policy makers. The literature on shared decision-making is extensive, dealing with the individual components of shared decision-making rather than a comprehensive process. This view of shared decision-making leaves healthcare providers to wonder how to integrate shared decision-making into practice. To understand shared decision-making as a comprehensive process from the perspective of the patient and provider in all healthcare settings. An integrative review was conducted applying a systematic approach involving a literature search, data evaluation, and data analysis. The search included articles from PubMed, CINAHL, the Cochrane Central Register of Controlled Trials, and PsycINFO from 1970 through 2016. Articles included quantitative experimental and non-experimental designs, qualitative, and theoretical articles about shared decision-making between all healthcare providers and patients in all healthcare settings. Fifty-two papers were included in this integrative review. Three categories emerged from the synthesis: (a) communication/ relationship building; (b) working towards a shared decision; and (c) action for shared decision-making. Each major theme contained sub-themes represented in the proposed visual representation for shared decision-making. A comprehensive understanding of shared decision-making between the nurse and the patient was identified. A visual representation offers a guide that depicts shared decision-making as a process taking place during a healthcare encounter with implications for the continuation of shared decisions over time offering patients an opportunity to return to the nurse for reconsiderations of past shared decisions.

Using wind plant data to increase reliability.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Peters, Valerie A.; Ogilvie, Alistair B.; McKenney, Bridget L.

2011-01-01

Operators interested in improving reliability should begin with a focus on the performance of the wind plant as a whole. To then understand the factors which drive individual turbine performance, which together comprise the plant performance, it is necessary to track a number of key indicators. Analysis of these key indicators can reveal the type, frequency, and cause of failures and will also identify their contributions to overall plant performance. The ideal approach to using data to drive good decisions includes first determining which critical decisions can be based on data. When those required decisions are understood, then the analysismore » required to inform those decisions can be identified, and finally the data to be collected in support of those analyses can be determined. Once equipped with high-quality data and analysis capabilities, the key steps to data-based decision making for reliability improvements are to isolate possible improvements, select the improvements with largest return on investment (ROI), implement the selected improvements, and finally to track their impact.« less

Decision Making in Health and Medicine

NASA Astrophysics Data System (ADS)

Hunink, Myriam; Glasziou, Paul; Siegel, Joanna; Weeks, Jane; Pliskin, Joseph; Elstein, Arthur; Weinstein, Milton C.

2001-11-01

Decision making in health care means navigating through a complex and tangled web of diagnostic and therapeutic uncertainties, patient preferences and values, and costs. In addition, medical therapies may include side effects, surgery may lead to undesirable complications, and diagnostic technologies may produce inconclusive results. In many clinical and health policy decisions it is necessary to counterbalance benefits and risks, and to trade off competing objectives such as maximizing life expectancy vs optimizing quality of life vs minimizing the required resources. This textbook plots a clear course through these complex and conflicting variables. It clearly explains and illustrates tools for integrating quantitative evidence-based data and subjective outcome values in making clinical and health policy decisions. An accompanying CD-ROM features solutions to the exercises, PowerPoint® presentations of the illustrations, and sample models and tables.

Informed shared decision-making supported by decision coaches for women with ductal carcinoma in situ: study protocol for a cluster randomized controlled trial.

PubMed

Berger-Höger, Birte; Liethmann, Katrin; Mühlhauser, Ingrid; Haastert, Burkhard; Steckelberg, Anke

2015-10-12

Women with breast cancer want to participate in treatment decision-making. Guidelines have confirmed the right of informed shared decision-making. However, previous research has shown that the implementation of informed shared decision-making is suboptimal for reasons of limited resources of physicians, power imbalances between patients and physicians and missing evidence-based patient information. We developed an informed shared decision-making program for women with primary ductal carcinoma in situ (DCIS). The program provides decision coaching for women by specialized nurses and aims at supporting involvement in decision-making and informed choices. In this trial, the informed shared decision-making program will be evaluated in breast care centers. A cluster randomized controlled trial will be conducted to compare the informed shared decision-making program with standard care. The program comprises an evidence-based patient decision aid and training of physicians (2 hours) and specialized breast care and oncology nurses (4 days) in informed shared decision-making. Sixteen certified breast care centers will be included, with 192 women with primary DCIS being recruited. Primary outcome is the extent of patients' involvement in shared decision-making as assessed by the MAPPIN-Odyad (Multifocal approach to the 'sharing' in shared decision-making: observer instrument dyad). Secondary endpoints include the sub-measures of the MAPPIN-inventory (MAPPIN-Onurse, MAPPIN-Ophysician, MAPPIN-Opatient, MAPPIN-Qnurse, MAPPIN-Qpatient and MAPPIN-Qphysician), informed choice, decisional conflict and the duration of encounters. It is expected that decision coaching and the provision of evidence-based patient decision aids will increase patients' involvement in decision-making with informed choices and reduce decisional conflicts and duration of physician encounters. Furthermore, an accompanying process evaluation will be conducted. To our knowledge, this is the first study investigating the implementation of decision coaches in German breast care centers. Current Controlled Trials ISRCTN46305518 , date of registration: 5 June 2015.

The temporal derivative of expected utility: a neural mechanism for dynamic decision-making.

PubMed

Zhang, Xian; Hirsch, Joy

2013-01-15

Real world tasks involving moving targets, such as driving a vehicle, are performed based on continuous decisions thought to depend upon the temporal derivative of the expected utility (∂V/∂t), where the expected utility (V) is the effective value of a future reward. However, the neural mechanisms that underlie dynamic decision-making are not well understood. This study investigates human neural correlates of both V and ∂V/∂t using fMRI and a novel experimental paradigm based on a pursuit-evasion game optimized to isolate components of dynamic decision processes. Our behavioral data show that players of the pursuit-evasion game adopt an exponential discounting function, supporting the expected utility theory. The continuous functions of V and ∂V/∂t were derived from the behavioral data and applied as regressors in fMRI analysis, enabling temporal resolution that exceeded the sampling rate of image acquisition, hyper-temporal resolution, by taking advantage of numerous trials that provide rich and independent manipulation of those variables. V and ∂V/∂t were each associated with distinct neural activity. Specifically, ∂V/∂t was associated with anterior and posterior cingulate cortices, superior parietal lobule, and ventral pallidum, whereas V was primarily associated with supplementary motor, pre and post central gyri, cerebellum, and thalamus. The association between the ∂V/∂t and brain regions previously related to decision-making is consistent with the primary role of the temporal derivative of expected utility in dynamic decision-making. Copyright © 2012 Elsevier Inc. All rights reserved.

The Temporal Derivative of Expected Utility: A Neural Mechanism for Dynamic Decision-making

PubMed Central

Zhang, Xian; Hirsch, Joy

2012-01-01

Real world tasks involving moving targets, such as driving a vehicle, are performed based on continuous decisions thought to depend upon the temporal derivative of the expected utility (∂V/∂t), where the expected utility (V) is the effective value of a future reward. However, those neural mechanisms that underlie dynamic decision-making are not well understood. This study investigates human neural correlates of both V and ∂V/∂t using fMRI and a novel experimental paradigm based on a pursuit-evasion game optimized to isolate components of dynamic decision processes. Our behavioral data show that players of the pursuit-evasion game adopt an exponential discounting function, supporting the expected utility theory. The continuous functions of V and ∂V/∂t were derived from the behavioral data and applied as regressors in fMRI analysis, enabling temporal resolution that exceeded the sampling rate of image acquisition, hyper-temporal resolution, by taking advantage of numerous trials that provide rich and independent manipulation of those variables. V and ∂V/∂t were each associated with distinct neural activity. Specifically, ∂V/∂t was associated with anterior and posterior cingulate cortices, superior parietal lobule, and ventral pallidum, whereas V was primarily associated with supplementary motor, pre and post central gyri, cerebellum, and thalamus. The association between the ∂V/∂t and brain regions previously related to decision-making is consistent with the primary role of the temporal derivative of expected utility in dynamic decision-making. PMID:22963852

Experiencing new forms of genetic choice: findings from an ethnographic study of preimplantation genetic diagnosis.

PubMed

Roberts, Celia; Franklin, Sarah

2004-12-01

Contemporary scientific and clinical knowledges and practices continue to make available new forms of genetic information, and to create new forms of reproductive choice. For example, couples at high risk of passing on a serious genetic condition to their offspring in Britain today have the opportunity to use Preimplantation Genetic Diagnosis (PGD) to select embryos that are unaffected by serious genetic disease. This information assists these couples in making reproductive choices. This article presents an analysis of patients' experiences of making the decision to undertake PGD treatment and of making reproductive choices based on genetic information. We present qualitative interview data from an ethnographic study of PGD based in two British clinics which indicate how these new forms of genetic choice are experienced by patients. Our data suggest that PGD patients make decisions about treatment in a complex way, taking multiple variables into account, and maintaining ongoing assessments of the multiple costs of engaging with PGD. Patients are aware of broader implications of their decisions, at personal, familial, and societal levels, as well as clinical ones. Based on these findings we argue that the ethical and social aspects of PGD are often as innovative as the scientific and medical aspects of this technique, and that in this sense, science cannot be described as "racing ahead" of society.

Multisensor satellite data for water quality analysis and water pollution risk assessment: decision making under deep uncertainty with fuzzy algorithm in framework of multimodel approach

NASA Astrophysics Data System (ADS)

Kostyuchenko, Yuriy V.; Sztoyka, Yulia; Kopachevsky, Ivan; Artemenko, Igor; Yuschenko, Maxim

2017-10-01

Multi-model approach for remote sensing data processing and interpretation is described. The problem of satellite data utilization in multi-modeling approach for socio-ecological risks assessment is formally defined. Observation, measurement and modeling data utilization method in the framework of multi-model approach is described. Methodology and models of risk assessment in framework of decision support approach are defined and described. Method of water quality assessment using satellite observation data is described. Method is based on analysis of spectral reflectance of aquifers. Spectral signatures of freshwater bodies and offshores are analyzed. Correlations between spectral reflectance, pollutions and selected water quality parameters are analyzed and quantified. Data of MODIS, MISR, AIRS and Landsat sensors received in 2002-2014 have been utilized verified by in-field spectrometry and lab measurements. Fuzzy logic based approach for decision support in field of water quality degradation risk is discussed. Decision on water quality category is making based on fuzzy algorithm using limited set of uncertain parameters. Data from satellite observations, field measurements and modeling is utilizing in the framework of the approach proposed. It is shown that this algorithm allows estimate water quality degradation rate and pollution risks. Problems of construction of spatial and temporal distribution of calculated parameters, as well as a problem of data regularization are discussed. Using proposed approach, maps of surface water pollution risk from point and diffuse sources are calculated and discussed.

Grey situation group decision-making method based on prospect theory.

PubMed

Zhang, Na; Fang, Zhigeng; Liu, Xiaqing

2014-01-01

This paper puts forward a grey situation group decision-making method on the basis of prospect theory, in view of the grey situation group decision-making problems that decisions are often made by multiple decision experts and those experts have risk preferences. The method takes the positive and negative ideal situation distance as reference points, defines positive and negative prospect value function, and introduces decision experts' risk preference into grey situation decision-making to make the final decision be more in line with decision experts' psychological behavior. Based on TOPSIS method, this paper determines the weight of each decision expert, sets up comprehensive prospect value matrix for decision experts' evaluation, and finally determines the optimal situation. At last, this paper verifies the effectiveness and feasibility of the method by means of a specific example.

Grey Situation Group Decision-Making Method Based on Prospect Theory

PubMed Central

Zhang, Na; Fang, Zhigeng; Liu, Xiaqing

2014-01-01

This paper puts forward a grey situation group decision-making method on the basis of prospect theory, in view of the grey situation group decision-making problems that decisions are often made by multiple decision experts and those experts have risk preferences. The method takes the positive and negative ideal situation distance as reference points, defines positive and negative prospect value function, and introduces decision experts' risk preference into grey situation decision-making to make the final decision be more in line with decision experts' psychological behavior. Based on TOPSIS method, this paper determines the weight of each decision expert, sets up comprehensive prospect value matrix for decision experts' evaluation, and finally determines the optimal situation. At last, this paper verifies the effectiveness and feasibility of the method by means of a specific example. PMID:25197706

Do online prognostication tools represent a valid alternative to genomic profiling in the context of adjuvant treatment of early breast cancer? A systematic review of the literature.

PubMed

El Hage Chehade, Hiba; Wazir, Umar; Mokbel, Kinan; Kasem, Abdul; Mokbel, Kefah

2018-01-01

Decision-making regarding adjuvant chemotherapy has been based on clinical and pathological features. However, such decisions are seldom consistent. Web-based predictive models have been developed using data from cancer registries to help determine the need for adjuvant therapy. More recently, with the recognition of the heterogenous nature of breast cancer, genomic assays have been developed to aid in the therapeutic decision-making. We have carried out a comprehensive literature review regarding online prognostication tools and genomic assays to assess whether online tools could be used as valid alternatives to genomic profiling in decision-making regarding adjuvant therapy in early breast cancer. Breast cancer has been recently recognized as a heterogenous disease based on variations in molecular characteristics. Online tools are valuable in guiding adjuvant treatment, especially in resource constrained countries. However, in the era of personalized therapy, molecular profiling appears to be superior in predicting clinical outcome and guiding therapy. Copyright © 2017 Elsevier Inc. All rights reserved.

Corticosterone and decision-making in male Wistar rats: the effect of corticosterone application in the infralimbic and orbitofrontal cortex.

PubMed

Koot, Susanne; Koukou, Magdalini; Baars, Annemarie; Hesseling, Peter; van 't Klooster, José; Joëls, Marian; van den Bos, Ruud

2014-01-01

Corticosteroid hormones, released after stress, are known to influence neuronal activity and produce a wide range of effects upon the brain. They affect cognitive tasks including decision-making. Recently it was shown that systemic injections of corticosterone (CORT) disrupt reward-based decision-making in rats when tested in a rat model of the Iowa Gambling Task (rIGT), i.e., rats do not learn across trial blocks to avoid the long-term disadvantageous option. This effect was associated with a change in neuronal activity in prefrontal brain areas, i.e., the infralimbic (IL), lateral orbitofrontal (lOFC) and insular cortex, as assessed by changes in c-Fos expression. Here, we studied whether injections of CORT directly into the IL and lOFC lead to similar changes in decision-making. As in our earlier study, CORT was injected during the final 3 days of the behavioral paradigm, 25 min prior to behavioral testing. Infusions of vehicle into the IL led to a decreased number of visits to the disadvantageous arm across trial blocks, while infusion with CORT did not. Infusions into the lOFC did not lead to differences in the number of visits to the disadvantageous arm between vehicle treated and CORT treated rats. However, compared to vehicle treated rats of the IL group, performance of vehicle treated rats of the lOFC group was impaired, possibly due to cannulation/infusion-related damage of the lOFC affecting decision-making. Overall, these results show that infusions with CORT into the IL are sufficient to disrupt decision-making performance, pointing to a critical role of the IL in corticosteroid effects on reward-based decision-making. The data do not directly support that the same holds true for infusions into the lOFC.

A qualitative study on community pharmacists' decision-making process when making a diagnosis.

PubMed

Sinopoulou, Vassiliki; Summerfield, Paul; Rutter, Paul

2017-12-01

Self-care policies are increasingly directing patients to seek advice from community pharmacists. This means pharmacists need to have sound diagnostic decision-making skills to enable them to recognise a variety of conditions. The aim of this study was to investigate the process by which pharmacists manage patient signs and symptoms and to explore their use of decision-making for diagnostic purposes. Data were collected through semi-structured, face-to-face interviews with community pharmacists working in England, between August 2013 and November 2014. Pharmacists were asked to share their experiences on how they performed patient consultations, and more specifically how they would approach a hypothetical headache scenario. As part of the interview, their sources of knowledge and experience were also explored. Framework analysis was used to identify themes and subthemes. Eight interviews were conducted with pharmacists who had a wide range of working practice, from 1 year through to 40 years of experience. The pharmacists' main motivations during consultations were product selection and risk minimisation. Their questioning approach and decision-making relied heavily on mnemonic methods. This led to poor quality information gathering-although pharmacists acknowledged they needed to "delve deeper" but were often unable to articulate how or why. Some pharmacists exhibited elements of clinical reasoning in their consultations, but this seemed, mostly, to be unconscious and subsequently applied inappropriately. Overall, pharmacists exhibited poor decision-making ability, and often decisions were based on personal belief and experiences rather than evidence. Community pharmacists relied heavily on mnemonic methods to manage patients' signs and symptoms with diagnosis-based decision-making being seldom employed. These findings suggest practicing pharmacists should receive more diagnostic training. © 2017 John Wiley & Sons, Ltd.

Looking at CER from the managed care organization perspective.

PubMed

Cannon, H Eric

2012-05-01

The amount of available comparative effectiveness research (CER) is increasing, giving managed care organizations (MCOs) more information to use in decision making. However, MCOs may not be prepared to integrate this new and voluminous data into their current practices and policies. To describe ways that health care reform will affect MCO populations in the future, to examine examples of how MCOs have utilized CER data in the past, and to identify questions that MCOs will have to address as they integrate CER into future decision making. Unquestionably, health care reform will change the U.S. market. Millions more insured individuals will be making purchasing decisions. In addition, health care reform will mean more CER data will be available, affecting the decisions MCOs must make. In the past, MCOs may not have used CER as effectively as they could in making formulary and other policy decisions. However, there are examples that show how CER can be integrated effectively, such as Intermountain Healthcare's use of CER to create treatment guidelines, which have been shown to lower costs and improve delivery of care. In the future, MCOs will need to assess their own abilities to utilize CER, including their infrastructure of expertise, hardware, software, and protocols and processes. MCOs will also need to understand how pertinent CER is to their own needs, how it may affect benefit design, and how it will affect their customers' needs. Health care reform, and the resultant growth of CER, will have significant impact on MCOs, who will need to invest in better infrastructure and new understandings of a transforming market, changing customer bases, and evolving data.

CEOS Contributions to Informing Energy Management and Policy Decision Making Using Space-Based Earth Observations

NASA Technical Reports Server (NTRS)

Eckman, Richard S.

2009-01-01

Earth observations are playing an increasingly significant role in informing decision making in the energy sector. In renewable energy applications, space-based observations now routinely augment sparse ground-based observations used as input for renewable energy resource assessment applications. As one of the nine Group on Earth Observations (GEO) societal benefit areas, the enhancement of management and policy decision making in the energy sector is receiving attention in activities conducted by the Committee on Earth Observation Satellites (CEOS). CEOS has become the "space arm" for the implementation of the Global Earth Observation System of Systems (GEOSS) vision. It is directly supporting the space-based, near-term tasks articulated in the GEO three-year work plan. This paper describes a coordinated program of demonstration projects conducted by CEOS member agencies and partners to utilize Earth observations to enhance energy management end-user decision support systems. I discuss the importance of engagement with stakeholders and understanding their decision support needs in successfully increasing the uptake of Earth observation products for societal benefit. Several case studies are presented, demonstrating the importance of providing data sets in formats and units familiar and immediately usable by decision makers. These projects show the utility of Earth observations to enhance renewable energy resource assessment in the developing world, forecast space-weather impacts on the power grid, and improve energy efficiency in the built environment.

Using multi-species occupancy models in structured decision making on managed lands

USGS Publications Warehouse

Sauer, John R.; Blank, Peter J.; Zipkin, Elise F.; Fallon, Jane E.; Fallon, Frederick W.

2013-01-01

Land managers must balance the needs of a variety of species when manipulating habitats. Structured decision making provides a systematic means of defining choices and choosing among alternative management options; implementation of a structured decision requires quantitative approaches to predicting consequences of management on the relevant species. Multi-species occupancy models provide a convenient framework for making structured decisions when the management objective is focused on a collection of species. These models use replicate survey data that are often collected on managed lands. Occupancy can be modeled for each species as a function of habitat and other environmental features, and Bayesian methods allow for estimation and prediction of collective responses of groups of species to alternative scenarios of habitat management. We provide an example of this approach using data from breeding bird surveys conducted in 2008 at the Patuxent Research Refuge in Laurel, Maryland, evaluating the effects of eliminating meadow and wetland habitats on scrub-successional and woodland-breeding bird species using summed total occupancy of species as an objective function. Removal of meadows and wetlands decreased value of an objective function based on scrub-successional species by 23.3% (95% CI: 20.3–26.5), but caused only a 2% (0.5, 3.5) increase in value of an objective function based on woodland species, documenting differential effects of elimination of meadows and wetlands on these groups of breeding birds. This approach provides a useful quantitative tool for managers interested in structured decision making.

Web-services-based spatial decision support system to facilitate nuclear waste siting

NASA Astrophysics Data System (ADS)

Huang, L. Xinglai; Sheng, Grant

2006-10-01

The availability of spatial web services enables data sharing among managers, decision and policy makers and other stakeholders in much simpler ways than before and subsequently has created completely new opportunities in the process of spatial decision making. Though generally designed for a certain problem domain, web-services-based spatial decision support systems (WSDSS) can provide a flexible problem-solving environment to explore the decision problem, understand and refine problem definition, and generate and evaluate multiple alternatives for decision. This paper presents a new framework for the development of a web-services-based spatial decision support system. The WSDSS is comprised of distributed web services that either have their own functions or provide different geospatial data and may reside in different computers and locations. WSDSS includes six key components, namely: database management system, catalog, analysis functions and models, GIS viewers and editors, report generators, and graphical user interfaces. In this study, the architecture of a web-services-based spatial decision support system to facilitate nuclear waste siting is described as an example. The theoretical, conceptual and methodological challenges and issues associated with developing web services-based spatial decision support system are described.

A Middle School Principal's and Teachers' Perceptions of Leadership Practices in Data-Driven Decision Making

ERIC Educational Resources Information Center

Godreau Cimma, Kelly L.

2011-01-01

The purpose of this qualitative case study was to describe one Connecticut middle school's voluntary implementation of a data-driven decision making process in order to improve student academic performance. Data-driven decision making is a component of Connecticut's accountability system to assist schools in meeting the requirements of the No…

The Financial and Non-Financial Aspects of Developing a Data-Driven Decision-Making Mindset in an Undergraduate Business Curriculum

ERIC Educational Resources Information Center

Bohler, Jeffrey; Krishnamoorthy, Anand; Larson, Benjamin

2017-01-01

Making data-driven decisions is becoming more important for organizations faced with confusing and often contradictory information available to them from their operating environment. This article examines one college of business' journey of developing a data-driven decision-making mindset within its undergraduate curriculum. Lessons learned may be…

Data Decision-Making and Program-Wide Implementation of the Pyramid Model. Roadmap to Effective Intervention Practices #7

ERIC Educational Resources Information Center

Fox, Lise; Veguilla, Myrna; Perez Binder, Denise

2014-01-01

The Technical Assistance Center on Social Emotional Intervention for Young Children (TACSEI) Roadmap on "Data Decision-Making and Program-Wide Implementation of the Pyramid Model" provides programs with guidance on how to collect and use data to ensure the implementation of the Pyramid Model with fidelity and decision-making that…

Using basic geographic information systems functionality to support sustainable forest management decision making and post-decision assessments

Treesearch

Ronald E. McRoberts; R. James Barbour; Krista M. Gebert; Greg C. Liknes; Mark D. Nelson; Dacia M. Meneguzzo; et al.

2006-01-01

Sustainable management of natural resources requires informed decision making and post-decision assessments of the results of those decisions. Increasingly, both activities rely on analyses of spatial data in the forms of maps and digital data layers. Fortunately, a variety of supporting maps and data layers rapidly are becoming available. Unfortunately, however, user-...

Motivational states influence effort-based decision making in rats: the role of dopamine in the nucleus accumbens.

PubMed

Mai, Bettina; Sommer, Susanne; Hauber, Wolfgang

2012-03-01

Decision-making policies are subject to modulation by changing motivational states. However, so far, little is known about the neurochemical mechanisms that bridge motivational states with decision making. Here we examined whether dopamine (DA) in the nucleus accumbens core (AcbC) modulates the effects of motivational states on effort-based decision making. Using a cost-benefit T-maze task in rats, we examined the effects of AcbC DA depletions on effort-based decision making, in particular on the sensitivity of effort-based decision making to a shift from a hungry to a sated state. The results demonstrated that, relative to sham controls, rats with AcbC DA depletion in a hungry as well as in a sated state had a reduced preference for effortful but large-reward action. This finding provides further support for the notion that AcbC DA regulates how much effort to invest for rewards. Importantly, our results further revealed that effort-based decision making in lesioned rats, as in sham controls, was still sensitive to a shift from a hungry to a sated state; that is, their preferences for effortful large-reward actions became lower after a shift from a restricted to a free-feeding regimen. These finding indicate that AcbC DA is not necessarily involved in mediating the effects of a shift in motivational state on decision-making policies.

A Multimethod Analysis of Shared Decision-Making in Hospice Interdisciplinary Team Meetings Including Family Caregivers

PubMed Central

Washington, Karla T.; Oliver, Debra Parker; Gage, L. Ashley; Albright, David L.; Demiris, George

2015-01-01

Background Much of the existing research on shared decision-making in hospice and palliative care focuses on the provider-patient dyad; little is known about shared decision-making that is inclusive of family members of patients with advanced disease. Aim We sought to describe shared decision-making as it occurred in hospice interdisciplinary team meetings that included family caregivers as participants using video-conferencing technology. Design We conducted a multimethod study in which we used content and thematic analysis techniques to analyze video-recordings of hospice interdisciplinary team meetings (n = 100), individual interviews of family caregivers (n = 73) and hospice staff members (n = 78), and research field notes. Setting/participants Participants in the original studies from which data for this analysis were drawn were hospice family caregivers and staff members employed by one of five different community-based hospice agencies located in the Midwestern United States. Results Shared decision-making occurred infrequently in hospice interdisciplinary team meetings that included family caregivers. Barriers to shared decision-making included time constraints, communication skill deficits, unaddressed emotional needs, staff absences, and unclear role expectations. The hospice philosophy of care, current trends in health care delivery, the interdisciplinary nature of hospice teams, and the designation of a team leader/facilitator supported shared decision-making. Conclusions The involvement of family caregivers in hospice interdisciplinary team meetings using video-conferencing technology creates a useful platform for shared decision-making; however, steps must be taken to transform family caregivers from meeting attendees to shared decision-makers. PMID:26281854

A multimethod analysis of shared decision-making in hospice interdisciplinary team meetings including family caregivers.

PubMed

Washington, Karla T; Oliver, Debra Parker; Gage, L Ashley; Albright, David L; Demiris, George

2016-03-01

Much of the existing research on shared decision-making in hospice and palliative care focuses on the provider-patient dyad; little is known about shared decision-making that is inclusive of family members of patients with advanced disease. We sought to describe shared decision-making as it occurred in hospice interdisciplinary team meetings that included family caregivers as participants using video-conferencing technology. We conducted a multimethod study in which we used content and thematic analysis techniques to analyze video-recordings of hospice interdisciplinary team meetings (n = 100), individual interviews of family caregivers (n = 73) and hospice staff members (n = 78), and research field notes. Participants in the original studies from which data for this analysis were drawn were hospice family caregivers and staff members employed by one of five different community-based hospice agencies located in the Midwestern United States. Shared decision-making occurred infrequently in hospice interdisciplinary team meetings that included family caregivers. Barriers to shared decision-making included time constraints, communication skill deficits, unaddressed emotional needs, staff absences, and unclear role expectations. The hospice philosophy of care, current trends in healthcare delivery, the interdisciplinary nature of hospice teams, and the designation of a team leader/facilitator supported shared decision-making. The involvement of family caregivers in hospice interdisciplinary team meetings using video-conferencing technology creates a useful platform for shared decision-making; however, steps must be taken to transform family caregivers from meeting attendees to shared decision-makers. © The Author(s) 2015.

Comparing decision making between cancer patients and the general population: thoughts, emotions, or social influence?

PubMed

Yang, Z Janet; McComas, Katherine A; Gay, Geri K; Leonard, John P; Dannenberg, Andrew J; Dillon, Hildy

2012-01-01

This study extends a risk information seeking and processing model to explore the relative effect of cognitive processing strategies, positive and negative emotions, and normative beliefs on individuals' decision making about potential health risks. Most previous research based on this theoretical framework has examined environmental risks. Applying this risk communication model to study health decision making presents an opportunity to explore theoretical boundaries of the model, while also bringing this research to bear on a pressing medical issue: low enrollment in clinical trials. Comparative analysis of data gathered from 2 telephone surveys of a representative national sample (n = 500) and a random sample of cancer patients (n = 411) indicated that emotions played a more substantive role in cancer patients' decisions to enroll in a potential trial, whereas cognitive processing strategies and normative beliefs had greater influences on the decisions of respondents from the national sample.

From moral to legal judgment: the influence of normative context in lawyers and other academics

PubMed Central

Spranger, Tade M.; Erk, Susanne; Walter, Henrik

2011-01-01

Various kinds of normative judgments are an integral part of everyday life. We extended the scrutiny of social cognitive neuroscience into the domain of legal decisions, investigating two groups, lawyers and other academics, during moral and legal decision-making. While we found activation of brain areas comprising the so-called ‘moral brain’ in both conditions, there was stronger activation in the left dorsolateral prefrontal cortex and middle temporal gyrus particularly when subjects made legal decisions, suggesting that these were made in respect to more explicit rules and demanded more complex semantic processing. Comparing both groups, our data show that behaviorally lawyers conceived themselves as emotionally less involved during normative decision-making in general. A group × condition interaction in the dorsal anterior cingulate cortex suggests a modulation of normative decision-making by attention based on subjects’ normative expertise. PMID:20194515

From moral to legal judgment: the influence of normative context in lawyers and other academics.

PubMed

Schleim, Stephan; Spranger, Tade M; Erk, Susanne; Walter, Henrik

2011-01-01

Various kinds of normative judgments are an integral part of everyday life. We extended the scrutiny of social cognitive neuroscience into the domain of legal decisions, investigating two groups, lawyers and other academics, during moral and legal decision-making. While we found activation of brain areas comprising the so-called 'moral brain' in both conditions, there was stronger activation in the left dorsolateral prefrontal cortex and middle temporal gyrus particularly when subjects made legal decisions, suggesting that these were made in respect to more explicit rules and demanded more complex semantic processing. Comparing both groups, our data show that behaviorally lawyers conceived themselves as emotionally less involved during normative decision-making in general. A group × condition interaction in the dorsal anterior cingulate cortex suggests a modulation of normative decision-making by attention based on subjects' normative expertise.

Validation workflow for a clinical Bayesian network model in multidisciplinary decision making in head and neck oncology treatment.

PubMed

Cypko, Mario A; Stoehr, Matthaeus; Kozniewski, Marcin; Druzdzel, Marek J; Dietz, Andreas; Berliner, Leonard; Lemke, Heinz U

2017-11-01

Oncological treatment is being increasingly complex, and therefore, decision making in multidisciplinary teams is becoming the key activity in the clinical pathways. The increased complexity is related to the number and variability of possible treatment decisions that may be relevant to a patient. In this paper, we describe validation of a multidisciplinary cancer treatment decision in the clinical domain of head and neck oncology. Probabilistic graphical models and corresponding inference algorithms, in the form of Bayesian networks, can support complex decision-making processes by providing a mathematically reproducible and transparent advice. The quality of BN-based advice depends on the quality of the model. Therefore, it is vital to validate the model before it is applied in practice. For an example BN subnetwork of laryngeal cancer with 303 variables, we evaluated 66 patient records. To validate the model on this dataset, a validation workflow was applied in combination with quantitative and qualitative analyses. In the subsequent analyses, we observed four sources of imprecise predictions: incorrect data, incomplete patient data, outvoting relevant observations, and incorrect model. Finally, the four problems were solved by modifying the data and the model. The presented validation effort is related to the model complexity. For simpler models, the validation workflow is the same, although it may require fewer validation methods. The validation success is related to the model's well-founded knowledge base. The remaining laryngeal cancer model may disclose additional sources of imprecise predictions.

Qualitative analysis of patient-centered decision attributes associated with initiating hepatitis C treatment.

PubMed

Zuchowski, Jessica L; Hamilton, Alison B; Pyne, Jeffrey M; Clark, Jack A; Naik, Aanand D; Smith, Donna L; Kanwal, Fasiha

2015-10-01

In this era of a constantly changing landscape of antiviral treatment options for chronic viral hepatitis C (CHC), shared clinical decision-making addresses the need to engage patients in complex treatment decisions. However, little is known about the decision attributes that CHC patients consider when making treatment decisions. We identify key patient-centered decision attributes, and explore relationships among these attributes, to help inform the development of a future CHC shared decision-making aid. Semi-structured qualitative interviews with CHC patients at four Veterans Health Administration (VHA) hospitals, in three comparison groups: contemplating CHC treatment at the time of data collection (Group 1), recently declined CHC treatment (Group 2), or recently started CHC treatment (Group 3). Participant descriptions of decision attributes were analyzed for the entire sample as well as by patient group and by gender. Twenty-nine Veteran patients participated (21 males, eight females): 12 were contemplating treatment, nine had recently declined treatment, and eight had recently started treatment. Patients on average described eight (range 5-13) decision attributes. The attributes most frequently reported overall were: physical side effects (83%); treatment efficacy (79%), new treatment drugs in development (55%); psychological side effects (55%); and condition of the liver (52%), with some variation based on group and gender. Personal life circumstance attributes (such as availability of family support and the burden of financial responsibilities) influencing treatment decisions were also noted by all participants. Multiple decision attributes were interrelated in highly complex ways. Participants considered numerous attributes in their CHC treatment decisions. A better understanding of these attributes that influence patient decision-making is crucial in order to inform patient-centered clinical approaches to care (such as shared decision-making augmented with relevant decision-making aids) that respond to patients' needs, preferences, and circumstances.

Risk-based decision-making framework for the selection of sediment dredging option.

PubMed

Manap, Norpadzlihatun; Voulvoulis, Nikolaos

2014-10-15

The aim of this study was to develop a risk-based decision-making framework for the selection of sediment dredging option. Descriptions using case studies of the newly integrated, holistic and staged framework were followed. The first stage utilized the historical dredging monitoring data and the contamination level in media data into Ecological Risk Assessment phases, which have been altered for benefits in cost, time and simplicity. How Multi-Criteria Decision Analysis (MCDA) can be used to analyze and prioritize dredging areas based on environmental, socio-economic and managerial criteria was described for the next stage. The results from MCDA will be integrated into Ecological Risk Assessment to characterize the degree of contamination in the prioritized areas. The last stage was later described using these findings and analyzed using MCDA, in order to identify the best sediment dredging option, accounting for the economic, environmental and technical aspects of dredging, which is beneficial for dredging and sediment management industries. Copyright © 2014 Elsevier B.V. All rights reserved.

Clinicians’ perspectives of parental decision-making following diagnosis of a severe congenital anomaly: a qualitative study

PubMed Central

Lotto, Robyn; Smith, Lucy K; Armstrong, Natalie

2017-01-01

Objective To explore clinicians’ perspectives on supporting parents’ decision-making following diagnosis of a severe congenital anomaly, and how this is shaped by current policy. Methods This paper reports data collated as part of a larger project examining parents’ decision-making following antenatal diagnosis. The focus of this paper is the data arising from semistructured interviews conducted with 18 clinicians, with findings further supported by data generated from consultations between clinicians and parents. All interviews and consultations were audio-recorded and transcribed verbatim, with analysis based on the constant comparative approach. Results Three key themes emerged which together shape the practice of clinicians working in this area: first, the law governing termination of pregnancy (TOP) and how clinicians believe this influences the context in which decisions about whether to terminate or continue an affected pregnancy are made; second, approaches to the management of cases seen as particularly challenging; and third, how clinicians understand their role when working with parents. These themes combine to create a strong desire on the part of clinicians for parents to engage in a particular ‘rational’ form of decision-making and to be able to demonstrate the enactment of this. This is seen as important in order to ensure the ‘right’ decision has been reached and, particularly when the decision is to terminate, will withstand possible scrutiny. Conclusions The policy context in which these decisions are made strongly shapes how clinicians practise and what they want to see from the parents with whom they work. The ways in which they seek to overcome the difficulties in interpreting the law may result in variations in the offer of late TOP, both between and within units. This may inadvertently affect the options available to women least able to engage in this idealised form of decision-making. PMID:28588110

Clinicians' perspectives of parental decision-making following diagnosis of a severe congenital anomaly: a qualitative study.

PubMed

Lotto, Robyn; Smith, Lucy K; Armstrong, Natalie

2017-06-06

To explore clinicians' perspectives on supporting parents' decision-making following diagnosis of a severe congenital anomaly, and how this is shaped by current policy. This paper reports data collated as part of a larger project examining parents' decision-making following antenatal diagnosis. The focus of this paper is the data arising from semistructured interviews conducted with 18 clinicians, with findings further supported by data generated from consultations between clinicians and parents. All interviews and consultations were audio-recorded and transcribed verbatim, with analysis based on the constant comparative approach. Three key themes emerged which together shape the practice of clinicians working in this area: first, the law governing termination of pregnancy (TOP) and how clinicians believe this influences the context in which decisions about whether to terminate or continue an affected pregnancy are made; second, approaches to the management of cases seen as particularly challenging; and third, how clinicians understand their role when working with parents. These themes combine to create a strong desire on the part of clinicians for parents to engage in a particular 'rational' form of decision-making and to be able to demonstrate the enactment of this. This is seen as important in order to ensure the 'right' decision has been reached and, particularly when the decision is to terminate, will withstand possible scrutiny. The policy context in which these decisions are made strongly shapes how clinicians practise and what they want to see from the parents with whom they work. The ways in which they seek to overcome the difficulties in interpreting the law may result in variations in the offer of late TOP, both between and within units. This may inadvertently affect the options available to women least able to engage in this idealised form of decision-making. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

How do patients between the age of 65 and 75 use a web-based decision aid for treatment choice in localized prostate cancer?

PubMed

Schrijvers, Jessie; Vanderhaegen, Joke; Van Poppel, Hendrik; Haustermans, Karin; Van Audenhove, Chantal

2013-08-01

This study was designed to evaluate the use of a web-based decision aid by a 65plus patient group in their decision-making process for treatment of localized prostate cancer. Of particular interest was the use of technology features such as patients' statements, comparative tables, and a values clarification tool. One hundred men from the University Hospital of Leuven campus, Gasthuisberg, were invited to use the web-based decision aid in their decision-making process. Twenty-six men were excluded based on non- or limited use of the decision aid. Of the remaining 74 men, user specifications, decision aid surfing characteristics by means of web-log data, and especially the use of technology features were analyzed. Men spent on average 30 minutes on the web-based decision aid. Most time was spent on the pages with information on treatment options. These pages were also most frequently accessed. The use of the feature 'comparative tables' was the highest, followed by the 'values clarification tool'. According to age (<70 or >70 years) differences were observed for the time spent on the decision aid, the pages accessed, and the use of the technology features. Despite concerns about the usability of a web-based decision aid for elderly patients, these results indicated that the majority of 65plus persons with good internet skills use a web-based decision aid as well as its incorporated technology features. © 2013 Wiley Publishing Asia Pty Ltd and Chinese Cochrane Center, West China Hospital of Sichuan University.

A cross-sectional survey of supports for evidence-informed decision-making in healthcare organisations: a research protocol.

PubMed

Ouimet, Mathieu; Lavis, John N; Léon, Grégory; Ellen, Moriah E; Bédard, Pierre-Olivier; Grimshaw, Jeremy M; Gagnon, Marie-Pierre

2014-10-09

This protocol builds on the development of a) a framework that identified the various supports (i.e. positions, activities, interventions) that a healthcare organisation or health system can implement for evidence-informed decision-making (EIDM) and b) a qualitative study that showed the current mix of supports that some Canadian healthcare organisations have in place and the ones that are perceived to facilitate the use of research evidence in decision-making. Based on these findings, we developed a web survey to collect cross-sectional data about the specific supports that regional health authorities and hospitals in two Canadian provinces (Ontario and Quebec) have in place to facilitate EIDM. This paper describes the methods for a cross-sectional web survey among 32 regional health authorities and 253 hospitals in the provinces of Quebec and Ontario (Canada) to collect data on the current mix of organisational supports that these organisations have in place to facilitate evidence-informed decision-making. The data will be obtained through a two-step survey design: a 10-min survey among CEOs to identify key units and individuals in regard to our objectives (step 1) and a 20-min survey among managers of the key units identified in step 1 to collect information about the activities performed by their unit regarding the acquisition, assessment, adaptation and/or dissemination of research evidence in decision-making (step 2). The study will target three types of informants: CEOs, library/documentation centre managers and all other key managers whose unit is involved in the acquisition, assessment, adaptation/packaging and/or dissemination of research evidence in decision-making. We developed an innovative data collection system to increase the likelihood that only the best-informed respondent available answers each survey question. The reporting of the results will be done using descriptive statistics of supports by organisation type and by province. This study will be the first to collect and report large-scale cross-sectional data on the current mix of supports health system organisations in the two most populous Canadian provinces have in place for evidence-informed decision-making. The study will also provide useful information to researchers on how to collect organisation-level data with reduced risk of self-reporting bias.

Training Decisions Technology Analysis

DTIC Science & Technology

1992-06-01

4.5.1 Relational Data Base Management 69 4.5.2 TASCS Data Content 69 4.5.3 Relationships with TDS 69 4.6 Other Air Force Modeling R&D 70 4.6.1 Time ...executive decision making were first developed by M. S. Scott Morton in the early 1970’s who, at that time , termed them " management decision systems" (Scott...Allocations to Training Settings o Managers ’ Preferences for Task Allocations to Training Settings o Times Required to Training Tasks in Various

Probabilistic reward- and punishment-based learning in opioid addiction: Experimental and computational data.

PubMed

Myers, Catherine E; Sheynin, Jony; Balsdon, Tarryn; Luzardo, Andre; Beck, Kevin D; Hogarth, Lee; Haber, Paul; Moustafa, Ahmed A

2016-01-01

Addiction is the continuation of a habit in spite of negative consequences. A vast literature gives evidence that this poor decision-making behavior in individuals addicted to drugs also generalizes to laboratory decision making tasks, suggesting that the impairment in decision-making is not limited to decisions about taking drugs. In the current experiment, opioid-addicted individuals and matched controls with no history of illicit drug use were administered a probabilistic classification task that embeds both reward-based and punishment-based learning trials, and a computational model of decision making was applied to understand the mechanisms describing individuals' performance on the task. Although behavioral results showed that opioid-addicted individuals performed as well as controls on both reward- and punishment-based learning, the modeling results suggested subtle differences in how decisions were made between the two groups. Specifically, the opioid-addicted group showed decreased tendency to repeat prior responses, meaning that they were more likely to "chase reward" when expectancies were violated, whereas controls were more likely to stick with a previously-successful response rule, despite occasional expectancy violations. This tendency to chase short-term reward, potentially at the expense of developing rules that maximize reward over the long term, may be a contributing factor to opioid addiction. Further work is indicated to better understand whether this tendency arises as a result of brain changes in the wake of continued opioid use/abuse, or might be a pre-existing factor that may contribute to risk for addiction. Copyright © 2015 Elsevier B.V. All rights reserved.

SU-E-J-04: A Data-Driven, Response-Based, Multi-Criteria Decision Support System for Personalized Lung Radiation Treatment Planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Luo, Y; McShan, D; Schipper, M

2014-06-01

Purpose: To develop a decision support tool to predict a patient's potential overall survival (OS) and radiation induced toxicity (RIT) based on clinical factors and responses during the course of radiotherapy, and suggest appropriate radiation dose adjustments to improve therapeutic effect. Methods: Important relationships between a patient's basic information and their clinical features before and during the radiation treatment are identified from historical clinical data by using statistical learning and data mining approaches. During each treatment period, a data analysis (DA) module predicts radiotherapy features such as time to local progression (TTLP), time to distant metastases (TTDM), radiation toxicity tomore » different organs, etc., under possible future treatment plans based on patient specifics or responses. An information fusion (IF) module estimates intervals for a patient's OS and the probabilities of RIT from a treatment plan by integrating the outcomes of module DA. A decision making (DM) module calculates “satisfaction” with the predicted radiation outcome based on trade-offs between OS and RIT, and finds the best treatment plan for the next time period via multi-criteria optimization. Results: Using physical and biological data from 130 lung cancer patients as our test bed, we were able to train and implement the 3 modules of our decision support tool. Examples demonstrate how it can help predict a new patient's potential OS and RIT with different radiation dose plans along with how these combinations change with dose, thus presenting a range of satisfaction/utility for use in individualized decision support. Conclusion: Although the decision support tool is currently developed from a small patient sample size, it shows the potential for the improvement of each patient's satisfaction in personalized radiation therapy. The radiation treatment outcome prediction and decision making model needs to be evaluated with more patients and demonstrated for use in radiation treatments for other cancers. P01-CA59827;R01CA142840.« less

Video-based training to improve perceptual-cognitive decision-making performance of Australian football umpires.

PubMed

Larkin, Paul; Mesagno, Christopher; Berry, Jason; Spittle, Michael; Harvey, Jack

2018-02-01

Decision-making is a central component of the in-game performance of Australian football umpires; however, current umpire training focuses largely on physiological development with decision-making skills development conducted via explicit lecture-style meetings with limited practice devoted to making actual decisions. Therefore, this study investigated the efficacy of a video-based training programme, aimed to provide a greater amount of contextualised visual experiences without explicit instruction, to improve decision-making skills of umpires. Australian football umpires (n = 52) were recruited from metropolitan and regional Division 1 competitions. Participants were randomly assigned to an intervention or control group and classified according to previous umpire game experience (i.e., experienced; less experienced). The intervention group completed a 12-week video-based decision-making training programme, with decision-making performance assessed at pre-training, and 1-week retention and 3-week retention periods. The control group did not complete any video-based training. Results indicated a significant Group (intervention; Control) × Test interaction (F(1, 100) = 3.98; P = 0.02, partial ῆ 2  = 0.074), with follow-up pairwise comparisons indicating significant within-group differences over time for the intervention group. In addition, decision-making performance of the less experienced umpires in the intervention group significantly improved (F(2, 40) = 5.03, P = 0.01, partial ῆ 2  = 0.201). Thus, video-based training programmes may be a viable adjunct to current training programmes to hasten decision-making development, especially for less experienced umpires.

Factors influencing the surgical decision for the treatment of degenerative lumbar stenosis in a preference-based shared decision-making process.

PubMed

Kim, Ho-Joong; Park, Jae-Young; Kang, Kyoung-Tak; Chang, Bong-Soon; Lee, Choon-Ki; Yeom, Jin S

2015-02-01

In a preference-based shared decision-making system, several subjective and/or objective factors such as pain severity, degree of disability, and the radiological severity of canal stenosis may influence the final surgical decision for the treatment of lumbar spinal stenosis (LSS). However, our understanding of the shared decision-making process and the significance of each factor remain primitive. In the present study, we aimed to investigate which factors influence the surgical decision for the treatment of LSS when using a preference-based, shared decision-making process. We included 555 patients, aged 45-80 years, who used a preference-based shared decision-making process and were treated conservatively or surgically for chronic leg and/or back pain caused by LSS from April 2012 to December 2012. Univariate and multivariable-adjusted logistic regression analyses were used to assess the association of surgical decision making with age, sex, body mass index, symptom duration, radiologic stenotic grade, Oswestry Disability Index (ODI), visual analog scale (VAS) scores for back and leg pain, Short Form-36 (SF-36) subscales, and motor weakness. In univariate analysis, the following variables were associated with a higher odds of a surgical decision for LSS: male sex; the VAS score for leg pain; ODI; morphological stenotic grades B, C, and D; motor weakness; and the physical function, physical role, bodily pain, social function, and emotional role of the SF-36 subscales. Multivariate analysis revealed that male sex, ODI, morphological stenotic grades C and D, and motor weakness were significantly associated with a higher possibility of a surgical decision. Motor weakness, male sex, morphological stenotic grade, and the amount of disability are critical factors leading to a surgical decision for LSS when using a preference-based shared decision-making process.

Decision insight into stakeholder conflict for ERN.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Siirola, John; Tidwell, Vincent Carroll; Benz, Zachary O.

Participatory modeling has become an important tool in facilitating resource decision making and dispute resolution. Approaches to modeling that are commonly used in this context often do not adequately account for important human factors. Current techniques provide insights into how certain human activities and variables affect resource outcomes; however, they do not directly simulate the complex variables that shape how, why, and under what conditions different human agents behave in ways that affect resources and human interactions related to them. Current approaches also do not adequately reveal how the effects of individual decisions scale up to have systemic level effectsmore » in complex resource systems. This lack of integration prevents the development of more robust models to support decision making and dispute resolution processes. Development of integrated tools is further hampered by the fact that collection of primary data for decision-making modeling is costly and time consuming. This project seeks to develop a new approach to resource modeling that incorporates both technical and behavioral modeling techniques into a single decision-making architecture. The modeling platform is enhanced by use of traditional and advanced processes and tools for expedited data capture. Specific objectives of the project are: (1) Develop a proof of concept for a new technical approach to resource modeling that combines the computational techniques of system dynamics and agent based modeling, (2) Develop an iterative, participatory modeling process supported with traditional and advance data capture techniques that may be utilized to facilitate decision making, dispute resolution, and collaborative learning processes, and (3) Examine potential applications of this technology and process. The development of this decision support architecture included both the engineering of the technology and the development of a participatory method to build and apply the technology. Stakeholder interaction with the model and associated data capture was facilitated through two very different modes of engagement, one a standard interface involving radio buttons, slider bars, graphs and plots, while the other utilized an immersive serious gaming interface. The decision support architecture developed through this project was piloted in the Middle Rio Grande Basin to examine how these tools might be utilized to promote enhanced understanding and decision-making in the context of complex water resource management issues. Potential applications of this architecture and its capacity to lead to enhanced understanding and decision-making was assessed through qualitative interviews with study participants who represented key stakeholders in the basin.« less

The use of control charts by laypeople and hospital decision-makers for guiding decision making.

PubMed

Schmidtke, K A; Watson, D G; Vlaev, I

2017-07-01

Graphs presenting healthcare data are increasingly available to support laypeople and hospital staff's decision making. When making these decisions, hospital staff should consider the role of chance-that is, random variation. Given random variation, decision-makers must distinguish signals (sometimes called special-cause data) from noise (common-cause data). Unfortunately, many graphs do not facilitate the statistical reasoning necessary to make such distinctions. Control charts are a less commonly used type of graph that support statistical thinking by including reference lines that separate data more likely to be signals from those more likely to be noise. The current work demonstrates for whom (laypeople and hospital staff) and when (treatment and investigative decisions) control charts strengthen data-driven decision making. We present two experiments that compare people's use of control and non-control charts to make decisions between hospitals (funnel charts vs. league tables) and to monitor changes across time (run charts with control lines vs. run charts without control lines). As expected, participants more accurately identified the outlying data using a control chart than using a non-control chart, but their ability to then apply that information to more complicated questions (e.g., where should I go for treatment?, and should I investigate?) was limited. The discussion highlights some common concerns about using control charts in hospital settings.

The Interplay of Hippocampus and Ventromedial Prefrontal Cortex in Memory-Based Decision Making

PubMed Central

Weilbächer, Regina A.; Gluth, Sebastian

2016-01-01

Episodic memory and value-based decision making are two central and intensively studied research domains in cognitive neuroscience, but we are just beginning to understand how they interact to enable memory-based decisions. The two brain regions that have been associated with episodic memory and value-based decision making are the hippocampus and the ventromedial prefrontal cortex, respectively. In this review article, we first give an overview of these brain–behavior associations and then focus on the mechanisms of potential interactions between the hippocampus and ventromedial prefrontal cortex that have been proposed and tested in recent neuroimaging studies. Based on those possible interactions, we discuss several directions for future research on the neural and cognitive foundations of memory-based decision making. PMID:28036071

The Adaptability of Career Decision-Making Profiles: Associations with Self-Efficacy, Emotional Difficulties, and Decision Status

ERIC Educational Resources Information Center

Gadassi, Reuma; Gati, Itamar; Wagman-Rolnick, Halleli

2013-01-01

The present study investigated a new model for characterizing the way individuals make career decisions (career decision-making profiles [CDMP]). Using data from 285 students in a preacademic program, the present study assessed the association of the CDMP's dimensions with the Emotional and Personality-related Career decision-making Difficulties…

Reducing uncertainty in value-based pricing using evidence development agreements: the case of continuous intraduodenal infusion of levodopa/carbidopa (Duodopa®) in Sweden.

PubMed

Willis, Michael; Persson, Ulf; Zoellner, York; Gradl, Birgit

2010-01-01

Value-based pricing (VBP), whereby prices are set according to the perceived benefits offered to the consumer at a time when costs and benefits are characterized by considerable uncertainty and are then reviewed ex post, is a much discussed topic in pharmaceutical reimbursement. It is usually combined with coverage with evidence development (CED), a tool in which manufacturers are granted temporary reimbursement but are required to collect and submit additional health economic data at review. Many countries, including the UK, are signalling shifts in this direction. Several countries, including Sweden, have already adopted this approach and offer good insight into the benefits and pitfalls in actual practice. To describe VBP reimbursement decision making using CED in actual practice in Sweden. Decision making by The Dental and Pharmaceutical Benefits Agency (TLV) in Sweden was reviewed using a case study of continuous intraduodenal infusion of levodopa/carbidopa (Duodopa®) in the treatment of advanced Parkinson's disease (PD) with severe motor fluctuations. The manufacturer of Duodopa® applied for reimbursement in late 2003. While the proper economic data were not included in the submission, TLV granted reimbursement until early 2005 to provide time for the manufacturer to submit a formal economic evaluation. The re-submission with economic data was considered inadequate to judge cost effectiveness, so TLV granted an additional extension of reimbursement until August 2007, at which time conclusive data were expected. The manufacturer initiated a 3-year, prospective health economic study and a formal economic model. Data from a pre-planned interim analysis of the data were loaded into the model and the cost-effectiveness ratio was the basis of the next re-submission. TLV concluded that the data were suitable for making a definite decision and that the drug was not cost effective, deciding to discontinue reimbursement for any new patients (current patients were unaffected). The manufacturer continued to collect data and to improve the economic model and re-submitted in 2008. New data and the improved model resulted in reduced uncertainty and a lower cost-effectiveness ratio in the range of Swedish kronor (SEK)430,000 per QALY gained in the base-case analysis, ranging up to SEK900,000 in the most conservative sensitivity analysis, resulting in reimbursement being granted. The case of Duodopa® provides excellent insight into VBP reimbursement decision making in combination with CED and ex post review in actual practice. Publicly available decisions document the rigorous, time-consuming process (four iterations were required before a final decision could be reached). The data generated as part of the risk-sharing agreement proved correct the initial decision to grant limited coverage despite lack of economic data. Access was provided to 100 patients while evidence was generated. Economic appraisal differs from clinical assessment, and decision makers benefit from analysis of naturalistic, actual practice data. Despite reviewing the initial trial-based, 'piggy-back' economic analysis, TLV was uncertain of the cost effectiveness in actual practice and deferred a final decision until observational data from the DAPHNE study became available. Second, acceptance of economic modelling and use of temporary reimbursement conditional on additional evidence development provide a mechanism for risk sharing between TLV and manufacturers, which enabled patient access to a drug with proven clinical benefit while necessary evidence to support claims of cost effectiveness could be generated.

Shared Decision-Making for Nursing Practice: An Integrative Review

PubMed Central

Truglio-Londrigan, Marie; Slyer, Jason T.

2018-01-01

Background: Shared decision-making has received national and international interest by providers, educators, researchers, and policy makers. The literature on shared decision-making is extensive, dealing with the individual components of shared decision-making rather than a comprehensive process. This view of shared decision-making leaves healthcare providers to wonder how to integrate shared decision-making into practice. Objective: To understand shared decision-making as a comprehensive process from the perspective of the patient and provider in all healthcare settings. Methods: An integrative review was conducted applying a systematic approach involving a literature search, data evaluation, and data analysis. The search included articles from PubMed, CINAHL, the Cochrane Central Register of Controlled Trials, and PsycINFO from 1970 through 2016. Articles included quantitative experimental and non-experimental designs, qualitative, and theoretical articles about shared decision-making between all healthcare providers and patients in all healthcare settings. Results: Fifty-two papers were included in this integrative review. Three categories emerged from the synthesis: (a) communication/ relationship building; (b) working towards a shared decision; and (c) action for shared decision-making. Each major theme contained sub-themes represented in the proposed visual representation for shared decision-making. Conclusion: A comprehensive understanding of shared decision-making between the nurse and the patient was identified. A visual representation offers a guide that depicts shared decision-making as a process taking place during a healthcare encounter with implications for the continuation of shared decisions over time offering patients an opportunity to return to the nurse for reconsiderations of past shared decisions. PMID:29456779

The Career Decision-Making Competence: A New Construct for the Career Realm

ERIC Educational Resources Information Center

Ceschi, Andrea; Costantini, Arianna; Phillips, Susan D.; Sartori, Riccardo

2017-01-01

Purpose: This paper aims to link findings from laboratory-based decision-making research and decision-making competence (DMC) aspects that may be central for career-related decision-making processes. Past research has identified individual differences in rational responses in decision situations, which the authors refer to as DMC. Although there…

From Career Decision-Making Styles to Career Decision-Making Profiles: A Multidimensional Approach

ERIC Educational Resources Information Center

Gati, Itamar; Landman, Shiri; Davidovitch, Shlomit; Asulin-Peretz, Lisa; Gadassi, Reuma

2010-01-01

Previous research on individual differences in career decision-making processes has often focused on classifying individuals into a few types of decision-making "styles" based on the most dominant trait or characteristic of their approach to the decision process (e.g., rational, intuitive, dependent; Harren, 1979). In this research, an…

Overview of research addressing ethical dimensions of participation in traumatic stress studies: autonomy and beneficence.

PubMed

Newman, Elana; Kaloupek, Danny

2009-12-01

One element of the design of human research studies is ethically informed decision-making. Key issues include the safety, costs, and benefits of participation. Historically, much of this decision-making was based on opinion rather than formal evidence. Recently, however, investigators in the traumatic stress field have begun to collect data that are relevant to these decisions. In this article, the authors focus on issues emanating from the ethical concepts of autonomy and respect for persons and beneficence and nonmaleficence, and then summarize relevant evidence from studies with trauma-exposed individuals. Discussion addresses implications of this evidence for research practice and policy, and identifies some potentially informative data collections opportunities for future trauma studies.

What Districts Can Do To Improve Instruction and Achievement in All Schools.

ERIC Educational Resources Information Center

Togneri, Wendy

2003-01-01

A study of five high-poverty districts making strides in improving student achievement revealed that these districts focused on systemwide strategies including new approaches to professional development; making decisions based on data, not instinct; and redefining leadership roles. (MLF)

Co-Constructing Distributed Leadership: District and School Connections in Data-Driven Decision-Making

ERIC Educational Resources Information Center

Park, Vicki; Datnow, Amanda

2009-01-01

The purpose of this paper is to examine leadership practices in school systems that are implementing data-driven decision-making employing the theory of distributed leadership. With the advent of No Child Left Behind Act of 2001 (NCLB) in the US, educational leaders are now required to analyse, interpret and use data to make informed decisions in…

A two-phased fuzzy decision making procedure for IT supplier selection

NASA Astrophysics Data System (ADS)

Shohaimay, Fairuz; Ramli, Nazirah; Mohamed, Siti Rosiah; Mohd, Ainun Hafizah

2013-09-01

In many studies on fuzzy decision making, linguistic terms are usually represented by corresponding fixed triangular or trapezoidal fuzzy numbers. However, the fixed fuzzy numbers used in decision making process may not explain the actual respondents' opinions. Hence, a two-phased fuzzy decision making procedure is proposed. First, triangular fuzzy numbers were built based on respondents' opinions on the appropriate range (0-100) for each seven-scale linguistic terms. Then, the fuzzy numbers were integrated into fuzzy decision making model. The applicability of the proposed method is demonstrated in a case study of supplier selection in Information Technology (IT) department. The results produced via the developed fuzzy numbers were consistent with the results obtained using fixed fuzzy numbers. However, with different set of fuzzy numbers based on respondents, there is a difference in the ranking of suppliers based on criterion X1 (background of supplier). Hopefully the proposed model which incorporates fuzzy numbers based on respondents will provide a more significant meaning towards future decision making.

Special Education Teachers' Perceptions and Intentions toward Data Collection

ERIC Educational Resources Information Center

Ruble, Lisa A.; McGrew, John H.; Wong, Wing Hang; Missall, Kristen N.

2018-01-01

Although data-based decision making is an evidence-based practice, many special educators have difficulty applying the practice within daily routines. We applied the theory of planned behavior (TPB) to understand the influences that promote or hinder early childhood special educators' intentions to collect data. We assessed three influences on…

Defining decision making: a qualitative study of international experts' views on surgical trainee decision making.

PubMed

Rennie, Sarah C; van Rij, Andre M; Jaye, Chrystal; Hall, Katherine H

2011-06-01

Decision making is a key competency of surgeons; however, how best to assess decisions and decision makers is not clearly established. The aim of the present study was to identify criteria that inform judgments about surgical trainees' decision-making skills. A qualitative free text web-based survey was distributed to recognized international experts in Surgery, Medical Education, and Cognitive Research. Half the participants were asked to identify features of good decisions, characteristics of good decision makers, and essential factors for developing good decision-making skills. The other half were asked to consider these areas in relation to poor decision making. Template analysis of free text responses was performed. Twenty-nine (52%) experts responded to the survey, identifying 13 categories for judging a decision and 14 for judging a decision maker. Twelve features/characteristics overlapped (considered, informed, well timed, aware of limitations, communicated, knowledgeable, collaborative, patient-focused, flexible, able to act on the decision, evidence-based, and coherent). Fifteen categories were generated for essential factors leading to development of decision-making skills that fall into three major themes (personal qualities, training, and culture). The categories compiled from the perspectives of good/poor were predominantly the inverse of each other; however, the weighting given to some categories varied. This study provides criteria described by experts when considering surgical decisions, decision makers, and development of decision-making skills. It proposes a working definition of a good decision maker. Understanding these criteria will enable clinical teachers to better recognize and encourage good decision-making skills and identify poor decision-making skills for remediation.

Improving IT Portfolio Management Decision Confidence Using Multi-Criteria Decision Making and Hypervariate Display Techniques

ERIC Educational Resources Information Center

Landmesser, John Andrew

2014-01-01

Information technology (IT) investment decision makers are required to process large volumes of complex data. An existing body of knowledge relevant to IT portfolio management (PfM), decision analysis, visual comprehension of large volumes of information, and IT investment decision making suggest Multi-Criteria Decision Making (MCDM) and…

Using evidence-based algorithms to improve clinical decision making: the case of a first-time anterior shoulder dislocation.

PubMed

Federer, Andrew E; Taylor, Dean C; Mather, Richard C

2013-09-01

Decision making in health care has evolved substantially over the last century. Up until the late 1970s, medical decision making was predominantly intuitive and anecdotal. It was based on trial and error and involved high levels of problem solving. The 1980s gave way to empirical medicine, which was evidence based probabilistic, and involved pattern recognition and less problem solving. Although this represented a major advance in the quality of medical decision making, limitations existed. The advantages of the gold standard of the randomized controlled clinical trial (RCT) are well-known and this technique is irreplaceable in its ability to answer critical clinical questions. However, the RCT does have drawbacks. RCTs are expensive and can only capture a snapshot in time. As treatments change and new technologies emerge, new expensive clinical trials must be undertaken to reevaluate them. Furthermore, in order to best evaluate a single intervention, other factors must be controlled. In addition, the study population may not match that of another organization or provider. Although evidence-based medicine has provided powerful data for clinicians, effectively and efficiently tailoring it to the individual has not yet evolved. We are now in a period of transition from this evidence-based era to one dominated by the personalization and customization of care. It will be fueled by policy decisions to shift financial responsibility to the patient, creating a powerful and sophisticated consumer, unlike any patient we have known before. The challenge will be to apply medical evidence and personal preferences to medical decisions and deliver it efficiently in the increasingly busy clinical setting. In this article, we provide a robust review of the concepts of customized care and some of techniques to deliver it. We will illustrate this through a personalized decision model for the treatment decision after a first-time anterior shoulder dislocation.

Grey Language Hesitant Fuzzy Group Decision Making Method Based on Kernel and Grey Scale

PubMed Central

Diao, Yuzhu; Hu, Aqin

2018-01-01

Based on grey language multi-attribute group decision making, a kernel and grey scale scoring function is put forward according to the definition of grey language and the meaning of the kernel and grey scale. The function introduces grey scale into the decision-making method to avoid information distortion. This method is applied to the grey language hesitant fuzzy group decision making, and the grey correlation degree is used to sort the schemes. The effectiveness and practicability of the decision-making method are further verified by the industry chain sustainable development ability evaluation example of a circular economy. Moreover, its simplicity and feasibility are verified by comparing it with the traditional grey language decision-making method and the grey language hesitant fuzzy weighted arithmetic averaging (GLHWAA) operator integration method after determining the index weight based on the grey correlation. PMID:29498699

Grey Language Hesitant Fuzzy Group Decision Making Method Based on Kernel and Grey Scale.

PubMed

Li, Qingsheng; Diao, Yuzhu; Gong, Zaiwu; Hu, Aqin

2018-03-02

Based on grey language multi-attribute group decision making, a kernel and grey scale scoring function is put forward according to the definition of grey language and the meaning of the kernel and grey scale. The function introduces grey scale into the decision-making method to avoid information distortion. This method is applied to the grey language hesitant fuzzy group decision making, and the grey correlation degree is used to sort the schemes. The effectiveness and practicability of the decision-making method are further verified by the industry chain sustainable development ability evaluation example of a circular economy. Moreover, its simplicity and feasibility are verified by comparing it with the traditional grey language decision-making method and the grey language hesitant fuzzy weighted arithmetic averaging (GLHWAA) operator integration method after determining the index weight based on the grey correlation.

SYNTHESIS OF SPATIAL DATA FOR DECISION-MAKING

EPA Science Inventory

EPA'S Regional Vulnerability Assessment Program (ReVA) has developed a web-based statistical tool that synthesizes available spatial data into indices of condition, vulnerability (risk, considering cumulative effects), and feasibility of management options. The Environmental Deci...

A framework for designing and analyzing binary decision-making strategies in cellular systems†

PubMed Central

Porter, Joshua R.; Andrews, Burton W.; Iglesias, Pablo A.

2015-01-01

Cells make many binary (all-or-nothing) decisions based on noisy signals gathered from their environment and processed through noisy decision-making pathways. Reducing the effect of noise to improve the fidelity of decision-making comes at the expense of increased complexity, creating a tradeoff between performance and metabolic cost. We present a framework based on rate distortion theory, a branch of information theory, to quantify this tradeoff and design binary decision-making strategies that balance low cost and accuracy in optimal ways. With this framework, we show that several observed behaviors of binary decision-making systems, including random strategies, hysteresis, and irreversibility, are optimal in an information-theoretic sense for various situations. This framework can also be used to quantify the goals around which a decision-making system is optimized and to evaluate the optimality of cellular decision-making systems by a fundamental information-theoretic criterion. As proof of concept, we use the framework to quantify the goals of the externally triggered apoptosis pathway. PMID:22370552

Promoting evidence-based practice in pharmacies.

PubMed

Toklu, Hale Zerrin

2015-01-01

Evidence-based medicine aims to optimize decision-making by using evidence from well-designed and conducted research. The concept of reliable evidence is essential, since the number of electronic information resources is increasing in parallel to the increasing number and type of drugs on the market. The decision-making process is a complex and requires an extensive evaluation as well as the interpretation of the data obtained. Different sources provide different levels of evidence for decision-making. Not all the data have the same value as the evidence. Rational use of medicine requires that the patients receive "medicines appropriate to their clinical needs, in doses that meet their own individual requirements, for an adequate period of time, and at the lowest cost to them and their community." Pharmacists have a crucial role in the health system to maintain the rational use of medicine and provide pharmaceutical care to patients, because they are the drug experts who are academically trained for this purpose. The rational use of the pharmacist's workforce will improve the outcome of pharmacotherapy as well as decreasing the global health costs.

Federated health information architecture: Enabling healthcare providers and policymakers to use data for decision-making.

PubMed

Kumar, Manish; Mostafa, Javed; Ramaswamy, Rohit

2018-05-01

Health information systems (HIS) in India, as in most other developing countries, support public health management but fail to enable healthcare providers to use data for delivering quality services. Such a failure is surprising, given that the population healthcare data that the system collects are aggregated from patient records. An important reason for this failure is that the health information architecture (HIA) of the HIS is designed primarily to serve the information needs of policymakers and program managers. India has recognised the architectural gaps in its HIS and proposes to develop an integrated HIA. An enabling HIA that attempts to balance the autonomy of local systems with the requirements of a centralised monitoring agency could meet the diverse information needs of various stakeholders. Given the lack of in-country knowledge and experience in designing such an HIA, this case study was undertaken to analyse HIS in the Bihar state of India and to understand whether it would enable healthcare providers, program managers and policymakers to use data for decision-making. Based on a literature review and data collected from interviews with key informants, this article proposes a federated HIA, which has the potential to improve HIS efficiency; provide flexibility for local innovation; cater to the diverse information needs of healthcare providers, program managers and policymakers; and encourage data-based decision-making.

Decision-support systems for natural-hazards and land-management issues

USGS Publications Warehouse

Dinitz, Laura; Forney, William; Byrd, Kristin

2012-01-01

Scientists at the USGS Western Geographic Science Center are developing decision-support systems (DSSs) for natural-hazards and land-management issues. DSSs are interactive computer-based tools that use data and models to help identify and solve problems. These systems can provide crucial support to policymakers, planners, and communities for making better decisions about long-term natural hazards mitigation and land-use planning.

Automatic rule generation for high-level vision

NASA Technical Reports Server (NTRS)

Rhee, Frank Chung-Hoon; Krishnapuram, Raghu

1992-01-01

A new fuzzy set based technique that was developed for decision making is discussed. It is a method to generate fuzzy decision rules automatically for image analysis. This paper proposes a method to generate rule-based approaches to solve problems such as autonomous navigation and image understanding automatically from training data. The proposed method is also capable of filtering out irrelevant features and criteria from the rules.

School-Based Decision Making: Linking Decisions to Learning. Third-Year Report to the Prichard Committee.

ERIC Educational Resources Information Center

David, Jane L.

Under the Kentucky Education Reform Act (KERA), School-Based Decision Making (SBDM) is the provision that creates school councils and delegates to them the authority to make important educational decisions to improve student performance. This paper describes findings from the third year of a 5-year study of SBDM that focused on early examples of…

Data-driven decision support for radiologists: re-using the National Lung Screening Trial dataset for pulmonary nodule management.

PubMed

Morrison, James J; Hostetter, Jason; Wang, Kenneth; Siegel, Eliot L

2015-02-01

Real-time mining of large research trial datasets enables development of case-based clinical decision support tools. Several applicable research datasets exist including the National Lung Screening Trial (NLST), a dataset unparalleled in size and scope for studying population-based lung cancer screening. Using these data, a clinical decision support tool was developed which matches patient demographics and lung nodule characteristics to a cohort of similar patients. The NLST dataset was converted into Structured Query Language (SQL) tables hosted on a web server, and a web-based JavaScript application was developed which performs real-time queries. JavaScript is used for both the server-side and client-side language, allowing for rapid development of a robust client interface and server-side data layer. Real-time data mining of user-specified patient cohorts achieved a rapid return of cohort cancer statistics and lung nodule distribution information. This system demonstrates the potential of individualized real-time data mining using large high-quality clinical trial datasets to drive evidence-based clinical decision-making.

Shared decision-making - Rhetoric and reality: Women's experiences and perceptions of adjuvant treatment decision-making for breast cancer.

PubMed

Mahmoodi, Neda; Sargeant, Sally

2017-01-01

This interview-based study uses phenomenology as a theoretical framework and thematic analysis to challenge existing explanatory frameworks of shared decision-making, in an exploration of women's experiences and perceptions of shared decision-making for adjuvant treatment in breast cancer. Three themes emerged are as follows: (1) women's desire to participate in shared decision-making, (2) the degree to which shared decision-making is perceived to be shared and (3) to what extent are women empowered within shared decision-making. Studying breast cancer patients' subjective experiences of adjuvant treatment decision-making provides a broader perspective on patient participatory role preferences and doctor-patient power dynamics within shared decision-making for breast cancer.

Chronic Exposure to Methamphetamine Disrupts Reinforcement-Based Decision Making in Rats.

PubMed

Groman, Stephanie M; Rich, Katherine M; Smith, Nathaniel J; Lee, Daeyeol; Taylor, Jane R

2018-03-01

The persistent use of psychostimulant drugs, despite the detrimental outcomes associated with continued drug use, may be because of disruptions in reinforcement-learning processes that enable behavior to remain flexible and goal directed in dynamic environments. To identify the reinforcement-learning processes that are affected by chronic exposure to the psychostimulant methamphetamine (MA), the current study sought to use computational and biochemical analyses to characterize decision-making processes, assessed by probabilistic reversal learning, in rats before and after they were exposed to an escalating dose regimen of MA (or saline control). The ability of rats to use flexible and adaptive decision-making strategies following changes in stimulus-reward contingencies was significantly impaired following exposure to MA. Computational analyses of parameters that track choice and outcome behavior indicated that exposure to MA significantly impaired the ability of rats to use negative outcomes effectively. These MA-induced changes in decision making were similar to those observed in rats following administration of a dopamine D2/3 receptor antagonist. These data use computational models to provide insight into drug-induced maladaptive decision making that may ultimately identify novel targets for the treatment of psychostimulant addiction. We suggest that the disruption in utilization of negative outcomes to adaptively guide dynamic decision making is a new behavioral mechanism by which MA rigidly biases choice behavior.

Return-to-Play in 2017 and the Role of Shared Decision-Making in Patients with Inherited and Acquired Channelopathies and Cardiomyopathies.

PubMed

Afshar, Kia; Bunch, T Jared

2017-09-14

Shared decision-making is based upon a physician-patient encounter in which there is adequate education using aids if needed, a mutual discussion of how to assist the patient in weighing risks and benefits, and a supportive environment that allows the patient to deliberate on the clinical decision and make their own choice. This decision-making paradigm centers on the principles of autonomy and self-determination. Physical activity is a critical part of healthy lifestyle choices that helps lower risk of cardiovascular disease or the progression of it. Exercise is also a significant contributor to quality of life in many patients in additional to the health benefits. In patients with inherited or acquired cardiovascular disease, exercise may increase risk of electrical and hemodynamic instability. There is a paucity of data to guide physicians and committees that create guidelines regarding athletic and fitness participation in these patients, particularly when the patient wants to participate in those activities that are considered moderate-severe in intensity. As a consequence, the principles of shared decision-making are critical for physicians to use to help patients with cardiovascular disease make the best decision regarding fitness participation that will minimize their risk of new disease or progression of their disease and enhance their quality of life.

Women's decision-making autonomy and children's schooling in rural Mozambique.

PubMed

Luz, Luciana; Agadjanian, Victor

2015-03-24

Women's decision-making autonomy in developing settings has been shown to improve child survival and health outcomes. However, little research has addressed possible connections between women's autonomy and children's schooling. To examine the relationship between rural women's decision-making autonomy and enrollment status of primary school-age children living in their households and how this relationship differs by child's gender. The analysis uses data from a 2009 survey of rural households in four districts of Gaza province in southern Mozambique. Multilevel logistic models predict the probability of being in school for children between 6 and 14 years old. The results show a positive association of women's decision-making autonomy with the probability of being enrolled in primary school for daughters, but not for sons. The effect of women's autonomy is net of other women's characteristics typically associated with enrollment and does not mediate the effects of those characteristics. Based on the results, we argue that women with higher levels of decision-making autonomy may have a stronger preference for daughters' schooling and may have a greater say in making and implementing decisions regarding daughters' education, compared to women with lower autonomy levels. Results also illustrate a need for considering a broader set of autonomy-related characteristics when examining the effects of women's status on children's educational outcomes.

Neuroanatomical basis for recognition primed decision making.

PubMed

Hudson, Darren

2013-01-01

Effective decision making under time constraints is often overlooked in medical decision making. The recognition primed decision making (RPDM) model was developed by Gary Klein based on previous recognized situations to develop a satisfactory solution to the current problem. Bayes Theorem is the most popular decision making model in medicine but is limited by the need for adequate time to consider all probabilities. Unlike other decision making models, there is a potential neurobiological basis for RPDM. This model has significant implication for health informatics and medical education.

Risk perception and decision processes underlying informed consent to research participation.

PubMed

Reynolds, William W; Nelson, Robert M

2007-11-01

According to the rational choice model, informed consent should consist of a systematic, step-by-step evaluation of all information pertinent to the treatment or research participation decision. Research shows that people frequently deviate from this normative model, however, employing decision-making shortcuts, or heuristics. In this paper we report findings from a qualitative study of 32 adolescents and (their) 31 parents who were recruited from two Northeastern US hospitals and asked to consider the risks of and make hypothetical decisions about research participation. The purpose of this study was to increase our understanding of how diabetic and at-risk adolescents (i.e., those who are obese and/or have a family history of diabetes) and their parents perceive risks and make decisions about research participation. Using data collected from adolescents and parents, we identify heuristic decision processes in which participant perceptions of risk magnitude, which are formed quickly and intuitively and appear to be based on affective responses to information, are far more prominent and central to the participation decision than are perceptions of probability. We discuss participants' use of decision-making heuristics in the context of recent research on affect and decision processes, and we consider the implications of these findings for researchers.

A method to harness global crowd-sourced data to understand travel behavior in avalanche terrain.

NASA Astrophysics Data System (ADS)

Hendrikx, J.; Johnson, J.

2015-12-01

To date, most studies of the human dimensions of decision making in avalanche terrain has focused on two areas - post-accident analysis using accident reports/interviews and, the development of tools as decision forcing aids. We present an alternate method using crowd-sourced citizen science, for understanding decision-making in avalanche terrain. Our project combines real-time GPS tracking via a smartphone application, with internet based surveys of winter backcountry users as a method to describe and quantify travel practices in concert with group decision-making dynamics, and demographic data of participants during excursions. Effectively, we use the recorded GPS track taken within the landscape as an expression of the decision making processes and terrain usage by the group. Preliminary data analysis shows that individual experience levels, gender, avalanche hazard, and group composition all influence the ways in which people travel in avalanche terrain. Our results provide the first analysis of coupled real-time GPS tracking of the crowd while moving in avalanche terrain combined with psychographic and demographic correlates. This research will lead to an improved understanding of real-time decision making in avalanche terrain. In this paper we will specifically focus on the presentation of the methods used to solicit, and then harness the crowd to obtain data in a unique and innovative application of citizen science where the movements within the terrain are the desired output data (Figure 1). Figure 1: Example GPS tracks sourced from backcountry winter users in the Teton Pass area (Wyoming), from the 2014-15 winter season, where tracks in red represent those recorded as self-assessed experts (as per our survey), and where tracks in blue represent those recorded as self-assessed intermediates. All tracks shown were obtained under similar avalanche conditions. Statistical analysis of terrain metrics showed that the experts used steeper terrain than the intermediate users under similar avalanche conditions, demonstrating different terrain choice and use as a function of experience rather than hazard level.

Beyond shared decision-making: Collaboration in the age of recovery from serious mental illness.

PubMed

Treichler, Emily B H; Spaulding, William D

2017-01-01

The role that people with serious mental illness (SMI) play in making decisions about their own treatment and rehabilitation is attracting increasing attention and scrutiny. This attention is embedded in a broader social/consumer movement, the recovery movement , whose agenda includes extensive reform of the mental health system and advancing respect for the dignity and autonomy of people with SMI. Shared decision-making (SDM) is an approach for enhancing consumer participation in health-care decision-making. SDM translates straightforwardly to specific clinical procedures that systematically identify domains of decision-making and guide the practitioner and consumer through making the decisions. In addition, Collaborative decision-making (CDM) is a set of guiding principles that avoids the connotations and limitations of SDM. CDM looks broadly at the range of decisions to be made in mental health care, and assigns consumers and providers equal responsibility and power in the decision-making process. It recognizes the diverse history, knowledge base, and values of each consumer by assuming patients can lead and contribute to decision-making, contributing both value-based information and technical information. This article further discusses the importance of CDM for people with SMI. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Building Capacity for Data-Driven Decision Making in African HIV Testing Programs: Field Perspectives on Data Use Workshops.

PubMed

Courtenay-Quirk, Cari; Spindler, Hilary; Leidich, Aimee; Bachanas, Pam

2016-12-01

Strategic, high quality HIV testing services (HTS) delivery is an essential step towards reaching the end of AIDS by 2030. We conducted HTS Data Use workshops in five African countries to increase data use for strategic program decision-making. Feedback was collected on the extent to which workshop skills and tools were applied in practice and to identify future capacity-building needs. We later conducted six semistructured phone interviews with workshop planning teams and sent a web-based survey to 92 past participants. The HTS Data Use workshops provided accessible tools that were readily learned by most respondents. While most respondents reported increased confidence in interpreting data and frequency of using such tools over time, planning team representatives indicated ongoing needs for more automated tools that can function across data systems. To achieve ambitious global HIV/AIDS targets, national decision makers may continue to seek tools and skill-building opportunities to monitor programs and identify opportunities to refine strategies.

From Population Databases to Research and Informed Health Decisions and Policy.

PubMed

Machluf, Yossy; Tal, Orna; Navon, Amir; Chaiter, Yoram

2017-01-01

In the era of big data, the medical community is inspired to maximize the utilization and processing of the rapidly expanding medical datasets for clinical-related and policy-driven research. This requires a medical database that can be aggregated, interpreted, and integrated at both the individual and population levels. Policymakers seek data as a lever for wise, evidence-based decision-making and information-driven policy. Yet, bridging the gap between data collection, research, and policymaking, is a major challenge. To bridge this gap, we propose a four-step model: (A) creating a conjoined task force of all relevant parties to declare a national program to promote collaborations; (B) promoting a national digital records project, or at least a network of synchronized and integrated databases, in an accessible transparent manner; (C) creating an interoperative national research environment to enable the analysis of the organized and integrated data and to generate evidence; and (D) utilizing the evidence to improve decision-making, to support a wisely chosen national policy. For the latter purpose, we also developed a novel multidimensional set of criteria to illuminate insights and estimate the risk for future morbidity based on current medical conditions. Used by policymakers, providers of health plans, caregivers, and health organizations, we presume this model will assist transforming evidence generation to support the design of health policy and programs, as well as improved decision-making about health and health care, at all levels: individual, communal, organizational, and national.

Decision-Making Phenomena Described by Expert Nurses Working in Urban Community Health Settings.

ERIC Educational Resources Information Center

Watkins, Mary P.

1998-01-01

Expert community health nurses (n=28) described crucial clinical situations. Content analysis revealed that decision making was both rational and intuitive. Eight themes were identified: decision-making focus, type, purpose, decision-maker characteristics, sequencing of events, data collection methods, facilitators/barriers, and decision-making…

Cancer patient decision making related to clinical trial participation: an integrative review with implications for patients' relational autonomy.

PubMed

Bell, Jennifer A H; Balneaves, Lynda G

2015-04-01

Oncology clinical trials are necessary for the improvement of patient care as they have the ability to confirm the efficacy and safety of novel cancer treatments and in so doing, contribute to a solid evidence base on which practitioners and patients can make informed treatment decisions. However, only 3-5 % of adult cancer patients enroll in clinical trials. Lack of participation compromises the success of clinical trials and squanders an opportunity for improving patient outcomes. This literature review summarizes the factors and contexts that influence cancer patient decision making related to clinical trial participation. An integrative review was undertaken within PubMed, CINAHL, and EMBASE databases for articles written between 1995 and 2012 and archived under relevant keywords. Articles selected were data-based, written in English, and limited to adult cancer patients. In the 51 articles reviewed, three main types of factors were identified that influence cancer patients' decision making about participation in clinical trials: personal, social, and system factors. Subthemes included patients' trust in their physician and the research process, undue influence within the patient-physician relationship, and systemic social inequalities. How these factors interact and influence patients' decision-making process and relational autonomy, however, is insufficiently understood. Future research is needed to further elucidate the sociopolitical barriers and facilitators of clinical trial participation and to enhance ethical practice within clinical trial enrolment. This research will inform targeted education and support interventions to foster patients' relational autonomy in the decision-making process and potentially improve clinical trial participation rates.

Canceled connections: Lesion-derived network mapping helps explain differences in performance on a complex decision-making task

PubMed Central

Sutterer, Matthew J.; Bruss, Joel; Boes, Aaron D.; Voss, Michelle W.; Bechara, Antoine; Tranel, Daniel

2016-01-01

Studies of patients with brain damage have highlighted a broad neural network of limbic and prefrontal areas as important for adaptive decision-making. However, some patients with damage outside these regions have impaired decision-making behavior, and the behavioral impairments observed in these cases are often attributed to the general variability in behavior following brain damage, rather than a deficit in a specific brain-behavior relationship. A novel approach, lesion-derived network mapping, uses healthy subject resting-state functional connectivity (RSFC) data to infer the areas that would be connected with each patient’s lesion area in healthy adults. Here, we used this approach to investigate whether there was a systematic pattern of connectivity associated with decision-making performance in patients with focal damage in areas not classically associated with decision-making. These patients were categorized a priori into “impaired” or “unimpaired” groups based on their performance on the Iowa Gambling Task (IGT). Lesion-derived network maps based on the impaired patients showed overlap in somatosensory, motor and insula cortices, to a greater extent than patients who showed unimpaired IGT performance. Akin to the classic concept of “diaschisis” (von Monakow, 1914), this focus on the remote effects that focal damage can have on large-scale distributed brain networks has the potential to inform not only differences in decision-making behavior, but also other cognitive functions or neurological syndromes where a distinct phenotype has eluded neuroanatomical classification and brain-behavior relationships appear highly heterogeneous. PMID:26994344

Prediction Error Representation in Individuals With Generalized Anxiety Disorder During Passive Avoidance.

PubMed

White, Stuart F; Geraci, Marilla; Lewis, Elizabeth; Leshin, Joseph; Teng, Cindy; Averbeck, Bruno; Meffert, Harma; Ernst, Monique; Blair, James R; Grillon, Christian; Blair, Karina S

2017-02-01

Deficits in reinforcement-based decision making have been reported in generalized anxiety disorder. However, the pathophysiology of these deficits is largely unknown; published studies have mainly examined adolescents, and the integrity of core functional processes underpinning decision making remains undetermined. In particular, it is unclear whether the representation of reinforcement prediction error (PE) (the difference between received and expected reinforcement) is disrupted in generalized anxiety disorder. This study addresses these issues in adults with the disorder. Forty-six unmedicated individuals with generalized anxiety disorder and 32 healthy comparison subjects group-matched on IQ, gender, and age performed a passive avoidance task while undergoing functional MRI. Data analyses were performed using a computational modeling approach. Behaviorally, individuals with generalized anxiety disorder showed impaired reinforcement-based decision making. Imaging results revealed that during feedback, individuals with generalized anxiety disorder relative to healthy subjects showed a reduced correlation between PE and activity within the ventromedial prefrontal cortex, ventral striatum, and other structures implicated in decision making. In addition, individuals with generalized anxiety disorder relative to healthy participants showed a reduced correlation between punishment PEs, but not reward PEs, and activity within the left and right lentiform nucleus/putamen. This is the first study to identify computational impairments during decision making in generalized anxiety disorder. PE signaling is significantly disrupted in individuals with the disorder and may lead to their decision-making deficits and excessive worry about everyday problems by disrupting the online updating ("reality check") of the current relationship between the expected values of current response options and the actual received rewards and punishments.

Patient and physician views of shared decision making in cancer.

PubMed

Tamirisa, Nina P; Goodwin, James S; Kandalam, Arti; Linder, Suzanne K; Weller, Susan; Turrubiate, Stella; Silva, Colleen; Riall, Taylor S

2017-12-01

Engaging patients in shared decision making involves patient knowledge of treatment options and physician elicitation of patient preferences. Our aim was to explore patient and physician perceptions of shared decision making in clinical encounters for cancer care. Patients and physicians were asked open-ended questions regarding their perceptions of shared decision making throughout their cancer care. Transcripts of interviews were coded and analysed for shared decision-making themes. At an academic medical centre, 20 cancer patients with a range of cancer diagnoses, stages of cancer and time from diagnosis, and eight physicians involved in cancer care were individually interviewed. Most physicians reported providing patients with written information. However, most patients reported that written information was too detailed and felt that the physicians did not assess the level of information they wished to receive. Most patients wanted to play an active role in the treatment decision, but also wanted the physician's recommendation, such as what their physician would choose for him/herself or a family member in a similar situation. While physicians stated that they incorporated patient autonomy in decision making, most provided data without making treatment recommendations in the format preferred by most patients. We identified several communication gaps in cancer care. While patients want to be involved in the decision-making process, they also want physicians to provide evidence-based recommendations in the context of their individual preferences. However, physicians often are reluctant to provide a recommendation that will bias the patient. © 2017 The Authors Health Expectations Published by John Wiley & Sons Ltd.

A public health decision support system model using reasoning methods.

PubMed

Mera, Maritza; González, Carolina; Blobel, Bernd

2015-01-01

Public health programs must be based on the real health needs of the population. However, the design of efficient and effective public health programs is subject to availability of information that can allow users to identify, at the right time, the health issues that require special attention. The objective of this paper is to propose a case-based reasoning model for the support of decision-making in public health. The model integrates a decision-making process and case-based reasoning, reusing past experiences for promptly identifying new population health priorities. A prototype implementation of the model was performed, deploying the case-based reasoning framework jColibri. The proposed model contributes to solve problems found today when designing public health programs in Colombia. Current programs are developed under uncertain environments, as the underlying analyses are carried out on the basis of outdated and unreliable data.

Geospatial Based Information System Development in Public Administration for Sustainable Development and Planning in Urban Environment

NASA Astrophysics Data System (ADS)

Kouziokas, Georgios N.

2016-09-01

It is generally agreed that the governmental authorities should actively encourage the development of an efficient framework of information and communication technology initiatives so as to advance and promote sustainable development and planning strategies. This paper presents a prototype Information System for public administration which was designed to facilitate public management and decision making for sustainable development and planning. The system was developed by using several programming languages and programming tools and also a Database Management System (DBMS) for storing and managing urban data of many kinds. Furthermore, geographic information systems were incorporated into the system in order to make possible to the authorities to deal with issues of spatial nature such as spatial planning. The developed system provides a technology based management of geospatial information, environmental and crime data of urban environment aiming at improving public decision making and also at contributing to a more efficient sustainable development and planning.

The Association Between Psychological Distress and Decision Regret During Armed Conflict Among Hospital Personnel.

PubMed

Ben-Ezra, Menachem; Bibi, Haim

2016-09-01

The association between psychological distress and decision regret during armed conflict among hospital personnel is of interest. The objective of this study was to learn of the association between psychological distress and decision regret during armed conflict. Data was collected from 178 hospital personnel in Barzilai Medical Center in Ashkelon, Israel during Operation Protective Edge. The survey was based on intranet data collection about: demographics, self-rated health, life satisfaction, psychological distress and decision regret. Among hospital personnel, having higher psychological distress and being young were associated with higher decision regret. This study adds to the existing knowledge by providing novel data about the association between psychological distress and decision regret among hospital personnel during armed conflict. This data opens a new venue of future research to other potentially detrimental factor on medical decision making and medical error done during crisis.

Big data: the management revolution.

PubMed

McAfee, Andrew; Brynjolfsson, Erik

2012-10-01

Big data, the authors write, is far more powerful than the analytics of the past. Executives can measure and therefore manage more precisely than ever before. They can make better predictions and smarter decisions. They can target more-effective interventions in areas that so far have been dominated by gut and intuition rather than by data and rigor. The differences between big data and analytics are a matter of volume, velocity, and variety: More data now cross the internet every second than were stored in the entire internet 20 years ago. Nearly real-time information makes it possible for a company to be much more agile than its competitors. And that information can come from social networks, images, sensors, the web, or other unstructured sources. The managerial challenges, however, are very real. Senior decision makers have to learn to ask the right questions and embrace evidence-based decision making. Organizations must hire scientists who can find patterns in very large data sets and translate them into useful business information. IT departments have to work hard to integrate all the relevant internal and external sources of data. The authors offer two success stories to illustrate how companies are using big data: PASSUR Aerospace enables airlines to match their actual and estimated arrival times. Sears Holdings directly analyzes its incoming store data to make promotions much more precise and faster.

A randomized comparison between league tables and funnel plots to inform health care decision-making.

PubMed

Anell, Anders; Hagberg, Oskar; Liedberg, Fredrik; Ryden, Stefan

2016-12-01

Comparison of provider performance is commonly used to inform health care decision-making. Little attention has been paid to how data presentations influence decisions. This study analyzes differences in suggested actions by decision-makers informed by league tables or funnel plots. Decision-makers were invited to a survey and randomized to compare hospital performance using either league tables or funnel plots for four different measures within the area of cancer care. For each measure, decision-makers were asked to suggest actions towards 12-16 hospitals (no action, ask for more information, intervene) and provide feedback related to whether the information provided had been useful. Swedish health care. Two hundred and twenty-one decision-makers at administrative and clinical levels. Data presentations in the form of league tables or funnel plots. Number of actions suggested by participants. Proportion of appropriate actions. For all four measures, decision-makers tended to suggest more actions based on the information provided in league tables compared to funnel plots (44% vs. 21%, P < 0.001). Actions were on average more appropriate for funnel plots. However, when using funnel plots, decision-makers more often missed to react even when appropriate. The form of data presentation had an influence on decision-making. With league tables, decision-makers tended to suggest more actions compared to funnel plots. A difference in sensitivity and specificity conditioned by the form of presentation could also be identified, with different implications depending on the purpose of comparisons. Explanations and visualization aids are needed to support appropriate actions. © The Author 2016. Published by Oxford University Press in association with the International Society for Quality in Health Care. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Data Informed Decision Making--Perspectives of Oklahoma Superintendents

ERIC Educational Resources Information Center

Kettles, Thomas D.

2017-01-01

This descriptive, multiple case study was designed to convey a clear portrayal of the DIDM practice of six superintendents and to provide a description of what these superintendents employ during their decision making process. The ability of local education leaders to strategically influence the use of data for decision making has a large effect…

Low Cognitive Impulsivity Is Associated with Better Gain and Loss Learning in a Probabilistic Decision-Making Task

PubMed Central

Cáceres, Pablo; San Martín, René

2017-01-01

Many advances have been made over the last decades in describing, on the one hand, the link between reward-based learning and decision-making, and on the other hand, the link between impulsivity and decision-making. However, the association between reward-based learning and impulsivity remains poorly understood. In this study, we evaluated the association between individual differences in loss-minimizing and gain-maximizing behavior in a learning-based probabilistic decision-making task and individual differences in cognitive impulsivity. We found that low cognitive impulsivity was associated both with a better performance minimizing losses and maximizing gains during the task. These associations remained significant after controlling for mathematical skills and gender as potential confounders. We discuss potential mechanisms through which cognitive impulsivity might interact with reward-based learning and decision-making. PMID:28261137

Low Cognitive Impulsivity Is Associated with Better Gain and Loss Learning in a Probabilistic Decision-Making Task.

PubMed

Cáceres, Pablo; San Martín, René

2017-01-01

Many advances have been made over the last decades in describing, on the one hand, the link between reward-based learning and decision-making, and on the other hand, the link between impulsivity and decision-making. However, the association between reward-based learning and impulsivity remains poorly understood. In this study, we evaluated the association between individual differences in loss-minimizing and gain-maximizing behavior in a learning-based probabilistic decision-making task and individual differences in cognitive impulsivity. We found that low cognitive impulsivity was associated both with a better performance minimizing losses and maximizing gains during the task. These associations remained significant after controlling for mathematical skills and gender as potential confounders. We discuss potential mechanisms through which cognitive impulsivity might interact with reward-based learning and decision-making.

Introducing high-cost health care to patients: dentists' accounts of offering dental implant treatment.

PubMed

Vernazza, Christopher R; Rousseau, Nikki; Steele, Jimmy G; Ellis, Janice S; Thomason, John Mark; Eastham, Jane; Exley, Catherine

2015-02-01

The decision-making process within health care has been widely researched, with shared decision-making, where both patients and clinicians share technical and personal information, often being cited as the ideal model. To date, much of this research has focused on systems where patients receive their care and treatment free at the point of contact (either in government-funded schemes or in insurance-based schemes). Oral health care often involves patients making direct payments for their care and treatment, and less is known about how this payment affects the decision-making process. It is clear that patient characteristics influence decision-making, but previous evidence suggests that clinicians may assume characteristics rather than eliciting them directly. The aim was to explore the influences on how dentists' engaged in the decision-making process surrounding a high-cost item of health care, dental implant treatments (DITs). A qualitative study using semi-structured interviews was undertaken using a purposive sample of primary care dentists (n = 25). Thematic analysis was undertaken to reveal emerging key themes. There were differences in how dentists discussed and offered implants. Dentists made decisions about whether to offer implants based on business factors, professional and legal obligations and whether they perceived the patient to be motivated to have treatment and their ability to pay. There was evidence that assessment of these characteristics was often based on assumptions derived from elements such as the appearance of the patient, the state of the patient's mouth and demographic details. The data suggest that there is a conflict between three elements of acting as a healthcare professional: minimizing provision of unneeded treatment, trying to fully involve patients in shared decisions and acting as a business person with the potential for financial gain. It might be expected that in the context of a high-cost healthcare intervention for which patients pay the bill themselves, that decision-making would be closer to an informed than a paternalistic model. Our research suggests that paternalistic decision-making is still practised and is influenced by assumptions about patient characteristics. Better tools and training may be required to support clinicians in this area of practice. © 2014 The Authors. Community Dentistry and Oral Epidemiology Published by John Wiley & Sons Ltd.

Thermodynamic view on decision-making process: emotions as a potential power vector of realization of the choice.

PubMed

Pakhomov, Anton; Sudin, Natalya

2013-12-01

This research is devoted to possible mechanisms of decision-making in frames of thermodynamic principles. It is also shown that the decision-making system in reply to emotion includes vector component which seems to be often a necessary condition to transfer system from one state to another. The phases of decision-making system can be described as supposed to be nonequilibrium and irreversible to which thermodynamics laws are applied. The mathematical model of a decision choice, proceeding from principles of the nonlinear dynamics considering instability of movement and bifurcation is offered. The thermodynamic component of decision-making process on the basis of vector transfer of energy induced by emotion at the given time is surveyed. It is proposed a three-modular model of decision making based on principles of thermodynamics. Here it is suggested that at entropy impact due to effect of emotion, on the closed system-the human brain,-initially arises chaos, then after fluctuations of possible alternatives which were going on-reactions of brain zones in reply to external influence, an order is forming and there is choice of alternatives, according to primary entrance conditions and a state of the closed system. Entropy calculation of a choice expectation of negative and positive emotion shows judgment possibility of existence of "the law of emotion conservation" in accordance with several experimental data.

Preferences of acutely ill patients for participation in medical decision-making.

PubMed

Wilkinson, C; Khanji, M; Cotter, P E; Dunne, O; O'Keeffe, S T

2008-04-01

To determine patient preferences for information and for participation in decision-making, and the determinants of these preferences in patients recently admitted to an acute hospital. Prospective questionnaire-based study. Medical wards of an acute teaching hospital. One hundred and fifty-two consecutive acute medical inpatients, median age 74 years. Standardised assessment included abbreviated mental test and subjective measure of severity of illness. Patients' desire for information was assessed using a 5-point Likert scale, and their desire for a role in medical decision-making using the Degner Control of Preferences Scale. Of the 152 patients, 93 (61%) favoured a passive approach to decision-making (either "leave all decisions to the doctor" or "doctor makes final decision but seriously considers my opinion." In contrast, 101 (66%) patients sought "very extensive" or "a lot" of information about their condition. No significant effects of age, sex, socio-economic group or severity of acute illness on desire for information or the Degner scale result were found. There was no agreement between patients' preferences on the Degner scale and their doctors' predictions of those preferences. Acute medical inpatients want to receive a lot of information about their illness, but most prefer a relatively passive role in decision-making. The only way to determine individual patient preferences is to ask them; preferences cannot be predicted from clinical or sociodemographic data.

Internet use in pregnancy informs women's decision making: a web-based survey.

PubMed

Lagan, Briege M; Sinclair, Marlene; Kernohan, W George

2010-06-01

Internet access and usage is almost ubiquitous, providing new opportunities and increasing challenges for health care practitioners and users. With pregnant women reportedly turning to the Internet for information during pregnancy, a better understanding of this behavior is needed. The objective of this study was to ascertain why and how pregnant women use the Internet as a health information source, and the overall effect it had on their decision making. Kuhlthau's (1993) information-seeking model was adapted to provide the underpinning theoretical framework for the study. The design was exploratory and descriptive. Data were collected using a valid and reliable web-based questionnaire. Over a 12-week period, 613 women from 24 countries who had confirmed that they had used the Internet for pregnancy-related information during their pregnancy completed and submitted a questionnaire. Most women (97%) used search engines such as Google to identify online web pages to access a large variety of pregnancy-related information and to use the Internet for pregnancy-related social networking, support, and electronic commerce (i.e., e-commerce). Almost 94 percent of women used the Internet to supplement information already provided by health professionals and 83 percent used it to influence their pregnancy decision making. Nearly half of the respondents reported dissatisfaction with information given by health professionals (48.6%) and lack of time to ask health professionals questions (46.5%) as key factors influencing them to access the Internet. Statistically, women's confidence levels significantly increased with respect to making decisions about their pregnancy after Internet usage (p < 0.05). In this study, the Internet played a significant part in the respondents' health information seeking and decision making in pregnancy. Health professionals need to be ready to support pregnant women in online data retrieval, interpretation, and application.

Special Education Eligibility: An Examination of the Decision-Making Process

ERIC Educational Resources Information Center

Kirkland, Erin K. B.

2012-01-01

The purpose of this study was to investigate the influence of private practitioner and educational advocate opinions on school-based administrators' decision-making thought processes when making a recommendation for special education eligibility. Special education eligibility is a school-based team decision that involves multiple…

Decision Making: New Paradigm for Education.

ERIC Educational Resources Information Center

Wales, Charles E.; And Others

1986-01-01

Defines education's new paradigm as schooling based on decision making, the critical thinking skills serving it, and the knowledge base supporting it. Outlines a model decision-making process using a hypothetical breakfast problem; a late riser chooses goals, generates ideas, develops an action plan, and implements and evaluates it. (4 references)…

School-Based Decision Making: A Principal-Agent Perspective.

ERIC Educational Resources Information Center

Ferris, James M.

1992-01-01

A principal-agent framework is used to examine potential gains in educational performance and potential threats to public accountability that school-based decision-making proposals pose. Analysis underscores the need to tailor the design of decentralized decision making to the sources of poor educational performance and threats to school…

The provision of information and informed decision-making on prenatal screening for Down syndrome: a questionnaire- and register-based survey in a non-selected population.

PubMed

Schoonen, Marleen; Wildschut, Hajo; Essink-Bot, Marie-Louise; Peters, Ingrid; Steegers, Eric; de Koning, Harry

2012-06-01

Evaluating the information provision procedure about prenatal screening for Down syndrome, using informed decision-making as a quality-indicator. Questionnaire- and register-based surveys. Midwives associated with 59 midwifery practices completed process data for 6435 pregnancies. Pregnant women (n=510) completed questionnaires on informed decision-making. Midwives offered information to 98.5% of women; 62.6% of them wished to receive information, of these, 81.9% actually received information. Decision-relevant knowledge was adequate in 89.0% of responding women. Knowledge about Down syndrome was less adequate than knowledge about the screening program. Participants in the screening program had higher knowledge scores on Down syndrome and on the screening program than non-participants. Of the women who intended to participate (35.8%), 3.1% had inadequate knowledge. A total of 75.5% of women made an informed decision; 94.3% of women participating in the screening program, and 64.9% of women not participating. This quality assurance study showed high levels of informed decision-making and a relatively low participation rate in the national screening program for Down syndrome in the Netherlands. Knowledge of the Down syndrome condition needs to be improved. This evaluation may serve as a pilot study for quality monitoring studies at a national level. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Effects of Computer-Based Training on Procedural Modifications to Standard Functional Analyses

ERIC Educational Resources Information Center

Schnell, Lauren K.; Sidener, Tina M.; DeBar, Ruth M.; Vladescu, Jason C.; Kahng, SungWoo

2018-01-01

Few studies have evaluated methods for training decision-making when functional analysis data are undifferentiated. The current study evaluated computer-based training to teach 20 graduate students to arrange functional analysis conditions, analyze functional analysis data, and implement procedural modifications. Participants were exposed to…

Sustainability Based Decision Making

EPA Science Inventory

With sustainability as the “true north” for EPA research, a premium is placed on the ability to make decisions under highly complex and uncertain conditions. The primary challenge is reconciling disparate criteria toward credible and defensible decisions. Making decisions on on...

Effort-Based Decision-Making in Schizophrenia.

PubMed

Culbreth, Adam J; Moran, Erin K; Barch, Deanna M

2018-08-01

Motivational impairment has long been associated with schizophrenia but the underlying mechanisms are not clearly understood. Recently, a small but growing literature has suggested that aberrant effort-based decision-making may be a potential contributory mechanism for motivational impairments in psychosis. Specifically, multiple reports have consistently demonstrated that individuals with schizophrenia are less willing than healthy controls to expend effort to obtain rewards. Further, this effort-based decision-making deficit has been shown to correlate with severity of negative symptoms and level of functioning, in many but not all studies. In the current review, we summarize this literature and discuss several factors that may underlie aberrant effort-based decision-making in schizophrenia.

A Hybrid-Cloud Science Data System Enabling Advanced Rapid Imaging & Analysis for Monitoring Hazards

NASA Astrophysics Data System (ADS)

Hua, H.; Owen, S. E.; Yun, S.; Lundgren, P.; Moore, A. W.; Fielding, E. J.; Radulescu, C.; Sacco, G.; Stough, T. M.; Mattmann, C. A.; Cervelli, P. F.; Poland, M. P.; Cruz, J.

2012-12-01

Volcanic eruptions, landslides, and levee failures are some examples of hazards that can be more accurately forecasted with sufficient monitoring of precursory ground deformation, such as the high-resolution measurements from GPS and InSAR. In addition, coherence and reflectivity change maps can be used to detect surface change due to lava flows, mudslides, tornadoes, floods, and other natural and man-made disasters. However, it is difficult for many volcano observatories and other monitoring agencies to process GPS and InSAR products in an automated scenario needed for continual monitoring of events. Additionally, numerous interoperability barriers exist in multi-sensor observation data access, preparation, and fusion to create actionable products. Combining high spatial resolution InSAR products with high temporal resolution GPS products--and automating this data preparation & processing across global-scale areas of interests--present an untapped science and monitoring opportunity. The global coverage offered by satellite-based SAR observations, and the rapidly expanding GPS networks, can provide orders of magnitude more data on these hazardous events if we have a data system that can efficiently and effectively analyze the voluminous raw data, and provide users the tools to access data from their regions of interest. Currently, combined GPS & InSAR time series are primarily generated for specific research applications, and are not implemented to run on large-scale continuous data sets and delivered to decision-making communities. We are developing an advanced service-oriented architecture for hazard monitoring leveraging NASA-funded algorithms and data management to enable both science and decision-making communities to monitor areas of interests via seamless data preparation, processing, and distribution. Our objectives: * Enable high-volume and low-latency automatic generation of NASA Solid Earth science data products (InSAR and GPS) to support hazards monitoring. * Facilitate NASA-USGS collaborations to share NASA InSAR and GPS data products, which are difficult to process in high-volume and low-latency, for decision-support. * Enable interoperable discovery, access, and sharing of NASA observations and derived actionable products, and between the observation and decision-making communities. * Enable their improved understanding through visualization, mining, and cross-agency sharing. Existing InSAR & GPS processing packages and other software are integrated for generating geodetic decision support monitoring products. We employ semantic and cloud-based data management and processing techniques for handling large data volumes, reducing end product latency, codifying data system information with semantics, and deploying interoperable services for actionable products to decision-making communities.

What is the impact of the Internet on decision-making in pregnancy? A global study.

PubMed

Lagan, Briege M; Sinclair, Marlene; Kernohan, W George

2011-12-01

  Women need access to evidence-based information to make informed choices in pregnancy. A search for health information is one of the major reasons that people worldwide access the Internet. Recent years have witnessed an increase in Internet usage by women seeking pregnancy-related information. The aim of this study was to build on previous quantitative studies to explore women's experiences and perceptions of using the Internet for retrieving pregnancy-related information, and its influence on their decision-making processes.   This global study drew on the interpretive qualitative traditions together with a theoretical model on information seeking, adapted to understand Internet use in pregnancy and its role in relation to decision-making. Thirteen asynchronous online focus groups across five countries were conducted with 92 women who had accessed the Internet for pregnancy-related information over a 3-month period. Data were readily transferred and analyzed deductively.   The overall analysis indicates that the Internet is having a visible impact on women's decision making in regards to all aspects of their pregnancy. The key emergent theme was the great need for information. Four broad themes also emerged: "validate information,"empowerment,"share experiences," and "assisted decision-making." Women also reported how the Internet provided support, its negative and positive aspects, and as a source of accurate, timely information.   Health professionals have a responsibility to acknowledge that women access the Internet for support and pregnancy-related information to assist in their decision-making. Health professionals must learn to work in partnership with women to guide them toward evidence-based websites and be prepared to discuss the ensuing information. © 2011, Copyright the Authors. Journal compilation © 2011, Wiley Periodicals, Inc.

Including all voices in international data-sharing governance.

PubMed

Kaye, Jane; Terry, Sharon F; Juengst, Eric; Coy, Sarah; Harris, Jennifer R; Chalmers, Don; Dove, Edward S; Budin-Ljøsne, Isabelle; Adebamowo, Clement; Ogbe, Emilomo; Bezuidenhout, Louise; Morrison, Michael; Minion, Joel T; Murtagh, Madeleine J; Minari, Jusaku; Teare, Harriet; Isasi, Rosario; Kato, Kazuto; Rial-Sebbag, Emmanuelle; Marshall, Patricia; Koenig, Barbara; Cambon-Thomsen, Anne

2018-03-07

Governments, funding bodies, institutions, and publishers have developed a number of strategies to encourage researchers to facilitate access to datasets. The rationale behind this approach is that this will bring a number of benefits and enable advances in healthcare and medicine by allowing the maximum returns from the investment in research, as well as reducing waste and promoting transparency. As this approach gains momentum, these data-sharing practices have implications for many kinds of research as they become standard practice across the world. The governance frameworks that have been developed to support biomedical research are not well equipped to deal with the complexities of international data sharing. This system is nationally based and is dependent upon expert committees for oversight and compliance, which has often led to piece-meal decision-making. This system tends to perpetuate inequalities by obscuring the contributions and the important role of different data providers along the data stream, whether they be low- or middle-income country researchers, patients, research participants, groups, or communities. As research and data-sharing activities are largely publicly funded, there is a strong moral argument for including the people who provide the data in decision-making and to develop governance systems for their continued participation. We recommend that governance of science becomes more transparent, representative, and responsive to the voices of many constituencies by conducting public consultations about data-sharing addressing issues of access and use; including all data providers in decision-making about the use and sharing of data along the whole of the data stream; and using digital technologies to encourage accessibility, transparency, and accountability. We anticipate that this approach could enhance the legitimacy of the research process, generate insights that may otherwise be overlooked or ignored, and help to bring valuable perspectives into the decision-making around international data sharing.

Emergent collective decision-making: Control, model and behavior

NASA Astrophysics Data System (ADS)

Shen, Tian

In this dissertation we study emergent collective decision-making in social groups with time-varying interactions and heterogeneously informed individuals. First we analyze a nonlinear dynamical systems model motivated by animal collective motion with heterogeneously informed subpopulations, to examine the role of uninformed individuals. We find through formal analysis that adding uninformed individuals in a group increases the likelihood of a collective decision. Secondly, we propose a model for human shared decision-making with continuous-time feedback and where individuals have little information about the true preferences of other group members. We study model equilibria using bifurcation analysis to understand how the model predicts decisions based on the critical threshold parameters that represent an individual's tradeoff between social and environmental influences. Thirdly, we analyze continuous-time data of pairs of human subjects performing an experimental shared tracking task using our second proposed model in order to understand transient behavior and the decision-making process. We fit the model to data and show that it reproduces a wide range of human behaviors surprisingly well, suggesting that the model may have captured the mechanisms of observed behaviors. Finally, we study human behavior from a game-theoretic perspective by modeling the aforementioned tracking task as a repeated game with incomplete information. We show that the majority of the players are able to converge to playing Nash equilibrium strategies. We then suggest with simulations that the mean field evolution of strategies in the population resemble replicator dynamics, indicating that the individual strategies may be myopic. Decisions form the basis of control and problems involving deciding collectively between alternatives are ubiquitous in nature and in engineering. Understanding how multi-agent systems make decisions among alternatives also provides insight for designing decentralized control laws for engineering applications from mobile sensor networks for environmental monitoring to collective construction robots. With this dissertation we hope to provide additional methodology and mathematical models for understanding the behavior and control of collective decision-making in multi-agent systems.

The Assisted Decision-Making (Capacity) Bill 2013: content, commentary, controversy.

PubMed

Kelly, B D

2015-03-01

Ireland's Assisted Decision-Making (Capacity) Bill (2013) aims to reform the law relating to persons who require assistance exercising their decision-making capacity. When finalised, the Bill will replace Ireland's outdated Ward of Court system which has an all-or-nothing approach to capacity; does not adequately define capacity; is poorly responsive to change; makes unwieldy provision for appointing decision-makers; and has insufficient provision for review. To explore the content and implications of the Assisted Decision-Making (Capacity) Bill. Review of the content of the Assisted Decision-Making (Capacity) Bill and related literature. The new Bill includes a presumption of capacity and defines lack of capacity. All interventions must minimise restriction of rights and freedom, and have due regard for "dignity, bodily integrity, privacy and autonomy". The Bill proposes legal frameworks for "assisted decision-making" (where an individual voluntarily appoints someone to assist with specific decisions relating to personal welfare or property and affairs, by, among other measures, assisting the individual to communicate his or her "will and preferences"); "co-decision-making" (where the Circuit Court declares the individual's capacity is reduced but he or she can make specific decisions with a co-decision-maker to share authority); "decision-making representatives" (substitute decision-making); "enduring power of attorney"; and "informal decision-making on personal welfare matters" (without apparent oversight). These measures, if implemented, will shift Ireland's capacity laws away from an approach based on "best interests" to one based on "will and preferences", and increase compliance with the United Nations' Convention on the Rights of Persons with Disabilities.

Mild cognitive impairment is associated with poorer decision-making in community-based older persons.

PubMed

Han, S Duke; Boyle, Patricia A; James, Bryan D; Yu, Lei; Bennett, David A

2015-04-01

To test the hypothesis that mild cognitive impairment (MCI) is associated with poorer financial and healthcare decision-making. Community-based epidemiological cohort study. Communities throughout northeastern Illinois. Older persons without dementia from the Rush Memory and Aging Project (N = 730). All participants underwent a detailed clinical evaluation and decision-making assessment using a measure that closely approximates materials used in real-world financial and healthcare settings. This allowed for measurement of total decision-making and financial and healthcare decision-making. Regression models were used to examine whether MCI was associated with a lower level of decision-making. In subsequent analyses, the relationship between specific cognitive systems (episodic memory, semantic memory, working memory, perceptual speed, visuospatial ability) and decision-making was explored in participants with MCI. MCI was associated with lower total, financial, and healthcare decision-making scores after accounting for the effects of age, education, and sex. The effect of MCI on total decision-making was equivalent to the effect of more than 10 additional years of age. Additional models showed that, when considering multiple cognitive systems, perceptual speed accounted for the most variance in decision-making in participants with MCI. Persons with MCI may have poorer financial and healthcare decision-making in real-world situations, and perceptual speed may be an important contributor to poorer decision-making in persons with MCI. © 2015, Copyright the Authors Journal compilation © 2015, The American Geriatrics Society.

Novel Statistical Approach to Determine Inflammatory Bowel Disease: Patients' Perspectives on Shared Decision Making.

PubMed

Siegel, Corey A; Lofland, Jennifer H; Naim, Ahmad; Gollins, Jan; Walls, Danielle M; Rudder, Laura E; Reynolds, Chuck

2016-02-01

Limited information is available on patients' perspectives of shared decision-making practices used in inflammatory bowel disease (IBD). The aim of this study was to examine patient insights regarding shared decision making among patients with IBD using novel statistical technology to analyze qualitative data. Two 10-patient focus groups (10 ulcerative colitis patients and 10 Crohn's disease patients) were conducted in Chicago in January 2012 to explore patients' experiences, concerns, and preferences related to shared decision making. Key audio excerpts of focus group insights were embedded within a 25-min online patient survey and used for moment-to-moment affect trace analysis. A total of 355 IBD patients completed the survey (ulcerative colitis 51 %; Crohn's disease 49 %; female 54 %; 18-50 years of age 50 %). The majority of patients (66 %) reported increased satisfaction when they participated in shared decision making. Three unique patient clusters were identified based on their involvement in shared decision making: satisfied, content, and dissatisfied. Satisfied patients (18 %) had a positive physician relationship and a high level of trust with their physician. Content patients (48 %) had a moderate level of trust with their physician. Dissatisfied patients (34 %) had a life greatly affected by IBD, a low level of trust of their physician, a negative relationship with their physician, were skeptical of decisions, and did not rely on their physician for assistance. This study provides valuable insights regarding patients' perceptions of the shared decision-making process in IBD treatment using a novel moment-to-moment hybrid technology approach. Patient perspectives in this study indicate an increased desire for shared decision making in determining an optimal IBD treatment plan.

Knowledge bases, clinical decision support systems, and rapid learning in oncology.

PubMed

Yu, Peter Paul

2015-03-01

One of the most important benefits of health information technology is to assist the cognitive process of the human mind in the face of vast amounts of health data, limited time for decision making, and the complexity of the patient with cancer. Clinical decision support tools are frequently cited as a technologic solution to this problem, but to date useful clinical decision support systems (CDSS) have been limited in utility and implementation. This article describes three unique sources of health data that underlie fundamentally different types of knowledge bases which feed into CDSS. CDSS themselves comprise a variety of models which are discussed. The relationship of knowledge bases and CDSS to rapid learning health systems design is critical as CDSS are essential drivers of rapid learning in clinical care. Copyright © 2015 by American Society of Clinical Oncology.

An Integrated Approach of Fuzzy Linguistic Preference Based AHP and Fuzzy COPRAS for Machine Tool Evaluation.

PubMed

Nguyen, Huu-Tho; Md Dawal, Siti Zawiah; Nukman, Yusoff; Aoyama, Hideki; Case, Keith

2015-01-01

Globalization of business and competitiveness in manufacturing has forced companies to improve their manufacturing facilities to respond to market requirements. Machine tool evaluation involves an essential decision using imprecise and vague information, and plays a major role to improve the productivity and flexibility in manufacturing. The aim of this study is to present an integrated approach for decision-making in machine tool selection. This paper is focused on the integration of a consistent fuzzy AHP (Analytic Hierarchy Process) and a fuzzy COmplex PRoportional ASsessment (COPRAS) for multi-attribute decision-making in selecting the most suitable machine tool. In this method, the fuzzy linguistic reference relation is integrated into AHP to handle the imprecise and vague information, and to simplify the data collection for the pair-wise comparison matrix of the AHP which determines the weights of attributes. The output of the fuzzy AHP is imported into the fuzzy COPRAS method for ranking alternatives through the closeness coefficient. Presentation of the proposed model application is provided by a numerical example based on the collection of data by questionnaire and from the literature. The results highlight the integration of the improved fuzzy AHP and the fuzzy COPRAS as a precise tool and provide effective multi-attribute decision-making for evaluating the machine tool in the uncertain environment.

Mourning dove hunting regulation strategy based on annual harvest statistics and banding data

USGS Publications Warehouse

Otis, D.L.

2006-01-01

Although managers should strive to base game bird harvest management strategies on mechanistic population models, monitoring programs required to build and continuously update these models may not be in place. Alternatively, If estimates of total harvest and harvest rates are available, then population estimates derived from these harvest data can serve as the basis for making hunting regulation decisions based on population growth rates derived from these estimates. I present a statistically rigorous approach for regulation decision-making using a hypothesis-testing framework and an assumed framework of 3 hunting regulation alternatives. I illustrate and evaluate the technique with historical data on the mid-continent mallard (Anas platyrhynchos) population. I evaluate the statistical properties of the hypothesis-testing framework using the best available data on mourning doves (Zenaida macroura). I use these results to discuss practical implementation of the technique as an interim harvest strategy for mourning doves until reliable mechanistic population models and associated monitoring programs are developed.

Remote Sensing Applications to Water Quality Management in Florida

NASA Astrophysics Data System (ADS)

Lehrter, J. C.; Schaeffer, B. A.; Hagy, J.; Spiering, B.; Barnes, B.; Hu, C.; Le, C.; McEachron, L.; Underwood, L. W.; Ellis, C.; Fisher, B.

2013-12-01

Optical datasets from estuarine and coastal systems are increasingly available for remote sensing algorithm development, validation, and application. With validated algorithms, the data streams from satellite sensors can provide unprecedented spatial and temporal data for local and regional coastal water quality management. Our presentation will highlight two recent applications of optical data and remote sensing to water quality decision-making in coastal regions of the state of Florida; (1) informing the development of estuarine and coastal nutrient criteria for the state of Florida and (2) informing the rezoning of the Florida Keys National Marine Sanctuary. These efforts involved building up the underlying science to demonstrate the applicability of satellite data as well as an outreach component to educate decision-makers about the use, utility, and uncertainties of remote sensing data products. Scientific developments included testing existing algorithms and generating new algorithms for water clarity and chlorophylla in case II (CDOM or turbidity dominated) estuarine and coastal waters and demonstrating the accuracy of remote sensing data products in comparison to traditional field based measurements. Including members from decision-making organizations on the research team and interacting with decision-makers early and often in the process were key factors for the success of the outreach efforts and the eventual adoption of satellite data into the data records and analyses used in decision-making. Florida coastal water bodies (black boxes) for which remote sensing imagery were applied to derive numeric nutrient criteria and in situ observations (black dots) used to validate imagery. Florida ocean color applied to development of numeric nutrient criteria

On the scene: St Mary's Hospital, Madison, Wisconsin.

PubMed

Baker, Christine; Beglinger, Joan Ellis; Derosa, Jody; Griffin, Carla; Laham, Mary; Leonard, Mary Kay; Vanderkolk, Caprice

2009-01-01

In this article, we discuss Shared Governance as the foundation of our nursing professional practice model. Through the use of case examples and reflections from our management team, we demonstrate how this accountability-based practice model promotes excellence through developing, connecting, and engaging people, clarifying and communicating goals, using data to make decisions, and even shaping our organizational response to a critical incident. We close with a look to our future as our hospital embraces whole-system shared decision making.

Hesitant Fuzzy Thermodynamic Method for Emergency Decision Making Based on Prospect Theory.

PubMed

Ren, Peijia; Xu, Zeshui; Hao, Zhinan

2017-09-01

Due to the timeliness of emergency response and much unknown information in emergency situations, this paper proposes a method to deal with the emergency decision making, which can comprehensively reflect the emergency decision making process. By utilizing the hesitant fuzzy elements to represent the fuzziness of the objects and the hesitant thought of the experts, this paper introduces the negative exponential function into the prospect theory so as to portray the psychological behaviors of the experts, which transforms the hesitant fuzzy decision matrix into the hesitant fuzzy prospect decision matrix (HFPDM) according to the expectation-levels. Then, this paper applies the energy and the entropy in thermodynamics to take the quantity and the quality of the decision values into account, and defines the thermodynamic decision making parameters based on the HFPDM. Accordingly, a whole procedure for emergency decision making is conducted. What is more, some experiments are designed to demonstrate and improve the validation of the emergency decision making procedure. Last but not the least, this paper makes a case study about the emergency decision making in the firing and exploding at Port Group in Tianjin Binhai New Area, which manifests the effectiveness and practicability of the proposed method.

Decision Making under Ambiguity and Objective Risk in Higher Age - A Review on Cognitive and Emotional Contributions.

PubMed

Liebherr, Magnus; Schiebener, Johannes; Averbeck, Heike; Brand, Matthias

2017-01-01

The ability of decision making plays a highly relevant role in our survival, but is adversely affected during the process of aging. The present review aims to provide a better understanding of age-related differences in decision making and the role of cognitive and emotional factors in this context. We reviewed the literature about age-effects on decision-making performance, focusing on decision making under ambiguous and objective risk. In decisions under ambiguous risks, as measured by the Iowa Gambling Task, decisions are based on the experiences with consequences. In this case, many articles have attributed age-related impairments in decision making to changes in emotional and somatic reward- and punishment processing. In decisions under objective risks, as measured for example by the Game of Dice Task, decisions can be based on explicit information about risks and consequences. In this case, age-related changes have been attributed mainly to a cognitive decline, particularly impaired executive functions. However, recent findings challenge these conclusions. The present review summarizes neuropsychological and neurophysiological findings of age-related differences in decision making under ambiguous and objective risk. In this context, the relevance of learning, but also of cognitive and emotional contributors - responsible for age-related differences in decision making - are additionally pointed out.

Decision Making under Ambiguity and Objective Risk in Higher Age – A Review on Cognitive and Emotional Contributions

PubMed Central

Liebherr, Magnus; Schiebener, Johannes; Averbeck, Heike; Brand, Matthias

2017-01-01

The ability of decision making plays a highly relevant role in our survival, but is adversely affected during the process of aging. The present review aims to provide a better understanding of age-related differences in decision making and the role of cognitive and emotional factors in this context. We reviewed the literature about age-effects on decision-making performance, focusing on decision making under ambiguous and objective risk. In decisions under ambiguous risks, as measured by the Iowa Gambling Task, decisions are based on the experiences with consequences. In this case, many articles have attributed age-related impairments in decision making to changes in emotional and somatic reward- and punishment processing. In decisions under objective risks, as measured for example by the Game of Dice Task, decisions can be based on explicit information about risks and consequences. In this case, age-related changes have been attributed mainly to a cognitive decline, particularly impaired executive functions. However, recent findings challenge these conclusions. The present review summarizes neuropsychological and neurophysiological findings of age-related differences in decision making under ambiguous and objective risk. In this context, the relevance of learning, but also of cognitive and emotional contributors – responsible for age-related differences in decision making – are additionally pointed out. PMID:29270145

Mentor judgements and decision-making in the assessment of student nurse competence in practice: A mixed-methods study.

PubMed

Burden, Sarah; Topping, Anne Elizabeth; O'Halloran, Catherine

2018-05-01

To investigate how mentors form judgements and reach summative assessment decisions regarding student competence in practice. Competence assessment is a significant component of pre-registration nursing programmes in the United Kingdom. Concerns exist that assessments are subjective, lack consistency and that mentors fail to judge student performance as unsatisfactory. A two-stage sequential embedded mixed-methods design. Data collected 2012-2013. This study involved a whole student cohort completing a UK undergraduate adult nursing programme (N = 41). Stage 1: quantitative data on mentor conduct of assessment interviews and the final decision recorded (N = 330 from 270 mentors) were extracted from student Practice Assessment Documents (PADs). Stage 2: mentor feedback in student PADs was used in Stimulated Recall interviews with a purposive sample of final placement mentors (N = 17). These were thematically analysed. Findings were integrated to develop a theoretically driven model of mentor decision-making. Course assessment strategies and documentation had limited effect in framing mentor judgements and decisions. Rather, mentors amassed impressions, moderated by expectations of an "idealized student" by practice area and programme stage that influenced their management and outcome of the assessment process. These impressions were accumulated and combined into judgements that informed the final decision. This process can best be understood and conceptualized through the Brunswik's lens model of social judgement. Mentor decisions were reasoned and there was a shared understanding of judgement criteria and their importance. This impression-based nature of mentor decision-making questions the reliability and validity of competency-based assessments used in nursing pre-registration programmes. © 2017 John Wiley & Sons Ltd.

Spatially explicit multi-criteria decision analysis for managing vector-borne diseases

PubMed Central

2011-01-01

The complex epidemiology of vector-borne diseases creates significant challenges in the design and delivery of prevention and control strategies, especially in light of rapid social and environmental changes. Spatial models for predicting disease risk based on environmental factors such as climate and landscape have been developed for a number of important vector-borne diseases. The resulting risk maps have proven value for highlighting areas for targeting public health programs. However, these methods generally only offer technical information on the spatial distribution of disease risk itself, which may be incomplete for making decisions in a complex situation. In prioritizing surveillance and intervention strategies, decision-makers often also need to consider spatially explicit information on other important dimensions, such as the regional specificity of public acceptance, population vulnerability, resource availability, intervention effectiveness, and land use. There is a need for a unified strategy for supporting public health decision making that integrates available data for assessing spatially explicit disease risk, with other criteria, to implement effective prevention and control strategies. Multi-criteria decision analysis (MCDA) is a decision support tool that allows for the consideration of diverse quantitative and qualitative criteria using both data-driven and qualitative indicators for evaluating alternative strategies with transparency and stakeholder participation. Here we propose a MCDA-based approach to the development of geospatial models and spatially explicit decision support tools for the management of vector-borne diseases. We describe the conceptual framework that MCDA offers as well as technical considerations, approaches to implementation and expected outcomes. We conclude that MCDA is a powerful tool that offers tremendous potential for use in public health decision-making in general and vector-borne disease management in particular. PMID:22206355

Correlates of unmet need for contraception in Bangladesh: does couples' concordance in household decision making matter?

PubMed

Uddin, Jalal; Pulok, Mohammad Habibullah; Sabah, Md Nasim-Us

2016-07-01

A large body of literature has highlighted that women's household decision-making power is associated with better reproductive health outcomes, while most of the studies tend to measure such power from only women's point of view. Using both husband's and wife's matched responses to decision-making questions, this study examined the association between couples' concordant and discordant decision makings, and wife's unmet need for contraception in Bangladesh. This study used couple's data set (n=3336) from Bangladesh Demographic and Health Survey of 2007. Multivariate logistic regression was used to examine the likelihood of unmet need for contraception among married women of reproductive age. Study results suggested that couples who support the equalitarian power structure seemed to be more powerful in meeting the unmet demand for contraception. Logistic regression analysis revealed that compared to couple's concordant joint decision making, concordance in husband-only or other's involvement in decision making was associated with higher odds of unmet need for contraception. Wives exposed to family planning information discussed family planning more often with husbands, and those from richest households were less likely to have unmet need for contraception. Couple's concordant joint decision making, reflecting the concept of equalitarian power structure, appeared to be a significant analytic category. Policy makers in the field of family planning may promote community-based outreach programs and communication campaigns for family planning focusing on egalitarian gender roles in the household. Copyright © 2016 Elsevier Inc. All rights reserved.

District decision-making for health in low-income settings: a feasibility study of a data-informed platform for health in India, Nigeria and Ethiopia.

PubMed

Avan, Bilal Iqbal; Berhanu, Della; Umar, Nasir; Wickremasinghe, Deepthi; Schellenberg, Joanna

2016-09-01

Low-resource settings often have limited use of local data for health system planning and decision-making. To promote local data use for decision-making and priority setting, we propose an adapted framework: a data-informed platform for health (DIPH) aimed at guiding coordination, bringing together key data from the public and private sectors on inputs and processes. In working to transform this framework from a concept to a health systems initiative, we undertook a series of implementation research activities including background assessment, testing and scaling up of the intervention. This first paper of four reports the feasibility of the approach in a district health systems context in five districts of India, Nigeria and Ethiopia. We selected five districts using predefined criteria and in collaboration with governments. After scoping visits, an in-depth field visit included interviews with key health stakeholders, focus group discussions with service-delivery staff and record review. For analysis, we used five dimensions of feasibility research based on the TELOS framework: technology and systems, economic, legal and political, operational and scheduling feasibility. We found no standardized process for data-based district level decision-making, and substantial obstacles in all three countries. Compared with study areas in Ethiopia and Nigeria, the health system in Uttar Pradesh is relatively amenable to the DIPH, having relative strengths in infrastructure, technological and technical expertise, and financial resources, as well as a district-level stakeholder forum. However, a key challenge is the absence of an effective legal framework for engagement with India's extensive private health sector. While priority-setting may depend on factors beyond better use of local data, we conclude that a formative phase of intervention development and pilot-testing is warranted as a next step. © The Author 2016. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine.

District decision-making for health in low-income settings: a feasibility study of a data-informed platform for health in India, Nigeria and Ethiopia

PubMed Central

Avan, Bilal Iqbal; Berhanu, Della; Umar, Nasir; Wickremasinghe, Deepthi; Schellenberg, Joanna

2016-01-01

Low-resource settings often have limited use of local data for health system planning and decision-making. To promote local data use for decision-making and priority setting, we propose an adapted framework: a data-informed platform for health (DIPH) aimed at guiding coordination, bringing together key data from the public and private sectors on inputs and processes. In working to transform this framework from a concept to a health systems initiative, we undertook a series of implementation research activities including background assessment, testing and scaling up of the intervention. This first paper of four reports the feasibility of the approach in a district health systems context in five districts of India, Nigeria and Ethiopia. We selected five districts using predefined criteria and in collaboration with governments. After scoping visits, an in-depth field visit included interviews with key health stakeholders, focus group discussions with service-delivery staff and record review. For analysis, we used five dimensions of feasibility research based on the TELOS framework: technology and systems, economic, legal and political, operational and scheduling feasibility. We found no standardized process for data-based district level decision-making, and substantial obstacles in all three countries. Compared with study areas in Ethiopia and Nigeria, the health system in Uttar Pradesh is relatively amenable to the DIPH, having relative strengths in infrastructure, technological and technical expertise, and financial resources, as well as a district-level stakeholder forum. However, a key challenge is the absence of an effective legal framework for engagement with India’s extensive private health sector. While priority-setting may depend on factors beyond better use of local data, we conclude that a formative phase of intervention development and pilot-testing is warranted as a next step. PMID:27591204

Behavioral and Neural Adaptation in Approach Behavior.

PubMed

Wang, Shuo; Falvello, Virginia; Porter, Jenny; Said, Christopher P; Todorov, Alexander

2018-06-01

People often make approachability decisions based on perceived facial trustworthiness. However, it remains unclear how people learn trustworthiness from a population of faces and whether this learning influences their approachability decisions. Here we investigated the neural underpinning of approach behavior and tested two important hypotheses: whether the amygdala adapts to different trustworthiness ranges and whether the amygdala is modulated by task instructions and evaluative goals. We showed that participants adapted to the stimulus range of perceived trustworthiness when making approach decisions and that these decisions were further modulated by the social context. The right amygdala showed both linear response and quadratic response to trustworthiness level, as observed in prior studies. Notably, the amygdala's response to trustworthiness was not modulated by stimulus range or social context, a possible neural dynamic adaptation. Together, our data have revealed a robust behavioral adaptation to different trustworthiness ranges as well as a neural substrate underlying approach behavior based on perceived facial trustworthiness.