A Decision Support System for Managing a Diverse Portfolio of Technology Resources

NASA Technical Reports Server (NTRS)

Smith, J.

2000-01-01

This paper describes an automated decision support system designed to facilitate the management of a continuously changing portfolio of technologies as new technologies are deployed and older technologies are decommissioned.

Advancing beyond the system: telemedicine nurses' clinical reasoning using a computerised decision support system for patients with COPD - an ethnographic study.

PubMed

Barken, Tina Lien; Thygesen, Elin; Söderhamn, Ulrika

2017-12-28

Telemedicine is changing traditional nursing care, and entails nurses performing advanced and complex care within a new clinical environment, and monitoring patients at a distance. Telemedicine practice requires complex disease management, advocating that the nurses' reasoning and decision-making processes are supported. Computerised decision support systems are being used increasingly to assist reasoning and decision-making in different situations. However, little research has focused on the clinical reasoning of nurses using a computerised decision support system in a telemedicine setting. Therefore, the objective of the study is to explore the process of telemedicine nurses' clinical reasoning when using a computerised decision support system for the management of patients with chronic obstructive pulmonary disease. The factors influencing the reasoning and decision-making processes were investigated. In this ethnographic study, a combination of data collection methods, including participatory observations, the think-aloud technique, and a focus group interview was employed. Collected data were analysed using qualitative content analysis. When telemedicine nurses used a computerised decision support system for the management of patients with complex, unstable chronic obstructive pulmonary disease, two categories emerged: "the process of telemedicine nurses' reasoning to assess health change" and "the influence of the telemedicine setting on nurses' reasoning and decision-making processes". An overall theme, termed "advancing beyond the system", represented the connection between the reasoning processes and the telemedicine work and setting, where being familiar with the patient functioned as a foundation for the nurses' clinical reasoning process. In the telemedicine setting, when supported by a computerised decision support system, nurses' reasoning was enabled by the continuous flow of digital clinical data, regular video-mediated contact and shared decision-making with the patient. These factors fostered an in-depth knowledge of the patients and acted as a foundation for the nurses' reasoning process. Nurses' reasoning frequently advanced beyond the computerised decision support system recommendations. Future studies are warranted to develop more accurate algorithms, increase system maturity, and improve the integration of the digital clinical information with clinical experiences, to support telemedicine nurses' reasoning process.

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.

Modifications and integration of the electronic tracking board in a pediatric emergency department.

PubMed

Dexheimer, Judith W; Kennebeck, Stephanie

2013-07-01

Electronic health records (EHRs) are used for data storage; provider, laboratory, and patient communication; clinical decision support; procedure and medication orders; and decision support alerts. Clinical decision support is part of any EHR and is designed to help providers make better decisions. The emergency department (ED) poses a unique environment to the use of EHRs and clinical decision support. Used effectively, computerized tracking boards can help improve flow, communication, and the dissemination of pertinent visit information between providers and other departments in a busy ED. We discuss the unique modifications and decisions made in the implementation of an EHR and computerized tracking board in a pediatric ED. We discuss the changing views based on provider roles, customization to the user interface including the layout and colors, decision support, tracking board best practices collected from other institutions and colleagues, and a case study of using reminders on the electronic tracking board to drive pain reassessments.

Collaborative modelling and integrated decision support system analysis of a developed terminal lake basin

USGS Publications Warehouse

Niswonger, Richard G.; Allander, Kip K.; Jeton, Anne E.

2014-01-01

A terminal lake basin in west-central Nevada, Walker Lake, has undergone drastic change over the past 90 yrs due to upstream water use for agriculture. Decreased inflows to the lake have resulted in 100 km2 decrease in lake surface area and a total loss of fisheries due to salinization. The ecologic health of Walker Lake is of great concern as the lake is a stopover point on the Pacific route for migratory birds from within and outside the United States. Stakeholders, water institutions, and scientists have engaged in collaborative modeling and the development of a decision support system that is being used to develop and analyze management change options to restore the lake. Here we use an integrated management and hydrologic model that relies on state-of-the-art simulation capabilities to evaluate the benefits of using integrated hydrologic models as components of a decision support system. Nonlinear feedbacks among climate, surface-water and groundwater exchanges, and water use present challenges for simulating realistic outcomes associated with management change. Integrated management and hydrologic modeling provides a means of simulating benefits associated with management change in the Walker River basin where drastic changes in the hydrologic landscape have taken place over the last century. Through the collaborative modeling process, stakeholder support is increasing and possibly leading to management change options that result in reductions in Walker Lake salt concentrations, as simulated by the decision support system.

Linking climate change and fish conservation efforts using spatially explicit decision support tools

Treesearch

Douglas P. Peterson; Seth J. Wenger; Bruce E. Rieman; Daniel J. Isaak

2013-01-01

Fisheries professionals are increasingly tasked with incorporating climate change projections into their decisions. Here we demonstrate how a structured decision framework, coupled with analytical tools and spatial data sets, can help integrate climate and biological information to evaluate management alternatives. We present examples that link downscaled climate...

Impact of different training strategies on the accuracy of a Bayesian network for predicting hospital admission.

PubMed

Leegon, Jeffrey; Aronsky, Dominik

2006-01-01

The healthcare environment is constantly changing. Probabilistic clinical decision support systems need to recognize and incorporate the changing patterns and adjust the decision model to maintain high levels of accuracy. Using data from >75,000 ED patients during a 19-month study period we examined the impact of various static and dynamic training strategies on a decision support system designed to predict hospital admission status for ED patients. Training durations ranged from 1 to 12 weeks. During the study period major institutional changes occurred that affected the system's performance level. The average area under the receiver operating characteristic curve was higher and more stable when longer training periods were used. The system showed higher accuracy when retrained an updated with more recent data as compared to static training period. To adjust for temporal trends the accuracy of decision support systems can benefit from longer training periods and retraining with more recent data.

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

Developing an Ecosystem Services online Decision Support Tool to Assess the Impacts of Climate Change and Urban Growth in the Santa Cruz Watershed; Where We Live, Work, and Play

EPA Science Inventory

Processes through which ecosystems provide goods or benefit people can be referred to as "ecosystems services”, which may be quantified to clarify decision-making, with techniques including cost-benefit analysis. We are developing an online decision support tool, the Santa Cruz W...

Decision support systems in water and wastewater treatment process selection and design: a review.

PubMed

Hamouda, M A; Anderson, W B; Huck, P M

2009-01-01

The continuously changing drivers of the water treatment industry, embodied by rigorous environmental and health regulations and the challenge of emerging contaminants, necessitates the development of decision support systems for the selection of appropriate treatment trains. This paper explores a systematic approach to developing decision support systems, which includes the analysis of the treatment problem(s), knowledge acquisition and representation, and the identification and evaluation of criteria controlling the selection of optimal treatment systems. The objective of this article is to review approaches and methods used in decision support systems developed to aid in the selection, sequencing of unit processes and design of drinking water, domestic wastewater, and industrial wastewater treatment systems. Not surprisingly, technical considerations were found to dominate the logic of the developed systems. Most of the existing decision-support tools employ heuristic knowledge. It has been determined that there is a need to develop integrated decision support systems that are generic, usable and consider a system analysis approach.

The Association Between Social Support and Stages of Change in Survivors of Intimate Partner Violence.

PubMed

Zapor, Heather; Wolford-Clevenger, Caitlin; Johnson, Dawn M

2018-04-01

For survivors of intimate partner violence (IPV), it is often difficult to take steps to establish safety and obtain a violence free life. Researchers have applied stage of change theory to aid in understanding the experience of survivors, as well as, the factors that can help women who desire to make changes in or break free from a violent relationship. Social support is one factor that can be helpful to IPV survivors who are attempting to make changes in their relationship. The purpose of the current study was to examine the differences in social support experienced by women who are at varying points in the process of change. Shelter residents ( N = 191) participated in this cross-sectional non-experimental study. Analyses demonstrated five distinct clusters or profiles of change among study participants and were labeled by the authors as follows: preparticipation, decision making, engagement, ambivalent, and action. All forms of social support (i.e., structural, functional, and satisfaction) were generally higher for individuals more engaged in the process of change. More specifically, differences were noted between the action and decision-making clusters and the engagement and decision-making clusters. These findings suggest that it is vital that clinicians working with survivors of IPV not only assess but also tailor interventions to meet survivors where they are in the process of change. Further, interventions that foster survivors' abilities to develop reliable and satisfying social support networks will be beneficial for survivors of IPV.

Whose decision is it anyway? How clinicians support decision-making participation after acquired brain injury.

PubMed

Knox, Lucy; Douglas, Jacinta M; Bigby, Christine

2013-01-01

To raise professional awareness of factors that may influence the support offered by clinicians to people with acquired brain injury (ABI), and to consider the potential implications of these factors in terms of post-injury rehabilitation and living. A review of the literature was conducted to identify factors that determine how clinicians provide support and influence opportunities for individuals with ABI to participate in decision making across the rehabilitation continuum. Clinical case studies are used to highlight two specific issues: (1) hidden assumptions on the part of the practitioner, and (2) perceptions of risk operating in clinical practice. There are a range of factors which may influence the decision-making support provided by clinicians and, ultimately, shape lifetime outcomes for individuals with ABI. A multidimensional framework may assist clinicians to identify relevant factors and consider their potential implications including those that influence how clinicians involved in supporting decision making approach this task. Participation in decision making is an undisputed human right and central to the provision of person-centred care. Further research is required to understand how clinical practice can maximise both opportunities and support for increased decision-making participation by individuals with ABI. There is an increasing focus on the rights of all individuals to be supported to participate in decision making about their life. A number of changes associated with ABI mean that individuals with ABI will require support with decision making. Clinicians have a critical role in providing this support over the course of the rehabilitation continuum. Clinicians need to be aware of the range of factors that may influence the decision-making support they provide. A multidimensional framework may be used by clinicians to identify influences on the decision-making support they provide.

Understanding the stakeholders' intention to use economic decision-support tools: A cross-sectional study with the tobacco return on investment tool.

PubMed

Cheung, Kei Long; Evers, Silvia M A A; Hiligsmann, Mickaël; Vokó, Zoltán; Pokhrel, Subhash; Jones, Teresa; Muñoz, Celia; Wolfenstetter, Silke B; Józwiak-Hagymásy, Judit; de Vries, Hein

2016-01-01

Despite an increased number of economic evaluations of tobacco control interventions, the uptake by stakeholders continues to be limited. Understanding the underlying mechanism in adopting such economic decision-support tools by stakeholders is therefore important. By applying the I-Change Model, this study aims to identify which factors determine potential uptake of an economic decision-support tool, i.e., the Return on Investment tool. Stakeholders (decision-makers, purchasers of services/pharma products, professionals/service providers, evidence generators and advocates of health promotion) were interviewed in five countries, using an I-Change based questionnaire. MANOVA's were conducted to assess differences between intenders and non-intenders regarding beliefs. A multiple regression analysis was conducted to identify the main explanatory variables of intention to use an economic decision-support tool. Ninety-three stakeholders participated. Significant differences in beliefs were found between non-intenders and intenders: risk perception, attitude, social support, and self-efficacy towards using the tool. Regression showed that demographics, pre-motivational, and motivational factors explained 69% of the variation in intention. This study is the first to provide a theoretical framework to understand differences in beliefs between stakeholders who do or do not intend to use economic decision-support tools, and empirically corroborating the framework. This contributes to our understanding of the facilitators and barriers to the uptake of these studies. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Managing Decisions on Changes in the Virtual Enterprise Evolution

NASA Astrophysics Data System (ADS)

Drissen-Silva, Marcus Vinicius; Rabelo, Ricardo José

VE evolution deals with problems that happen during the VE operation and that put on risk planned results. This requires the application of problem-solving mechanisms to guarantee the construction of a new but feasible VE plan. Grounded on Project Management and Decision Support Systems foundations, this paper proposes a distributed collaborative decision support system to manage the VE evolution. Its main rationale is that VE’s members are autonomous and hence that all the affected partners should discuss about the necessary changes on the current VE’s plan. In the proposed approach, this discussion is guided by a decision protocol, and the impact of decisions can be evaluated. Results of a first prototype implementation are presented and discussed, with a special focus on the part which regulates the argumentation, voting and comparison of possible solutions.

Hypothesis-Driven Story Building: Counteracting Human Cognitive Biases to Improve Medical Diagnosis Support

ERIC Educational Resources Information Center

Zhu, Shizhuo

2010-01-01

Clinical decision-making is challenging mainly because of two factors: (1) patient conditions are often complicated with partial and changing information; (2) people have cognitive biases in their decision-making and information-seeking. Consequentially, misdiagnoses and ineffective use of resources may happen. To better support clinical…

Cost accounting in health care: fad or fundamental?

PubMed

Kaskiw, E A; Hanlon, P; Wulf, P

1987-11-01

The drastic changes in the environment affecting hospitals have caused management to look toward capturing and reporting cost information to make decisions. These decisions will, in part, shape the way hospitals continue to do business. This article focuses on the data requirements necessary to support product and operational management decisions facing today's hospitals. In addition, the difference in data needed to support product and operational management is explored.

Getting the Balance Right: Conceptual Considerations Concerning Legal Capacity and Supported Decision-Making.

PubMed

Parker, Malcolm

2016-09-01

The United Nations Convention on the Rights of Persons with Disabilities urges and requires changes to how signatories discharge their duties to people with intellectual disabilities, in the direction of their greater recognition as legal persons with expanded decision-making rights. Australian jurisdictions are currently undertaking inquiries and pilot projects that explore how these imperatives should be implemented. One of the important changes advocated is to move from guardianship models to supported or assisted models of decision-making. A driving force behind these developments is a strong allegiance to the social model of disability, in the formulation of the Convention, in inquiries and pilot projects, in implementation and in the related academic literature. Many of these instances suffer from confusing and misleading statements and conceptual misinterpretations of certain elements such as legal capacity, decision-making capacity, and support for decision-making. This paper analyses some of these confusions and their possible negative implications for supported decision-making instruments and those whose interests these instruments would serve, and advises a more incremental development of existing guardianship regimes. This provides a more realistic balance between neglecting the real limits of those with mental disabilities and thereby ignoring their identity and particularity, and continuing to bring them equally and fully into society.

Changing hospitals, choosing chemotherapy and deciding you've made the right choice: Understanding the role of online support groups in different health decision-making activities.

PubMed

Sillence, Elizabeth; Bussey, Lauren

2017-05-01

To investigate the ways in which people use online support groups (OSGs) in relation to their health decision-making and to identify the key features of the resource that support those activities. Eighteen participants who used OSGs for a range of health conditions participated in qualitative study in which they were interviewed about their experiences of using OSGs in relation to decision-making. Exploration of their experiences was supported by discussion of illustrative quotes. Across the health conditions OSGs supported two main decision-making activities: (i) prompting decision making and (ii) evaluating and confirming decisions already made. Depending on the activity, participants valued information about the process, the experience and the outcome of patient narratives. The importance of forum interactivity was highlighted in relation to advice-seeking and the selection of relevant personal experiences. People use OSGs in different ways to support their health related decision-making valuing the different content types of the narratives and the interactivity provided by the resource. Engaging with OSGs helps people in a number of different ways in relation to decision-making. However, it only forms one part of people's decision-making strategies and appropriate resources should be signposted where possible. Copyright © 2017 Elsevier B.V. All rights reserved.

Implementing shared decision making in routine mental health care

PubMed Central

Slade, Mike

2017-01-01

Shared decision making (SDM) in mental health care involves clinicians and patients working together to make decisions. The key elements of SDM have been identified, decision support tools have been developed, and SDM has been recommended in mental health at policy level. Yet implementation remains limited. Two justifications are typically advanced in support of SDM. The clinical justification is that SDM leads to improved outcome, yet the available empirical evidence base is inconclusive. The ethical justification is that SDM is a right, but clinicians need to balance the biomedical ethical principles of autonomy and justice with beneficence and non‐maleficence. It is argued that SDM is “polyvalent”, a sociological concept which describes an idea commanding superficial but not deep agreement between disparate stakeholders. Implementing SDM in routine mental health services is as much a cultural as a technical problem. Three challenges are identified: creating widespread access to high‐quality decision support tools; integrating SDM with other recovery‐supporting interventions; and responding to cultural changes as patients develop the normal expectations of citizenship. Two approaches which may inform responses in the mental health system to these cultural changes – social marketing and the hospitality industry – are identified. PMID:28498575

Decision support systems and the healthcare strategic planning process: a case study.

PubMed

Lundquist, D L; Norris, R M

1991-01-01

The repertoire of applications that comprises health-care decision support systems (DSS) includes analyses of clinical, financial, and operational activities. As a whole, these applications facilitate developing comprehensive and interrelated business and medical models that support the complex decisions required to successfully manage today's health-care organizations. Kennestone Regional Health Care System's use of DSS to facilitate strategic planning has precipitated marked changes in the organization's method of determining capital allocations. This case study discusses Kennestone's use of DSS in the strategic planning process, including profiles of key DSS modeling components.

The development of an online decision support tool for organizational readiness for change.

PubMed

Khan, Sobia; Timmings, Caitlyn; Moore, Julia E; Marquez, Christine; Pyka, Kasha; Gheihman, Galina; Straus, Sharon E

2014-05-10

Much importance has been placed on assessing readiness for change as one of the earliest steps of implementation, but measuring it can be a complex and daunting task. Organizations and individuals struggle with how to reliably and accurately measure readiness for change. Several measures have been developed to help organizations assess readiness, but these are often underused due to the difficulty of selecting the right measure. In response to this challenge, we will develop and test a prototype of a decision support tool that is designed to guide individuals interested in implementation in the selection of an appropriate readiness assessment measure for their setting. A multi-phase approach will be used to develop the decision support tool. First, we will identify key measures for assessing organizational readiness for change from a recently completed systematic review. Included measures will be those developed for healthcare settings (e.g., acute care, public health, mental health) and that have been deemed valid and reliable. Second, study investigators and field experts will engage in a mapping exercise to categorize individual items of included measures according to key readiness constructs from an existing framework. Third, a stakeholder panel will be recruited and consulted to determine the feasibility and relevance of the selected measures using a modified Delphi process. Fourth, findings from the mapping exercise and stakeholder consultation will inform the development of a decision support tool that will guide users in appropriately selecting change readiness measures. Fifth, the tool will undergo usability testing. Our proposed decision support tool will address current challenges in the field of organizational change readiness by aiding individuals in selecting a valid and reliable assessment measure that is relevant to user needs and practice settings. We anticipate that implementers and researchers who use our tool will be more likely to conduct readiness for change assessments in their settings when planning for implementation. This, in turn, may contribute to more successful implementation outcomes. We will test this tool in a future study to determine its efficacy and impact on implementation processes.

Participatory Decision Making.

ERIC Educational Resources Information Center

King, M. Bruce; And Others

Shifting from traditional, hierarchical bureaucracies to participatory governance and decision making is a major theme in school restructuring. This paper focuses on the involvement of teachers in key aspects of school decision making. Specifically, the paper describes how changes in power relations supported teachers' focus on improving the…

Dashboard visualizations: Supporting real-time throughput decision-making.

PubMed

Franklin, Amy; Gantela, Swaroop; Shifarraw, Salsawit; Johnson, Todd R; Robinson, David J; King, Brent R; Mehta, Amit M; Maddow, Charles L; Hoot, Nathan R; Nguyen, Vickie; Rubio, Adriana; Zhang, Jiajie; Okafor, Nnaemeka G

2017-07-01

Providing timely and effective care in the emergency department (ED) requires the management of individual patients as well as the flow and demands of the entire department. Strategic changes to work processes, such as adding a flow coordination nurse or a physician in triage, have demonstrated improvements in throughput times. However, such global strategic changes do not address the real-time, often opportunistic workflow decisions of individual clinicians in the ED. We believe that real-time representation of the status of the entire emergency department and each patient within it through information visualizations will better support clinical decision-making in-the-moment and provide for rapid intervention to improve ED flow. This notion is based on previous work where we found that clinicians' workflow decisions were often based on an in-the-moment local perspective, rather than a global perspective. Here, we discuss the challenges of designing and implementing visualizations for ED through a discussion of the development of our prototype Throughput Dashboard and the potential it holds for supporting real-time decision-making. Copyright © 2017. Published by Elsevier Inc.

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.

Algorithm for decision support as the tool for control system of industries with variable assortment of products

NASA Astrophysics Data System (ADS)

Ladaniuk, Anatolii; Ivashchuk, Viacheslav; Kisała, Piotr; Askarova, Nursanat; Sagymbekova, Azhar

2015-12-01

Conditions of diversification of enterprise products are involving for changes of higher levels of management hierarchy, so it's leading by tasks correcting and changing schedule for operating of production plans. Ordinary solve by combination of enterprise resource are planning and management execution system often has exclusively statistical content. So, the development of decision support system, that helps to use knowledge about subject for capabilities estimating and order of operation of production object is relevant in this time.

Group Health's participation in a shared decision-making demonstration yielded lessons, such as role of culture change.

PubMed

King, Jaime; Moulton, Benjamin

2013-02-01

In 2007 Washington State became the first state to enact legislation encouraging the use of shared decision making and decision aids to address deficiencies in the informed-consent process. Group Health volunteered to fulfill a legislated mandate to study the costs and benefits of integrating these shared decision-making processes into clinical practice across a range of conditions for which multiple treatment options are available. The Group Health Demonstration Project, conducted during 2009-11, yielded five key lessons for successful implementation, including the synergy between efforts to reduce practice variation and increase shared decision making; the need to support modifications in practice with changes in physician training and culture; and the value of identifying best implementation methods through constant evaluation and iterative improvement. These lessons, and the legislated provisions that supported successful implementation, can guide other states and health care institutions moving toward informed patient choice as the standard of care for medical decision making.

A Framework for a Decision Support System in a Hierarchical Extended Enterprise Decision Context

NASA Astrophysics Data System (ADS)

Boza, Andrés; Ortiz, Angel; Vicens, Eduardo; Poler, Raul

Decision Support System (DSS) tools provide useful information to decision makers. In an Extended Enterprise, a new goal, changes in the current objectives or small changes in the extended enterprise configuration produce a necessary adjustment in its decision system. A DSS in this context must be flexible and agile to make suitable an easy and quickly adaptation to this new context. This paper proposes to extend the Hierarchical Production Planning (HPP) structure to an Extended Enterprise decision making context. In this way, a framework for DSS in Extended Enterprise context is defined using components of HPP. Interoperability details have been reviewed to identify the impact in this framework. The proposed framework allows overcoming some interoperability barriers, identifying and organizing components for a DSS in Extended Enterprise context, and working in the definition of an architecture to be used in the design process of a flexible DSS in Extended Enterprise context which can reuse components for futures Extended Enterprise configurations.

The Effect of Providing Life Support on Nurses' Decision Making Regarding Life Support for Themselves and Family Members in Japan.

PubMed

Shaku, Fumio; Tsutsumi, Madoka

2016-12-01

Decision making in terminal illness has recently received increased attention. In Japan, patients and their families typically make decisions without understanding either the severity of illness or the efficacy of life-supporting treatments at the end of life. Japanese culture traditionally directs the family to make decisions for the patient. This descriptive study examined the influence of the experiences of 391 Japanese nurses caring for dying patients and family members and how that experience changed their decision making for themselves and their family members. The results were mixed but generally supported the idea that the more experience nurses have in caring for the dying, the less likely they would choose to institute lifesupport measures for themselves and family members. The results have implications for discussions on end-of-life care. © The Author(s) 2016.

75 FR 52733 - Record of Decision (ROD) for Fort Bliss Army Growth and Force Structure Realignment

Federal Register 2010, 2011, 2012, 2013, 2014

2010-08-27

... alternative consists of actions in three different categories (stationing/training, land use changes, and... (Stationing Action Alternative 4); land use changes that allow fixed site bivouac areas, mission support... supports Army expansion, future stationing actions, and land use changes and training infrastructure...

Operational seasonal forecasting of crop performance.

PubMed

Stone, Roger C; Meinke, Holger

2005-11-29

Integrated, interdisciplinary crop performance forecasting systems, linked with appropriate decision and discussion support tools, could substantially improve operational decision making in agricultural management. Recent developments in connecting numerical weather prediction models and general circulation models with quantitative crop growth models offer the potential for development of integrated systems that incorporate components of long-term climate change. However, operational seasonal forecasting systems have little or no value unless they are able to change key management decisions. Changed decision making through incorporation of seasonal forecasting ultimately has to demonstrate improved long-term performance of the cropping enterprise. Simulation analyses conducted on specific production scenarios are especially useful in improving decisions, particularly if this is done in conjunction with development of decision-support systems and associated facilitated discussion groups. Improved management of the overall crop production system requires an interdisciplinary approach, where climate scientists, agricultural scientists and extension specialists are intimately linked with crop production managers in the development of targeted seasonal forecast systems. The same principle applies in developing improved operational management systems for commodity trading organizations, milling companies and agricultural marketing organizations. Application of seasonal forecast systems across the whole value chain in agricultural production offers considerable benefits in improving overall operational management of agricultural production.

Operational seasonal forecasting of crop performance

PubMed Central

Stone, Roger C; Meinke, Holger

2005-01-01

Integrated, interdisciplinary crop performance forecasting systems, linked with appropriate decision and discussion support tools, could substantially improve operational decision making in agricultural management. Recent developments in connecting numerical weather prediction models and general circulation models with quantitative crop growth models offer the potential for development of integrated systems that incorporate components of long-term climate change. However, operational seasonal forecasting systems have little or no value unless they are able to change key management decisions. Changed decision making through incorporation of seasonal forecasting ultimately has to demonstrate improved long-term performance of the cropping enterprise. Simulation analyses conducted on specific production scenarios are especially useful in improving decisions, particularly if this is done in conjunction with development of decision-support systems and associated facilitated discussion groups. Improved management of the overall crop production system requires an interdisciplinary approach, where climate scientists, agricultural scientists and extension specialists are intimately linked with crop production managers in the development of targeted seasonal forecast systems. The same principle applies in developing improved operational management systems for commodity trading organizations, milling companies and agricultural marketing organizations. Application of seasonal forecast systems across the whole value chain in agricultural production offers considerable benefits in improving overall operational management of agricultural production. PMID:16433097

Characterizing uncertain sea-level rise projections to support investment decisions.

PubMed

Sriver, Ryan L; Lempert, Robert J; Wikman-Svahn, Per; Keller, Klaus

2018-01-01

Many institutions worldwide are considering how to include uncertainty about future changes in sea-levels and storm surges into their investment decisions regarding large capital infrastructures. Here we examine how to characterize deeply uncertain climate change projections to support such decisions using Robust Decision Making analysis. We address questions regarding how to confront the potential for future changes in low probability but large impact flooding events due to changes in sea-levels and storm surges. Such extreme events can affect investments in infrastructure but have proved difficult to consider in such decisions because of the deep uncertainty surrounding them. This study utilizes Robust Decision Making methods to address two questions applied to investment decisions at the Port of Los Angeles: (1) Under what future conditions would a Port of Los Angeles decision to harden its facilities against extreme flood scenarios at the next upgrade pass a cost-benefit test, and (2) Do sea-level rise projections and other information suggest such conditions are sufficiently likely to justify such an investment? We also compare and contrast the Robust Decision Making methods with a full probabilistic analysis. These two analysis frameworks result in similar investment recommendations for different idealized future sea-level projections, but provide different information to decision makers and envision different types of engagement with stakeholders. In particular, the full probabilistic analysis begins by aggregating the best scientific information into a single set of joint probability distributions, while the Robust Decision Making analysis identifies scenarios where a decision to invest in near-term response to extreme sea-level rise passes a cost-benefit test, and then assembles scientific information of differing levels of confidence to help decision makers judge whether or not these scenarios are sufficiently likely to justify making such investments. Results highlight the highly-localized and context dependent nature of applying Robust Decision Making methods to inform investment decisions.

Characterizing uncertain sea-level rise projections to support investment decisions

PubMed Central

Lempert, Robert J.; Wikman-Svahn, Per; Keller, Klaus

2018-01-01

Many institutions worldwide are considering how to include uncertainty about future changes in sea-levels and storm surges into their investment decisions regarding large capital infrastructures. Here we examine how to characterize deeply uncertain climate change projections to support such decisions using Robust Decision Making analysis. We address questions regarding how to confront the potential for future changes in low probability but large impact flooding events due to changes in sea-levels and storm surges. Such extreme events can affect investments in infrastructure but have proved difficult to consider in such decisions because of the deep uncertainty surrounding them. This study utilizes Robust Decision Making methods to address two questions applied to investment decisions at the Port of Los Angeles: (1) Under what future conditions would a Port of Los Angeles decision to harden its facilities against extreme flood scenarios at the next upgrade pass a cost-benefit test, and (2) Do sea-level rise projections and other information suggest such conditions are sufficiently likely to justify such an investment? We also compare and contrast the Robust Decision Making methods with a full probabilistic analysis. These two analysis frameworks result in similar investment recommendations for different idealized future sea-level projections, but provide different information to decision makers and envision different types of engagement with stakeholders. In particular, the full probabilistic analysis begins by aggregating the best scientific information into a single set of joint probability distributions, while the Robust Decision Making analysis identifies scenarios where a decision to invest in near-term response to extreme sea-level rise passes a cost-benefit test, and then assembles scientific information of differing levels of confidence to help decision makers judge whether or not these scenarios are sufficiently likely to justify making such investments. Results highlight the highly-localized and context dependent nature of applying Robust Decision Making methods to inform investment decisions. PMID:29414978

Dairy cow culling strategies: making economical culling decisions.

PubMed

Lehenbauer, T W; Oltjen, J W

1998-01-01

The purpose of this report was to examine important economic elements of culling decisions, to review progress in development of culling decision support systems, and to discern some of the potentially rewarding areas for future research on culling models. Culling decisions have an important influence on the economic performance of the dairy but are often made in a nonprogrammed fashion and based partly on the intuition of the decision maker. The computer technology that is available for dairy herd management has made feasible the use of economic models to support culling decisions. Financial components--including profit, cash flow, and risk--are major economic factors affecting culling decisions. Culling strategies are further influenced by short-term fluctuations in cow numbers as well as by planned herd expansion. Changes in herd size affect the opportunity cost for postponed replacement and may alter the relevance of optimization strategies that assume a fixed herd size. Improvements in model components related to biological factors affecting future cow performance, including milk production, reproductive status, and mastitis, appear to offer the greatest economic potential for enhancing culling decision support systems. The ultimate value of any culling decision support system for developing economic culling strategies will be determined by its results under field conditions.

Towards Supporting Patient Decision-making In Online Diabetes Communities

PubMed Central

Zhang, Jing; Marmor, Rebecca; Huh, Jina

2017-01-01

As of 2014, 29.1 million people in the US have diabetes. Patients with diabetes have evolving information needs around complex lifestyle and medical decisions. As their conditions progress, patients need to sporadically make decisions by understanding alternatives and comparing options. These moments along the decision-making process present a valuable opportunity to support their information needs. An increasing number of patients visit online diabetes communities to fulfill their information needs. To understand how patients attempt to fulfill the information needs around decision-making in online communities, we reviewed 801 posts from an online diabetes community and included 79 posts for in-depth content analysis. The findings revealed motivations for posters’ inquiries related to decision-making including the changes in disease state, increased self-awareness, and conflict of information received. Medication and food were the among the most popular topics discussed as part of their decision-making inquiries. Additionally, We present insights for automatically identifying those decision-making inquiries to efficiently support information needs presented in online health communities. PMID:29854261

Home care decision support using an Arden engine--merging smart home and vital signs data.

PubMed

Marschollek, Michael; Bott, Oliver J; Wolf, Klaus-H; Gietzelt, Matthias; Plischke, Maik; Madiesh, Moaaz; Song, Bianying; Haux, Reinhold

2009-01-01

The demographic change with a rising proportion of very old people and diminishing resources leads to an intensification of the use of telemedicine and home care concepts. To provide individualized decision support, data from different sources, e.g. vital signs sensors and home environmental sensors, need to be combined and analyzed together. Furthermore, a standardized decision support approach is necessary. The aim of our research work is to present a laboratory prototype home care architecture that integrates data from different sources and uses a decision support system based on the HL7 standard Arden Syntax for Medical Logical Modules. Data from environmental sensors connected to a home bus system are stored in a data base along with data from wireless medical sensors. All data are analyzed using an Arden engine with the medical knowledge represented in Medical Logic Modules. Multi-modal data from four different sensors in the home environment are stored in a single data base and are analyzed using an HL7 standard conformant decision support system. Individualized home care decision support must be based on all data available, including context data from smart home systems and medical data from electronic health records. Our prototype implementation shows the feasibility of using an Arden engine for decision support in a home setting. Our future work will include the utilization of medical background knowledge for individualized decision support, as there is no one-size-fits-all knowledge base in medicine.

Geographic information systems applications for climate change decision-making : Peer exchange summary report, Atlanta, Georgia, September 26-27, 2011

DOT National Transportation Integrated Search

2011-09-30

On September 26-27, 2011, the FHWA's Office of Planning sponsored a 1.5 day peer exchange focusing on the use of GIS to support transportation related climate change decisions. This report provides overviews of the presentations given at the peer exc...

Enlisting qualitative methods to improve environmental monitoring

EPA Science Inventory

Environmental monitoring tracks ecological changes in order to support environmental management decisions. Monitoring design is driven by natural scientists, usually lacking a formal social science basis. However, human perspectives drive environmental resource decisions, with ...

CHANGES SDSS: the development of a Spatial Decision Support System for analysing changing hydro-meteorological risk

NASA Astrophysics Data System (ADS)

van Westen, Cees; Bakker, Wim; Zhang, Kaixi; Jäger, Stefan; Assmann, Andre; Kass, Steve; Andrejchenko, Vera; Olyazadeh, Roya; Berlin, Julian; Cristal, Irina

2014-05-01

Within the framework of the EU FP7 Marie Curie Project CHANGES (www.changes-itn.eu) and the EU FP7 Copernicus project INCREO (http://www.increo-fp7.eu) a spatial decision support system is under development with the aim to analyse the effect of risk reduction planning alternatives on reducing the risk now and in the future, and support decision makers in selecting the best alternatives. The Spatial Decision Support System will be composed of a number of integrated components. The Risk Assessment component allows to carry out spatial risk analysis, with different degrees of complexity, ranging from simple exposure (overlay of hazard and assets maps) to quantitative analysis (using different hazard types, temporal scenarios and vulnerability curves) resulting into risk curves. The platform does not include a component to calculate hazard maps, and existing hazard maps are used as input data for the risk component. The second component of the SDSS is a risk reduction planning component, which forms the core of the platform. This component includes the definition of risk reduction alternatives (related to disaster response planning, risk reduction measures and spatial planning) and links back to the risk assessment module to calculate the new level of risk if the measure is implemented, and a cost-benefit (or cost-effectiveness/ Spatial Multi Criteria Evaluation) component to compare the alternatives and make decision on the optimal one. The third component of the SDSS is a temporal scenario component, which allows to define future scenarios in terms of climate change, land use change and population change, and the time periods for which these scenarios will be made. The component doesn't generate these scenarios but uses input maps for the effect of the scenarios on the hazard and assets maps. The last component is a communication and visualization component, which can compare scenarios and alternatives, not only in the form of maps, but also in other forms (risk curves, tables, graphs). The envisaged users of the platform are organizations involved in planning of risk reduction measures, and that have staff capable of visualizing and analysing spatial data at a municipal scale.

E-DECIDER Decision Support Gateway For Earthquake Disaster Response

NASA Astrophysics Data System (ADS)

Glasscoe, M. T.; Stough, T. M.; Parker, J. W.; Burl, M. C.; Donnellan, A.; Blom, R. G.; Pierce, M. E.; Wang, J.; Ma, Y.; Rundle, J. B.; Yoder, M. R.

2013-12-01

Earthquake Data Enhanced Cyber-Infrastructure for Disaster Evaluation and Response (E-DECIDER) is a NASA-funded project developing capabilities for decision-making utilizing remote sensing data and modeling software in order to provide decision support for earthquake disaster management and response. E-DECIDER incorporates earthquake forecasting methodology and geophysical modeling tools developed through NASA's QuakeSim project in order to produce standards-compliant map data products to aid in decision-making following an earthquake. Remote sensing and geodetic data, in conjunction with modeling and forecasting tools, help provide both long-term planning information for disaster management decision makers as well as short-term information following earthquake events (i.e. identifying areas where the greatest deformation and damage has occurred and emergency services may need to be focused). E-DECIDER utilizes a service-based GIS model for its cyber-infrastructure in order to produce standards-compliant products for different user types with multiple service protocols (such as KML, WMS, WFS, and WCS). The goal is to make complex GIS processing and domain-specific analysis tools more accessible to general users through software services as well as provide system sustainability through infrastructure services. The system comprises several components, which include: a GeoServer for thematic mapping and data distribution, a geospatial database for storage and spatial analysis, web service APIs, including simple-to-use REST APIs for complex GIS functionalities, and geoprocessing tools including python scripts to produce standards-compliant data products. These are then served to the E-DECIDER decision support gateway (http://e-decider.org), the E-DECIDER mobile interface, and to the Department of Homeland Security decision support middleware UICDS (Unified Incident Command and Decision Support). The E-DECIDER decision support gateway features a web interface that delivers map data products including deformation modeling results (slope change and strain magnitude) and aftershock forecasts, with remote sensing change detection results under development. These products are event triggered (from the USGS earthquake feed) and will be posted to event feeds on the E-DECIDER webpage and accessible via the mobile interface and UICDS. E-DECIDER also features a KML service that provides infrastructure information from the FEMA HAZUS database through UICDS and the mobile interface. The back-end GIS service architecture and front-end gateway components form a decision support system that is designed for ease-of-use and extensibility for end-users.

A multicriteria decision making model for assessment and selection of an ERP in a logistics context

NASA Astrophysics Data System (ADS)

Pereira, Teresa; Ferreira, Fernanda A.

2017-07-01

The aim of this work is to apply a methodology of decision support based on a multicriteria decision analyses (MCDA) model that allows the assessment and selection of an Enterprise Resource Planning (ERP) in a Portuguese logistics company by Group Decision Maker (GDM). A Decision Support system (DSS) that implements a MCDA - Multicriteria Methodology for the Assessment and Selection of Information Systems / Information Technologies (MMASSI / IT) is used based on its features and facility to change and adapt the model to a given scope. Using this DSS it was obtained the information system that best suited to the decisional context, being this result evaluated through a sensitivity and robustness analysis.

Forest climate change Vulnerability and Adaptation Assessment in Himalayas

NASA Astrophysics Data System (ADS)

Chitale, V. S.; Shrestha, H. L.; Agarwal, N. K.; Choudhurya, D.; Gilani, H.; Dhonju, H. K.; Murthy, M. S. R.

2014-11-01

Forests offer an important basis for creating and safeguarding more climate-resilient communities over Hindu Kush Himalayan region. The forest ecosystem vulnerability assessment to climate change and developing knowledge base to identify and support relevant adaptation strategies is realized as an urgent need. The multi scale adaptation strategies portray increasing complexity with the increasing levels in terms of data requirements, vulnerability understanding and decision making to choose a particular adaptation strategy. We present here how such complexities could be addressed and adaptation decisions could be either directly supported by open source remote sensing based forestry products or geospatial analysis and modelled products. The forest vulnerability assessment under climate change scenario coupled with increasing forest social dependence was studied using IPCC Landscape scale Vulnerability framework in Chitwan-Annapurna Landscape (CHAL) situated in Nepal. Around twenty layers of geospatial information on climate, forest biophysical and forest social dependence data was used to assess forest vulnerability and associated adaptation needs using self-learning decision tree based approaches. The increase in forest fires, evapotranspiration and reduction in productivity over changing climate scenario was observed. The adaptation measures on enhancing productivity, improving resilience, reducing or avoiding pressure with spatial specificity are identified to support suitable decision making. The study provides spatial analytical framework to evaluate multitude of parameters to understand vulnerabilities and assess scope for alternative adaptation strategies with spatial explicitness.

Youth advocacy as a tool for environmental and policy changes that support physical activity and nutrition: an evaluation study in San Diego County.

PubMed

Linton, Leslie S; Edwards, Christine C; Woodruff, Susan I; Millstein, Rachel A; Moder, Cheryl

2014-03-27

As evidence grows about the benefits of policy and environmental changes to support active living and healthy eating, effective tools for implementing change must be developed. Youth advocacy, a successful strategy in the field of tobacco control, should be evaluated for its potential in the field of obesity prevention. San Diego State University collaborated with the San Diego County Childhood Obesity Initiative to evaluate Youth Engagement and Action for Health! (YEAH!), a youth advocacy project to engage youth and adult mentors in advocating for neighborhood improvements in physical activity and healthy eating opportunities. Study objectives included documenting group process and success of groups in engaging in community advocacy with decision makers. In 2011 and 2012, YEAH! group leaders were recruited from the San Diego County Childhood Obesity Initiative's half-day train-the-trainer seminars for adult leaders. Evaluators collected baseline and postproject survey data from youth participants and adult group leaders and interviewed decision makers. Of the 21 groups formed, 20 completed the evaluation, conducted community assessments, and advocated with decision makers. Various types of decision makers were engaged, including school principals, food service personnel, city council members, and parks and recreation officials. Eleven groups reported change(s) implemented as a result of their advocacy, 4 groups reported changes pending, and 5 groups reported no change as a result of their efforts. Even a brief training session, paired with a practical manual, technical assistance, and commitment of adult leaders and youth may successfully engage decision makers and, ultimately, bring about change.

It's Not Just About More Data: Translation of Science and Decision Support Evaluation for Climate Impact Indicators

NASA Astrophysics Data System (ADS)

Kenney, M. A.

2014-12-01

The U.S. Global Change Research Program is currently considering establishing a National Climate Indicators System, which would be a set of physical, ecological, and societal indicators that would communicate key aspects of climate changes, impacts, vulnerabilities, and preparedness to inform mitigation and adaptation decisions. Thus, over the past several years 150+ scientists and practitioners representing a range of expertise from the climate system to natural systems to human sectors have developed a set of indicator recommendations that could be used as a first step to establishing such an indicator system. These recommendations have been implemented into a pilot system, with the goal of working with stakeholder communities to evaluate the understandability of individual indicators and learn how users are combining indicators for their own understanding or decision needs through this multiple Federal agency decision support platform. This prototype system provides the perfect test bed for evaluating the translation of scientific data - observations, remote sensing, and citizen science data -- and data products, such as indicators, for decision-making audiences. Often translation of scientific information into decision support products is developed and improved given intuition and feedback. Though this can be useful in many cases, more rigorous testing using social science methodologies would provide greater assurance that the data products are useful for the intended audiences. I will present some initial research using surveys to assess the understandability of indicators and whether that understanding is influenced by one's attitude toward climate change. Such information is critical to assess whether products developed for scientists by scientists have been appropriately translated for non-scientists, thus assuring that the data will have some value for the intended audience. Such survey information will provide a data driven approach to further develop and improve the National Climate Indicators System and could be applied to improve other decision support systems.

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 Integrated Web-based Decision Support System in Disaster Risk Management

NASA Astrophysics Data System (ADS)

Aye, Z. C.; Jaboyedoff, M.; Derron, M. H.

2012-04-01

Nowadays, web based decision support systems (DSS) play an essential role in disaster risk management because of their supporting abilities which help the decision makers to improve their performances and make better decisions without needing to solve complex problems while reducing human resources and time. Since the decision making process is one of the main factors which highly influence the damages and losses of society, it is extremely important to make right decisions at right time by combining available risk information with advanced web technology of Geographic Information System (GIS) and Decision Support System (DSS). This paper presents an integrated web-based decision support system (DSS) of how to use risk information in risk management efficiently and effectively while highlighting the importance of a decision support system in the field of risk reduction. Beyond the conventional systems, it provides the users to define their own strategies starting from risk identification to the risk reduction, which leads to an integrated approach in risk management. In addition, it also considers the complexity of changing environment from different perspectives and sectors with diverse stakeholders' involvement in the development process. The aim of this platform is to contribute a part towards the natural hazards and geosciences society by developing an open-source web platform where the users can analyze risk profiles and make decisions by performing cost benefit analysis, Environmental Impact Assessment (EIA) and Strategic Environmental Assessment (SEA) with the support of others tools and resources provided. There are different access rights to the system depending on the user profiles and their responsibilities. The system is still under development and the current version provides maps viewing, basic GIS functionality, assessment of important infrastructures (e.g. bridge, hospital, etc.) affected by landslides and visualization of the impact-probability matrix in terms of socio-economic dimension.

Factors that contribute to physician variability in decisions to limit life support in the ICU: a qualitative study.

PubMed

Wilson, Michael E; Rhudy, Lori M; Ballinger, Beth A; Tescher, Ann N; Pickering, Brian W; Gajic, Ognjen

2013-06-01

Our aim was to explore reasons for physician variability in decisions to limit life support in the intensive care unit (ICU) utilizing qualitative methodology. Single center study consisting of semi-structured interviews with experienced physicians and nurses. Seventeen intensivists from medical (n = 7), surgical (n = 5), and anesthesia (n = 5) critical care backgrounds, and ten nurses from medical (n = 5) and surgical (n = 5) ICU backgrounds were interviewed. Principles of grounded theory were used to analyze the interview transcripts. Eleven factors within four categories were identified that influenced physician variability in decisions to limit life support: (1) physician work environment-workload and competing priorities, shift changes and handoffs, and incorporation of nursing input; (2) physician experiences-of unexpected patient survival, and of limiting life support in physician's family; (3) physician attitudes-investment in a good surgical outcome, specialty perspective, values and beliefs; and (4) physician relationship with patient and family-hearing the patient's wishes firsthand, engagement in family communication, and family negotiation. We identified several factors which physicians and nurses perceived were important sources of physician variability in decisions to limit life support. Ways to raise awareness and ameliorate the potentially adverse effects of factors such as workload, competing priorities, shift changes, and handoffs should be explored. Exposing intensivists to long term patient outcomes, formalizing nursing input, providing additional training, and emphasizing firsthand knowledge of patient wishes may improve decision making.

Design and implementation of a risk assessment module in a spatial decision support system

NASA Astrophysics Data System (ADS)

Zhang, Kaixi; van Westen, Cees; Bakker, Wim

2014-05-01

The spatial decision support system named 'Changes SDSS' is currently under development. The goal of this system is to analyze changing hydro-meteorological hazards and the effect of risk reduction alternatives to support decision makers in choosing the best alternatives. The risk assessment module within the system is to assess the current risk, analyze the risk after implementations of risk reduction alternatives, and analyze the risk in different future years when considering scenarios such as climate change, land use change and population growth. The objective of this work is to present the detailed design and implementation plan of the risk assessment module. The main challenges faced consist of how to shift the risk assessment from traditional desktop software to an open source web-based platform, the availability of input data and the inclusion of uncertainties in the risk analysis. The risk assessment module is developed using Ext JS library for the implementation of user interface on the client side, using Python for scripting, as well as PostGIS spatial functions for complex computations on the server side. The comprehensive consideration of the underlying uncertainties in input data can lead to a better quantification of risk assessment and a more reliable Changes SDSS, since the outputs of risk assessment module are the basis for decision making module within the system. The implementation of this module will contribute to the development of open source web-based modules for multi-hazard risk assessment in the future. This work is part of the "CHANGES SDSS" project, funded by the European Community's 7th Framework Program.

Decision Support and Shared Decision Making About Active Surveillance Versus Active Treatment Among Men Diagnosed with Low-Risk Prostate Cancer: a Pilot Study.

PubMed

Myers, Ronald E; Leader, Amy E; Censits, Jean Hoffman; Trabulsi, Edouard J; Keith, Scott W; Petrich, Anett M; Quinn, Anna M; Den, Robert B; Hurwitz, Mark D; Lallas, Costas D; Hegarty, Sarah E; Dicker, Adam P; Zeigler-Johnson, Charnita M; Giri, Veda N; Ayaz, Hasan; Gomella, Leonard G

2018-02-01

This study aimed to explore the effects of a decision support intervention (DSI) and shared decision making (SDM) on knowledge, perceptions about treatment, and treatment choice among men diagnosed with localized low-risk prostate cancer (PCa). At a multidisciplinary clinic visit, 30 consenting men with localized low-risk PCa completed a baseline survey, had a nurse-mediated online DS session to clarify preference for active surveillance (AS) or active treatment (AT), and met with clinicians for SDM. Participants also completed a follow-up survey at 30 days. We assessed change in treatment knowledge, decisional conflict, and perceptions and identified predictors of AS. At follow-up, participants exhibited increased knowledge (p < 0.001), decreased decisional conflict (p < 0.001), and more favorable perceptions of AS (p = 0.001). Furthermore, 25 of the 30 participants (83 %) initiated AS. Increased family and clinician support predicted this choice (p < 0.001). DSI/SDM prepared patients to make an informed decision. Perceived support of the decision facilitated patient choice of AS.

Distributed decision support for the 21st century mission space

NASA Astrophysics Data System (ADS)

McQuay, William K.

2002-07-01

The past decade has produced significant changes in the conduct of military operations: increased humanitarian missions, asymmetric warfare, the reliance on coalitions and allies, stringent rules of engagement, concern about casualties, and the need for sustained air operations. Future mission commanders will need to assimilate a tremendous amount of information, make quick-response decisions, and quantify the effects of those decisions in the face of uncertainty. Integral to this process is creating situational assessment-understanding the mission space, simulation to analyze alternative futures, current capabilities, planning assessments, course-of-action assessments, and a common operational picture-keeping everyone on the same sheet of paper. Decision support tools in a distributed collaborative environment offer the capability of decomposing these complex multitask processes and distributing them over a dynamic set of execution assets. Decision support technologies can semi-automate activities, such as planning an operation, that have a reasonably well-defined process and provide machine-level interfaces to refine the myriad of information that is not currently fused. The marriage of information and simulation technologies provides the mission commander with a collaborative virtual environment for planning and decision support.

Nurse managers' decision-making in daily unit operation in peri-operative settings: a cross-sectional descriptive study.

PubMed

Siirala, Eriikka; Peltonen, Laura-Maria; Lundgrén-Laine, Heljä; Salanterä, Sanna; Junttila, Kristiina

2016-09-01

To describe the tactical and the operational decisions made by nurse managers when managing the daily unit operation in peri-operative settings. Management is challenging as situations change rapidly and decisions are constantly made. Understanding decision-making in this complex environment helps to develop decision support systems to support nurse managers' operative and tactical decision-making. Descriptive cross-sectional design. Data were collected from 20 nurse managers with the think-aloud method during the busiest working hours and analysed using thematic content analysis. Nurse managers made over 700 decisions; either ad hoc (n = 289), near future (n = 268) or long-term (n = 187) by nature. Decisions were often made simultaneously with many interruptions. Ad hoc decisions covered staff allocation, ensuring adequate staff, rescheduling surgical procedures, confirmation tangible resources and following-up the daily unit operation. Decisions in the near future were: planning of surgical procedures and tangible resources, and planning staff allocation. Long-term decisions were: human recourses, nursing development, supplies and equipment, and finances in the unit. Decision-making was vulnerable to interruptions, which sometimes complicated the managing tasks. The results can be used when planning decision support systems and when defining the nurse managers' tasks in peri-operative settings. © 2016 John Wiley & Sons Ltd.

D-WISE: Diabetes Web-Centric Information and Support Environment: conceptual specification and proposed evaluation.

PubMed

Abidi, Samina; Vallis, Michael; Raza Abidi, Syed Sibte; Piccinini-Vallis, Helena; Imran, Syed Ali

2014-06-01

To develop and evaluate Diabetes Web-Centric Information and Support Environment (D-WISE) that offers 1) a computerized decision-support system to assist physicians to A) use the Canadian Diabetes Association clinical practice guidelines (CDA CPGs) to recommend evidence-informed interventions; B) offer a computerized readiness assessment strategy to help physicians administer behaviour-change strategies to help patients adhere to disease self-management programs; and 2) a patient-specific diabetes self-management application, accessible through smart mobile devices, that offers behaviour-change interventions to engage patients in self-management. The above-mentioned objectives were pursued through a knowledge management approach that involved 1) Translation of paper-based CDA CPGs and behaviour-change models as computerized decision-support tools that will assist physicians to offer evidence-informed and personalized diabetes management and behaviour-change strategies; 2) Engagement of patients in their diabetes care by generating a diabetes self-management program that takes into account their preferences, challenges and needs; 3) Empowering patients to self-manage their condition by providing them with personalized educational and motivational messages through a mobile self-management application. The theoretical foundation of our research is grounded in behaviour-change models and healthcare knowledge management. We used 1) knowledge modelling to computerize the paper-based CDA CPGs and behaviour-change models, in particular, the behaviour-change strategy elements of A) readiness-to-change assessments; B) motivation-enhancement interventions categorized along the lines of patients' being ready, ambivalent or not ready; and C) self-efficacy enhancement. The CDA CPGs and the behaviour-change models are modelled and computerized in terms of A) a diabetes management ontology that serves as the knowledge resource for all the services offered by D-WISE; B) decision support services that use logic-based reasoning algorithms to utilize the knowledge encoded within the diabetes management ontology to assist physicians by recommending patient-specific diabetes-management interventions and behaviour-change strategies; C) a mobile diabetes self-management application to engage and educate diabetes patients to self-manage their condition in a home-based setting while working in concert with their family physicians. We have been successful in creating and conducting a usability assessment of the physician decision support tool. These results will be published once the patient self- management application has been evaluated. D-WISE will be evaluated through pilot studies measuring 1) the usability of the e-Health interventions; and 2) the impact of the interventions on patients' behaviour changes and diabetes control. Copyright © 2014 Canadian Diabetes Association. Published by Elsevier Inc. All rights reserved.

Everyday decision-making in dementia: findings from a longitudinal interview study of people with dementia and family carers.

PubMed

Samsi, Kritika; Manthorpe, Jill

2013-06-01

Exercising choice and control over decisions is central to quality of life. The Mental Capacity Act 2005 (England and Wales) provides a legal framework to safeguard the rights of people with dementia to make their own decisions for as long as possible. The impact of this on long-term planning has been investigated; everyday decision-making in people's own homes remains unexplored. Using a phenomenological approach, we interviewed 12 dyads (one person with dementia + one carer) four times over one year to ascertain experience of decision-making, how decisions were negotiated, and how dynamics changed. Qualitative interviews were conducted in people's own homes, and thematic analysis was applied to transcripts. Respecting autonomy, decision-specificity and best interests underlay most everyday decisions in this sample. Over time, dyads transitioned from supported decision-making, where person with dementia and carer made decisions together, to substituted decision-making, where carers took over much decision-making. Points along this continuum represented carers' active involvement in retaining their relative's engagement through providing cues, reducing options, using retrospective information, and using the best interests principle. Long-term spouse carers seemed most equipped to make substitute decisions for their spouses; adult children and friend carers struggled with this. Carers may gradually take on decision-making for people with dementia. This can bring with it added stresses, such as determining their relative's decision-making capacity and weighing up what is in their best interests. Practitioners and support services should provide timely advice to carers and people with dementia around everyday decision-making, and be mindful how abilities may change.

Computerised decision support in physical activity interventions: A systematic literature review.

PubMed

Triantafyllidis, Andreas; Filos, Dimitris; Claes, Jomme; Buys, Roselien; Cornelissen, Véronique; Kouidi, Evangelia; Chouvarda, Ioanna; Maglaveras, Nicos

2018-03-01

The benefits of regular physical activity for health and quality of life are unarguable. New information, sensing and communication technologies have the potential to play a critical role in computerised decision support and coaching for physical activity. We provide a literature review of recent research in the development of physical activity interventions employing computerised decision support, their feasibility and effectiveness in healthy and diseased individuals, and map out challenges and future research directions. We searched the bibliographic databases of PubMed and Scopus to identify physical activity interventions with computerised decision support utilised in a real-life context. Studies were synthesized according to the target user group, the technological format (e.g., web-based or mobile-based) and decision-support features of the intervention, the theoretical model for decision support in health behaviour change, the study design, the primary outcome, the number of participants and their engagement with the intervention, as well as the total follow-up duration. From the 24 studies included in the review, the highest percentage (n = 7, 29%) targeted sedentary healthy individuals followed by patients with prediabetes/diabetes (n = 4, 17%) or overweight individuals (n = 4, 17%). Most randomized controlled trials reported significantly positive effects of the interventions, i.e., increase in physical activity (n = 7, 100%) for 7 studies assessing physical activity measures, weight loss (n = 3, 75%) for 4 studies assessing diet, and reductions in glycosylated hemoglobin (n = 2, 66%) for 3 studies assessing glycose concentration. Accelerometers/pedometers were used in almost half of the studies (n = 11, 46%). Most adopted decision support features included personalised goal-setting (n = 16, 67%) and motivational feedback sent to the users (n = 15, 63%). Fewer adopted features were integration with electronic health records (n = 3, 13%) and alerts sent to caregivers (n = 4, 17%). Theoretical models of decision support in health behaviour to drive the development of the intervention were not reported in most studies (n = 14, 58%). Interventions employing computerised decision support have the potential to promote physical activity and result in health benefits for both diseased and healthy individuals, and help healthcare providers to monitor patients more closely. Objectively measured activity through sensing devices, integration with clinical systems used by healthcare providers and theoretical frameworks for health behaviour change need to be employed in a larger scale in future studies in order to realise the development of evidence-based computerised systems for physical activity monitoring and coaching. Copyright © 2017 Elsevier B.V. All rights reserved.

A new ball game: the United Nations Convention on the Rights of Persons with Disabilities and assumptions in care for people with dementia.

PubMed

Smith, Anita; Sullivan, Danny

2012-09-01

The United Nations Convention on the Rights of Persons with Disabilities is a powerful international instrument which imposes significant responsibilities on signatories. This column discusses changes in the definition of legal capacity which will have significant impacts on decision-making related to people with dementia. Various restrictions and limitations on personal freedoms are discussed in light of the Convention. The main focus is on challenges to existing paradigms of substitute decision-making, which are in wide use through a guardianship model. Under Art 12 of the Convention, moves to supported decision-making will result in significant changes in ensuring the rights of people with dementia. There are challenges ahead in implementing supported decision-making schemes, not only due to tension with existing practices and legislation, but also the difficulty of developing and resourcing workable schemes. This is particularly so with advanced dementia, which is acknowledged as a pressing issue for Australia due to effective health care, an ageing population and changing expectations.

Designing Dynamic Adaptive Policy Pathways using Many-Objective Robust Decision Making

NASA Astrophysics Data System (ADS)

Kwakkel, Jan; Haasnoot, Marjolijn

2017-04-01

Dealing with climate risks in water management requires confronting a wide variety of deeply uncertain factors, while navigating a many dimensional space of trade-offs amongst objectives. There is an emerging body of literature on supporting this type of decision problem, under the label of decision making under deep uncertainty. Two approaches within this literature are Many-Objective Robust Decision Making, and Dynamic Adaptive Policy Pathways. In recent work, these approaches have been compared. One of the main conclusions of this comparison was that they are highly complementary. Many-Objective Robust Decision Making is a model based decision support approach, while Dynamic Adaptive Policy Pathways is primarily a conceptual framework for the design of flexible strategies that can be adapted over time in response to how the future is actually unfolding. In this research we explore this complementarity in more detail. Specifically, we demonstrate how Many-Objective Robust Decision Making can be used to design adaptation pathways. We demonstrate this combined approach using a water management problem, in the Netherlands. The water level of Lake IJselmeer, the main fresh water resource of the Netherlands, is currently managed through discharge by gravity. Due to climate change, this won't be possible in the future, unless water levels are changed. Changing the water level has undesirable flood risk and spatial planning consequences. The challenge is to find promising adaptation pathways that balance objectives related to fresh water supply, flood risk, and spatial issues, while accounting for uncertain climatic and land use change. We conclude that the combination of Many-Objective Robust Decision Making and Dynamic Adaptive Policy Pathways is particularly suited for dealing with deeply uncertain climate risks.

Shared Decision Making and Motivational Interviewing: Achieving Patient-Centered Care Across the Spectrum of Health Care Problems

PubMed Central

Elwyn, Glyn; Dehlendorf, Christine; Epstein, Ronald M.; Marrin, Katy; White, James; Frosch, Dominick L.

2014-01-01

Patient-centered care requires different approaches depending on the clinical situation. Motivational interviewing and shared decision making provide practical and well-described methods to accomplish patient-centered care in the context of situations where medical evidence supports specific behavior changes and the most appropriate action is dependent on the patient’s preferences. Many clinical consultations may require elements of both approaches, however. This article describes these 2 approaches—one to address ambivalence to medically indicated behavior change and the other to support patients in making health care decisions in cases where there is more than one reasonable option—and discusses how clinicians can draw on these approaches alone and in combination to achieve patient-centered care across the range of health care problems. PMID:24821899

Incorporating geodiversity into conservation decisions.

PubMed

Comer, Patrick J; Pressey, Robert L; Hunter, Malcolm L; Schloss, Carrie A; Buttrick, Steven C; Heller, Nicole E; Tirpak, John M; Faith, Daniel P; Cross, Molly S; Shaffer, Mark L

2015-06-01

In a rapidly changing climate, conservation practitioners could better use geodiversity in a broad range of conservation decisions. We explored selected avenues through which this integration might improve decision making and organized them within the adaptive management cycle of assessment, planning, implementation, and monitoring. Geodiversity is seldom referenced in predominant environmental law and policy. With most natural resource agencies mandated to conserve certain categories of species, agency personnel are challenged to find ways to practically implement new directives aimed at coping with climate change while retaining their species-centered mandate. Ecoregions and ecological classifications provide clear mechanisms to consider geodiversity in plans or decisions, the inclusion of which will help foster the resilience of conservation to climate change. Methods for biodiversity assessment, such as gap analysis, climate change vulnerability analysis, and ecological process modeling, can readily accommodate inclusion of a geophysical component. We adapted others' approaches for characterizing landscapes along a continuum of climate change vulnerability for the biota they support from resistant, to resilient, to susceptible, and to sensitive and then summarized options for integrating geodiversity into planning in each landscape type. In landscapes that are relatively resistant to climate change, options exist to fully represent geodiversity while ensuring that dynamic ecological processes can change over time. In more susceptible landscapes, strategies aiming to maintain or restore ecosystem resilience and connectivity are paramount. Implementing actions on the ground requires understanding of geophysical constraints on species and an increasingly nimble approach to establishing management and restoration goals. Because decisions that are implemented today will be revisited and amended into the future, increasingly sophisticated forms of monitoring and adaptation will be required to ensure that conservation efforts fully consider the value of geodiversity for supporting biodiversity in the face of a changing climate. © 2015 Society for Conservation Biology.

Youth Advocacy as a Tool for Environmental and Policy Changes That Support Physical Activity and Nutrition: An Evaluation Study in San Diego County

PubMed Central

Edwards, Christine C.; Woodruff, Susan I.; Millstein, Rachel A.; Moder, Cheryl

2014-01-01

Background As evidence grows about the benefits of policy and environmental changes to support active living and healthy eating, effective tools for implementing change must be developed. Youth advocacy, a successful strategy in the field of tobacco control, should be evaluated for its potential in the field of obesity prevention. Community Context San Diego State University collaborated with the San Diego County Childhood Obesity Initiative to evaluate Youth Engagement and Action for Health! (YEAH!), a youth advocacy project to engage youth and adult mentors in advocating for neighborhood improvements in physical activity and healthy eating opportunities. Study objectives included documenting group process and success of groups in engaging in community advocacy with decision makers. Methods In 2011 and 2012, YEAH! group leaders were recruited from the San Diego County Childhood Obesity Initiative’s half-day train-the-trainer seminars for adult leaders. Evaluators collected baseline and postproject survey data from youth participants and adult group leaders and interviewed decision makers. Outcomes Of the 21 groups formed, 20 completed the evaluation, conducted community assessments, and advocated with decision makers. Various types of decision makers were engaged, including school principals, food service personnel, city council members, and parks and recreation officials. Eleven groups reported change(s) implemented as a result of their advocacy, 4 groups reported changes pending, and 5 groups reported no change as a result of their efforts. Interpretation Even a brief training session, paired with a practical manual, technical assistance, and commitment of adult leaders and youth may successfully engage decision makers and, ultimately, bring about change. PMID:24674636

Current Directions in Adding Value to Earth Observation Products for Decision Support

NASA Astrophysics Data System (ADS)

Ryker, S. J.

2015-12-01

Natural resource managers and infrastructure planners face increasingly complex challenges, given competing demands for resources and changing conditions due to climate and land use change. These pressures create demand for high-quality, timely data; for both one-time decision support and long-term monitoring; and for techniques to articulate the value of resources in monetary and nonmonetary terms. To meet the need for data, the U.S. government invests several billion dollars per year in Earth observations collected from satellite, airborne, terrestrial, and ocean-based systems. Earth observation-based decision support is coming of age; user surveys show that these data are used in an increasing variety of analyses. For example, since the U.S. Department of the Interior/U.S. Geological Survey's (USGS) 2008 free and open data policy for the Landsat satellites, downloads from the USGS archive have increased from 20,000 Landsat scenes per year to 10 million per year and climbing, with strong growth in both research and decision support fields. However, Earth observation-based decision support still poses users a number of challenges. Many of those Landsat downloads support a specialized community of remote sensing scientists, though new technologies promise to increase the usability of remotely sensed data for the larger GIS community supporting planning and resource management. Serving this larger community also requires supporting the development of increasingly interpretive products, and of new approaches to host and update products. For example, automating updates will add value to new essential climate variable products such as surface water extent and wildfire burned area extent. Projections of future urbanization in the southeastern U.S. are most useful when long-term land cover trends are integrated with street-level community data and planning tools. The USGS assessment of biological carbon sequestration in vegetation and shallow soils required a significant research investment in satellite and in situ measurements and biogeochemical and climate modeling, and is already providing decision support at a variety of scales; once operationalized, it will be a tool for adaptive management from field-scale soil and wetland conservation projects to national-scale policy.

Providing Global Change Information for Decision-Making: Capturing and Presenting Provenance

NASA Technical Reports Server (NTRS)

Ma, Xiaogang; Fox, Peter; Tilmes, Curt; Jacobs, Katherine; Waple, Anne

2014-01-01

Global change information demands access to data sources and well-documented provenance to provide evidence needed to build confidence in scientific conclusions and, in specific applications, to ensure the information's suitability for use in decision-making. A new generation of Web technology, the Semantic Web, provides tools for that purpose. The topic of global change covers changes in the global environment (including alterations in climate, land productivity, oceans or other water resources, atmospheric composition and or chemistry, and ecological systems) that may alter the capacity of the Earth to sustain life and support human systems. Data and findings associated with global change research are of great public, government, and academic concern and are used in policy and decision-making, which makes the provenance of global change information especially important. In addition, since different types of decisions benefit from different types of information, understanding how to capture and present the provenance of global change information is becoming more of an imperative in adaptive planning.

Let the Games Begin: New Opportunities to Address Climate Change Communication, Education, and Decision Support

NASA Astrophysics Data System (ADS)

Rooney-varga, J. N.; Sterman, J.; Jones, A.; Johnston, E.; Rath, K.; Nease, J.

2014-12-01

A rapid transition to a low-carbon, climate-resilient society is not only possible, but could also bring many co-benefits for public health, economic wellbeing, social equity, and more. The science supporting an urgent need for such a transition has never been clearer. Yet, social science data are also clear: the public in the US (and many other similar developed economies) does not, on average, share this sense of urgency, nor have policymakers shown a willingness to put scientific evidence above the perceptions of their constituents. The gulf between scientific and public understanding of climate change has spurred research on climate change communication, learning, and decision-making, identifying barriers such as misconceptions and faulty mental models of the climate and energy systems; poor understanding of complex, dynamic systems generally; and affective and social barriers to learning and action. There is also a growing opportunity to address these barriers, through tools that rely on active learning, that are social, engaging (and even fun), and that are grounded in rigorous science. An increasing number of decision-support computer simulations are being developed, intended to make complex technical problems accessible to non-experts in an interactive format. At the same time, the use of scenario planning, role-playing games, and active learning approaches are gaining ground in policy and education spheres. Simulation-based role-playing games bring these approaches together and can provide powerful learning experiences: they offer the potential to compress time and reality; create experiences without requiring the 'real thing;' explore the consequences of our decisions that often unfold over decades; and open affective and social learning pathways. Here, we offer a perspective on the potential of these tools in climate change education, communication, and decision-support, and a brief demonstration of one tool we have developed, World Energy.

Decision-making and outcomes of hearing help-seekers: A self-determination theory perspective.

PubMed

Ridgway, Jason; Hickson, Louise; Lind, Christopher

2016-07-01

To explore the explanatory power of a self-determination theory (SDT) model of health behaviour change for hearing aid adoption decisions and fitting outcomes. A quantitative approach was taken for this longitudinal cohort study. Participants completed questionnaires adapted from SDT that measured autonomous motivation, autonomy support, and perceived competence for hearing aids. Hearing aid fitting outcomes were obtained with the international outcomes inventory for hearing aids (IOI-HA). Sociodemographic and audiometric information was collected. Participants were 216 adult first-time hearing help-seekers (125 hearing aid adopters, 91 non-adopters). Regression models assessed the impact of autonomous motivation and autonomy support on hearing aid adoption and hearing aid fitting outcomes. Sociodemographic and audiometric factors were also taken into account. Autonomous motivation, but not autonomy support, was associated with increased hearing aid adoption. Autonomy support was associated with increased perceived competence for hearing aids, reduced activity limitation and increased hearing aid satisfaction. Autonomous motivation was positively associated with hearing aid satisfaction. The SDT model is potentially useful in understanding how hearing aid adoption decisions are made, and how hearing health behaviour is internalized and maintained over time. Autonomy supportive practitioners may improve outcomes by helping hearing aid adopters maintain internalized change.

Decision making by urgency gating: theory and experimental support.

PubMed

Thura, David; Beauregard-Racine, Julie; Fradet, Charles-William; Cisek, Paul

2012-12-01

It is often suggested that decisions are made when accumulated sensory information reaches a fixed accuracy criterion. This is supported by many studies showing a gradual build up of neural activity to a threshold. However, the proposal that this build up is caused by sensory accumulation is challenged by findings that decisions are based on information from a time window much shorter than the build-up process. Here, we propose that in natural conditions where the environment can suddenly change, the policy that maximizes reward rate is to estimate evidence by accumulating only novel information and then compare the result to a decreasing accuracy criterion. We suggest that the brain approximates this policy by multiplying an estimate of sensory evidence with a motor-related urgency signal and that the latter is primarily responsible for neural activity build up. We support this hypothesis using human behavioral data from a modified random-dot motion task in which motion coherence changes during each trial.

Patient factors that influence clinicians' decision making in self-management support: A clinical vignette study.

PubMed

Bos-Touwen, Irene D; Trappenburg, Jaap C A; van der Wulp, Ineke; Schuurmans, Marieke J; de Wit, Niek J

2017-01-01

Self-management support is an integral part of current chronic care guidelines. The success of self-management interventions varies between individual patients, suggesting a need for tailored self-management support. Understanding the role of patient factors in the current decision making of health professionals can support future tailoring of self-management interventions. The aim of this study is to identify the relative importance of patient factors in health professionals' decision making regarding self-management support. A factorial survey was presented to primary care physicians and nurses. The survey consisted of clinical vignettes (case descriptions), in which 11 patient factors were systematically varied. Each care provider received a set of 12 vignettes. For each vignette, they decided whether they would give this patient self-management support and whether they expected this support to be successful. The associations between respondent decisions and patient factors were explored using ordered logit regression. The survey was completed by 60 general practitioners and 80 nurses. Self-management support was unlikely to be provided in a third of the vignettes. The most important patient factor in the decision to provide self-management support as well as in the expectation that self-management support would be successful was motivation, followed by patient-provider relationship and illness perception. Other factors, such as depression or anxiety, education level, self-efficacy and social support, had a small impact on decisions. Disease, disease severity, knowledge of disease, and age were relatively unimportant factors. This is the first study to explore the relative importance of patient factors in decision making and the expectations regarding the provision of self-management support to chronic disease patients. By far, the most important factor considered was patient's motivation; unmotivated patients were less likely to receive self-management support. Future tailored interventions should incorporate strategies to enhance motivation in unmotivated patients. Furthermore, care providers should be better equipped to promote motivational change in their patients.

Family planning decisions for parents of children with a rare genetic condition: A scoping review.

PubMed

Gee, Melanie; Piercy, Hilary; Machaczek, Katarzyna

2017-12-01

Expansion of newborn screening programmes increases the complexity around reproductive choices, both in terms of the increased number of parents faced with making reproductive decisions from the earliest days of their affected child's life, and the number of conditions for which such decisions have to be made. We conducted a scoping review to explore: (i) reproductive decision-making among parents of children with recessive genetic conditions; and, (ii) the involvement of healthcare services in facilitating and supporting those decisions. Systematic search processes involved seven bibliographic databases, citation, and grey literature searches. From an initial total of 311 identified articles, seven met the inclusion criteria and were included in the review. The extracted data were organised around three themes: factors influencing reproductive decisions taken by parents, how those factors changed over time, and the involvement of healthcare services in supporting and facilitating reproductive decisions. Most studies focused on attitudes towards, and uptake of, pre-natal diagnosis (PND) and termination. None of the studies considered the wider range of reproductive choices facing all parents, including those of children with conditions for whom PND and termination is not available or where good health outcomes make these options less justifiable. The literature provided little insight into the role of healthcare staff in providing family planning support for these parents. There is a need to better understand the support parents need in their decision-making, and who is best placed to provide that support. Copyright © 2017 Elsevier B.V. All rights reserved.

Air Quality Response Modeling for Decision Support | Science ...

EPA Pesticide Factsheets

Air quality management relies on photochemical models to predict the responses of pollutant concentrations to changes in emissions. Such modeling is especially important for secondary pollutants such as ozone and fine particulate matter which vary nonlinearly with changes in emissions. Numerous techniques for probing pollutant-emission relationships within photochemical models have been developed and deployed for a variety of decision support applications. However, atmospheric response modeling remains complicated by the challenge of validating sensitivity results against observable data. This manuscript reviews the state of the science of atmospheric response modeling as well as efforts to characterize the accuracy and uncertainty of sensitivity results. The National Exposure Research Laboratory′s (NERL′s) Atmospheric Modeling and Analysis Division (AMAD) conducts research in support of EPA′s mission to protect human health and the environment. AMAD′s research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the Nation′s air quality and for assessing changes in air quality and air pollutant exposures, as affected by changes in ecosystem management and regulatory decisions. AMAD is responsible for providing a sound scientific and technical basis for regulatory policies based on air quality models to improve ambient air quality. The models developed by AMAD are being use

The Burn Medical Assistant: Developing Machine Learning Algorithms to Aid in the Estimation of Burn Wound Size

DTIC Science & Technology

2017-10-01

hypothesis that a computer machine learning algorithm can analyze and classify burn injures using multispectral imaging within 5% of an expert clinician...morbidity. In response to these challenges, the USAISR developed and obtained FDA 510(k) clearance of the Burn Navigator™, a computer decision support... computer decision support software (CDSS), can significantly change the CDSS algorithm’s recommendations and thus the total fluid administered to a

Using decision trees to characterize verbal communication during change and stuck episodes in the therapeutic process

PubMed Central

Masías, Víctor H.; Krause, Mariane; Valdés, Nelson; Pérez, J. C.; Laengle, Sigifredo

2015-01-01

Methods are needed for creating models to characterize verbal communication between therapists and their patients that are suitable for teaching purposes without losing analytical potential. A technique meeting these twin requirements is proposed that uses decision trees to identify both change and stuck episodes in therapist-patient communication. Three decision tree algorithms (C4.5, NBTree, and REPTree) are applied to the problem of characterizing verbal responses into change and stuck episodes in the therapeutic process. The data for the problem is derived from a corpus of 8 successful individual therapy sessions with 1760 speaking turns in a psychodynamic context. The decision tree model that performed best was generated by the C4.5 algorithm. It delivered 15 rules characterizing the verbal communication in the two types of episodes. Decision trees are a promising technique for analyzing verbal communication during significant therapy events and have much potential for use in teaching practice on changes in therapeutic communication. The development of pedagogical methods using decision trees can support the transmission of academic knowledge to therapeutic practice. PMID:25914657

Using decision trees to characterize verbal communication during change and stuck episodes in the therapeutic process.

PubMed

Masías, Víctor H; Krause, Mariane; Valdés, Nelson; Pérez, J C; Laengle, Sigifredo

2015-01-01

Methods are needed for creating models to characterize verbal communication between therapists and their patients that are suitable for teaching purposes without losing analytical potential. A technique meeting these twin requirements is proposed that uses decision trees to identify both change and stuck episodes in therapist-patient communication. Three decision tree algorithms (C4.5, NBTree, and REPTree) are applied to the problem of characterizing verbal responses into change and stuck episodes in the therapeutic process. The data for the problem is derived from a corpus of 8 successful individual therapy sessions with 1760 speaking turns in a psychodynamic context. The decision tree model that performed best was generated by the C4.5 algorithm. It delivered 15 rules characterizing the verbal communication in the two types of episodes. Decision trees are a promising technique for analyzing verbal communication during significant therapy events and have much potential for use in teaching practice on changes in therapeutic communication. The development of pedagogical methods using decision trees can support the transmission of academic knowledge to therapeutic practice.

Modeling the Mental Health Practice Change Preferences of Educators: A Discrete-Choice Conjoint Experiment.

PubMed

Cunningham, Charles E; Barwick, Melanie; Short, Kathy; Chen, Yvonne; Rimas, Heather; Ratcliffe, Jenna; Mielko, Stephanie

2014-01-01

Schools are sometimes slow to adopt evidence-based strategies for improving the mental health outcomes of students. This study used a discrete-choice conjoint experiment to model factors influencing the decision of educators to adopt strategies for improving children's mental health outcomes. A sample of 1,010 educators made choices between hypothetical mental health practice change strategies composed by systematically varying the four levels of 16 practice change attributes. Latent class analysis yielded two segments with different practice change preferences. Both segments preferred small-group workshops, conducted by engaging experts, teaching skills applicable to all students. Participants expressed little interest in Internet options. The support of colleagues, administrators, and unions exerted a strong influence on the practice change choices of both segments. The Change Ready segment, 77.1 % of the sample, was more intent on adopting new strategies to improve the mental health of students. They preferred that schools, rather than the provincial ministry of education, make practice change decisions, coaching was provided to all participants, and participants received post-training follow-up sessions. The Demand Sensitive segment (22.9 %) was less intent on practice change. They preferred that individual teachers make practice change decisions, recommended discretionary coaching, and chose no post-training follow-up support. This study emphasizes the complex social, organizational, and policy context within which educators make practice change decisions. Efforts to disseminate strategies to improve the mental health outcomes of students need to be informed by the preferences of segments of educators who are sensitive to different dimensions of the practice change process. In the absence of a broad consensus of educators, administrators, and unions, potentially successful practice changes are unlikely to be adopted.

Informing Public Perceptions About Climate Change: A 'Mental Models' Approach.

PubMed

Wong-Parodi, Gabrielle; Bruine de Bruin, Wändi

2017-10-01

As the specter of climate change looms on the horizon, people will face complex decisions about whether to support climate change policies and how to cope with climate change impacts on their lives. Without some grasp of the relevant science, they may find it hard to make informed decisions. Climate experts therefore face the ethical need to effectively communicate to non-expert audiences. Unfortunately, climate experts may inadvertently violate the maxims of effective communication, which require sharing communications that are truthful, brief, relevant, clear, and tested for effectiveness. Here, we discuss the 'mental models' approach towards developing communications, which aims to help experts to meet the maxims of effective communications, and to better inform the judgments and decisions of non-expert audiences.

GLIMPSE: A decision support tool for simultaneously achieving our air quality management and climate change mitigation goals

NASA Astrophysics Data System (ADS)

Pinder, R. W.; Akhtar, F.; Loughlin, D. H.; Henze, D. K.; Bowman, K. W.

2012-12-01

Poor air quality, ecosystem damages, and climate change all are caused by the combustion of fossil fuels, yet environmental management often addresses each of these challenges separately. This can lead to sub-optimal strategies and unintended consequences. Here we present GLIMPSE -- a decision support tool for simultaneously achieving our air quality and climate change mitigation goals. GLIMPSE comprises of two types of models, (i) the adjoint of the GEOS-Chem chemical transport model, to calculate the relationship between emissions and impacts at high spatial resolution, and (ii) the MARKAL energy system model, to calculate the relationship between energy technologies and emissions. This presentation will demonstrate how GLIMPSE can be used to explore energy scenarios to better achieve both improved air quality and mitigate climate change. Second, this presentation will discuss how space-based observations can be incorporated into GLIMPSE to improve decision-making. NASA satellite products, namely ozone radiative forcing from the Tropospheric Emission Spectrometer (TES), are used to extend GLIMPSE to include the impact of emissions on ozone radiative forcing. This provides a much needed observational constraint on ozone radiative forcing.

The impact of social and organizational factors on workers' coping with musculoskeletal symptoms.

PubMed

Torp, S; Riise, T; Moen, B E

2001-07-01

Workers with musculoskeletal symptoms are often advised to cope with their symptoms by changing their working technique and by using lifting equipment. The main objective of this study was to test the hypothesis that negative social and organizational factors where people are employed may prevent workers from implementing these coping strategies. A total of 1,567 automobile garage workers (72%) returned a questionnaire concerning coping with musculoskeletal symptoms and social and organizational factors. When job demands, decision authority, social support, and management support related to health, environment, and safety (HES) were used as predictor variables in a multiple regression model, coping as the outcome variable was correlated with decision authority, social support, and HES-related management support (standardized beta=.079,.12, and.13, respectively). When an index for health-related support and control was added to the model, it correlated with coping (standardized beta=.36), whereas the other relationships disappeared. Decision authority and social support entail health-related support and control that, in turn, influences coping.

Autonomous Task Management and Decision Support Tools

NASA Technical Reports Server (NTRS)

Burian, Barbara

2017-01-01

For some time aircraft manufacturers and researchers have been pursuing mechanisms for reducing crew workload and providing better decision support to the pilots, especially during non-normal situations. Some previous attempts to develop task managers or pilot decision support tools have not resulted in robust and fully functional systems. However, the increasing sophistication of sensors and automated reasoners, and the exponential surge in the amount of digital data that is now available create a ripe environment for the development of a robust, dynamic, task manager and decision support tool that is context sensitive and integrates information from a wide array of on-board and off aircraft sourcesa tool that monitors systems and the overall flight situation, anticipates information needs, prioritizes tasks appropriately, keeps pilots well informed, and is nimble and able to adapt to changing circumstances. This presentation will discuss the many significant challenges and issues associated with the development and functionality of such a system for use on the aircraft flight deck.

Health care workers and their needs: the forgotten shadow of AIM research.

PubMed

Lillehaug, S I; Lajoie, S

1998-01-01

The field of AI in Medicine (AIM) seems to have accepted that decision support is, and will be, needed within most medical domains. As society calls for cost-effectiveness, and human expertise or expert guidance are not always available, decision support systems (DSSs) are proposed as the solutions. These solutions, however, do not necessarily correspond with the basic needs of their targeted users. We will show this through a review of the literature related to health care workers and the various factors that have an influence on their performances. Furthermore, we will use these empirical findings to argue that the AIM community must go beyond its decision support philosophy, whereby the gaps in human expertise are filled in by the computer. In the future, joint emphasis must be placed on decision support and the promotion towards independent and self-sufficient problem solving. In order to implement this paradigm change, the AIM community will have to incorporate findings from the research discipline of AI in Education.

Climate Change and Sea Level Rise: A Challenge to Science and Society

NASA Astrophysics Data System (ADS)

Plag, H.

2009-12-01

Society is challenged by the risk of an anticipated rise of coastal Local Sea Level (LSL) as a consequence of future global warming. Many low-lying and often subsiding and densely populated coastal areas are under risk of increased inundation, with potentially devastating consequences for the global economy, society, and environment. Faced with a trade-off between imposing the very high costs of coastal protection and adaptation upon today's national economies and leaving the costs of potential major disasters to future generations, governments and decision makers are in need of scientific support for the development of mitigation and adaptation strategies for the coastal zone. Low-frequency to secular changes in LSL are the result of many interacting Earth system processes. The complexity of the Earth system makes it difficult to predict Global Sea Level (GSL) rise and, even more so, LSL changes over the next 100 to 200 years. Humans have re-engineered the planet and changed major features of the Earth surface and the atmosphere, thus ruling out extrapolation of past and current changes into the future as a reasonable approach. The risk of rapid changes in ocean circulation and ice sheet mass balance introduces the possibility of unexpected changes. Therefore, science is challenged with understanding and constraining the full range of plausible future LSL trajectories and with providing useful support for informed decisions. In the face of largely unpredictable future sea level changes, monitoring of the relevant processes and development of a forecasting service on realistic time scales is crucial as decision support. Forecasting and "early warning" for LSL rise would have to aim at decadal time scales, giving coastal managers sufficient time to react if the onset of rapid changes would require an immediate response. The social, environmental, and economic risks associated with potentially large and rapid LSL changes are enormous. Therefore, in the light of the current uncertainties and the unpredictable nature of some of the forcing processes for LSL changes, the focus of scientific decision support may have to shift from projections of LSL trajectories on century time scales to the development of models and monitoring systems for a forecasting service on decadal time scales. The requirements for such a LSL forecasting service and the current obstacles will be discussed.

A new framework for modeling decisions about changing information: The Piecewise Linear Ballistic Accumulator model

PubMed Central

Heathcote, Andrew

2016-01-01

In the real world, decision making processes must be able to integrate non-stationary information that changes systematically while the decision is in progress. Although theories of decision making have traditionally been applied to paradigms with stationary information, non-stationary stimuli are now of increasing theoretical interest. We use a random-dot motion paradigm along with cognitive modeling to investigate how the decision process is updated when a stimulus changes. Participants viewed a cloud of moving dots, where the motion switched directions midway through some trials, and were asked to determine the direction of motion. Behavioral results revealed a strong delay effect: after presentation of the initial motion direction there is a substantial time delay before the changed motion information is integrated into the decision process. To further investigate the underlying changes in the decision process, we developed a Piecewise Linear Ballistic Accumulator model (PLBA). The PLBA is efficient to simulate, enabling it to be fit to participant choice and response-time distribution data in a hierarchal modeling framework using a non-parametric approximate Bayesian algorithm. Consistent with behavioral results, PLBA fits confirmed the presence of a long delay between presentation and integration of new stimulus information, but did not support increased response caution in reaction to the change. We also found the decision process was not veridical, as symmetric stimulus change had an asymmetric effect on the rate of evidence accumulation. Thus, the perceptual decision process was slow to react to, and underestimated, new contrary motion information. PMID:26760448

Investigation and design of a Project Management Decision Support System for the 4950th Test Wing.

DTIC Science & Technology

1986-03-01

all decision makers is the need for memory aids (reports, hand written notes, mental memory joggers, etc.). 4. Even in similar decision making ... memories to synthesize a decision- making process based on their individual styles, skills, and knowledge (Sprague, 1982: 106). Control mechanisms...representations shown in Figures 4.9 and 4.10 provide a means to this objective. By enabling a manager to make and record reasonable changes to

Strategic control in decision-making under uncertainty.

PubMed

Venkatraman, Vinod; Huettel, Scott A

2012-04-01

Complex economic decisions - whether investing money for retirement or purchasing some new electronic gadget - often involve uncertainty about the likely consequences of our choices. Critical for resolving that uncertainty are strategic meta-decision processes, which allow people to simplify complex decision problems, evaluate outcomes against a variety of contexts, and flexibly match behavior to changes in the environment. In recent years, substantial research has implicated the dorsomedial prefrontal cortex (dmPFC) in the flexible control of behavior. However, nearly all such evidence comes from paradigms involving executive function or response selection, not complex decision-making. Here, we review evidence that demonstrates that the dmPFC contributes to strategic control in complex decision-making. This region contains a functional topography such that the posterior dmPFC supports response-related control, whereas the anterior dmPFC supports strategic control. Activation in the anterior dmPFC signals changes in how a decision problem is represented, which in turn can shape computational processes elsewhere in the brain. Based on these findings, we argue for both generalized contributions of the dmPFC to cognitive control, and specific computational roles for its subregions depending upon the task demands and context. We also contend that these strategic considerations are likely to be critical for decision-making in other domains, including interpersonal interactions in social settings. © 2012 The Authors. European Journal of Neuroscience © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

Strategic Control in Decision Making under Uncertainty

PubMed Central

Venkatraman, Vinod; Huettel, Scott

2012-01-01

Complex economic decisions – whether investing money for retirement or purchasing some new electronic gadget – often involve uncertainty about the likely consequences of our choices. Critical for resolving that uncertainty are strategic meta-decision processes, which allow people to simplify complex decision problems, to evaluate outcomes against a variety of contexts, and to flexibly match behavior to changes in the environment. In recent years, substantial research implicates the dorsomedial prefrontal cortex (dmPFC) in the flexible control of behavior. However, nearly all such evidence comes from paradigms involving executive function or response selection, not complex decision making. Here, we review evidence that demonstrates that the dmPFC contributes to strategic control in complex decision making. This region contains a functional topography such that the posterior dmPFC supports response-related control while the anterior dmPFC supports strategic control. Activation in the anterior dmPFC signals changes in how a decision problem is represented, which in turn can shape computational processes elsewhere in the brain. Based on these findings, we argue both for generalized contributions of the dmPFC to cognitive control, and for specific computational roles for its subregions depending upon the task demands and context. We also contend that these strategic considerations are also likely to be critical for decision making in other domains, including interpersonal interactions in social settings. PMID:22487037

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.

A Qualitative Study of How Health Coaches Support Patients in Making Health-Related Decisions and Behavioral Changes

PubMed Central

Thom, David H.; Wolf, Jessica; Gardner, Heather; DeVore, Denise; Lin, Michael; Ma, Andy; Ibarra-Castro, Ana; Saba, George

2016-01-01

PURPOSE Although health coaches are a growing resource for supporting patients in making health decisions, we know very little about the experience of health. We undertook a qualitative study of how health coaches support patients in making decisions and implementing changes to improve their health. METHODS We conducted 6 focus groups (3 in Spanish and 3 in English) with 25 patients and 5 friends or family members, followed by individual interviews with 42 patients, 17 family members, 17 health coaches, and 20 clinicians. Audio recordings were transcribed and analyzed by at least 2 members of the study team in ATLAS.ti using principles of grounded theory to identify themes and the relationship between them. RESULTS We identified 7 major themes that were related to each other in the final conceptual model. Similarities between health coaches and patients and the time health coaches spent with patients helped establish the health coach–patient relationship. The coach-patient relationship allowed for, and was further strengthened by, 4 themes of key coaching activities: education, personal support, practical support, and acting as a bridge between patients and clinicians. CONCLUSIONS We identified a conceptual model that supports the development of a strong relationship, which in turn provides the basis for effective coaching. These results can be used to design health coach training curricula and to support health coaches in practice. PMID:28376437

Practical Considerations in Creating School-Wide Positive Behavior Support in Public Schools

ERIC Educational Resources Information Center

Handler, Marcie W.; Rey, Jannette; Connell, James; Thier, Kimberly; Feinberg, Adam; Putnam, Robert

2007-01-01

School-wide positive behavior support (SWPBS) has been identified as an effective and efficient method to teach students prosocial skills. It requires both effective behavior support practices and systems that will support these changes, including data-based decision making among the school leadership team. There are many practical and systemic…

Adaptive decision processes in perceptual comparisons: effects of changes in the global difficulty context.

PubMed

Baranski, Joseph V; Petrusic, William M

2003-06-01

Adaptive decision processes were investigated in experiments involving an unexpected change in the global ease or difficulty of the task. Under accuracy stress, a shift from an easy to a difficult context induced a marked increase in decision time, but a shift from a difficult to an easy context did not. Under speed stress, a shift to a more difficult context induced lower accuracy and rated confidence, depending on the difficulty of the decisions. A view of caution developed in D. Vickers's (1979) accumulator theory--whereby one seeks to base decisions on more information--is compared with a view based on slow and fast guessing theory (W. M. Petrusic, 1992; W. M. Petrusic & J. V. Baranski, 1989a)--whereby one seeks to base decisions on more diagnostic information. On balance, the findings support the latter view.

A decision support system for drinking water production integrating health risks assessment.

PubMed

Delpla, Ianis; Monteith, Donald T; Freeman, Chris; Haftka, Joris; Hermens, Joop; Jones, Timothy G; Baurès, Estelle; Jung, Aude-Valérie; Thomas, Olivier

2014-07-18

The issue of drinking water quality compliance in small and medium scale water services is of paramount importance in relation to the 98/83/CE European Drinking Water Directive (DWD). Additionally, concerns are being expressed over the implementation of the DWD with respect to possible impacts on water quality from forecast changes in European climate with global warming and further anticipated reductions in north European acid emissions. Consequently, we have developed a decision support system (DSS) named ARTEM-WQ (AwaReness Tool for the Evaluation and Mitigation of drinking Water Quality issues resulting from environmental changes) to support decision making by small and medium plant operators and other water stakeholders. ARTEM-WQ is based on a sequential risk analysis approach that includes consideration of catchment characteristics, climatic conditions and treatment operations. It provides a holistic evaluation of the water system, while also assessing human health risks of organic contaminants potentially present in treated waters (steroids, pharmaceuticals, pesticides, bisphenol-a, polychlorobiphenyls, polycyclic aromatic hydrocarbons, petrochemical hydrocarbons and disinfection by-products; n = 109). Moreover, the system provides recommendations for improvement while supporting decision making in its widest context. The tool has been tested on various European catchments and shows a promising potential to inform water managers of risks and appropriate mitigative actions. Further improvements should include toxicological knowledge advancement, environmental background pollutant concentrations and the assessment of the impact of distribution systems on water quality variation.

Science and Systems in Support of Multi-hazard Early Warnings and Decisions

NASA Astrophysics Data System (ADS)

Pulwarty, R. S.

2015-12-01

The demand for improved climate knowledge and information is well documented. As noted in the IPCC (SREX, AR5), the UNISDR Global Assessment Reports and other assessments, this demand has increased pressure for information to support planning under changing rates and emergence of multiple hazards including climate extremes (drought, heat waves, floods). "Decision support" is now a popular term in the climate applications research community. While existing decision support activities can be identified in many disparate settings (e.g. federal, academic, private), the challenge of changing environments (coupled physical and social) is actually one of crafting implementation strategies for improving decision quality (not just meeting "user needs"). This includes overcoming weaknesses in co-production models, moving beyond DSSs as simply "software", coordinating innovation mapping and diffusion, and providing fora and gaming tools to identify common interests and differences in the way risks are perceived and managed among the affected groups. We outline the development and evolution of multi-hazard early warning systems in the United States and elsewhere, focusing on climate-related hazards. In particular, the presentation will focus on the climate science and information needed for (1) improved monitoring and modeling, (2) generating risk profiles, (3) developing information systems and scenarios for critical thresholds, (4) the net benefits of using new information (5) characterizing and bridging the "last mile" in the context of longer-term risk management.

Invited review: Helping dairy farmers to improve economic performance utilizing data-driving decision support tools.

PubMed

Cabrera, V E

2018-01-01

The objective of this review paper is to describe the development and application of a suite of more than 40 computerized dairy farm decision support tools contained at the University of Wisconsin-Madison (UW) Dairy Management website http://DairyMGT.info. These data-driven decision support tools are aimed to help dairy farmers improve their decision-making, environmental stewardship and economic performance. Dairy farm systems are highly dynamic in which changing market conditions and prices, evolving policies and environmental restrictions together with every time more variable climate conditions determine performance. Dairy farm systems are also highly integrated with heavily interrelated components such as the dairy herd, soils, crops, weather and management. Under these premises, it is critical to evaluate a dairy farm following a dynamic integrated system approach. For this approach, it is crucial to use meaningful data records, which are every time more available. These data records should be used within decision support tools for optimal decision-making and economic performance. Decision support tools in the UW-Dairy Management website (http://DairyMGT.info) had been developed using combination and adaptation of multiple methods together with empirical techniques always with the primary goal for these tools to be: (1) highly user-friendly, (2) using the latest software and computer technologies, (3) farm and user specific, (4) grounded on the best scientific information available, (5) remaining relevant throughout time and (6) providing fast, concrete and simple answers to complex farmers' questions. DairyMGT.info is a translational innovative research website in various areas of dairy farm management that include nutrition, reproduction, calf and heifer management, replacement, price risk and environment. This paper discusses the development and application of 20 selected (http://DairyMGT.info) decision support tools.

Decision making in the ageing brain: changes in affective and motivational circuits.

PubMed

Samanez-Larkin, Gregory R; Knutson, Brian

2015-05-01

As the global population ages, older decision makers will be required to take greater responsibility for their own physical, psychological and financial well-being. With this in mind, researchers have begun to examine the effects of ageing on decision making and associated neural circuits. A new 'affect-integration-motivation' (AIM) framework may help to clarify how affective and motivational circuits support decision making. Recent research has shed light on whether and how ageing influences these circuits, providing an interdisciplinary account of how ageing can alter decision making.

Decision making in the ageing brain: Changes in affective and motivational circuits

PubMed Central

Samanez-Larkin, Gregory R.; Knutson, Brian

2017-01-01

As the global population ages, older decision makers will be required to take greater responsibility for their own physical, psychological and financial well-being. With this in mind, researchers have begun to examine the effects of ageing on decision making and associated neural circuits. A new “affect, integration, motivation” (or AIM) framework may help clarify how affective and motivational circuits support decision making. Recent research has shed light on whether and how ageing influences these circuits, providing an interdisciplinary account of how ageing can alter decision making. PMID:25873038

Evaluating child welfare policies with decision-analytic simulation models.

PubMed

Goldhaber-Fiebert, Jeremy D; Bailey, Stephanie L; Hurlburt, Michael S; Zhang, Jinjin; Snowden, Lonnie R; Wulczyn, Fred; Landsverk, John; Horwitz, Sarah M

2012-11-01

The objective was to demonstrate decision-analytic modeling in support of Child Welfare policymakers considering implementing evidence-based interventions. Outcomes included permanency (e.g., adoptions) and stability (e.g., foster placement changes). Analyses of a randomized trial of KEEP-a foster parenting intervention-and NSCAW-1 estimated placement change rates and KEEP's effects. A microsimulation model generalized these findings to other Child Welfare systems. The model projected that KEEP could increase permanency and stability, identifying strategies targeting higher-risk children and geographical regions that achieve benefits efficiently. Decision-analytic models enable planners to gauge the value of potential implementations.

Orbital frontal cortex updates state-induced value change for decision-making.

PubMed

Baltz, Emily T; Yalcinbas, Ege A; Renteria, Rafael; Gremel, Christina M

2018-06-13

Recent hypotheses have posited that orbital frontal cortex (OFC) is important for using inferred consequences to guide behavior. Less clear is OFC's contribution to goal-directed or model-based behavior, where the decision to act is controlled by previous experience with the consequence or outcome. Investigating OFC's role in learning about changed outcomes separate from decision-making is not trivial and often the two are confounded. Here we adapted an incentive learning task to mice, where we investigated processes controlling experience-based outcome updating independent from inferred action control. We found chemogenetic OFC attenuation did not alter the ability to perceive motivational state-induced changes in outcome value but did prevent the experience-based updating of this change. Optogenetic inhibition of OFC excitatory neuron activity selectively when experiencing an outcome change disrupted the ability to update, leaving mice unable to infer the appropriate behavior. Our findings support a role for OFC in learning that controls decision-making. © 2018, Baltz et al.

Managing the Risks of Climate Change and Terrorism

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

Rosa, Eugene; Dietz, Tom; Moss, Richard H.

2012-04-07

Society has difficult decisions to make about how best to allocate its resources to ensure future sustainability. Risk assessment can be a valuable tool: it has long been used to support decisions to address environmental problems. But in a time when the risks to sustainability range from climate change to terrorism, applying risk assessment to sustainability will require careful rethinking. For new threats, we will need a new approach to risk assessment.

Planning for regime change and its aftermath

DTIC Science & Technology

2017-06-09

countries’ governing regimes since 9/11–Afghanistan, Iraq, and Libya–and U.S. policy at time of writing supports two more. Despite this experience...Iraq, and Libya–and U.S. policy at time of writing supports two more. Despite this experience, and the likely future need, the U.S. has no...time of writing , U.S. policy publicly supports regime change in Syria and North Korea. President Obama’s decision not to militarily intervene to

EVALUATING HYDROLOGICAL RESPONSE TO FORECASTED LAND-USE CHANGE: SCENARIO TESTING IN TWO WESTERN U.S. WATERSHEDS

EPA Science Inventory

Envisioning and evaluating future scenarios has emerged as a critical component of both science and social decision-making. The ability to assess, report, map, and forecast the life support functions of ecosystems is absolutely critical to our capacity to make informed decisions ...

Using multiobjective tradeoff sets and Multivariate Regression Trees to identify critical and robust decisions for long term water utility planning

NASA Astrophysics Data System (ADS)

Smith, R.; Kasprzyk, J. R.; Balaji, R.

2017-12-01

In light of deeply uncertain factors like future climate change and population shifts, responsible resource management will require new types of information and strategies. For water utilities, this entails potential expansion and efficient management of water supply infrastructure systems for changes in overall supply; changes in frequency and severity of climate extremes such as droughts and floods; and variable demands, all while accounting for conflicting long and short term performance objectives. Multiobjective Evolutionary Algorithms (MOEAs) are emerging decision support tools that have been used by researchers and, more recently, water utilities to efficiently generate and evaluate thousands of planning portfolios. The tradeoffs between conflicting objectives are explored in an automated way to produce (often large) suites of portfolios that strike different balances of performance. Once generated, the sets of optimized portfolios are used to support relatively subjective assertions of priorities and human reasoning, leading to adoption of a plan. These large tradeoff sets contain information about complex relationships between decisions and between groups of decisions and performance that, until now, has not been quantitatively described. We present a novel use of Multivariate Regression Trees (MRTs) to analyze tradeoff sets to reveal these relationships and critical decisions. Additionally, when MRTs are applied to tradeoff sets developed for different realizations of an uncertain future, they can identify decisions that are robust across a wide range of conditions and produce fundamental insights about the system being optimized.

Integrated Decision Support for Global Environmental Change Adaptation

NASA Astrophysics Data System (ADS)

Kumar, S.; Cantrell, S.; Higgins, G. J.; Marshall, J.; VanWijngaarden, F.

2011-12-01

Environmental changes are happening now that has caused concern in many parts of the world; particularly vulnerable are the countries and communities with limited resources and with natural environments that are more susceptible to climate change impacts. Global leaders are concerned about the observed phenomena and events such as Amazon deforestation, shifting monsoon patterns affecting agriculture in the mountain slopes of Peru, floods in Pakistan, water shortages in Middle East, droughts impacting water supplies and wildlife migration in Africa, and sea level rise impacts on low lying coastal communities in Bangladesh. These environmental changes are likely to get exacerbated as the temperatures rise, the weather and climate patterns change, and sea level rise continues. Large populations and billions of dollars of infrastructure could be affected. At Northrop Grumman, we have developed an integrated decision support framework for providing necessary information to stakeholders and planners to adapt to the impacts of climate variability and change at the regional and local levels. This integrated approach takes into account assimilation and exploitation of large and disparate weather and climate data sets, regional downscaling (dynamic and statistical), uncertainty quantification and reduction, and a synthesis of scientific data with demographic and economic data to generate actionable information for the stakeholders and decision makers. Utilizing a flexible service oriented architecture and state-of-the-art visualization techniques, this information can be delivered via tailored GIS portals to meet diverse set of user needs and expectations. This integrated approach can be applied to regional and local risk assessments, predictions and decadal projections, and proactive adaptation planning for vulnerable communities. In this paper we will describe this comprehensive decision support approach with selected applications and case studies to illustrate how this system of systems approach could help the local governments and concerned institutions worldwide to adapt to gradually changing environmental conditions as well as manage impacts of extreme events such as droughts, floods, heat waves, wildfires, hurricanes, and storm surges.

Using mobile health technology to deliver decision support for self-monitoring after lung transplantation.

PubMed

Jiang, Yun; Sereika, Susan M; DeVito Dabbs, Annette; Handler, Steven M; Schlenk, Elizabeth A

2016-10-01

Lung transplant recipients (LTR) experience problems recognizing and reporting critical condition changes during their daily health self-monitoring. Pocket PATH(®), a mobile health application, was designed to provide automatic feedback messages to LTR to guide decisions for detecting and reporting critical values of health indicators. To examine the degree to which LTR followed decision support messages to report recorded critical values, and to explore predictors of appropriately following technology decision support by reporting critical values during the first year after transplantation. A cross-sectional correlational study was conducted to analyze existing data from 96 LTR who used the Pocket PATH for daily health self-monitoring. When a critical value is entered, the device automatically generated a feedback message to guide LTR about when and what to report to their transplant coordinators. Their socio-demographics and clinical characteristics were obtained before discharge. Their use of Pocket PATH for health self-monitoring during 12 months was categorized as low (≤25% of days), moderate (>25% to ≤75% of days), and high (>75% of days) use. Following technology decision support was defined by the total number of critical feedback messages appropriately handled divided by the total number of critical feedback messages generated. This variable was dichotomized by whether or not all (100%) feedback messages were appropriately followed. Binary logistic regression was used to explore predictors of appropriately following decision support. Of the 96 participants, 53 had at least 1 critical feedback message generated during 12 months. Of these 53 participants, the average message response rate was 90% and 33 (62%) followed 100% decision support. LTR who moderately used Pocket PATH (n=23) were less likely to follow technology decision support than the high (odds ratio [OR]=0.11, p=0.02) and low (OR=0.04, p=0.02) use groups. The odds of following decision support were reduced in LTR whose income met basic needs (OR=0.01, p=0.01) or who had longer hospital stays (OR=0.94, p=0.004). A significant interaction was found between gender and past technology experience (OR=0.21, p=0.03), suggesting that with increased past technology experience, the odds of following decision support to report all critical values decreased in men but increased in women. The majority of LTR responded appropriately to mobile technology-based decision support for reporting recorded critical values. Appropriately following technology decision support was associated with gender, income, experience with technology, length of hospital stay, and frequency of use of technology for self-monitoring. Clinicians should monitor LTR, who are at risk for poor reporting of recorded critical values, more vigilantly even when LTR are provided with mobile technology decision support. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Complex Decision-Making in Heart Failure: A Systematic Review and Thematic Analysis.

PubMed

Hamel, Aimee V; Gaugler, Joseph E; Porta, Carolyn M; Hadidi, Niloufar Niakosari

Heart failure follows a highly variable and difficult course. Patients face complex decisions, including treatment with implantable cardiac defibrillators, mechanical circulatory support, and heart transplantation. The course of decision-making across multiple treatments is unclear yet integral to providing informed and shared decision-making. Recognizing commonalities across treatment decisions could help nurses and physicians to identify opportunities to introduce discussions and support shared decision-making. The specific aims of this review are to examine complex treatment decision-making, specifically implantable cardiac defibrillators, ventricular assist device, and cardiac transplantation, and to recognize commonalities and key points in the decisional process. MEDLINE, CINAHL, PsycINFO, and Web of Science were searched for English-language studies that included qualitative findings reflecting the complexity of heart failure decision-making. Using a 3-step process, findings were synthesized into themes and subthemes. Twelve articles met criteria for inclusion. Participants included patients, caregivers, and clinicians and included decisions to undergo and decline treatment. Emergent themes were "processing the decision," "timing and prognostication," and "considering the future." Subthemes described how participants received and understood information about the therapy, making and changing a treatment decision, timing their decision and gauging health status outcomes in the context of their decision, the influence of a life or death decision, and the future as a factor in their decisional process. Commonalities were present across therapies, which involved the timing of discussions, the delivery of information, and considerations of the future. Exploring this further could help support patient-centered care and optimize shared decision-making interventions.

Harnessing ecosystem models and multi-criteria decision analysis for the support of forest management.

PubMed

Wolfslehner, Bernhard; Seidl, Rupert

2010-12-01

The decision-making environment in forest management (FM) has changed drastically during the last decades. Forest management planning is facing increasing complexity due to a widening portfolio of forest goods and services, a societal demand for a rational, transparent decision process and rising uncertainties concerning future environmental conditions (e.g., climate change). Methodological responses to these challenges include an intensified use of ecosystem models to provide an enriched, quantitative information base for FM planning. Furthermore, multi-criteria methods are increasingly used to amalgamate information, preferences, expert judgments and value expressions, in support of the participatory and communicative dimensions of modern forestry. Although the potential of combining these two approaches has been demonstrated in a number of studies, methodological aspects in interfacing forest ecosystem models (FEM) and multi-criteria decision analysis (MCDA) are scarcely addressed explicitly. In this contribution we review the state of the art in FEM and MCDA in the context of FM planning and highlight some of the crucial issues when combining ecosystem and preference modeling. We discuss issues and requirements in selecting approaches suitable for supporting FM planning problems from the growing body of FEM and MCDA concepts. We furthermore identify two major challenges in a harmonized application of FEM-MCDA: (i) the design and implementation of an indicator-based analysis framework capturing ecological and social aspects and their interactions relevant for the decision process, and (ii) holistic information management that supports consistent use of different information sources, provides meta-information as well as information on uncertainties throughout the planning process.

Harnessing Ecosystem Models and Multi-Criteria Decision Analysis for the Support of Forest Management

NASA Astrophysics Data System (ADS)

Wolfslehner, Bernhard; Seidl, Rupert

2010-12-01

The decision-making environment in forest management (FM) has changed drastically during the last decades. Forest management planning is facing increasing complexity due to a widening portfolio of forest goods and services, a societal demand for a rational, transparent decision process and rising uncertainties concerning future environmental conditions (e.g., climate change). Methodological responses to these challenges include an intensified use of ecosystem models to provide an enriched, quantitative information base for FM planning. Furthermore, multi-criteria methods are increasingly used to amalgamate information, preferences, expert judgments and value expressions, in support of the participatory and communicative dimensions of modern forestry. Although the potential of combining these two approaches has been demonstrated in a number of studies, methodological aspects in interfacing forest ecosystem models (FEM) and multi-criteria decision analysis (MCDA) are scarcely addressed explicitly. In this contribution we review the state of the art in FEM and MCDA in the context of FM planning and highlight some of the crucial issues when combining ecosystem and preference modeling. We discuss issues and requirements in selecting approaches suitable for supporting FM planning problems from the growing body of FEM and MCDA concepts. We furthermore identify two major challenges in a harmonized application of FEM-MCDA: (i) the design and implementation of an indicator-based analysis framework capturing ecological and social aspects and their interactions relevant for the decision process, and (ii) holistic information management that supports consistent use of different information sources, provides meta-information as well as information on uncertainties throughout the planning process.

Adapting agriculture to climate change in Kenya: household strategies and determinants.

PubMed

Bryan, Elizabeth; Ringler, Claudia; Okoba, Barrack; Roncoli, Carla; Silvestri, Silvia; Herrero, Mario

2013-01-15

Countries in Sub-Saharan Africa are particularly vulnerable to climate change, given dependence on agricultural production and limited adaptive capacity. Based on farm household and Participatory Rural Appraisal data collected from districts in various agroecological zones in Kenya, this paper examines farmers' perceptions of climate change, ongoing adaptation measures, and factors influencing farmers' decisions to adapt. The results show that households face considerable challenges in adapting to climate change. While many households have made small adjustments to their farming practices in response to climate change (in particular, changing planting decisions), few households are able to make more costly investments, for example in agroforestry or irrigation, although there is a desire to invest in such measures. This emphasizes the need for greater investments in rural and agricultural development to support the ability of households to make strategic, long-term decisions that affect their future well-being. Copyright © 2012 Elsevier Ltd. All rights reserved.

Multi-Criteria Decision Making for a Spatial Decision Support System on the Analysis of Changing Risk

NASA Astrophysics Data System (ADS)

Olyazadeh, Roya; van Westen, Cees; Bakker, Wim H.; Aye, Zar Chi; Jaboyedoff, Michel; Derron, Marc-Henri

2014-05-01

Natural hazard risk management requires decision making in several stages. Decision making on alternatives for risk reduction planning starts with an intelligence phase for recognition of the decision problems and identifying the objectives. Development of the alternatives and assigning the variable by decision makers to each alternative are employed to the design phase. Final phase evaluates the optimal choice by comparing the alternatives, defining indicators, assigning a weight to each and ranking them. This process is referred to as Multi-Criteria Decision Making analysis (MCDM), Multi-Criteria Evaluation (MCE) or Multi-Criteria Analysis (MCA). In the framework of the ongoing 7th Framework Program "CHANGES" (2011-2014, Grant Agreement No. 263953) of the European Commission, a Spatial Decision Support System is under development, that has the aim to analyse changes in hydro-meteorological risk and provide support to selecting the best risk reduction alternative. This paper describes the module for Multi-Criteria Decision Making analysis (MCDM) that incorporates monetary and non-monetary criteria in the analysis of the optimal alternative. The MCDM module consists of several components. The first step is to define criteria (or Indicators) which are subdivided into disadvantages (criteria that indicate the difficulty for implementing the risk reduction strategy, also referred to as Costs) and advantages (criteria that indicate the favorability, also referred to as benefits). In the next step the stakeholders can use the developed web-based tool for prioritizing criteria and decision matrix. Public participation plays a role in decision making and this is also planned through the use of a mobile web-version where the general local public can indicate their agreement on the proposed alternatives. The application is being tested through a case study related to risk reduction of a mountainous valley in the Alps affected by flooding. Four alternatives are evaluated in this case study namely: construction of defense structures, relocation, implementation of an early warning system and spatial planning regulations. Some of the criteria are determined partly in other modules of the CHANGES SDSS, such as the costs for implementation, the risk reduction in monetary values, and societal risk. Other criteria, which could be environmental, economic, cultural, perception in nature, are defined by different stakeholders such as local authorities, expert organizations, private sector, and local public. In the next step, the stakeholders weight the importance of the criteria by pairwise comparison and visualize the decision matrix, which is a matrix based on criteria versus alternatives values. Finally alternatives are ranked by Analytic Hierarchy Process (AHP) method. We expect that this approach will help the decision makers to ease their works and reduce their costs, because the process is more transparent, more accurate and involves a group decision. In that way there will be more confidence in the overall decision making process. Keywords: MCDM, Analytic Hierarchy Process (AHP), SDSS, Natural Hazard Risk Management

Enabling Responsible Energy Decisions: What People Know, Want to Know, and Need to Know about Climate Change

NASA Astrophysics Data System (ADS)

PytlikZillig, L. M.; Tomkins, A. J.; Harrington, J. A.

2012-12-01

As part of a broader regional effort focused on climate change education and rural communities, this paper focuses on a specific effort to understand effective approaches to two presumably complementary goals: The goal of increasing knowledge about climate change and climate science in a community, and the goal of having communities use climate change and climate science information when making decisions. In this paper, we explore the argument that people do not need or want to know about climate change, in order to make responsible and sustainable energy decisions. Furthermore, we hypothesize that involvement in making responsible and sustainable energy decisions will increase openness and readiness to process climate science information, and thus increase learning about climate change in subsequent exposures to such information. Support for these hypotheses would suggest that rather than encouraging education to enable action (including engagement in attempts to make responsible decisions), efforts should focus on encouraging actions first and education second. To investigate our hypotheses, we will analyze and report results from efforts to engage residents from a medium-sized Midwestern city to give input on future programs involving sustainable energy use. The engagement process (which will not be complete until after the AGU deadline) involves an online survey and an optional face-to-face discussion with city officials and experts in energy-related areas. The online survey includes brief information about current local energy programs, questions assessing knowledge of climate change, and an open-ended question asking what additional information residents need in order to make good decisions and recommendations concerning the energy programs. To examine support for our hypotheses, we will report (1) relationships between subjective and objective knowledge of climate science and willingness to attend the face-to-face discussion about the city's energy decisions and actual attendance at the event, (2) a content analysis of what residents say they want and need to know in order to make decisions and recommendations about the city's energy programs, and (3) pilot results from a comparison of learning from a reading about climate change presented prior to the event, after the event, or presented to those who were willing to attend the face-to-face event but did not attend. We will discuss the results in terms of their implications for the relationship between knowledge and behavior, versus change in knowledge and change in behavior.

Opportunities and Examples for Integration of Socio-environmental Approaches to Support Climate-informed Decisions

NASA Astrophysics Data System (ADS)

Kenney, M. A.

2014-12-01

Climate and environmental decisions require science that couples human and natural systems to quantify or articulate the observed physical, natural, and societal changes or likely consequences of different decision options. Despite the need for such policy-relevant research, multidisciplinary collaborations can be wrought with challenges of data integration, model interoperability, and communication across disciplinary divides. In this talk, I will present several examples where I have collaborated with colleagues from the physical, natural, and social sciences to develop novel, actionable science to inform decision-making. Specifically, I will discuss a cost analysis of water and sediment diversions to optimize land building in the Mississippi River delta (winner of American Geophysical Union Water Resources Research Editor's Choice Award 2014) and the development of a National Climate Indicator System that uses knowledge across the physical, natural, and social sciences to establish an end-to-end indicator system of climate changes, impacts, vulnerabilities, and responses. The latter project is in the process of moving from research to operations, an additional challenge and opportunity, as we work with the U.S. Global Change Research Program and their affiliated Federal agencies to establish it beyond the research prototype. Using these examples, I will provide some lessons learned that would have general applicability to socio-environmental research collaborations and integration of data, models, and information systems to support climate and environmental decision-making.

A common mechanism underlies changes of mind about decisions and confidence.

PubMed

van den Berg, Ronald; Anandalingam, Kavitha; Zylberberg, Ariel; Kiani, Roozbeh; Shadlen, Michael N; Wolpert, Daniel M

2016-02-01

Decisions are accompanied by a degree of confidence that a selected option is correct. A sequential sampling framework explains the speed and accuracy of decisions and extends naturally to the confidence that the decision rendered is likely to be correct. However, discrepancies between confidence and accuracy suggest that confidence might be supported by mechanisms dissociated from the decision process. Here we show that this discrepancy can arise naturally because of simple processing delays. When participants were asked to report choice and confidence simultaneously, their confidence, reaction time and a perceptual decision about motion were explained by bounded evidence accumulation. However, we also observed revisions of the initial choice and/or confidence. These changes of mind were explained by a continuation of the mechanism that led to the initial choice. Our findings extend the sequential sampling framework to vacillation about confidence and invites caution in interpreting dissociations between confidence and accuracy.

CIRUN: Climate Information Responding to User Needs

NASA Astrophysics Data System (ADS)

Busalacchi, A. J.

2009-12-01

The Earth System will experience real climate change over the next 50 years, exceeding the scope of natural climate variability. A paramount question facing society is how to adapt to this certainty of climate variability and change. In response, OSTP and NOAA are considering how comprehensive climate services would best inform decisions about adaptation. Similarly, NASA is considering the optimal configuration of the next generation of Earth, environmental, and climate observations to be deployed over the coming 10-20 years. Moreover, much of the added-value information for specific climate-related decisions will be provided by private, academic and non-governmental organizations. In this context, over the past several years the University of Maryland has established the CIRUN (Climate Information: Responding to User Needs) initiative to identify the nature of national needs for climate information and services from a decision support perspective. To date, CIRUN has brought together decisionmakers in a number of sectors to help understand their perspectives on climate with the goal of improving the usefulness of climate information, observations and prediction products to specific user communities. CIRUN began with a major workshop in October 2007 that convened 430 participants in agriculture, parks and recreation, terrestrial ecosystems, insurance/investment, energy, national security, state/local/municipal, water, human health, commerce and manufacturing, transportation, and coastal/marine sectors. Plenary speakers such as Norman Augustine, R. James Woolsey, James Mahoney, and former Senator Joseph Tydings, breakout panel sessions, and participants provided input based on the following: - How would you characterize the exposure or vulnerability to climate variability or change impacting your organization? - Does climate variability and/or change currently factor into your organization's objectives or operations? - Are any of your existing plans being affected by climate or projections of climate change? - Is your organization developing a plan for adapting to climate change? - What are your needs for climate observations, predictions, and services? Please cite one or more specific examples when possible. - Do you currently have access to the climate information your organization needs? - What next steps are needed to assure effective use of climate services in your decision making? As a result, a dialogue with various user communities and a subsequent series of more sector specific workshops has been established regarding how significantly enhanced climate observations, data management, modeling, and predictions can provide valuable decision support for business and policy decisions. In particular, CIRUN has helped - To identify how users, stakeholders, and decision makers are influenced by climate on time scales from seasons to decades - To identify the needs and requirements of users, stakeholders, and decision makers for climate information, observations, predictions, and services from global to local scales - To identify what adaptation measures are being considered in the private and public sectors, and how this might result in new classes of information for decision support - To recommend principal elements of the path forward toward more effective use of climate services in decision making.

Developing rural community health risk assessments for climate change: a Tasmanian pilot study.

PubMed

Bell, Erica J; Turner, Paul; Meinke, Holger; Holbrook, Neil J

2015-01-01

This article examines the development and pilot implementation of an approach to support local community decision-makers to plan health adaptation responses to climate change. The approach involves health and wellbeing risk assessment supported through the use of an electronic tool. While climate change is a major foreseeable public health threat, the extent to which health services are prepared for, or able to adequately respond to, climate change impact-related risks remains unclear. Building health decision-support mechanisms in order to involve and empower local stakeholders to help create the basis for agreement on these adaptive actions is an important first step. The primary research question was 'What can be learned from pilot implementation of a community health and well-being risk assessment (CHWRA) information technology-based tool designed to support understanding of, and decision-making on, local community challenges and opportunities associated with health risks posed by climate change? The article examines the complexity of climate change science to adaptation translational processes, with reference to existing research literature on community development. This is done in the context of addressing human health risks for rural and remote communities in Tasmania, Australia. This process is further examined through the pilot implementation of an electronic tool designed to support the translation of physically based climate change impact information into community-level assessments of health risks and adaptation priorities. The procedural and technical nature of the CHWRA tool is described, and the implications of the data gathered from stakeholder workshops held at three rural Tasmanian local government sites are considered and discussed. Bushfire, depression and waterborne diseases were identified by community stakeholders as being potentially 'catastrophic' health effects 'likely' to 'almost certain' to occur at one or more Tasmanian rural sites - based on an Intergovernmental Panel on Climate Change style of assessment. Consensus statements from stakeholders also suggested concern with health sector adaptation capacity and community resilience, and what community stakeholders defined as 'last straw' climate effects in already stressed communities. Preventative action and community engagement were also seen as important, especially with regard to managing the ways that climate change can multiply socioeconomic and health outcome inequality. Above all, stakeholder responses emphasised the importance of an applied, complexity-oriented understanding of how climate and climate change impacts affect local communities and local services to compromise the overall quality of human health in these communities. Complex community-level assessments about climate change and related health risks and responses can be captured electronically in ways that offer potentially actionable information about priorities for health sector adaptation, as a first step in planning. What is valuable about these community judgements is the creation of shared values and commitments. Future iteration of the IT tool could include decision-support modules to support best practice health sector adaptation scenarios, providing participants with opportunities to develop their know-how about health sector adaptation to climate change. If managed carefully, such tools could work within a balanced portfolio of measures to help reduce the rising health burden from climate change.

The neural correlates of risky decision making across short and long runs

PubMed Central

Rao, Li-Lin; Dunn, John C.; Zhou, Yuan; Li, Shu

2015-01-01

People frequently change their preferences for options of gambles which they play once compared to those they play multiple times. In general, preferences for repeated play gambles are more consistent with the expected values of the options. According to the one-process view, the change in preference is due to a change in the structure of the gamble that is relevant to decision making. According to the two-process view, the change is attributable to a shift in the decision making strategy that is used. To adjudicate between these two theories, we asked participants to choose between gambles played once or 100 times, and to choose between them based on their expected value. Consistent with the two-process theory, we found a set of brain regions that were sensitive to the extent of behavioral change between single and aggregated play and also showed significant (de)activation in the expected value choice task. These results support the view that people change their decision making strategies for risky choice considered once or multiple times. PMID:26516095

Preference, resistance to change, and the cumulative decision model.

PubMed

Grace, Randolph C

2018-01-01

According to behavioral momentum theory (Nevin & Grace, 2000a), preference in concurrent chains and resistance to change in multiple schedules are independent measures of a common construct representing reinforcement history. Here I review the original studies on preference and resistance to change in which reinforcement variables were manipulated parametrically, conducted by Nevin, Grace and colleagues between 1997 and 2002, as well as more recent research. The cumulative decision model proposed by Grace and colleagues for concurrent chains is shown to provide a good account of both preference and resistance to change, and is able to predict the increased sensitivity to reinforcer rate and magnitude observed with constant-duration components. Residuals from fits of the cumulative decision model to preference and resistance to change data were positively correlated, supporting the prediction of behavioral momentum theory. Although some questions remain, the learning process assumed by the cumulative decision model, in which outcomes are compared against a criterion that represents the average outcome value in the current context, may provide a plausible model for the acquisition of differential resistance to change. © 2018 Society for the Experimental Analysis of Behavior.

Climate change and biofuel wheat: A case study of Southern Saskatchewan

USDA-ARS?s Scientific Manuscript database

This study assessed potential impacts of climate change on wheat production as a biofuel crop in southern Saskatchewan, Canada. The Decision Support System for Agrotechnology Transfer-Cropping System Model (DSSAT-CSM) was used to simulate biomass and grain yield under three climate change scenarios ...

Normative evidence accumulation in unpredictable environments

PubMed Central

Glaze, Christopher M; Kable, Joseph W; Gold, Joshua I

2015-01-01

In our dynamic world, decisions about noisy stimuli can require temporal accumulation of evidence to identify steady signals, differentiation to detect unpredictable changes in those signals, or both. Normative models can account for learning in these environments but have not yet been applied to faster decision processes. We present a novel, normative formulation of adaptive learning models that forms decisions by acting as a leaky accumulator with non-absorbing bounds. These dynamics, derived for both discrete and continuous cases, depend on the expected rate of change of the statistics of the evidence and balance signal identification and change detection. We found that, for two different tasks, human subjects learned these expectations, albeit imperfectly, then used them to make decisions in accordance with the normative model. The results represent a unified, empirically supported account of decision-making in unpredictable environments that provides new insights into the expectation-driven dynamics of the underlying neural signals. DOI: http://dx.doi.org/10.7554/eLife.08825.001 PMID:26322383

Water Planning in Phoenix: Managing Risk in the Face of Climatic Uncertainty

NASA Astrophysics Data System (ADS)

Gober, P.

2009-12-01

The Decision Center for a Desert City (DCDC) was founded in 2004 to develop scientifically-credible support tools to improve water management decisions in the face of growing climatic uncertainty and rapid urbanization in metropolitan Phoenix. At the center of DCDC's effort is WaterSim, a model that integrates information about water supply from groundwater, the Colorado River, and upstream watersheds and water demand from land use change and population growth. Decision levers enable users to manipulate model outcomes in response to climate change scenarios, drought conditions, population growth rates, technology innovations, lifestyle changes, and policy decisions. WaterSim allows users to examine the risks of water shortage from global climate change, the tradeoffs between groundwater sustainability and lifestyle choices, the effects of various policy decisions, and the consequences of delaying policy for the exposure to risk. WaterSim is an important point of contact for DCDC’s relationships with local decision makers. Knowledge, tools, and visualizations are co-produced—by scientists and policy makers, and the Center’s social scientists mine this co-production process for new insights about model development and application. WaterSim is less a static scientific product and more a dynamic process of engagement between decision makers and scientists.

EVALUATING HYDROLOGICAL RESPONSE TO FORECASTED LAND-USE CHANGE: SCENARIO TESTING WITH THE AUTOMATED GEOSPATIAL WATERSHED ASSESSMENT (AGWA) TOOL

EPA Science Inventory

Envisioning and evaluating future scenarios has emerged as a critical component of both science and social decision-making. The ability to assess, report, map, and forecast the life support functions of ecosystems is absolutely critical to our capacity to make informed decisions...

Cogenerating a Competency-based HRM Degree: A Model and Some Lessons from Experience.

ERIC Educational Resources Information Center

Wooten, Kevin C.; Elden, Max

2001-01-01

A competency-based degree program in human resource management was co-generated by six groups of stakeholders who synthesized competency models using group decision support software. The program focuses on core human resource processes, general business management, strategic decision making and problem solving, change management, and personal…

Fire science application and integration in support of decision making

Treesearch

Tom Zimmerman

2011-01-01

Wildland fire management in the United States has historically been a challenging and complex program governed by a multitude of factors including situational status, objectives, operational capability, science and technology, and changes and advances in all these factors. The improvement and advancement of risk-informed decision making has the potential to improve...

The Evaluation of Role-Playing in the Context of Teaching Climate Change

ERIC Educational Resources Information Center

Belova, Nadja; Eilks, Ingo; Feierabend, Timo

2015-01-01

Role-plays are a common pedagogical tool in the Social Sciences. As an imitation of societal practices, role-plays are thought to support the development of argumentation and decision-making skills among learners. However, argumentation and decision making are also goals in science education in general and in socioscientific issues-oriented…

Adults with Intellectual and Developmental Disabilities and Participation in Decision Making: Ethical Considerations for Professional-Client Practice

ERIC Educational Resources Information Center

Lotan, Gurit; Ells, Carolyn

2010-01-01

In this article, the authors challenge professionals to re-examine assumptions about basic concepts and their implications in supporting adults with intellectual and developmental disabilities. The authors focus on decisions with significant implications, such as planning transition from school to adult life, changing living environments, and…

Scenario Analysis: Evaluating Biodiversity Response to Forecasted Land-Use Change in the San Pedro River Basin (U.S.-Mexico)

EPA Science Inventory

Envisioning and evaluating future scenarios has emerged as a critical component of both science and social decision-making. The ability to assess, report, map, and forecast the life support functions of ecosystems is absolutely critical to our capacity to make informed decisions...

A Decision Making Methodology in Support of the Business Rules Lifecycle

NASA Technical Reports Server (NTRS)

Wild, Christopher; Rosca, Daniela

1998-01-01

The business rules that underlie an enterprise emerge as a new category of system requirements that represent decisions about how to run the business, and which are characterized by their business-orientation and their propensity for change. In this report, we introduce a decision making methodology which addresses several aspects of the business rules lifecycle: acquisition, deployment and evolution. We describe a meta-model for representing business rules in terms of an enterprise model, and also a decision support submodel for reasoning about and deriving the rules. The possibility for lifecycle automated assistance is demonstrated in terms of the automatic extraction of business rules from the decision structure. A system based on the metamodel has been implemented, including the extraction algorithm. This is the final report for Daniela Rosca's PhD fellowship. It describes the work we have done over the past year, current research and the list of publications associated with her thesis topic.

Forecasting the effects of land-use and climate change on wildlife communities and habitats in the lower Mississippi Valley

USGS Publications Warehouse

Faulkner, Stephen P.

2010-01-01

Landscape patterns and processes reflect both natural ecosystem attributes and the policy and management decisions of individual Federal, State, county, and private organizations. Land-use regulation, water management, and habitat conservation and restoration efforts increasingly rely on landscape-level approaches that incorporate scientific information into the decision-making process. Since management actions are implemented to affect future conditions, decision-support models are necessary to forecast potential future conditions resulting from these decisions. Spatially explicit modeling approaches enable testing of different scenarios and help evaluate potential outcomes of management actions in conjunction with natural processes such as climate change. The ability to forecast the effects of changing land use and climate is critically important to land and resource managers since their work is inherently site specific, yet conservation strategies and practices are expressed at higher spatial and temporal scales that must be considered in the decisionmaking process.

The Relationships of Self-Esteem, Future Time Perspective, Positive Affect, Social Support, and Career Decision: A Longitudinal Multilevel Study

PubMed Central

Park, In-Jo; Kim, Minhee; Kwon, Seungwoo; Lee, Hae-Gyoung

2018-01-01

This study aimed, first, to determine whether the intra-individual variability in positive affect was related to the intra-individual variability in career decision-making self-efficacy, and career choice anxiety. The second objective was to examine whether social support moderates the relationship between affect and these outcome variables. The third objective was to find out how career decision-making self-efficacy and career choice anxiety change according to self-esteem and future time perspective. We conducted a study using the daily diary method in which participants were asked to rate their affect or attitudes for 21 consecutive days. In total, 128 university students participated in this study. The main results were as follows. First, positive affect was associated positively with career decision-making self-efficacy and negatively with career choice anxiety. Second, social support had a synergy effect with positive affect to influence career choice anxiety. Third, self-esteem was related positively to career decision-making self-efficacy and negatively to career choice anxiety. We discuss theoretical and practical implications. PMID:29755381

The Relationships of Self-Esteem, Future Time Perspective, Positive Affect, Social Support, and Career Decision: A Longitudinal Multilevel Study.

PubMed

Park, In-Jo; Kim, Minhee; Kwon, Seungwoo; Lee, Hae-Gyoung

2018-01-01

This study aimed, first, to determine whether the intra-individual variability in positive affect was related to the intra-individual variability in career decision-making self-efficacy, and career choice anxiety. The second objective was to examine whether social support moderates the relationship between affect and these outcome variables. The third objective was to find out how career decision-making self-efficacy and career choice anxiety change according to self-esteem and future time perspective. We conducted a study using the daily diary method in which participants were asked to rate their affect or attitudes for 21 consecutive days. In total, 128 university students participated in this study. The main results were as follows. First, positive affect was associated positively with career decision-making self-efficacy and negatively with career choice anxiety. Second, social support had a synergy effect with positive affect to influence career choice anxiety. Third, self-esteem was related positively to career decision-making self-efficacy and negatively to career choice anxiety. We discuss theoretical and practical implications.

Distributed collaborative environments for predictive battlespace awareness

NASA Astrophysics Data System (ADS)

McQuay, William K.

2003-09-01

The past decade has produced significant changes in the conduct of military operations: asymmetric warfare, the reliance on dynamic coalitions, stringent rules of engagement, increased concern about collateral damage, and the need for sustained air operations. Mission commanders need to assimilate a tremendous amount of information, make quick-response decisions, and quantify the effects of those decisions in the face of uncertainty. Situational assessment is crucial in understanding the battlespace. Decision support tools in a distributed collaborative environment offer the capability of decomposing complex multitask processes and distributing them over a dynamic set of execution assets that include modeling, simulations, and analysis tools. Decision support technologies can semi-automate activities, such as analysis and planning, that have a reasonably well-defined process and provide machine-level interfaces to refine the myriad of information that the commander must fused. Collaborative environments provide the framework and integrate models, simulations, and domain specific decision support tools for the sharing and exchanging of data, information, knowledge, and actions. This paper describes ongoing AFRL research efforts in applying distributed collaborative environments to predictive battlespace awareness.

The Pacific Northwest's Climate Impacts Group: Climate Science in the Public Interest

NASA Astrophysics Data System (ADS)

Mantua, N.; Snover, A.

2006-12-01

Since its inception in 1995, the University of Washington's Climate Impacts Group (CIG) (funded under NOAA's Regional Integrated Science and Assessments (RISA) Program) has become the leader in exploring the impacts of climate variability and climate change on natural and human systems in the U.S. Pacific Northwest (PNW), specifically climate impacts on water, forest, fish and coastal resource systems. The CIG's research provides PNW planners, decision makers, resource managers, local media, and the general public with valuable knowledge of ways in which the region's key natural resources are vulnerable to changes in climate, and how this vulnerability can be reduced. The CIG engages in climate science in the public interest, conducting original research on the causes and consequences of climate variability and change for the PNW and developing forecasts and decision support tools to support the use of this information in federal, state, local, tribal, and private sector resource management decisions. The CIG's focus on the intersection of climate science and public policy has placed the CIG nationally at the forefront of regional climate impacts assessment and integrated analysis.

Design of an Aircrew Scheduling Decision Aid for the 6916th Electronic Security Squadron.

DTIC Science & Technology

1987-06-01

Security Classification) Design of an Aircrew Scheduling Decision Aid for the 6916th Electronic Security Squadron 12. PERSONAL AUTHOR(S) Thomas J. Kopf...Because of the great number of possible scheduling alternatives, it is difficult to find an optimal solution to-the scheduling problem. Additionally...changes to the original schedule make it even more difficult to find an optimal solution. The emergence of capable microcompu- ters, decision support

Testing take-the-best in new and changing environments.

PubMed

Lee, Michael D; Blanco, Gabrielle; Bo, Nikole

2017-08-01

Take-the-best is a decision-making strategy that chooses between alternatives, by searching the cues representing the alternatives in order of cue validity, and choosing the alternative with the first discriminating cue. Theoretical support for take-the-best comes from the "fast and frugal" approach to modeling cognition, which assumes decision-making strategies need to be fast to cope with a competitive world, and be simple to be robust to uncertainty and environmental change. We contribute to the empirical evaluation of take-the-best in two ways. First, we generate four new environments-involving bridge lengths, hamburger prices, theme park attendances, and US university rankings-supplementing the relatively limited number of naturally cue-based environments previously considered. We find that take-the-best is as accurate as rival decision strategies that use all of the available cues. Secondly, we develop 19 new data sets characterizing the change in cities and their populations in four countries. We find that take-the-best maintains its accuracy and limited search as the environments change, even if cue validities learned in one environment are used to make decisions in another. Once again, we find that take-the-best is as accurate as rival strategies that use all of the cues. We conclude that these new evaluations support the theoretical claims of the accuracy, frugality, and robustness for take-the-best, and that the new data sets provide a valuable resource for the more general study of the relationship between effective decision-making strategies and the environments in which they operate.

A Decision Support System for Drinking Water Production Integrating Health Risks Assessment

PubMed Central

Delpla, Ianis; Monteith, Donald T.; Freeman, Chris; Haftka, Joris; Hermens, Joop; Jones, Timothy G.; Baurès, Estelle; Jung, Aude-Valérie; Thomas, Olivier

2014-01-01

The issue of drinking water quality compliance in small and medium scale water services is of paramount importance in relation to the 98/83/CE European Drinking Water Directive (DWD). Additionally, concerns are being expressed over the implementation of the DWD with respect to possible impacts on water quality from forecast changes in European climate with global warming and further anticipated reductions in north European acid emissions. Consequently, we have developed a decision support system (DSS) named ARTEM-WQ (AwaReness Tool for the Evaluation and Mitigation of drinking Water Quality issues resulting from environmental changes) to support decision making by small and medium plant operators and other water stakeholders. ARTEM-WQ is based on a sequential risk analysis approach that includes consideration of catchment characteristics, climatic conditions and treatment operations. It provides a holistic evaluation of the water system, while also assessing human health risks of organic contaminants potentially present in treated waters (steroids, pharmaceuticals, pesticides, bisphenol-a, polychlorobiphenyls, polycyclic aromatic hydrocarbons, petrochemical hydrocarbons and disinfection by-products; n = 109). Moreover, the system provides recommendations for improvement while supporting decision making in its widest context. The tool has been tested on various European catchments and shows a promising potential to inform water managers of risks and appropriate mitigative actions. Further improvements should include toxicological knowledge advancement, environmental background pollutant concentrations and the assessment of the impact of distribution systems on water quality variation. PMID:25046634

Social Policies for Family Caregivers.

ERIC Educational Resources Information Center

Barer, Barbara M.

Demographic changes, changes in women's work roles, and changes in the nature of the family have increased the importance of identifying the effects of government policy on family cohesion and living arrangement decisions. The effect of public policy on the nation's largest source of caregivers, the family support system, is a key issue. While…

A Bridging Opportunities Work-frame to develop mobile applications for clinical decision making

PubMed Central

van Rooij, Tibor; Rix, Serena; Moore, James B; Marsh, Sharon

2015-01-01

Background: Mobile applications (apps) providing clinical decision support (CDS) may show the greatest promise when created by and for frontline clinicians. Our aim was to create a generic model enabling healthcare providers to direct the development of CDS apps. Methods: We combined Change Management with a three-tier information technology architecture to stimulate CDS app development. Results: A Bridging Opportunities Work-frame model was developed. A test case was used to successfully develop an app. Conclusion: Healthcare providers can re-use this globally applicable model to actively create and manage regional decision support applications to translate evidence-based medicine in the use of emerging medication or novel treatment regimens. PMID:28031883

WORKING AND CARING: THE SIMULTANEOUS DECISION OF LABOR FORCE PARTICIPATION AND INFORMAL ELDERLY AND CHILD SUPPORT ACT IVITIES IN MEXICO*

PubMed Central

van Gameren, Edwin; Velandia Naranjo, Durfari

2016-01-01

We analyze factors determining women’s decisions to participate in the labor market and provide elderly care and nonfinancial support to their (grand)children. We use data from the Mexican Health and Aging Study, a survey of people aged 50 and over, applying a three-equation, reduced-form SUR model. Results suggest that care needs are the driving force behind caregiving activities. Traditional roles also appear to be relevant in the labor force participation decision: women with a closer labor market connection when they were young are more likely to work. Simulations of demographic changes illustrate potential effects for future caregiving and participation rates. PMID:26924883

Design and implementation of the standards-based personal intelligent self-management system (PICS).

PubMed

von Bargen, Tobias; Gietzelt, Matthias; Britten, Matthias; Song, Bianying; Wolf, Klaus-Hendrik; Kohlmann, Martin; Marschollek, Michael; Haux, Reinhold

2013-01-01

Against the background of demographic change and a diminishing care workforce there is a growing need for personalized decision support. The aim of this paper is to describe the design and implementation of the standards-based personal intelligent care systems (PICS). PICS makes consistent use of internationally accepted standards such as the Health Level 7 (HL7) Arden syntax for the representation of the decision logic, HL7 Clinical Document Architecture for information representation and is based on a open-source service-oriented architecture framework and a business process management system. Its functionality is exemplified for the application scenario of a patient suffering from congestive heart failure. Several vital signs sensors provide data for the decision support system, and a number of flexible communication channels are available for interaction with patient or caregiver. PICS is a standards-based, open and flexible system enabling personalized decision support. Further development will include the implementation of components on small computers and sensor nodes.

Hybrid Method for Mobile learning Cooperative: Study of Timor Leste

NASA Astrophysics Data System (ADS)

da Costa Tavares, Ofelia Cizela; Suyoto; Pranowo

2018-02-01

In the modern world today the decision support system is very useful to help in solving a problem, so this study discusses the learning process of savings and loan cooperatives in Timor Leste. The purpose of the observation is that the people of Timor Leste are still in the process of learning the use DSS for good saving and loan cooperative process. Based on existing research on the Timor Leste community on credit cooperatives, a mobile application will be built that will help the cooperative learning process in East Timorese society. The methods used for decision making are AHP (Analytical Hierarchy Process) and SAW (simple additive Weighting) method to see the result of each criterion and the weight of the value. The result of this research is mobile leaning cooperative in decision support system by using SAW and AHP method. Originality Value: Changed the two methods of mobile application development using AHP and SAW methods to help the decision support system process of a savings and credit cooperative in Timor Leste.

Beyond Wiki to Judgewiki for Transparent Climate Change Decisions

NASA Astrophysics Data System (ADS)

Capron, M. E.

2008-12-01

Climate Change is like the prisoner's dilemma, a zero-sum game, or cheating in sports. Everyone and every country is tempted to selfishly maintain or advance their standard of living. The tremendous difference between standards of living amplifies the desire to opt out of Climate Change solutions adverse to economic competitiveness. Climate Change is also exceedingly complex. No one person, one organization, one country, or partial collection of countries has the capacity and the global support needed to make decisions on Climate Change solutions. There are thousands of potential actions, tens of thousands of known and unknown environmental and economic impacts. Some actions are belatedly found to be unsustainable beyond token volumes, corn ethanol or soy-biodiesel for example. Mankind can address human nature and complexity with a globally transparent information and decision process available to all 7 billion of us. We need a process that builds trust and simplifies complexity. Fortunately, we have the Internet for trust building communication and computers to simplify complexity. Mankind can produce new software tailored to the challenge. We would combine group information collection software (a wiki) with a decision-matrix (a judge), market forecasting, and video games to produce the tool mankind needs for trust building transparent decisions on Climate Change actions. The resulting software would be a judgewiki.

The National Danish Water Resources Model - using an integrated groundwater - surface water model for decision support and WFD implementation in a changing climate

NASA Astrophysics Data System (ADS)

Lajer Hojberg, Anker; Hinsby, Klaus; Jørgen Henriksen, Hans; Troldborg, Lars

2014-05-01

Integrated and sustainable water resources management and development of river basin management plans according to the Water Framework Directive is getting increasingly complex especially when taking projected climate change into account. Furthermore, uncertainty in future developments and incomplete knowledge of the physical system introduces a high degree of uncertainty in the decision making process. Knowledge based decision making is therefore vital for formulation of robust management plans and to allow assessment of the inherent uncertainties. The Department of Hydrology at the Geological Survey of Denmark and Greenland started in 1996 to develop a mechanistically, transient and spatially distributed groundwater-surface water model - the DK-model - for the assessment of groundwater quantitative status accounting for interactions with surface water and anthropogenic changes, such as extraction strategies and land use, as well as climate change. The model has been subject to continuous update building on hydrogeological knowledge established by the regional water authorities and other national research institutes. With the on-going improvement of the DK-model it is now increasingly applied both by research projects and for decision support e.g. in implementation of the Water Framework Directive or to support other decisions related to protection of water resources (quantitative and chemical status), ecosystems and the built environment. At present, the DK-model constitutes the backbone of a strategic modelling project funded by the Danish Environmental Protection Agency, with the aim of developing a modelling complex that will provide the foundation of the implementation of the Water Framework Directive. Since 2003 the DK-model has been used in more than 25 scientific papers and even more public reports. In the poster and the related review paper we describe the most important applications in both science and policy, where the DK-model has been used either directly or as an important starting point for assessing the impact of climate change on the quantity and quality of groundwater and surface water e.g. in relation to changes in water tables, runoff, nutrient loadings, flooding risks (coastal and hinterland), irrigation demands, sea level rise and seawater intrusion or to assess where geology or climate change create the largest uncertainty for evaluation of the development of water resources quantity and quality.

Impact of a goal setting and decision support telephone coaching intervention on diet, psychosocial, and decision outcomes among people with type 2 diabetes.

PubMed

Swoboda, Christine M; Miller, Carla K; Wills, Celia E

2017-07-01

Evaluate a 16-week decision support and goal-setting intervention to compare diet quality, decision, and diabetes-related outcomes to a control group. Adults with type 2 diabetes (n=54) were randomly assigned to an intervention or control group. Intervention group participants completed one in-person motivational interviewing and decision support session followed by seven biweekly telephone coaching calls. Participants reported previous goal attempts and set diet- and/or physical activity-related goals during coaching calls. Control group participants received information about local health care resources on the same contact schedule. There was a significant difference between groups for diabetes empowerment (p=0.045). A significant increase in diet quality, diabetes self-efficacy, and diabetes empowerment, and a significant decrease in diabetes distress and depressive symptoms (all p≤0.05) occurred in the intervention group. Decision confidence to achieve diet-related goals significantly improved from baseline to week 8 but then declined at study end (both p≤0.05). Setting specific diet-related goals may promote dietary change, and telephone coaching can improve psychosocial outcomes related to diabetes self-management. Informed shared decision making can facilitate progressively challenging yet attainable goals tailored to individuals' lifestyle. Decision coaching may empower patients to improve self-management practices and reduce distress. Copyright © 2017 Elsevier B.V. All rights reserved.

Changes in DSTO Support to Projects Arising From the 6th July 2006 DCIC Decision: Updated Guidance for Project S&T Plans

DTIC Science & Technology

2007-02-01

responsible to the Government for certifying these technical risks [4] and [5] The current funding model for Project S&T Plans is: • Pre-First...the new costing spreadsheets at Annexes C-E. 3.1 A complete set of S&T Activities The 6th July 2006 DCIC decisions to change the funding model increase...changes to the funding model mean that the set of S&T Activities in the Project S&T Plans will need to be categorised in new ways to fit in with the

Time to decision: the drivers of innovation adoption decisions

NASA Astrophysics Data System (ADS)

Ciganek, Andrew Paul; (Dave) Haseman, William; Ramamurthy, K.

2014-03-01

Organisations desire timeliness. Timeliness facilitates a better responsiveness to changes in an organisation's external environment to either attain or maintain competitiveness. Despite its importance, decision timeliness has not been explicitly examined. Decision timeliness is measured in this study as the time taken to commit to a decision. The research objective is to identify the drivers of decision timeliness in the context of adopting service-oriented architecture (SOA), an innovation for enterprise computing. A research model rooted in the technology-organisation-environment (TOE) framework is proposed and tested with data collected in a large-scale study. The research variables have been examined before in the context of adoption, but their applicability to the timeliness of innovation decision-making has not received much attention and their salience is unclear. The results support multiple hypothesised relationships, including the finding that a risk-oriented organisational culture as well as normative and coercive pressures accelerates decision timeliness. Top management support as well as the traditional innovation attributes (compatibility, relative advantage and complexity/ease-of-use) were not found to be significant when examining their influence on decision timeliness, which appears inconsistent with generally accepted knowledge and deserves further examination.

Barriers, facilitators and views about next steps to implementing supports for evidence-informed decision-making in health systems: a qualitative study.

PubMed

Ellen, Moriah E; Léon, Grégory; Bouchard, Gisèle; Ouimet, Mathieu; Grimshaw, Jeremy M; Lavis, John N

2014-12-05

Mobilizing research evidence for daily decision-making is challenging for health system decision-makers. In a previous qualitative paper, we showed the current mix of supports that Canadian health-care organizations have in place and the ones that are perceived to be helpful to facilitate the use of research evidence in health system decision-making. Factors influencing the implementation of such supports remain poorly described in the literature. Identifying the barriers to and facilitators of different interventions is essential for implementation of effective, context-specific, supports for evidence-informed decision-making (EIDM) in health systems. The purpose of this study was to identify (a) barriers and facilitators to implementing supports for EIDM in Canadian health-care organizations, (b) views about emerging development of supports for EIDM, and (c) views about the priorities to bridge the gaps in the current mix of supports that these organizations have in place. This qualitative study was conducted in three types of health-care organizations (regional health authorities, hospitals, and primary care practices) in two Canadian provinces (Ontario and Quebec). Fifty-seven in-depth semi-structured telephone interviews were conducted with senior managers, library managers, and knowledge brokers from health-care organizations that have already undertaken strategic initiatives in knowledge translation. The interviews were taped, transcribed, and then analyzed thematically using NVivo 9 qualitative data analysis software. Limited resources (i.e., money or staff), time constraints, and negative attitudes (or resistance) toward change were the most frequently identified barriers to implementing supports for EIDM. Genuine interest from health system decision-makers, notably their willingness to invest money and resources and to create a knowledge translation culture over time in health-care organizations, was the most frequently identified facilitator to implementing supports for EIDM. The most frequently cited views about emerging development of supports for EIDM were implementing accessible and efficient systems to support the use of research in decision-making (e.g., documentation and reporting tools, communication tools, and decision support tools) and developing and implementing an infrastructure or position where the accountability for encouraging knowledge use lies. The most frequently stated priorities for bridging the gaps in the current mix of supports that these organizations have in place were implementing technical infrastructures to support research use and to ensure access to research evidence and establishing formal or informal ties to researchers and knowledge brokers outside the organization who can assist in EIDM. These results provide insights on the type of practical implementation imperatives involved in supporting EIDM.

CALM: Complex Adaptive System (CAS)-Based Decision Support for Enabling Organizational Change

NASA Astrophysics Data System (ADS)

Adler, Richard M.; Koehn, David J.

Guiding organizations through transformational changes such as restructuring or adopting new technologies is a daunting task. Such changes generate workforce uncertainty, fear, and resistance, reducing morale, focus and performance. Conventional project management techniques fail to mitigate these disruptive effects, because social and individual changes are non-mechanistic, organic phenomena. CALM (for Change, Adaptation, Learning Model) is an innovative decision support system for enabling change based on CAS principles. CALM provides a low risk method for validating and refining change strategies that combines scenario planning techniques with "what-if" behavioral simulation. In essence, CALM "test drives" change strategies before rolling them out, allowing organizations to practice and learn from virtual rather than actual mistakes. This paper describes the CALM modeling methodology, including our metrics for measuring organizational readiness to respond to change and other major CALM scenario elements: prospective change strategies; alternate futures; and key situational dynamics. We then describe CALM's simulation engine for projecting scenario outcomes and its associated analytics. CALM's simulator unifies diverse behavioral simulation paradigms including: adaptive agents; system dynamics; Monte Carlo; event- and process-based techniques. CALM's embodiment of CAS dynamics helps organizations reduce risk and improve confidence and consistency in critical strategies for enabling transformations.

Adaptation by Stealth: Understanding climate information use across scales and decision spaces in water management in the United States

NASA Astrophysics Data System (ADS)

Kirchhoff, C.; Vang Rasmussen, L.; Lemos, M. C.

2016-12-01

While there has been considerable focus on understanding how factors related to the creation of climate knowledge affect its uptake and use, less attention has been paid to the actors, decisions, and processes through which climate information supports, or fails to support, action. This is particularly the case concerning how different scales of decision-making influence information uptake. In this study, we seek to understand how water and resource managers' decision space influences climate information use in two Great Lakes watersheds. We find that despite the availability of tailored climate information, actual use of information in decision making remains low. Reasons include: a) lack of willingness to place climate on agendas because local managers perceive climate change as politically risky and a difficult and intangible problem; b) lack of formal mandate or authority at the city and county scale to translate climate information into on-the-ground action, c) problems with the information itself, and d) perceived lack of demand for climate information by those managers who have the mandate and authority (e.g. at the state level) to use (or help others use) climate information. Our findings suggest that 1) climate scientists and information brokers should produce information that meets a range of decision needs and reserve intensive tailoring efforts for decision makers who have authority and willingness to employ climate information, 2) without support from higher levels of decision-making (e.g. state) it is unlikely that climate information use for adaptation decisions will accelerate significantly in the next few years, and 3) the trend towards adopting more sustainability and resilience practices over climate-specific actions should be supported as an important component of the climate adaptation repertoire.

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.

In Search of How Principals Change: A Qualitative Study of Events That Help and Hinder Administrator Support for School-Wide PBIS

ERIC Educational Resources Information Center

McIntosh, Kent; Kelm, Joanna L.; Canizal Delabra, Alondra

2016-01-01

Research has shown principal support to be a critical variable for implementing and sustaining evidence-based practices. However, there remains little understanding of the factors that may influence a principal's personal decision to support a practice. The purpose of the current study was to examine events that influenced principals' support for…

Physical, Ecological, and Societal Indicators for the National Climate Assessment

NASA Technical Reports Server (NTRS)

Kenney, Melissa A.; Chen, Robert; Baptista, Sandra R.; Quattrochi, Dale; O'Brien, Sheila

2011-01-01

The National Climate Assessment (NCA) is being conducted under the auspices of the U.S. Global Change Research Program (USGCRP), pursuant to the Global Change Research Act of 1990, Section 106, which requires a report to Congress every 4 years. The current NCA (http://globalchange.gov/what-we-do/assessment/) differs in multiple ways from previous U.S. climate assessment efforts, being: (1) more focused on supporting the Nation s activities in adaptation and mitigation and on evaluating the current state of scientific knowledge relative to climate impacts and trends; (2) a long-term, consistent process for evaluation of climate risks and opportunities and providing information to support decision-making processes within regions and sectors; and (3) establishing a permanent assessment capacity both inside and outside of the federal government. As a part of ongoing, long-term assessment activities, the NCA intends to develop an integrated strategic framework and deploy climate-relevant physical, ecological, and societal indicators. The NCA indicators framework is underdevelopment by the NCA Development and Advisory Committee Indicators Working Group and are envisioned as a relatively small number of policy-relevant integrated indicators designed to provide a consistent, objective, and transparent overview of major variations in climate impacts, vulnerabilities, adaptation, and mitigation activities across sectors, regions, and timeframes. The potential questions that could be addressed by these indicators include: How do we know that there is a changing climate and how is it expected to change in the future? Are important climate impacts and opportunities occurring or predicted to occur in the future? Are we adapting successfully? What are the vulnerabilities and resiliencies given a changing climate? Are we preparing adequately for extreme events? It is not expected that the NCA societal indicators would be linked directly to a single decision or portfolio of decisions, but subsets of indicators, or the data supporting the indicator, might be used to inform decision-making processes such as the development and implementation of climate adaptation strategies in a particular sector or region.

Physical, Ecological, and Societal Indicators for the National Climate Assessment

NASA Astrophysics Data System (ADS)

O'Brien, S.; Kenney, M.; Chen, R. S.; Baptista, S. R.; Quattrochi, D. A.

2011-12-01

The National Climate Assessment (NCA) is being conducted under the auspices of the U.S. Global Change Research Program (USGCRP), pursuant to the Global Change Research Act of 1990, Section 106, which requires a report to Congress every 4 years. The current NCA (http://globalchange.gov/what-we-do/assessment/) differs in multiple ways from previous U.S. climate assessment efforts, being: (1) more focused on supporting the Nation's activities in adaptation and mitigation and on evaluating the current state of scientific knowledge relative to climate impacts and trends; (2) a long-term, consistent process for evaluation of climate risks and opportunities and providing information to support decision-making processes within regions and sectors; and (3) establishing a permanent assessment capacity both inside and outside of the federal government. As a part of ongoing, long-term assessment activities, the NCA intends to develop an integrated strategic framework and deploy climate-relevant physical, ecological, and societal indicators. The NCA indicators framework is underdevelopment by the NCA Development and Advisory Committee Indicators Working Group and are envisioned as a relatively small number of policy-relevant integrated indicators designed to provide a consistent, objective, and transparent overview of major variations in climate impacts, vulnerabilities, adaptation, and mitigation activities across sectors, regions, and timeframes. The potential questions that could be addressed by these indicators include: -How do we know that there is a changing climate and how is it expected to change in the future? -Are important climate impacts and opportunities occurring or predicted to occur in the future? -Are we adapting successfully? -What are the vulnerabilities and resiliencies given a changing climate? -Are we preparing adequately for extreme events? It is not expected that the NCA indicators would be linked directly to a single decision or portfolio of decisions, but subsets of indicators, or the data supporting the indicator, might be used to inform decision-making processes such as the development and implementation of climate adaptation strategies in a particular sector or region.

ReefLink Database: A decision support tool for Linking Coral Reefs and Society Through Systems Thinking

EPA Science Inventory

Coral reefs provide the ecological foundation for productive and diverse fish and invertebrate communities that support multibillion dollar reef fishing and tourism industries. Yet reefs are threatened by growing coastal development, climate change, and over-exploitation. A key i...

Making the Most of Continuing Medical Education: Evidence of Transformative Learning During a Course in Evidence-Based Medicine and Decision Making.

PubMed

Sokol, Randi G; Shaughnessy, Allen F

2018-01-01

Continuing medical information courses have been criticized for not promoting behavior change among their participants. For behavior change to occur, participants often need to consciously reject previous ideas and transform their way of thinking. Transformational learning is a process that cultivates deep emotional responses and can lead to cognitive and behavioral change in learners, potentially facilitating rich learning experiences and expediting knowledge translation. We explored participants' experiences at a 2-day conference designed to support transformative learning as they encounter new concepts within Information Mastery, which challenge their previous frameworks around the topic of medical decision making. Using the lens of transformative learning theory, we asked: how does Information Mastery qualitatively promote perspective transformation and hence behavior change? We used a hermeneutic phenomenologic approach to capture the lived experience of 12 current and nine previous attendees of the "Information Mastery" course through individual interviews, focus groups, and observation. Data were thematically analyzed. Both prevoius and current conference attendees described how the delivery of new concepts about medical decision making evoked strong emotional responses, facilitated personal transformation, and propelled expedited behavior change around epistemological, moral, and information management themes, resulting in a newfound sense of self-efficacy, confidence, and ownership in their ability to make medical decisions. When the topic area holds the potential to foster a qualitative reframing of learners' guiding paradigms and worldviews, attention should be paid to supporting learners' personalized meaning-making process through transformative learning opportunities to promote translation into practice.

Assessing the vulnerability of human and biological communities to changing ecosystem services using a GIS-based multi-criteria decision support tool

USGS Publications Warehouse

Villarreal, Miguel; Norman, Laura M.; Labiosa, William B.

2012-01-01

In this paper we describe an application of a GIS-based multi-criteria decision support web tool that models and evaluates relative changes in ecosystem services to policy and land management decisions. The Santa Cruz Watershed Ecosystem Portfolio (SCWEPM) was designed to provide credible forecasts of responses to ecosystem drivers and stressors and to illustrate the role of land use decisions on spatial and temporal distributions of ecosystem services within a binational (U.S. and Mexico) watershed. We present two SCWEPM sub-models that when analyzed together address bidirectional relationships between social and ecological vulnerability and ecosystem services. The first model employs the Modified Socio-Environmental Vulnerability Index (M-SEVI), which assesses community vulnerability using information from U.S. and Mexico censuses on education, access to resources, migratory status, housing situation, and number of dependents. The second, relating land cover change to biodiversity (provisioning services), models changes in the distribution of terrestrial vertebrate habitat based on multitemporal vegetation and land cover maps, wildlife habitat relationships, and changes in land use/land cover patterns. When assessed concurrently, the models exposed some unexpected relationships between vulnerable communities and ecosystem services provisioning. For instance, the most species-rich habitat type in the watershed, Desert Riparian Forest, increased over time in areas occupied by the most vulnerable populations and declined in areas with less vulnerable populations. This type of information can be used to identify ecological conservation and restoration targets that enhance the livelihoods of people in vulnerable communities and promote biodiversity and ecosystem health.

The influence of science funding agencies in support of effective decision-maker scientist partnerships

NASA Astrophysics Data System (ADS)

Arnott, J. C.; Lemos, M. C.

2017-12-01

A wealth of evidence supports the idea that collaboration between scientists and decision-makers is an influential factor in generating actionable knowledge. Nevertheless, persistent obstacles across the research-policy-practice interface limit the amount of engagement that may be necessary to satisfy demands for information to support decisions. Funding agencies have been identified as one possible driver of change, but few multi-year studies have been conducted to trace the influence of program designs on research practices or other outcomes. To fill this gap, we examine a body of applied science projects (n=120) funded through NOAA's National Estuarine Research Reserve System from 1998-2014. Periodic innovation in the structure of this funding program, including requirements for end user engagement and the inclusion of collaboration specialists, offers a natural experiment from which to test hypotheses about the how funding program design influences research practice, utilization, and broader impacts. Using content analysis of project reports and interviews of project team members, end users, and program managers (n=40), we produce a data that can be analyzed through both statistical and qualitative methods. We find that funder mandates significantly influence the intensity of interaction between researchers and practitioners as well as affect long-term change in research cultures. When interaction intensifies, corresponding gains appear in the readiness of research to support decision-making and the readiness of user groups to incorporate findings into their work. While collaborative methods transform research practice and positively influence the applied contexts in which partnerships occur, it remains less clear whether this actually increases the direct use of scientific to inform decisions. For example, collaboration may lead to outcomes other than new knowledge or knowledge application, yielding many positive outcomes that are distinct from knowledge use itself. We find that improved and more flexible evaluation approaches at the project level and more nuanced, supported and guided by program sponsors, are needed.

The Cool Hand Luke Effect: Failure to Communicate Effectively (Invited)

NASA Astrophysics Data System (ADS)

Davidson, M. A.

2010-12-01

There is a growing concern with the accelerating rate of local sea level change and its implications for local and regional planning and development. While there are a growing number of local governments that are beginning to seriously consider their adaptation options, the vast majority of local leaders have not yet developed confidence in the various scenarios that are currently available. To adequately address the range of possible impacts and options for addressing local sea level change, one must have more than high resolution data, model output and decision support tools. We need to have a better understandin of the range of likely impacts upon and the value of local ecosystem services as well as as understanding of the foundations of the local economies. A sound scientific foundation must exist to support 'decision making under uncertainty' but we also need to understand the very local specific cultural frameworks within which decision makers must work. This is why working with local civic organizations, NGOs and other boundary organizations is increasingly important.

Estimating the potential water reuse based on fuzzy reasoning.

PubMed

Almeida, Giovana; Vieira, José; Marques, Alfeu Sá; Kiperstok, Asher; Cardoso, Alberto

2013-10-15

Studies worldwide suggest that the risk of water shortage in regions affected by climate change is growing. Decision support tools can help governments to identify future water supply problems in order to plan mitigation measures. Treated wastewater is considered a suitable alternative water resource and it is used for non-potable applications in many dry regions around the world. This work describes a decision support system (DSS) that was developed to identify current water reuse potential and the variables that determine the reclamation level. The DSS uses fuzzy inference system (FIS) as a tool and multi-criteria decision making is the conceptual approach behind the DSS. It was observed that water reuse level seems to be related to environmental factors such as drought, water exploitation index, water use, population density and the wastewater treatment rate, among others. A dataset was built to analyze these features through water reuse potential with a FIS that considered 155 regions and 183 cities. Despite some inexact fit between the classification and simulation data for agricultural and urban water reuse potential it was found that the FIS was suitable to identify the water reuse trend. Information on the water reuse potential is important because it issues a warning about future water supply needs based on climate change scenarios, which helps to support decision making with a view to tackling water shortage. Copyright © 2013 Elsevier Ltd. All rights reserved.

The impact of computer self-efficacy, computer anxiety, and perceived usability and acceptability on the efficacy of a decision support tool for colorectal cancer screening

PubMed Central

Lindblom, Katrina; Gregory, Tess; Flight, Ingrid H K; Zajac, Ian

2011-01-01

Objective This study investigated the efficacy of an internet-based personalized decision support (PDS) tool designed to aid in the decision to screen for colorectal cancer (CRC) using a fecal occult blood test. We tested whether the efficacy of the tool in influencing attitudes to screening was mediated by perceived usability and acceptability, and considered the role of computer self-efficacy and computer anxiety in these relationships. Methods Eighty-one participants aged 50–76 years worked through the on-line PDS tool and completed questionnaires on computer self-efficacy, computer anxiety, attitudes to and beliefs about CRC screening before and after exposure to the PDS, and perceived usability and acceptability of the tool. Results Repeated measures ANOVA found that PDS exposure led to a significant increase in knowledge about CRC and screening, and more positive attitudes to CRC screening as measured by factors from the Preventive Health Model. Perceived usability and acceptability of the PDS mediated changes in attitudes toward CRC screening (but not CRC knowledge), and computer self-efficacy and computer anxiety were significant predictors of individuals' perceptions of the tool. Conclusion Interventions designed to decrease computer anxiety, such as computer courses and internet training, may improve the acceptability of new health information technologies including internet-based decision support tools, increasing their impact on behavior change. PMID:21857024

Translating eHealth Visions from Strategy to Practice - A Benefit Management Approach.

PubMed

Villumsen, Sidsel; Nøhr, Christian; Faxvaag, Arild

2018-01-01

The municipalities and the Regional Health Authorities in Central Norway have been assigned a mandate to implement a shared electronic health record, Helseplattformen, reflecting the visions set out in the national eHealth white paper 'One Citizen - One Record'. This study identifies and describe anticipated benefit streams of clinical decision support in 'One Citizen - One Record' and the user requirement specification documents of Helseplattformen. This study found that the benefit stream of clinical decision support translates from the health policy visions stated in 'One Citizen - One Record' into Helseplattformen. However, business changes, although a critical element of achieving benefits, were not emphasised in either. This calls for the programme of Helseplattformen to pay careful attention to how the information system and information technology requirements must be accompanied by enabling changes as well as business changes in order to achieve the identified benefits of 'One Citizen - One Record' and Helseplattformen.

Psychosocial work environment and mental health: Job-strain and effort-reward imbalance models in a context of major organizational changes.

PubMed

Niedhammer, Isabelle; Chastang, Jean-François; David, Simone; Barouhiel, Lina; Barrandon, Guy

2006-01-01

This study explored the association between the two job-stress models, job-strain and effort-reward imbalance, and mental health outcomes in a working population exposed to major organizational changes. The cross-sectional study was based on 680 subjects, 504 men and 176 women. Psychosocial factors at work included: psychological demands, decision latitude, social support, effort, reward, and overcommitment. Mental health outcomes were depressive symptoms (CES-D) and psychiatric disorders (GHQ-12). Job strain, low decision latitude, effort-reward imbalance, and low reward (especially job instability) were found to be associated with depressive symptoms and/or psychiatric disorders among men. Overcommitment at work was a risk factor for both men and women. Social support at work played a role to reduce depressive symptoms for women. These findings emphasize the deleterious effects of psychosocial work environment on mental health during major organizational changes.

A decision support system to find the best water allocation strategies in a Mediterranean river basin in future scenarios of global change

NASA Astrophysics Data System (ADS)

Del Vasto-Terrientes, L.; Kumar, V.; Chao, T.-C.; Valls, A.

2016-03-01

Global change refers to climate changes, but also demographic, technological and economic changes. Predicted water scarcity will be critical in the coastal Mediterranean region, especially for provision to mid-sized and large-sized cities. This paper studies the case of the city of Tarragona, located at the Mediterranean area of north-eastern Spain (Catalonia). Several scenarios have been constructed to evaluate different sectorial water allocation policies to mitigate the water scarcity induced by global change. Future water supply and demand predictions have been made for three time spans. The decision support system presented is based on the outranking model, which constructs a partial pre-order based on pairwise preference relations among all the possible actions. The system analyses a hierarchical structure of criteria, including environmental and economic criteria. We compare several adaptation measures including alternative water sources, inter-basin water transfer and sectorial demand management coming from industry, agriculture and domestic sectors. Results indicate that the most appropriate water allocation strategies depend on the severity of the global change effects.

Risk communication, public engagement, and climate change: a role for emotions.

PubMed

Roeser, Sabine

2012-06-01

This article discusses the potential role that emotions might play in enticing a lifestyle that diminishes climate change. Climate change is an important challenge for society. There is a growing consensus that climate change is due to our behavior, but few people are willing to significantly adapt their lifestyle. Empirical studies show that people lack a sense of urgency: they experience climate change as a problem that affects people in distant places and in a far future. Several scholars have claimed that emotions might be a necessary tool in communication about climate change. This article sketches a theoretical framework that supports this hypothesis, drawing on insights from the ethics of risk and the philosophy of emotions. It has been shown by various scholars that emotions are important determinants in risk perception. However, emotions are generally considered to be irrational states and are hence excluded from communication and political decision making about risky technologies and climate change, or they are used instrumentally to create support for a position. However, the literature on the ethics of risk shows that the dominant, technocratic approach to risk misses the normative-ethical dimension that is inherent to decisions about acceptable risk. Emotion research shows that emotions are necessary for practical and moral decision making. These insights can be applied to communication about climate change. Emotions are necessary for understanding the moral impact of the risks of climate change, and they also paradigmatically provide for motivation. Emotions might be the missing link in effective communication about climate change. © 2012 Society for Risk Analysis.

Development of a Spatial Decision Support System for Analyzing Changes in Hydro-meteorological Risk

NASA Astrophysics Data System (ADS)

van Westen, Cees

2013-04-01

In the framework of the EU FP7 Marie Curie ITN Network "CHANGES: Changing Hydro-meteorological Risks, as Analyzed by a New Generation of European Scientists (http://www.changes-itn.eu)", a spatial decision support system is under development with the aim to analyze the effect of risk reduction planning alternatives on reducing the risk now and in the future, and support decision makers in selecting the best alternatives. The SDSS is one of the main outputs of the CHANGES network, which will develop an advanced understanding of how global changes, related to environmental and climate change as well as socio-economical change, may affect the temporal and spatial patterns of hydro-meteorological hazards and associated risks in Europe; how these changes can be assessed, modeled, and incorporated in sustainable risk management strategies, focusing on spatial planning, emergency preparedness and risk communication. The CHANGES network consists of 11 full partners and 6 associate partners of which 5 private companies, representing 10 European countries. The CHANGES network has hired 12 Early Stage Researchers (ESRs) and is currently hiring 3-6 researchers more for the implementation of the SDSS. The Spatial Decision Support System will be composed of a number of integrated components. The Risk Assessment component allows to carry out spatial risk analysis, with different degrees of complexity, ranging from simple exposure (overlay of hazard and assets maps) to quantitative analysis (using different hazard types, temporal scenarios and vulnerability curves) resulting into risk curves. The platform does not include a component to calculate hazard maps, and existing hazard maps are used as input data for the risk component. The second component of the SDSS is a risk reduction planning component, which forms the core of the platform. This component includes the definition of risk reduction alternatives (related to disaster response planning, risk reduction measures and spatial planning) and links back to the risk assessment module to calculate the new level of risk if the measure is implemented, and a cost-benefit (or cost-effectiveness/ Spatial Multi Criteria Evaluation) component to compare the alternatives and make decision on the optimal one. The third component of the SDSS is a temporal scenario component, which allows to define future scenarios in terms of climate change, land use change and population change, and the time periods for which these scenarios will be made. The component doesn't generate these scenarios but uses input maps for the effect of the scenarios on the hazard and assets maps. The last component is a communication and visualization component, which can compare scenarios and alternatives, not only in the form of maps, but also in other forms (risk curves, tables, graphs). The envisaged users of the platform are organizations involved in planning of risk reduction measures, and that have staff capable of visualizing and analyzing spatial data at a municipal scale. This paper presents the main components of the SDSS and the overall design and plans for the user interface.

Arctic Indicators of Change

NASA Astrophysics Data System (ADS)

Stanitski, D.; Druckenmiller, M.; Fetterer, F. M.; Gerst, M.; Intrieri, J. M.; Kenney, M. A.; Meier, W.; Overland, J. E.; Stroeve, J. C.; Trainor, S.

2016-12-01

The Arctic is undergoing unprecedented change. Indicators of change enable better decision-making at the community to policy levels. The results presented here focus on a subset of physical, biological, societal, and economic indicators of Arctic change recommended in one of a group of papers emanating from the earlier National Climate Indicators System (NCIS) work led by Kenney et al. (2016). The intent of the NCIS was to establish a "system of physical, natural, and societal indicators that communicate and inform decisions about key aspects of the physical climate, climate impacts, vulnerabilities, and preparedness" in support of the sustained U.S. National Climate Assessment. Our analysis, guided by a tailored selection and recommendation criteria, resulted in a list of "existing" indicators, as well as those "in development", "recommended", and "aspirational". A goal of this effort is to identify a set of both lagging and leading indicators that is based on reliable and sustained data sources with known user communities. We intend for these indicators to guide decision-makers in their responses to climate change, and ideally help inform decisions of groups like the Arctic Council and U.S. Global Change Research Program (USGCRP) as they develop plans and priorities.

Forecasted economic change and the self-fulfilling prophecy in economic decision-making

PubMed Central

2017-01-01

This study addresses the self-fulfilling prophecy effect, in the domain of economic decision-making. We present experimental data in support of the hypothesis that speculative forecasts of economic change can impact individuals’ economic decision behavior, prior to any realized changes. In a within-subjects experiment, participants (N = 40) played 180 trials in a Balloon Analogue Risk Talk (BART) in which they could make actual profit. Simple messages about possible (positive and negative) changes in outcome probabilities of future trials had significant effects on measures of risk taking (number of inflations) and actual profits in the game. These effects were enduring, even though no systematic changes in actual outcome probabilities took place following any of the messages. Risk taking also found to be reflected in reaction times revealing increasing reaction times with riskier decisions. Positive and negative economic forecasts affected reaction times slopes differently, with negative forecasts resulting in increased reaction time slopes as a function of risk. These findings suggest that forecasted positive or negative economic change can bias people’s mental model of the economy and reduce or stimulate risk taking. Possible implications for media-fulfilling prophecies in the domain of the economy are considered. PMID:28334031

Using Mobile & Personal Sensing Technologies to Support Health Behavior Change in Everyday Life: Lessons Learned

PubMed Central

Klasnja, Predrag; Consolvo, Sunny; McDonald, David W.; Landay, James A.; Pratt, Wanda

2009-01-01

Lifestyle modification is a key facet of the prevention and management of chronic diseases. Mobile devices that people already carry provide a promising platform for facilitating these lifestyle changes. This paper describes key lessons learned from the development and evaluation of two mobile systems for encouraging physical activity. We argue that by supporting persistent cognitive activation of health goals, encouraging an extensive range of relevant healthy behaviors, focusing on long-term patterns of activity, and facilitating social support as an optional but not primary motivator, systems can be developed that effectively motivate behavior change and provide support when and where people make decisions that affect their health. PMID:20351876

A common mechanism underlies changes of mind about decisions and confidence

PubMed Central

van den Berg, Ronald; Anandalingam, Kavitha; Zylberberg, Ariel; Kiani, Roozbeh; Shadlen, Michael N; Wolpert, Daniel M

2016-01-01

Decisions are accompanied by a degree of confidence that a selected option is correct. A sequential sampling framework explains the speed and accuracy of decisions and extends naturally to the confidence that the decision rendered is likely to be correct. However, discrepancies between confidence and accuracy suggest that confidence might be supported by mechanisms dissociated from the decision process. Here we show that this discrepancy can arise naturally because of simple processing delays. When participants were asked to report choice and confidence simultaneously, their confidence, reaction time and a perceptual decision about motion were explained by bounded evidence accumulation. However, we also observed revisions of the initial choice and/or confidence. These changes of mind were explained by a continuation of the mechanism that led to the initial choice. Our findings extend the sequential sampling framework to vacillation about confidence and invites caution in interpreting dissociations between confidence and accuracy. DOI: http://dx.doi.org/10.7554/eLife.12192.001 PMID:26829590

Climate Change, Public Health, and Decision Support: The New Threat of Vector-borne Disease

NASA Astrophysics Data System (ADS)

Grant, F.; Kumar, S.

2011-12-01

Climate change and vector-borne diseases constitute a massive threat to human development. It will not be enough to cut emissions of greenhouse gases-the tide of the future has already been established. Climate change and vector-borne diseases are already undermining the world's efforts to reduce extreme poverty. It is in the best interests of the world leaders to think in terms of concerted global actions, but adaptation and mitigation must be accomplished within the context of local community conditions, resources, and needs. Failure to act will continue to consign developed countries to completely avoidable health risks and significant expense. Failure to act will also reduce poorest of the world's population-some 2.6 billion people-to a future of diminished opportunity. Northrop Grumman has taken significant steps forward to develop the tools needed to assess climate change impacts on public health, collect relevant data for decision making, model projections at regional and local levels; and, deliver information and knowledge to local and regional stakeholders. Supporting these tools is an advanced enterprise architecture consisting of high performance computing, GIS visualization, and standards-based architecture. To address current deficiencies in local planning and decision making with respect to regional climate change and its effect on human health, our research is focused on performing a dynamical downscaling with the Weather Research and Forecasting (WRF) model to develop decision aids that translate the regional climate data into actionable information for users. For the present climate WRF was forced with the Max Planck Institute European Center/Hamburg Model version 5 (ECHAM5) General Circulation Model 20th century simulation. For the 21th century climate, we used an ECHAM5 simulation with the Special Report on Emissions (SRES) A1B emissions scenario. WRF was run in nested mode at spatial resolution of 108 km, 36 km and 12 km and 28 vertical levels. This model was examined relative to two mosquito vectors, both competent carriers of dengue fever, a viral, vector-borne disease. Models which incorporate public health considerations can enable decision makers to take proactive steps to mitigate the impacts and adapt to the changing environmental conditions. In this paper we provide a snapshot of our climate initiative and some examples relative to our public health practice work in vector-borne diseases to illustrate how integrated decision support could be of assistance to regional and local communities worldwide.

Multi-disciplinary assessments of climate change impacts on agriculture to support adaptation decision making in developing countries

NASA Astrophysics Data System (ADS)

Fujisawa, Mariko; Kanamaru, Hideki

2016-04-01

Many existing climate change impact studies, carried out by academic researchers, are disconnected from decision making processes of stakeholders. On the other hand many climate change adaptation projects in developing countries lack a solid evidence base of current and future climate impacts as well as vulnerabilities assessment at different scales. In order to fill this information gap, FAO has developed and implemented a tool "MOSAICC (Modelling System for Agricultural Impacts of Climate Change)" in several developing countries such as Morocco, the Philippines and Peru, and recently in Malawi and Zambia. MOSAICC employs a multi-disciplinary assessment approach to addressing climate change impacts and adaptation planning in the agriculture and food security sectors, and integrates five components from different academic disciplines: 1. Statistical downscaling of climate change projections, 2. Yield simulation of major crops at regional scale under climate change, 3. Surface hydrology simulation model, 4. Macroeconomic model, and 5. Forestry model. Furthermore MOSAICC has been developed as a capacity development tool for the national scientists so that they can conduct the country assessment themselves, using their own data, and reflect the outcome into the national adaptation policies. The outputs are nation-wide coverage, disaggregated at sub-national level to support strategic planning, investments and decisions by national policy makers. MOSAICC is designed in such a way to promote stakeholders' participation and strengthen technical capacities in developing countries. The paper presents MOSAICC and projects that used MOSAICC as a tool with case studies from countries.

Automation bias: empirical results assessing influencing factors.

PubMed

Goddard, Kate; Roudsari, Abdul; Wyatt, Jeremy C

2014-05-01

To investigate the rate of automation bias - the propensity of people to over rely on automated advice and the factors associated with it. Tested factors were attitudinal - trust and confidence, non-attitudinal - decision support experience and clinical experience, and environmental - task difficulty. The paradigm of simulated decision support advice within a prescribing context was used. The study employed within participant before-after design, whereby 26 UK NHS General Practitioners were shown 20 hypothetical prescribing scenarios with prevalidated correct and incorrect answers - advice was incorrect in 6 scenarios. They were asked to prescribe for each case, followed by being shown simulated advice. Participants were then asked whether they wished to change their prescription, and the post-advice prescription was recorded. Rate of overall decision switching was captured. Automation bias was measured by negative consultations - correct to incorrect prescription switching. Participants changed prescriptions in 22.5% of scenarios. The pre-advice accuracy rate of the clinicians was 50.38%, which improved to 58.27% post-advice. The CDSS improved the decision accuracy in 13.1% of prescribing cases. The rate of automation bias, as measured by decision switches from correct pre-advice, to incorrect post-advice was 5.2% of all cases - a net improvement of 8%. More immediate factors such as trust in the specific CDSS, decision confidence, and task difficulty influenced rate of decision switching. Lower clinical experience was associated with more decision switching. Age, DSS experience and trust in CDSS generally were not significantly associated with decision switching. This study adds to the literature surrounding automation bias in terms of its potential frequency and influencing factors. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Retooling the nurse executive for 21st century practice: decision support systems.

PubMed

Fralic, M F; Denby, C B

2000-01-01

Health care financing and care delivery systems are changing at almost warp speed. This requires new responses and new capabilities from contemporary nurse executives and calls for new approaches to the preparation of the next generation of nursing leaders. The premise of this article is that, in these highly unstable environments, the nurse executive faces the need to make high-impact decisions in relatively short time frames. A standardized process for objective decision making becomes essential. This article describes that process.

Modelling and Decision Support of Clinical Pathways

NASA Astrophysics Data System (ADS)

Gabriel, Roland; Lux, Thomas

The German health care market is under a rapid rate of change, forcing especially hospitals to provide high-quality services at low costs. Appropriate measures for more effective and efficient service provision are process orientation and decision support by information technology of clinical pathway of a patient. The essential requirements are adequate modelling of clinical pathways as well as usage of adequate systems, which are capable of assisting the complete path of a patient within a hospital, and preferably also outside of it, in a digital way. To fulfil these specifications the authors present a suitable concept, which meets the challenges of well-structured clinical pathways as well as rather poorly structured diagnostic and therapeutic decisions, by interplay of process-oriented and knowledge-based hospital information systems.

Sustaining Changes that Support Student Success in Community College

ERIC Educational Resources Information Center

Burdman, Pamela

2009-01-01

Because of the increasingly prominent role of foundations in supporting improved opportunities for community college students, it may be helpful to understand how foundations set priorities and make decisions. Some foundations engage in responsive grant making, whereby they outline priority areas and then respond to proposals received from the…

Support for Assessment Practice: Developing the Assessment Design Decisions Framework

ERIC Educational Resources Information Center

Bearman, Margaret; Dawson, Phillip; Boud, David; Bennett, Sue; Hall, Matt; Molloy, Elizabeth

2016-01-01

There are many excellent publications outlining features of assessment and feedback design in higher education. However, university educators often find these ideas challenging to realise in practice, as much of the literature focuses on institutional change rather than supporting academics. This paper describes the conceptual development of a…

Robustness of risk maps and survey networks to knowledge gaps about a new invasive pest

Treesearch

Denys Yemshanov; Frank H. Koch; Yakov Ben-Haim; William D. Smith

2010-01-01

In pest risk assessment it is frequently necessary to make management decisions regarding emerging threats under severe uncertainty. Although risk maps provide useful decision support for invasive alien species, they rarely address knowledge gaps associated with the underlying risk model or how they may change the risk estimates. Failure to recognize uncertainty leads...

An Ecosystem Service Evaluation Tool to Support Ridge-to-Reef Management and Conservation in Hawaii

NASA Astrophysics Data System (ADS)

Oleson, K.; Callender, T.; Delevaux, J. M. S.; Falinski, K. A.; Htun, H.; Jin, G.

2014-12-01

Faced with increasing anthropogenic stressors and diverse stakeholders, local managers are adopting a ridge-to-reef and multi-objective management approach to restore declining coral reef health state. An ecosystem services framework, which integrates ecological indicators and stakeholder values, can foster more applied and integrated research, data collection, and modeling, and thus better inform the decision-making process and realize decision outcomes grounded in stakeholders' values. Here, we describe a research program that (i) leverages remotely sensed and empirical data to build an ecosystem services-based decision-support tool geared towards ridge-to-reef management; and (ii) applies it as part of a structured, value-based decision-making process to inform management in west Maui, a NOAA coral reef conservation priority site. The tool links terrestrial and marine biophysical models in a spatially explicit manner to quantify and map changes in ecosystem services delivery resulting from management actions, projected climate change impacts, and adaptive responses. We couple model outputs with localized valuation studies to translate ecosystem service outcomes into benefits and their associated socio-cultural and/or economic values. Managers can use this tool to run scenarios during their deliberations to evaluate trade-offs, cost-effectiveness, and equity implications of proposed policies. Ultimately, this research program aims at improving the effectiveness, efficiency, and equity outcomes of ecosystem-based management. This presentation will describe our approach, summarize initial results from the terrestrial modeling and economic valuations for west Maui, and highlight how this decision support tool benefits managers in west Maui.

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.

Creating a GIS-Based Decision-Support System

NASA Technical Reports Server (NTRS)

Alvarado, Lori; Gates, Ann Q.; Gray, Bob; Reyes, Raul

1998-01-01

Tilting the Balance: Climate Variability and Water Resource Management in the Southwest, a regional conference hosted by the Pan American Center for Environmental Studies, will be held at The University of Texas at El Paso on March 2-4, 1998. The conference is supported through the US Global Change Research Program (USGCRP) established by the President in 1989, and codified by Congress in the Global Change Research Act of 1990. The NASA Mission to Planet Earth program is one of the workshops sponsors. The purpose of the regional workshops is to improve understanding of the consequences of global change. This workshop will be focused on issues along the border and the Rio Grande River and thus will bring together stakeholders from Mexico, California, Texas, New Mexico, Arizona and Colorado representing federal, state, and local governments; universities and laboratories; industry, agricultural and natural resource managers; and non-governmental organizations. This paper discusses the efforts of the NASA PACES center create a GIS-based decision-support system that can be used to facilitate discussion of the complex issues of resource management within the targeted international region.

Projected 2050 Model Simulations for the Chesapeake Bay ...

EPA Pesticide Factsheets

The Chesapeake Bay Program as has been tasked with assessing how changes in climate systems are expected to alter key variables and processes within the Watershed in concurrence with land use changes. EPA’s Office of Research and Development will be conducting historic and future, 2050, Weather Research and Forecast (WRF) metrological and Community Multiscale Air Quality (CMAQ) chemical transport model simulations to provide meteorological and nutrient deposition estimates for inclusion of the Chesapeake Bay Program’s assessment of how climate and land use change may impact water quality and ecosystem health. This presentation will present the timeline and research updates. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.

What is a good medical decision? A research agenda guided by perspectives from multiple stakeholders.

PubMed

Hamilton, Jada G; Lillie, Sarah E; Alden, Dana L; Scherer, Laura; Oser, Megan; Rini, Christine; Tanaka, Miho; Baleix, John; Brewster, Mikki; Craddock Lee, Simon; Goldstein, Mary K; Jacobson, Robert M; Myers, Ronald E; Zikmund-Fisher, Brian J; Waters, Erika A

2017-02-01

Informed and shared decision making are critical aspects of patient-centered care, which has contributed to an emphasis on decision support interventions to promote good medical decision making. However, researchers and healthcare providers have not reached a consensus on what defines a good decision, nor how to evaluate it. This position paper, informed by conference sessions featuring diverse stakeholders held at the 2015 Society of Behavioral Medicine and Society for Medical Decision Making annual meetings, describes key concepts that influence the decision making process itself and that may change what it means to make a good decision: interpersonal factors, structural constraints, affective influences, and values clarification methods. This paper also proposes specific research questions within each of these priority areas, with the goal of moving medical decision making research to a more comprehensive definition of a good medical decision, and enhancing the ability to measure and improve the decision making process.

Pupil dilation signals uncertainty and surprise in a learning gambling task.

PubMed

Lavín, Claudio; San Martín, René; Rosales Jubal, Eduardo

2013-01-01

Pupil dilation under constant illumination is a physiological marker where modulation is related to several cognitive functions involved in daily decision making. There is evidence for a role of pupil dilation change during decision-making tasks associated with uncertainty, reward-prediction errors and surprise. However, while some work suggests that pupil dilation is mainly modulated by reward predictions, others point out that this marker is related to uncertainty signaling and surprise. Supporting the latter hypothesis, the neural substrate of this marker is related to noradrenaline (NA) activity which has been also related to uncertainty signaling. In this work we aimed to test whether pupil dilation is a marker for uncertainty and surprise in a learning task. We recorded pupil dilation responses in 10 participants performing the Iowa Gambling Task (IGT), a decision-making task that requires learning and constant monitoring of outcomes' feedback, which are important variables within the traditional study of human decision making. Results showed that pupil dilation changes were modulated by learned uncertainty and surprise regardless of feedback magnitudes. Interestingly, greater pupil dilation changes were found during positive feedback (PF) presentation when there was lower uncertainty about a future negative feedback (NF); and by surprise during NF presentation. These results support the hypothesis that pupil dilation is a marker of learned uncertainty, and may be used as a marker of NA activity facing unfamiliar situations in humans.

Pupil dilation signals uncertainty and surprise in a learning gambling task

PubMed Central

Lavín, Claudio; San Martín, René; Rosales Jubal, Eduardo

2014-01-01

Pupil dilation under constant illumination is a physiological marker where modulation is related to several cognitive functions involved in daily decision making. There is evidence for a role of pupil dilation change during decision-making tasks associated with uncertainty, reward-prediction errors and surprise. However, while some work suggests that pupil dilation is mainly modulated by reward predictions, others point out that this marker is related to uncertainty signaling and surprise. Supporting the latter hypothesis, the neural substrate of this marker is related to noradrenaline (NA) activity which has been also related to uncertainty signaling. In this work we aimed to test whether pupil dilation is a marker for uncertainty and surprise in a learning task. We recorded pupil dilation responses in 10 participants performing the Iowa Gambling Task (IGT), a decision-making task that requires learning and constant monitoring of outcomes’ feedback, which are important variables within the traditional study of human decision making. Results showed that pupil dilation changes were modulated by learned uncertainty and surprise regardless of feedback magnitudes. Interestingly, greater pupil dilation changes were found during positive feedback (PF) presentation when there was lower uncertainty about a future negative feedback (NF); and by surprise during NF presentation. These results support the hypothesis that pupil dilation is a marker of learned uncertainty, and may be used as a marker of NA activity facing unfamiliar situations in humans. PMID:24427126

Decision support system for the operating room rescheduling problem.

PubMed

van Essen, J Theresia; Hurink, Johann L; Hartholt, Woutske; van den Akker, Bernd J

2012-12-01

Due to surgery duration variability and arrivals of emergency surgeries, the planned Operating Room (OR) schedule is disrupted throughout the day which may lead to a change in the start time of the elective surgeries. These changes may result in undesirable situations for patients, wards or other involved departments, and therefore, the OR schedule has to be adjusted. In this paper, we develop a decision support system (DSS) which assists the OR manager in this decision by providing the three best adjusted OR schedules. The system considers the preferences of all involved stakeholders and only evaluates the OR schedules that satisfy the imposed resource constraints. The decision rules used for this system are based on a thorough analysis of the OR rescheduling problem. We model this problem as an Integer Linear Program (ILP) which objective is to minimize the deviation from the preferences of the considered stakeholders. By applying this ILP to instances from practice, we determined that the given preferences mainly lead to (i) shifting a surgery and (ii) scheduling a break between two surgeries. By using these changes in the DSS, the performed simulation study shows that less surgeries are canceled and patients and wards are more satisfied, but also that the perceived workload of several departments increases to compensate this. The system can also be used to judge the acceptability of a proposed initial OR schedule.

The aging work force--helping employees navigate midlife.

PubMed

Leggett, Diane

2007-04-01

The baby-boom generation is aging and workplace demographics are changing. Employees in this age group are now middle-aged. Occupational health nurses are in a unique position to guide these individuals through decisions that can affect the years ahead. Individuals in midlife may experience both physical and psychological changes, including changing physical appearance, decreased stamina, loss of family or friends, and altered vision. In the workplace, annual assessments can include evaluations to address normal changes, personal expectations, and needed support, counseling, or referrals. Middle-aged men and women are at a predictable turning point in life that offers an opportunity for growth. Education in the workplace can assist these individuals as they adjust to changes in relationships, make health care decisions, and plan for retirement.

Developing an Ecosystem Services Online Decision Support Tool to Assess the Impacts of Climate Change and Urban Growth in the Santa Cruz Watershed: Where We Live, Work, and Play

USGS Publications Warehouse

Norman, Laura; Tallent-Halsell, Nita; Labiosa, William; Weber, Matt; McCoy, Amy; Hirschboeck, Katie; Callegary, James; van Riper, Charles; Gray, Floyd

2010-01-01

Using respective strengths of the biological, physical, and social sciences, we are developing an online decision support tool, the Santa Cruz Watershed Ecosystem Portfolio Model (SCWEPM), to help promote the use of information relevant to water allocation and land management in a binational watershed along the U.S.-Mexico border. The SCWEPM will include an ES valuation system within a suite of linked regional driver-response models and will use a multicriteria scenario-evaluation framework that builds on GIS analysis and spatially-explicit models that characterize important ecological, economic, and societal endpoints and consequences that are sensitive to climate patterns, regional water budgets, and regional LULC change in the SCW.

Socio-Hydrology Modelling for an Uncertain Future, with Examples from the USA and Canada (Invited)

NASA Astrophysics Data System (ADS)

White, D. D.; Gober, P.; Sampson, D. A.; Quay, R.; Kirkwood, C.

2013-12-01

Socio-hydrology brings an interest in human values, markets, social organizations and public policy to the traditional emphasis of water science on climate, hydrology, toxicology,and ecology. It also conveys a decision focus in the form of decision support tools, engagement, and new knowledge about the science-policy interface. This paper demonstrates how policy decisions and human behavior can be better integrated into climate and hydrological models to improve their usefulness for support in decision making. Examples from the Southwest USA and Western Canada highlight uncertainties, vulnerabilities, and critical tradeoffs facing water decision makers in the face of rapidly changing environmental and societal conditions. Irreducible uncertainties in downscaled climate and hydrological models limit the usefulness of climate-driven, predict-and-plan methods of water resource planning and management. Thus, it is argued that such methods should be replaced by approaches that use exploratory modelling, scenario planning, and risk assessment in which the emphasis is on managing uncertainty rather than on reducing it.

The development and application of a decision support system for land management in the Lake Tahoe Basin—The Land Use Simulation Model

USGS Publications Warehouse

Forney, William M.; Oldham, I. Benson; Crescenti, Neil

2013-01-01

This report describes and applies the Land Use Simulation Model (LUSM), the final modeling product for the long-term decision support project funded by the Southern Nevada Public Land Management Act and developed by the U.S. Geological Survey’s Western Geographic Science Center for the Lake Tahoe Basin. Within the context of the natural-resource management and anthropogenic issues of the basin and in an effort to advance land-use and land-cover change science, this report addresses the problem of developing the LUSM as a decision support system. It includes consideration of land-use modeling theory, fire modeling and disturbance in the wildland-urban interface, historical land-use change and its relation to active land management, hydrologic modeling and the impact of urbanization as related to the Lahontan Regional Water Quality Control Board’s recently developed Total Maximum Daily Load report for the basin, and biodiversity in urbanizing areas. The LUSM strives to inform land-management decisions in a complex regulatory environment by simulating parcel-based, land-use transitions with a stochastic, spatially constrained, agent-based model. The tool is intended to be useful for multiple purposes, including the multiagency Pathway 2007 regional planning effort, the Tahoe Regional Planning Agency (TRPA) Regional Plan Update, and complementary research endeavors and natural-resource-management efforts. The LUSM is an Internet-based, scenario-generation decision support tool for allocating retired and developed parcels over the next 20 years. Because USGS staff worked closely with TRPA staff and their “Code of Ordinances” and analyzed datasets of historical management and land-use practices, this report accomplishes the task of providing reasonable default values for a baseline scenario that can be used in the LUSM. One result from the baseline scenario for the model suggests that all vacant parcels could be allocated within 12 years. Results also include: assessment of model functionality, brief descriptions of the 7 basic output tables, assessment of the rate of change in land-use allocation pools over time, locations and amounts of the spatially explicit probabilities of land-use transitions by real estate commodity, and analysis of the state change from today’s existing land cover to potential land uses in the future. Assumptions and limitations of the model are presented. This report concludes with suggested next steps to support the continued utility of the LUSM and additional research avenues.

A qualitative analysis of coronary heart disease patient views of dietary adherence and web-based and mobile-based nutrition tools

PubMed Central

Yehle, Karen S.; Chen, Aleda M. H.; Plake, Kimberly S.; Yi, Ji Soo; Mobley, Amy R.

2012-01-01

PURPOSE Dietary adherence can be challenging for patients with coronary heart disease (CHD), as they may require multiple dietary changes. Choosing appropriate food items may be difficult or take extensive amounts of time without the aid of technology. The objective of this project was to (1) examine the dietary challenges faced by patients with CHD, (2) examine methods of coping with dietary challenges, (3) explore the feasibility of a web-based food decision support system, and (4) explore the feasibility of a mobile-based food decision support system. METHODS Food for the Heart (FFH), a website-based food decision support system, and Mobile Magic Lens (MML), a mobile-based system, were developed to aid in daily dietary choices. Three CHD patient focus groups were conducted and focused on CHD-associated dietary changes as well as the FFH and MML prototypes. A total of 20 CHD patients and 7 informal caregivers participated. Qualitative, content analysis was performed to find themes grounded in the responses. RESULTS Five predominant themes emerged: 1) decreasing carbohydrate intake and portion control are common dietary challenges, 2) clinician and social support makes dietary adherence easier, 3) FFH could make meal-planning and dietary adherence less complicated, 4) MML could save time and assist with healthy choices, and 5) additional features need to be added to make both tools more comprehensive. CONCLUSIONS FFH and MML may be tools that CHD patients would value in making food choices and adhering to dietary recommendations, especially if additional features are added to assist patients with changes. PMID:22760245

Supporting Students' Learning and Socioscientific Reasoning About Climate Change—the Effect of Computer-Based Concept Mapping Scaffolds

NASA Astrophysics Data System (ADS)

Eggert, Sabina; Nitsch, Anne; Boone, William J.; Nückles, Matthias; Bögeholz, Susanne

2017-02-01

Climate change is one of the most challenging problems facing today's global society (e.g., IPCC 2013). While climate change is a widely covered topic in the media, and abundant information is made available through the internet, the causes and consequences of climate change in its full complexity are difficult for individuals, especially non-scientists, to grasp. Science education is a field which can play a crucial role in fostering meaningful education of students to become climate literate citizens (e.g., NOAA 2009; Schreiner et al., 41, 3-50, 2005). If students are, at some point, to participate in societal discussions about the sustainable development of our planet, their learning with respect to such issues needs to be supported. This includes the ability to think critically, to cope with complex scientific evidence, which is often subject to ongoing inquiry, and to reach informed decisions on the basis of factual information as well as values-based considerations. The study presented in this paper focused on efforts to advance students in (1) their conceptual understanding about climate change and (2) their socioscientific reasoning and decision making regarding socioscientific issues in general. Although there is evidence that "knowledge" does not guarantee pro-environmental behavior (e.g. Schreiner et al., 41, 3-50, 2005; Skamp et al., 97(2), 191-217, 2013), conceptual, interdisciplinary understanding of climate change is an important prerequisite to change individuals' attitudes towards climate change and thus to eventually foster climate literate citizens (e.g., Clark et al. 2013). In order to foster conceptual understanding and socioscientific reasoning, a computer-based learning environment with an embedded concept mapping tool was utilized to support senior high school students' learning about climate change and possible solution strategies. The evaluation of the effect of different concept mapping scaffolds focused on the quality of student-generated concept maps, as well as on students' test performance with respect to conceptual knowledge as well as socioscientific reasoning and socioscientific decision making.

How people with dementia and their families decide about moving to a care home and support their needs: development of a decision aid, a qualitative study.

PubMed

Lord, Kathryn; Livingston, Gill; Robertson, Sarah; Cooper, Claudia

2016-03-21

People with dementia and their relatives find decisions about the person with dementia living in a care home difficult. We interviewed 20 people with dementia or family carers around the time of this decision in order to design a decision-aid. Decision-makers balanced the competing priorities of remaining somewhere familiar, family's wish they remain at home, reduction of risk and effects on carer's and person with dementia's physical health. The person with dementia frequently resented their lack of autonomy as decisions about care home moves were made after insight and judgment were impaired. Family consultation usually helped carers but sometimes exacerbated tensions. Direct professional support was appreciated where it was available. There is a need for healthcare professionals to facilitate these conversations around decision-making and to include more than signposting to other organisations. There is a need for a healthcare professional facilitated decision-aid. This should detail what might change for the person with dementia and their carer, possible resources and alternatives and assist in facilitating discussion with the wider family; further research will develop and test a tool to facilitate decision making about place of care needs.

Behaviour change in overweight and obese pregnancy: a decision tree to support the development of antenatal lifestyle interventions.

PubMed

Ainscough, Kate M; Lindsay, Karen L; O'Sullivan, Elizabeth J; Gibney, Eileen R; McAuliffe, Fionnuala M

2017-10-01

Antenatal healthy lifestyle interventions are frequently implemented in overweight and obese pregnancy, yet there is inconsistent reporting of the behaviour-change methods and behavioural outcomes. This limits our understanding of how and why such interventions were successful or not. The current paper discusses the application of behaviour-change theories and techniques within complex lifestyle interventions in overweight and obese pregnancy. The authors propose a decision tree to help guide researchers through intervention design, implementation and evaluation. The implications for adopting behaviour-change theories and techniques, and using appropriate guidance when constructing and evaluating interventions in research and clinical practice are also discussed. To enhance the evidence base for successful behaviour-change interventions during pregnancy, adoption of behaviour-change theories and techniques, and use of published guidelines when designing lifestyle interventions are necessary. The proposed decision tree may be a useful guide for researchers working to develop effective behaviour-change interventions in clinical settings. This guide directs researchers towards key literature sources that will be important in each stage of study development.

All Source Solution Decision Support Products Created for Stennis Space Center in Response to Hurricane Katrina

NASA Technical Reports Server (NTRS)

Ross, Kenton W.; Graham, William D.

2007-01-01

In the aftermath of Hurricane Katrina and in response to the needs of SSC (Stennis Space Center), NASA required the generation of decision support products with a broad range of geospatial inputs. Applying a systems engineering approach, the NASA ARTPO (Applied Research and Technology Project Office) at SSC evaluated the Center's requirements and source data quality. ARTPO identified data and information products that had the potential to meet decision-making requirements; included were remotely sensed data ranging from high-spatial-resolution aerial images through high-temporal-resolution MODIS (Moderate Resolution Imaging Spectroradiometer) products. Geospatial products, such as FEMA's (Federal Emergency Management Agency's) Advisory Base Flood Elevations, were also relevant. Where possible, ARTPO applied SSC calibration/validation expertise to both clarify the quality of various data source options and to validate that the inputs that were finally chosen met SSC requirements. ARTPO integrated various information sources into multiple decision support products, including two maps: Hurricane Katrina Inundation Effects at Stennis Space Center (highlighting surge risk posture) and Vegetation Change In and Around Stennis Space Center: Katrina and Beyond (highlighting fire risk posture).

Decision-support tools for Extreme Weather and Climate Events in the Northeast United States

NASA Astrophysics Data System (ADS)

Kumar, S.; Lowery, M.; Whelchel, A.

2013-12-01

Decision-support tools were assessed for the 2013 National Climate Assessment technical input document, "Climate Change in the Northeast, A Sourcebook". The assessment included tools designed to generate and deliver actionable information to assist states and highly populated urban and other communities in assessment of climate change vulnerability and risk, quantification of effects, and identification of adaptive strategies in the context of adaptation planning across inter-annual, seasonal and multi-decadal time scales. State-level adaptation planning in the Northeast has generally relied on qualitative vulnerability assessments by expert panels and stakeholders, although some states have undertaken initiatives to develop statewide databases to support vulnerability assessments by urban and local governments, and state agencies. The devastation caused by Superstorm Sandy in October 2012 has raised awareness of the potential for extreme weather events to unprecedented levels and created urgency for action, especially in coastal urban and suburban communities that experienced pronounced impacts - especially in New Jersey, New York and Connecticut. Planning approaches vary, but any adaptation and resiliency planning process must include the following: - Knowledge of the probable change in a climate variable (e.g., precipitation, temperature, sea-level rise) over time or that the climate variable will attain a certain threshold deemed to be significant; - Knowledge of intensity and frequency of climate hazards (past, current or future events or conditions with potential to cause harm) and their relationship with climate variables; - Assessment of climate vulnerabilities (sensitive resources, infrastructure or populations exposed to climate-related hazards); - Assessment of relative risks to vulnerable resources; - Identification and prioritization of adaptive strategies to address risks. Many organizations are developing decision-support tools to assist in the urban planning process by addressing some of these needs. In this paper we highlight the decision tools available today, discuss their application in selected case studies, and present a gap analysis with opportunities for innovation and future work.

Liminality and decision making for upper limb surgery in tetraplegia: a grounded theory.

PubMed

Dunn, Jennifer A; Hay-Smith, E Jean C; Whitehead, Lisa C; Keeling, Sally

2013-07-01

To explore, from the perspective of the person with tetraplegia, the issues that influenced decision making about upper limb surgery and develop a conceptual framework describing the decision making process. Purposive and theoretical sampling of 22 people with tetraplegia, followed by interviews. Ten people had upper limb surgery and 12 had not. Verbatim transcripts were analyzed with constructivist grounded theory. Participants responded to the offer of surgery in one of three ways: yes, let me have it; no thanks; or possibly. Many influences on the decision about surgery had a temporal element, such as hope for the cure or recovery from SCI, inadequate physical or social supports while rehabilitating, life roles and goals, and the avoidance of re-hospitalization. The conceptual framework illustrated that many participants entered a liminal state within which they required a stimulus to review their decision about upper limb surgery. Decision making is a temporal process, and for some the process was a prolonged and liminal one. Therefore, multiple offers for surgery are required to allow for changing thoughts and circumstances throughout an individual's lifetime. Flexibility with regard to timing for surgery and type of rehabilitation may increase the uptake, especially for women. • Multiple offers for upper limb surgery are required throughout an individual's lifetime to account for changing thoughts and priorities. • Identification of the type of support required (informational, emotional) may assist in decreasing the time taken to make the decision about surgery. • Flexibility in surgical and rehabilitation options, especially for women, may increase the uptake of surgery.

Nursing clinical practice changes to improve self-management in chronic obstructive pulmonary disease.

PubMed

Padilha, J M; Sousa, P A F; Pereira, F M S

2018-03-01

To propose nursing clinical practice changes to improve the development of patient self-management. Chronic obstructive pulmonary disease is one of the main causes of chronic morbidity, loss of quality of life and high mortality rates. Control of the disease's progression, the preservation of autonomy in self-care and maintenance of quality of life are extremely challenging for patients to execute in their daily living. However, there is still little evidence to support nursing clinical practice changes to improve the development of self-management. A participatory action research study was performed in a medicine inpatient department and the outpatient unit of a Portuguese hospital. The sample comprised 52 nurses and 99 patients. For data collection, we used interviews, participant observation and content analysis. The main elements of nursing clinical practice that were identified as a focus for improvement measures were the healthcare model, the organization of healthcare and the documentation of a support decision-making process. The specific guidelines, the provision of material to support decision-making and the optimization of information sharing between professionals positively influenced the change process. This change improved the development of self-management skills related to the awareness of the need for 'change', hope, involvement, knowledge and abilities. The implemented changes have improved health-related behaviours and clinical outcomes. To support self-management development skills, an effective nursing clinical practice change is needed. This study has demonstrated the relevance of a portfolio of techniques and tools to help patients adopt healthy behaviours. The involvement and participation of nurses and patients in the conceptualization, implementation and evaluation of policy change are fundamental issues to improve the quality of nursing care and clinical outcomes. © 2017 International Council of Nurses.

New Methods for Crafting Locally Decision-Relevant Scenarios

NASA Astrophysics Data System (ADS)

Lempert, R. J.

2015-12-01

Scenarios can play an important role in helping decision makers to imagine future worlds, both good and bad, different than the one with which we are familiar and to take concrete steps now to address the risks generated by climate change. At their best, scenarios can effectively represent deep uncertainty; integrate over multiple domains; and enable parties with different expectation and values to expand the range of futures they consider, to see the world from different points of view, and to grapple seriously with the potential implications of surprising or inconvenient futures. These attributes of scenario processes can prove crucial in helping craft effective responses to climate change. But traditional scenario methods can also fail to overcome difficulties related to choosing, communicating, and using scenarios to identify, evaluate, and reach consensus on appropriate policies. Such challenges can limit scenario's impact in broad public discourse. This talk will demonstrate how new decision support approaches can employ new quantitative tools that allow scenarios to emerge from a process of deliberation with analysis among stakeholders, rather than serve as inputs to it, thereby increasing the impacts of scenarios on decision making. This talk will demonstrate these methods in the design of a decision support tool to help residents of low lying coastal cities grapple with the long-term risks of sea level rise. In particular, this talk will show how information from the IPCC SSP's can be combined with local information to provide a rich set of locally decision-relevant information.

The Effects of Evidence Bounds on Decision-Making: Theoretical and Empirical Developments

PubMed Central

Zhang, Jiaxiang

2012-01-01

Converging findings from behavioral, neurophysiological, and neuroimaging studies suggest an integration-to-boundary mechanism governing decision formation and choice selection. This mechanism is supported by sequential sampling models of choice decisions, which can implement statistically optimal decision strategies for selecting between multiple alternative options on the basis of sensory evidence. This review focuses on recent developments in understanding the evidence boundary, an important component of decision-making raised by experimental findings and models. The article starts by reviewing the neurobiology of perceptual decisions and several influential sequential sampling models, in particular the drift-diffusion model, the Ornstein–Uhlenbeck model and the leaky-competing-accumulator model. In the second part, the article examines how the boundary may affect a model’s dynamics and performance and to what extent it may improve a model’s fits to experimental data. In the third part, the article examines recent findings that support the presence and site of boundaries in the brain. The article considers two questions: (1) whether the boundary is a spontaneous property of neural integrators, or is controlled by dedicated neural circuits; (2) if the boundary is variable, what could be the driving factors behind boundary changes? The review brings together studies using different experimental methods in seeking answers to these questions, highlights psychological and physiological factors that may be associated with the boundary and its changes, and further considers the evidence boundary as a generic mechanism to guide complex behavior. PMID:22870070

The influence of gene expression profiling on decisional conflict in decision making for early-stage breast cancer chemotherapy.

PubMed

MacDonald, Karen V; Bombard, Yvonne; Deal, Ken; Trudeau, Maureen; Leighl, Natasha; Marshall, Deborah A

2016-07-01

Women with early-stage breast cancer, of whom only 15% will experience a recurrence, are often conflicted or uncertain about taking chemotherapy. Gene expression profiling (GEP) of tumours informs risk prediction, potentially affecting treatment decisions. We examined whether receiving a GEP test score reduces decisional conflict in chemotherapy treatment decision making. A general population sample of 200 women completed the decisional conflict scale (DCS) at baseline (no GEP test score scenario) and after (scenario with GEP test score added) completing a discrete choice experiment survey for early-stage breast cancer chemotherapy. We scaled the 16-item DCS total scores and subscores from 0 to 100 and calculated means, standard deviations and change in scores, with significance (p < 0.05) based on matched pairs t-tests. We identified five respondent subgroups based on preferred treatment option; almost 40% did not change their chemotherapy decision after receiving GEP testing information. Total score and all subscores (uncertainty, informed, values clarity, support, and effective decision) decreased significantly in the respondent subgroup who were unsure about taking chemotherapy initially but changed to no chemotherapy (n =33). In the subgroup of respondents (n = 25) who chose chemotherapy initially but changed to unsure, effective decision subscore increased significantly. In the overall sample, changes in total and all subscores were non-significant. GEP testing adds value for women initially unsure about chemotherapy treatment with a decrease in decisional conflict. However, for women who are confident about their treatment decisions, GEP testing may not add value. Decisions to request GEP testing should be personalised based on patient preferences. Copyright © 2016 Elsevier Ltd. All rights reserved.

Decision support system based on DPSIR framework for a low flow Mediterranean river basin

NASA Astrophysics Data System (ADS)

Bangash, Rubab Fatima; Kumar, Vikas; Schuhmacher, Marta

2013-04-01

The application of decision making practices are effectively enhanced by adopting a procedural approach setting out a general methodological framework within which specific methods, models and tools can be integrated. Integrated Catchment Management is a process that recognizes the river catchment as a basic organizing unit for understanding and managing ecosystem process. Decision support system becomes more complex by considering unavoidable human activities within a catchment that are motivated by multiple and often competing criteria and/or constraints. DPSIR is a causal framework for describing the interactions between society and the environment. This framework has been adopted by the European Environment Agency and the components of this model are: Driving forces, Pressures, States, Impacts and Responses. The proposed decision support system is a two step framework based on DPSIR. Considering first three component of DPSIR, Driving forces, Pressures and States, hydrological and ecosystem services models are developed. The last two components, Impact and Responses, helped to develop Bayesian Network to integrate the models. This decision support system also takes account of social, economic and environmental aspects. A small river of Catalonia (Northeastern Spain), Francoli River with a low flow (~2 m3/s) is selected for integration of catchment assessment models and to improve knowledge transfer from research to the stakeholders with a view to improve decision making process. DHI's MIKE BASIN software is used to evaluate the low-flow Francolí River with respect to the water bodies' characteristics and also to assess the impact of human activities aiming to achieve good water status for all waters to comply with the WFD's River Basin Management Plan. Based on ArcGIS, MIKE BASIN is a versatile decision support tool that provides a simple and powerful framework for managers and stakeholders to address multisectoral allocation and environmental issues in river basins. While InVEST is a spatially explicit tool, used to model and map a suite of ecosystem services caused by land cover changes or climate change impacts. Moreover, results obtained from low-flow hydrological simulation and ecosystem services models serves as useful tools to develop decision support system based on DPSIR framework by integrating models. Bayesian Networks is used as a knowledge integration and visualization tool to summarize the outcomes of hydrological and ecosystem services models at the "Response" stage of DPSIR. Bayesian Networks provide a framework for modelling the logical relationship between catchment variables and decision objectives by quantifying the strength of these relationships using conditional probabilities. Participatory nature of this framework can provide better communication of water research, particularly in the context of a perceived lack of future awareness-raising with the public that helps to develop more sustainable water management strategies. Acknowledgements The present study was financially supported by Spanish Ministry of Economy and Competitiveness for its financial support through the project SCARCE (Consolider-Ingenio 2010 CSD2009-00065). R. F. Bangash also received PhD fellowship from AGAUR (Commissioner for Universities and Research of the Department of Innovation, Universities and Enterprise of the "Generalitat de Catalunya" and the European Social Fund).

Diverting the tourists: a spatial decision-support system for tourism planning on a developing island

NASA Astrophysics Data System (ADS)

Beedasy, Jaishree; Whyatt, Duncan

Mauritius is a small island (1865 km 2) in the Indian Ocean. Tourism is the third largest economic sector of the country, after manufacturing and agriculture. A limitation of space and the island's vulnerable ecosystem warrants a rational approach to tourism development. The main problems so far have been to manipulate and integrate all the factors affecting tourism planning and to match spatial data with their relevant attributes. A Spatial Decision Support System (SDSS) for sustainable tourism planning is therefore proposed. The proposed SDSS design would include a GIS as its core component. A first GIS model has already been constructed with available data. Supporting decision-making in a spatial context is implicit in the use of GIS. However the analytical capability of the GIS has to be enhanced to solve semi-structured problems, where subjective judgements come into play. The second part of the paper deals with the choice, implementation and customisation of a relevant model to develop a specialised SDSS. Different types of models and techniques are discussed, in particular a comparison of compensatory and non-compensatory approaches to multicriteria evaluation (MCE). It is concluded that compensatory multicriteria evaluation techniques increase the scope of the present GIS model as a decision-support tool. This approach gives the user or decision-maker the flexibility to change the importance of each criterion depending on relevant objectives.

Knowledge representation and management enabling intelligent interoperability - principles and standards.

PubMed

Blobel, Bernd

2013-01-01

Based on the paradigm changes for health, health services and underlying technologies as well as the need for at best comprehensive and increasingly automated interoperability, the paper addresses the challenge of knowledge representation and management for medical decision support. After introducing related definitions, a system-theoretical, architecture-centric approach to decision support systems (DSSs) and appropriate ways for representing them using systems of ontologies is given. Finally, existing and emerging knowledge representation and management standards are presented. The paper focuses on the knowledge representation and management part of DSSs, excluding the reasoning part from consideration.

Sound data management as a foundation for natural resources management and science

USGS Publications Warehouse

Burley, Thomas E.

2012-01-01

Effective decision making is closely related to the quality and completeness of available data and information. Data management helps to ensure data quality in any discipline and supports decision making. Managing data as a long-term scientific asset helps to ensure that data will be usable beyond the original intended application. Emerging issues in water-resources management and climate variability require the ability to analyze change in the conditions of natural resources over time. The availability of quality, well-managed, and documented data from the past and present helps support this requirement.

Getting the Most from the Twin Mars Rovers

NASA Technical Reports Server (NTRS)

Laufenberg, Larry

2003-01-01

The report discusses the Mixed-initiative Activity Planning GENerator (MARGEN) automatically generates activity plans for rovers. Decision support system mixes autonomous planning/scheduling with user modifications. Accommodating change. Technology spotlight

Realizing the Potential of Ecosystem Services: A Framework for Relating Ecological Changes to Economic Benefits

EPA Science Inventory

An analysis framework to link ecological change to economic benefits for multiple stakeholders requires several key components. First, since we aim to support policy decisions, the framework should link a factor that can be controlled or influenced by policy (discharge limit, ca...

A work-centered cognitively based architecture for decision support: the work-centered infomediary layer (WIL) model

NASA Astrophysics Data System (ADS)

Zachary, Wayne; Eggleston, Robert; Donmoyer, Jason; Schremmer, Serge

2003-09-01

Decision-making is strongly shaped and influenced by the work context in which decisions are embedded. This suggests that decision support needs to be anchored by a model (implicit or explicit) of the work process, in contrast to traditional approaches that anchor decision support to either context free decision models (e.g., utility theory) or to detailed models of the external (e.g., battlespace) environment. An architecture for cognitively-based, work centered decision support called the Work-centered Informediary Layer (WIL) is presented. WIL separates decision support into three overall processes that build and dynamically maintain an explicit context model, use the context model to identify opportunities for decision support and tailor generic decision-support strategies to the current context and offer them to the system-user/decision-maker. The generic decision support strategies include such things as activity/attention aiding, decision process structuring, work performance support (selective, contextual automation), explanation/ elaboration, infosphere data retrieval, and what if/action-projection and visualization. A WIL-based application is a work-centered decision support layer that provides active support without intent inferencing, and that is cognitively based without requiring classical cognitive task analyses. Example WIL applications are detailed and discussed.

Simulation-based planning for theater air warfare

NASA Astrophysics Data System (ADS)

Popken, Douglas A.; Cox, Louis A., Jr.

2004-08-01

Planning for Theatre Air Warfare can be represented as a hierarchy of decisions. At the top level, surviving airframes must be assigned to roles (e.g., Air Defense, Counter Air, Close Air Support, and AAF Suppression) in each time period in response to changing enemy air defense capabilities, remaining targets, and roles of opposing aircraft. At the middle level, aircraft are allocated to specific targets to support their assigned roles. At the lowest level, routing and engagement decisions are made for individual missions. The decisions at each level form a set of time-sequenced Courses of Action taken by opposing forces. This paper introduces a set of simulation-based optimization heuristics operating within this planning hierarchy to optimize allocations of aircraft. The algorithms estimate distributions for stochastic outcomes of the pairs of Red/Blue decisions. Rather than using traditional stochastic dynamic programming to determine optimal strategies, we use an innovative combination of heuristics, simulation-optimization, and mathematical programming. Blue decisions are guided by a stochastic hill-climbing search algorithm while Red decisions are found by optimizing over a continuous representation of the decision space. Stochastic outcomes are then provided by fast, Lanchester-type attrition simulations. This paper summarizes preliminary results from top and middle level models.

Supporting dynamic change detection: using the right tool for the task.

PubMed

Vallières, Benoît R; Hodgetts, Helen M; Vachon, François; Tremblay, Sébastien

2016-01-01

Detecting task-relevant changes in a visual scene is necessary for successfully monitoring and managing dynamic command and control situations. Change blindness-the failure to notice visual changes-is an important source of human error. Change History EXplicit (CHEX) is a tool developed to aid change detection and maintain situation awareness; and in the current study we test the generality of its ability to facilitate the detection of changes when this subtask is embedded within a broader dynamic decision-making task. A multitasking air-warfare simulation required participants to perform radar-based subtasks, for which change detection was a necessary aspect of the higher-order goal of protecting one's own ship. In this task, however, CHEX rendered the operator even more vulnerable to attentional failures in change detection and increased perceived workload. Such support was only effective when participants performed a change detection task without concurrent subtasks. Results are interpreted in terms of the NSEEV model of attention behavior (Steelman, McCarley, & Wickens, Hum. Factors 53:142-153, 2011; J. Exp. Psychol. Appl. 19:403-419, 2013), and suggest that decision aids for use in multitasking contexts must be designed to fit within the available workload capacity of the user so that they may truly augment cognition.

Implementing and Sustaining School Improvement. Principal's Research Review: Supporting the Principal's Data-Informed Decisions. Vol. 6, No. 2

ERIC Educational Resources Information Center

Protheroe, Nancy

2011-01-01

School improvement can be a complex, messy business. At its most basic, school improvement is change--change that might require people to abandon long-held beliefs and practices, shift roles, and learn new skills. Kilgore and Reynolds (2011) suggested that successful change requires that people change their perceptions as well as their actions.…

Using DCOM to support interoperability in forest ecosystem management decision support systems

Treesearch

W.D. Potter; S. Liu; X. Deng; H.M. Rauscher

2000-01-01

Forest ecosystems exhibit complex dynamics over time and space. Management of forest ecosystems involves the need to forecast future states of complex systems that are often undergoing structural changes. This in turn requires integration of quantitative science and engineering components with sociopolitical, regulatory, and economic considerations. The amount of data...

Climate Information Needs for Financial Decision Making

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

Higgins, Paul

Climate Information Needs for Financial Decision Making (Final Report) This Department of Energy workshop award (grant #DE-SC0008480) provided primary support for the American Meteorological Society’s study on climate information needs for financial decision making. The goal of this study was to help advance societal decision making by examining the implications of climate variability and change on near-term financial investments. We explored four key topics: 1) the conditions and criteria that influence returns on investment of major financial decisions, 2) the climate sensitivity of financial decisions, 3) climate information needs of financial decision makers, and 4) potential new mechanisms to promotemore » collaboration between scientists and financial decision makers. Better understanding of these four topics will help scientists provide the most useful information and enable financial decision makers to use scientific information most effectively. As a result, this study will enable leaders in business and government to make well-informed choices that help maximize long-term economic success and social wellbeing in the United States The outcomes of the study include a workshop, which brought together leaders from the scientific and financial decision making communities, a publication of the study report, and a public briefing of the results to the policy community. In addition, we will present the results to the scientific community at the AMS Annual Meeting in February, 2014. The study results were covered well by the media including Bloomberg News and E&E News. Upon request, we also briefed the Office of Science Technology Policy (OSTP) and the Council on Environmental Quality (CEQ) on the outcomes. We presented the results to the policy community through a public briefing in December on Capitol Hill. The full report is publicly available at www.ametsoc.org/cin. Summary of Key Findings The United States invests roughly $1.5 trillion U.S. dollars (USD) in capital assets each year across the public and private sectors (Orszag 2008; United States Census Bureau 2013). Extreme weather events create and exacerbate risks to these financial investments by contributing to: • Direct physical impacts on the investments themselves • Degradation of critical supporting infrastructure • Changes in the availability of key natural resources • Changes to workforce availability or capacity • Changes in the customer base • Supply chain disruptions • Legal liability • Shifts in the regulatory environment • Reductions in credit ratings Even small changes in weather can impact operations in critical economic sectors. As a result, maximizing returns on financial investments depends on accurately understanding and effectively accounting for these risks. Climate variability and change can either exacerbate existing risks or cause new sources of risk to emerge. Managing these risks most effectively will depend on scientific advances and increases in the capacity of financial decision makers to use the scientific knowledge that results. Barriers to using climate information must also be overcome. This study proposes three predefined levels of certainty for communicating about weather and climate risks: 1) possible (i.e., unknown likelihood or less than 50% chance of occurrence), 2) probable (greater than 50% chance of occurrence), and 3) effectively certain (at least 95% chance of occurrence). For example, it is effectively certain that a change in climate will alter weather patterns. It is probable that climate warming will cause increases in the intensity of some extreme events. It is possible that climate change will cause major and widespread disruptions to key planetary life-support services. Key recommendations of this study: 1) Identify climate-related risks and opportunities for financial decision making. 2) Create a framework to translate scientific information in clear and actionable terms for financial decision makers. 3) Analyze existing climate assessments and translate projected impacts into possible, probable, and effectively certain impacts. 4) Improve climate projections with respect to precipitation (timing, amount, and intensity), extreme events, and tails of probability distributions (i.e., low-probability but high-consequence events). 5) Increase spatial resolution of climate projections in order to provide climate information at the scale most relevant to financial investments. 6) Improve projections of the societal consequences of climate impacts through integrated assessments of physical, natural, and social sciences. 7) Create a user-friendly information repository and portal that provides easy access to information relevant to financial decision making. 8) Create and maintain opportunities to bring together financial decision makers, scientists, and service providers. Near-term financial decisions have long-term implications for the United States’ social and economic well-being that depend, in part, on climate variability and change. Investments will be most successful, and will advance the interests of society most effectively, if they are grounded in the best available knowledge & understanding.« less

An algorithmic interactive planning framework in support of sustainable technologies

NASA Astrophysics Data System (ADS)

Prica, Marija D.

This thesis addresses the difficult problem of generation expansion planning that employs the most effective technologies in today's changing electric energy industry. The electrical energy industry, in both the industrialized world and in developing countries, is experiencing transformation in a number of different ways. This transformation is driven by major technological breakthroughs (such as the influx of unconventional smaller-scale resources), by industry restructuring, changing environmental objectives, and the ultimate threat of resource scarcity. This thesis proposes a possible planning framework in support of sustainable technologies where sustainability is viewed as a mix of multiple attributes ranging from reliability and environmental impact to short- and long-term efficiency. The idea of centralized peak-load pricing, which accounts for the tradeoffs between cumulative operational effects and the cost of new investments, is the key concept in support of long-term planning in the changing industry. To start with, an interactive planning framework for generation expansion is posed as a distributed decision-making model. In order to reconcile the distributed sub-objectives of different decision makers with system-wide sustainability objectives, a new concept of distributed interactive peak load pricing is proposed. To be able to make the right decisions, the decision makers must have sufficient information about the estimated long-term electricity prices. The sub-objectives of power plant owners and load-serving entities are profit maximization. Optimized long-term expansion plans based on predicted electricity prices are communicated to the system-wide planning authority as long-run bids. The long-term expansion bids are cleared by the coordinating planner so that the system-wide long-term performance criteria are satisfied. The interactions between generation owners and the coordinating planning authority are repeated annually. We view the proposed interactive planning framework as a necessary paradigm for planning in the changing industry where choice must be reconciled with societal public objectives.

Multi-criteria decision analysis using hydrological indicators for decision support - a conceptual framework.

NASA Astrophysics Data System (ADS)

Butchart-Kuhlmann, Daniel; Kralisch, Sven; Meinhardt, Markus; Fleischer, Melanie

2017-04-01

Assessing the quantity and quality of water available in water stressed environments under various potential climate and land-use changes is necessary for good water and environmental resources management and governance. Within the region covered by the Southern African Science Service Centre for Climate Change and Adaptive Land Management (SASSCAL) project, such areas are common. One goal of the SASSCAL project is to develop and provide an integrated decision support system (DSS) with which decision makers (DMs) within a given catchment can obtain objective information regarding potential changes in water flow quantity and timing. The SASSCAL DSS builds upon existing data storage and distribution capability, through the SASSCAL Information System (IS), as well as the J2000 hydrological model. Using output from validated J2000 models, the SASSCAL DSS incorporates the calculation of a range of hydrological indicators based upon Indicators of Hydrological Alteration/Environmental Flow Components (IHA/EFC) calculated for a historic time series (pre-impact) and a set of model simulations based upon a selection of possible climate and land-use change scenarios (post-impact). These indicators, obtained using the IHA software package, are then used as input for a multi-criteria decision analysis (MCDA) undertaken using the open source diviz software package. The results of these analyses will provide DMs with an indication as to how various hydrological indicators within a catchment may be altered under different future scenarios, as well providing a ranking of how each scenario is preferred according to different DM preferences. Scenarios are represented through a combination of model input data and parameter settings in J2000, and preferences are represented through criteria weighting in the MCDA. Here, the methodology is presented and applied to the J2000 Luanginga model results using a set of hypothetical decision maker preference values as input for an MCDA based on the PROMETHEE II outranking method. Future work on the SASSCAL DSS will entail automation of this process, as well as its application to other hydrological models and land-use and/or climate change scenarios.

USGCRP assessments: Meeting the challenges of climate and global change

NASA Astrophysics Data System (ADS)

Dickinson, T.; Kuperberg, J. M.

2016-12-01

The United States Global Change Research Program (USGCRP) is a confederation of the research arms of 13 Federal departments and agencies. Its mission is to build a knowledge base that informs human responses to climate and global change through coordinated and integrated Federal programs of research, education, communication, and decision support. USGCRP has supported several initiatives to promote better understanding of climate change impacts on health, support responses, and build on the progress of the 2014 National Climate Assessment. Most recently, USGCRP released a new report, "The Impacts of Climate Change on Human Health: A Scientific Assessment". This presentation will provide an overview of USGCRP, highlight the importance of assessments, and introduce ways in which assessment findings and underlying data can be translated into critical tools to build resilience.

Land Cover Applications, Landscape Dynamics, and Global Change

USGS Publications Warehouse

Tieszen, Larry L.

2007-01-01

The Land Cover Applications, Landscape Dynamics, and Global Change project at U.S. Geological Survey (USGS) Center for Earth Resources Observation and Science (EROS) seeks to integrate remote sensing and simulation models to better understand and seek solutions to national and global issues. Modeling processes related to population impacts, natural resource management, climate change, invasive species, land use changes, energy development, and climate mitigation all pose significant scientific opportunities. The project activities use remotely sensed data to support spatial monitoring, provide sensitivity analyses across landscapes and large regions, and make the data and results available on the Internet with data access and distribution, decision support systems, and on-line modeling. Applications support sustainable natural resource use, carbon cycle science, biodiversity conservation, climate change mitigation, and robust simulation modeling approaches that evaluate ecosystem and landscape dynamics.

Urban Climate Resilience - Connecting climate models with decision support cyberinfrastructure using open standards

NASA Astrophysics Data System (ADS)

Bermudez, L. E.; Percivall, G.; Idol, T. A.

2015-12-01

Experts in climate modeling, remote sensing of the Earth, and cyber infrastructure must work together in order to make climate predictions available to decision makers. Such experts and decision makers worked together in the Open Geospatial Consortium's (OGC) Testbed 11 to address a scenario of population displacement by coastal inundation due to the predicted sea level rise. In a Policy Fact Sheet "Harnessing Climate Data to Boost Ecosystem & Water Resilience", issued by White House Office of Science and Technology (OSTP) in December 2014, OGC committed to increase access to climate change information using open standards. In July 2015, the OGC Testbed 11 Urban Climate Resilience activity delivered on that commitment with open standards based support for climate-change preparedness. Using open standards such as the OGC Web Coverage Service and Web Processing Service and the NetCDF and GMLJP2 encoding standards, Testbed 11 deployed an interoperable high-resolution flood model to bring climate model outputs together with global change assessment models and other remote sensing data for decision support. Methods to confirm model predictions and to allow "what-if-scenarios" included in-situ sensor webs and crowdsourcing. A scenario was in two locations: San Francisco Bay Area and Mozambique. The scenarios demonstrated interoperation and capabilities of open geospatial specifications in supporting data services and processing services. The resultant High Resolution Flood Information System addressed access and control of simulation models and high-resolution data in an open, worldwide, collaborative Web environment. The scenarios examined the feasibility and capability of existing OGC geospatial Web service specifications in supporting the on-demand, dynamic serving of flood information from models with forecasting capacity. Results of this testbed included identification of standards and best practices that help researchers and cities deal with climate-related issues. Results of the testbeds will now be deployed in pilot applications. The testbed also identified areas of additional development needed to help identify scientific investments and cyberinfrastructure approaches needed to improve the application of climate science research results to urban climate resilence.

Linking science, public values, and decision-making: Case study development for public deliberations about climate change resilience

NASA Astrophysics Data System (ADS)

Weller, N.; Bennett, I.; Bernstein, M.; Farooque, M.; Lloyd, J.; Lowenthal, C.; Sittenfeld, D.

2016-12-01

Actionable science seeks to align scientific inquiry with decision-making priorities to overcome rifts between scientific knowledge and the needs of decision makers. Combining actionable science with explorations of public values and priorities creates useful support for decision makers facing uncertainty, tradeoffs, and limited resources. As part of a broader project to create public forums about climate change resilience, we convened workshops with decision makers, resilience experts, and community stakeholders to discuss climate change resilience. Our goals were 1) to create case studies of resilience strategies for use in public deliberations at science museums across 8 U.S. cities; and 2) to build relationships with decision makers and stakeholders interested in these public deliberations. Prior to workshops, we created summaries of resilience strategies using academic literature, government assessments, municipal resilience plans, and conversations with workshop participants. Workshops began with example deliberation activities followed by semi-structured discussions of resilience strategies centered on 4 questions: 1) What are the key decisions to be made regarding each strategy? 2) What stakeholders and perspectives are relevant to each strategy? 3) What available data are relevant to each strategy? 4) What visualizations or other resources are useful for communicating things about each strategy? Workshops yielded actionable dialogue regarding issues of justice, feasibility, and the socio-ecological-technical systems impacted by climate change hazards and resilience strategies. For example, discussions of drought revealed systemic and individual-level challenges and opportunities; discussions of sea level rise included ways to account for the cultural significance of many coastal communities. The workshops provide a model for identifying decision-making priorities and tradeoffs and building partnerships among stakeholders, scientists, and decision makers.

The utility of decision support, clinical guidelines, and financial incentives as tools to achieve improved clinical performance.

PubMed

Goldfarb, S

1999-03-01

Whether one seeks to reduce inappropriate utilization of resources, improve diagnostic accuracy, increase utilization of effective therapies, or reduce the incidence of complications, the key to change is physician involvement in change. Unfortunately, a simple approach to the problem of inducing change in physician behavior is not available. There is a generally accepted view that expert, best-practice guidelines will improve clinical performance. However, there may be a bias to report positive results and a lack of careful analysis of guideline usage in routine practice in a "postmarketing" study akin to that seen in the pharmaceutical industry. Systems that allow the reliable assessment of quality of outcomes, efficiency of resource utilization, and accurate assessment of the risks associated with the care of given patient populations must be widely available before deciding whether an incentive-based system for providing the full range of medical care is feasible. Decision support focuses on providing information, ideally at the "point of service" and in the context of a particular clinical situation. Rules are self-imposed by physicians and are therefore much more likely to be adopted. As health care becomes corporatized, with increasing numbers of physicians employed by large organizations with the capacity to provide detailed information on the nature and quality of clinical care, it is possible that properly constructed guidelines, appropriate financial incentives, and robust forms of decision support will lead to a physician-led, process improvement approach to more rational and affordable health care.

[Shared decision making in breast cancer. Womens' attitudes].

PubMed

Martín-Fernández, Roberto; Abt-Sacks, Analía; Perestelo-Perez, Lilisbeth; Serrano-Aguilar, Pedro

2013-01-01

The patient autonomy and the greater role for women with breast cancer in the decisions about their health are recent issues in healthcare. The objective of this work is to identify and characterize the elements that influence them in treatment decisions. A phenomenological type qualitative study. Theoretical Sampling included 70 women diagnosed with breast cancer. 45 semi structured interviews and 3 focus groups were performed between October 2009 and July 2010 in 15 regions of Spain. The analysis was based on the principles of grounded theory with the support of Atlas.ti v6.1. Patients are likely to take an active or passive role regarding decision-making depending on different variables such as their age, the information available, their self-assessment as capable agents to make decisions and the relative importance given to physical appearance. As the disease progresses, it can cause a change in women attitude, from an initially passive attitude to a more active role. The attitude of health professionals concerning shared decision-making and the information they offer determines patient participation while the family plays an essential role as a support or reinforcement of decisions made by patients. The patients' attitude regarding the decision-making of patients is very variable, becoming increasingly important the emotional status, the level of information available and the influence of the context.

Assessment, design and control strategy development of a fuel cell hybrid electric vehicle for CSU's EcoCAR

NASA Astrophysics Data System (ADS)

Fox, Matthew D.

Advanced automotive technology assessment and powertrain design are increasingly performed through modeling, simulation, and optimization. But technology assessments usually target many competing criteria making any individual optimization challenging and arbitrary. Further, independent design simulations and optimizations take considerable time to execute, and design constraints and objectives change throughout the design process. Changes in design considerations usually require re-processing of simulations and more time. In this thesis, these challenges are confronted through CSU's participation in the EcoCAR2 hybrid vehicle design competition. The complexity of the competition's design objectives leveraged development of a decision support system tool to aid in multi-criteria decision making across technologies and to perform powertrain optimization. To make the decision support system interactive, and bypass the problem of long simulation times, a new approach was taken. The result of this research is CSU's architecture selection and component sizing, which optimizes a composite objective function representing the competition score. The selected architecture is an electric vehicle with an onboard range extending hydrogen fuel cell system. The vehicle has a 145kW traction motor, 18.9kWh of lithium ion battery, a 15kW fuel cell system, and 5kg of hydrogen storage capacity. Finally, a control strategy was developed that improves the vehicles performance throughout the driving range under variable driving conditions. In conclusion, the design process used in this research is reviewed and evaluated against other common design methodologies. I conclude, through the highlighted case studies, that the approach is more comprehensive than other popular design methodologies and is likely to lead to a higher quality product. The upfront modeling work and decision support system formulation will pay off in superior and timely knowledge transfer and more informed design decisions. The hypothesis is supported by the three case studies examined in this thesis.

Merging Energy Policy Decision Support, Education, and Communication: The 'World Energy' Simulation Role-Playing Game

NASA Astrophysics Data System (ADS)

Rooney-varga, J. N.; Franck, T.; Jones, A.; Sterman, J.; Sawin, E.

2013-12-01

To meet international goals for climate change mitigation and adaptation, as well as energy access and equity, there is an urgent need to explore and define energy policy paths forward. Despite this need, students, citizens, and decision-makers often hold deeply flawed mental models of the energy and climate systems. Here we describe a simulation role-playing game, World Energy, that provides an immersive learning experience in which participants can create their own path forward for global energy policy and learn about the impact of their policy choices on carbon dioxide emissions, temperature rise, energy supply mix, energy prices, and energy demand. The game puts players in the decision-making roles of advisors to the United Nations Sustainable Energy for All Initiative (drawn from international leaders from industry, governments, intergovernmental organizations, and citizens groups) and, using a state-of-the-art decision-support simulator, asks them to negotiate a plan for global energy policy. We use the En-ROADS (Energy Rapid Overview and Decision Support) simulator, which runs on a laptop computer in <0.1 sec. En-ROADS enables users to specify many factors, including R&D-driven cost reductions in fossil fuel-based, renewable, or carbon-neutral energy technologies; taxes and subsidies for different energy sources; performance standards and energy efficiency; emissions prices; policies to address other greenhouse gas emissions (e.g., methane, nitrous oxide, chlorofluorocarbons, etc.); and assumptions about GDP and population. In World Energy, participants must balance climate change mitigation goals with equity, prices and access to energy, and the political feasibility of policies. Initial results indicate participants gain insights into the dynamics of the energy and climate systems and greater understanding of the potential impacts policies.

Measuring the impact of diagnostic decision support on the quality of clinical decision making: development of a reliable and valid composite score.

PubMed

Ramnarayan, Padmanabhan; Kapoor, Ritika R; Coren, Michael; Nanduri, Vasantha; Tomlinson, Amanda L; Taylor, Paul M; Wyatt, Jeremy C; Britto, Joseph F

2003-01-01

Few previous studies evaluating the benefits of diagnostic decision support systems have simultaneously measured changes in diagnostic quality and clinical management prompted by use of the system. This report describes a reliable and valid scoring technique to measure the quality of clinical decision plans in an acute medical setting, where diagnostic decision support tools might prove most useful. Sets of differential diagnoses and clinical management plans generated by 71 clinicians for six simulated cases, before and after decision support from a Web-based pediatric differential diagnostic tool (ISABEL), were used. A composite quality score was calculated separately for each diagnostic and management plan by considering the appropriateness value of each component diagnostic or management suggestion, a weighted sum of individual suggestion ratings, relevance of the entire plan, and its comprehensiveness. The reliability and validity (face, concurrent, construct, and content) of these two final scores were examined. Two hundred fifty-two diagnostic and 350 management suggestions were included in the interrater reliability analysis. There was good agreement between raters (intraclass correlation coefficient, 0.79 for diagnoses, and 0.72 for management). No counterintuitive scores were demonstrated on visual inspection of the sets. Content validity was verified by a consultation process with pediatricians. Both scores discriminated adequately between the plans of consultants and medical students and correlated well with clinicians' subjective opinions of overall plan quality (Spearman rho 0.65, p < 0.01). The diagnostic and management scores for each episode showed moderate correlation (r = 0.51). The scores described can be used as key outcome measures in a larger study to fully assess the value of diagnostic decision aids, such as the ISABEL system.

Integrative review of clinical decision support for registered nurses in acute care settings.

PubMed

Dunn Lopez, Karen; Gephart, Sheila M; Raszewski, Rebecca; Sousa, Vanessa; Shehorn, Lauren E; Abraham, Joanna

2017-03-01

To report on the state of the science of clinical decision support (CDS) for hospital bedside nurses. We performed an integrative review of qualitative and quantitative peer-reviewed original research studies using a structured search of PubMed, Embase, Cumulative Index to Nursing and Applied Health Literature (CINAHL), Scopus, Web of Science, and IEEE Xplore (Institute of Electrical and Electronics Engineers Xplore Digital Library). We included articles that reported on CDS targeting bedside nurses and excluded in stages based on rules for titles, abstracts, and full articles. We extracted research design and methods, CDS purpose, electronic health record integration, usability, and process and patient outcomes. Our search yielded 3157 articles. After removing duplicates and applying exclusion rules, 28 articles met the inclusion criteria. The majority of studies were single-site, descriptive or qualitative (43%) or quasi-experimental (36%). There was only 1 randomized controlled trial. The purpose of most CDS was to support diagnostic decision-making (36%), guideline adherence (32%), medication management (29%), and situational awareness (25%). All the studies that included process outcomes (7) and usability outcomes (4) and also had analytic procedures to detect changes in outcomes demonstrated statistically significant improvements. Three of 4 studies that included patient outcomes and also had analytic procedures to detect change showed statistically significant improvements. No negative effects of CDS were found on process, usability, or patient outcomes. Clinical support systems targeting bedside nurses have positive effects on outcomes and hold promise for improving care quality; however, this research is lagging behind studies of CDS targeting medical decision-making in both volume and level of evidence. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Development and Validation of a Primary Care-Based Family Health History and Decision Support Program (MeTree)

PubMed Central

Orlando, Lori A.; Buchanan, Adam H.; Hahn, Susan E.; Christianson, Carol A.; Powell, Karen P.; Skinner, Celette Sugg; Chesnut, Blair; Blach, Colette; Due, Barbara; Ginsburg, Geoffrey S.; Henrich, Vincent C.

2016-01-01

INTRODUCTION Family health history is a strong predictor of disease risk. To reduce the morbidity and mortality of many chronic diseases, risk-stratified evidence-based guidelines strongly encourage the collection and synthesis of family health history to guide selection of primary prevention strategies. However, the collection and synthesis of such information is not well integrated into clinical practice. To address barriers to collection and use of family health histories, the Genomedical Connection developed and validated MeTree, a Web-based, patient-facing family health history collection and clinical decision support tool. MeTree is designed for integration into primary care practices as part of the genomic medicine model for primary care. METHODS We describe the guiding principles, operational characteristics, algorithm development, and coding used to develop MeTree. Validation was performed through stakeholder cognitive interviewing, a genetic counseling pilot program, and clinical practice pilot programs in 2 community-based primary care clinics. RESULTS Stakeholder feedback resulted in changes to MeTree’s interface and changes to the phrasing of clinical decision support documents. The pilot studies resulted in the identification and correction of coding errors and the reformatting of clinical decision support documents. MeTree’s strengths in comparison with other tools are its seamless integration into clinical practice and its provision of action-oriented recommendations guided by providers’ needs. LIMITATIONS The tool was validated in a small cohort. CONCLUSION MeTree can be integrated into primary care practices to help providers collect and synthesize family health history information from patients with the goal of improving adherence to risk-stratified evidence-based guidelines. PMID:24044145

Lessons from the Johns Hopkins Multi-Disciplinary Venous Thromboembolism (VTE) Prevention Collaborative

PubMed Central

Streiff, Michael B; Carolan, Howard T; Hobson, Deborah B; Kraus, Peggy S; Holzmueller, Christine G; Demski, Renee; Lau, Brandyn D; Biscup-Horn, Paula; Pronovost, Peter J

2012-01-01

Problem Venous thromboembolism (VTE) is a common cause of potentially preventable mortality, morbidity, and increased medical costs. Risk-appropriate prophylaxis can prevent most VTE events, but only a small fraction of patients at risk receive this treatment. Design Prospective quality improvement programme. Setting Johns Hopkins Hospital, Baltimore, Maryland, USA. Strategies for change A multidisciplinary team established a VTE Prevention Collaborative in 2005. The collaborative applied the four step TRIP (translating research into practice) model to develop and implement a mandatory clinical decision support tool for VTE risk stratification and risk-appropriate VTE prophylaxis for all hospitalised adult patients. Initially, paper based VTE order sets were implemented, which were then converted into 16 specialty-specific, mandatory, computerised, clinical decision support modules. Key measures for improvement VTE risk stratification within 24 hours of hospital admission and provision of risk-appropriate, evidence based VTE prophylaxis. Effects of change The VTE team was able to increase VTE risk assessment and ordering of risk-appropriate prophylaxis with paper based order sets to a limited extent, but achieved higher compliance with a computerised clinical decision support tool and the data feedback which it enabled. Risk-appropriate VTE prophylaxis increased from 26% to 80% for surgical patients and from 25% to 92% for medical patients in 2011. Lessons learnt A computerised clinical decision support tool can increase VTE risk stratification and risk-appropriate VTE prophylaxis among hospitalised adult patients admitted to a large urban academic medical centre. It is important to ensure the tool is part of the clinician’s normal workflow, is mandatory (computerised forcing function), and offers the requisite modules needed for every clinical specialty. PMID:22718994

Barriers to electric energy efficiency in Ghana

NASA Astrophysics Data System (ADS)

Berko, Joseph Kofi, Jr.

Development advocates argue that sustainable development strategies are the best means to permanently improve living standards in developing countries. Advocates' arguments are based on the technical, financial, and environmental advantages of sustainable development. However, they have not addressed the organizational and administrative decision-making issues which are key to successful implementation of sustainable development in developing countries. Using the Ghanaian electricity industry as a case study, this dissertation identifies and analyzes organizational structures, administrative mechanisms, and decision-maker viewpoints that critically affect the success of adoption and implementation of energy efficiency within a sustainable development framework. Utilizing semi-structured interviews in field research, decision-makers' perceptions of the pattern of the industry's development, causes of the electricity supply shortfall, and barriers to electricity-use efficiency were identified. Based on the initial findings, the study formulated a set of policy initiatives to establish support for energy use efficiency. In a second set of interviews, these policy suggestions were presented to some of the top decision-makers to elicit their reactions. According to the decision-makers, the electricity supply shortfall is due to rapid urbanization and increased industrial consumption as a result of the structural adjustment program, rural electrification, and the sudden release of suppressed loads. The study found a lack of initiative and collaboration among industry decision-makers, and a related divergence in decision-makers' concerns and viewpoints. Also, lacking are institutional support systems and knowledge of proven energy efficiency strategies and technologies. As a result, planning, and even the range of perceived solutions to choose from are supply-side oriented. The final chapter of the study presents implications of its findings and proposes that any implementation strategy will have to address the different decision-makers' concerns and viewpoints. These include the need for national policies to promote electric energy efficiency and institutional development to provide support, guidance and direction to an energy efficiency effort. It also proposes structural changes within the industry to reduce government influence by creating an independent regulatory board. Finally, it proposes the adoption of integrated resource planning strategies and changes in the supply-side dominated culture within the electric utilities.

Development, deployment and usability of a point-of-care decision support system for chronic disease management using the recently-approved HL7 decision support service standard.

PubMed

Lobach, David F; Kawamoto, Kensaku; Anstrom, Kevin J; Russell, Michael L; Woods, Peter; Smith, Dwight

2007-01-01

Clinical decision support is recognized as one potential remedy for the growing crisis in healthcare quality in the United States and other industrialized nations. While decision support systems have been shown to improve care quality and reduce errors, these systems are not widely available. This lack of availability arises in part because most decision support systems are not portable or scalable. The Health Level 7 international standard development organization recently adopted a draft standard known as the Decision Support Service standard to facilitate the implementation of clinical decision support systems using software services. In this paper, we report the first implementation of a clinical decision support system using this new standard. This system provides point-of-care chronic disease management for diabetes and other conditions and is deployed throughout a large regional health system. We also report process measures and usability data concerning the system. Use of the Decision Support Service standard provides a portable and scalable approach to clinical decision support that could facilitate the more extensive use of decision support systems.

Balance Sheets Versus Decision Dashboards to Support Patient Treatment Choices: A Comparative Analysis.

PubMed

Dolan, James G; Veazie, Peter J

2015-12-01

Growing recognition of the importance of involving patients in preference-driven healthcare decisions has highlighted the need to develop practical strategies to implement patient-centered shared decision-making. The use of tabular balance sheets to support clinical decision-making is well established. More recent evidence suggests that graphic, interactive decision dashboards can help people derive deeper a understanding of information within a specific decision context. We therefore conducted a non-randomized trial comparing the effects of adding an interactive dashboard to a static tabular balance sheet on patient decision-making. The study population consisted of members of the ResearchMatch registry who volunteered to participate in a study of medical decision-making. Two separate surveys were conducted: one in the control group and one in the intervention group. All participants were instructed to imagine they were newly diagnosed with a chronic illness and were asked to choose between three hypothetical drug treatments, which varied with regard to effectiveness, side effects, and out-of-pocket cost. Both groups made an initial treatment choice after reviewing a balance sheet. After a brief "washout" period, members of the control group made a second treatment choice after reviewing the balance sheet again, while intervention group members made a second treatment choice after reviewing an interactive decision dashboard containing the same information. After both choices, participants rated their degree of confidence in their choice on a 1 to 10 scale. Members of the dashboard intervention group were more likely to change their choice of preferred drug (10.2 versus 7.5%; p = 0.054) and had a larger increase in decision confidence than the control group (0.67 versus 0.075; p < 0.03). There were no statistically significant between-group differences in decisional conflict or decision aid acceptability. These findings suggest that clinical decision dashboards may be an effective point-of-care decision-support tool. Further research to explore this possibility is warranted.

Shared decision making after severe stroke-How can we improve patient and family involvement in treatment decisions?

PubMed

Visvanathan, Akila; Dennis, Martin; Mead, Gillian; Whiteley, William N; Lawton, Julia; Doubal, Fergus Neil

2017-12-01

People who are well may regard survival with disability as being worse than death. However, this is often not the case when those surviving with disability (e.g. stroke survivors) are asked the same question. Many routine treatments provided after an acute stroke (e.g. feeding via a tube) increase survival, but with disability. Therefore, clinicians need to support patients and families in making informed decisions about the use of these treatments, in a process termed shared decision making. This is challenging after acute stroke: there is prognostic uncertainty, patients are often too unwell to participate in decision making, and proxies may not know the patients' expressed wishes (i.e. values). Patients' values also change over time and in different situations. There is limited evidence on successful methods to facilitate this process. Changes targeted at components of shared decision making (e.g. decision aids to provide information and discussing patient values) increase patient satisfaction. How this influences decision making is unclear. Presumably, a "shared decision-making tool" that introduces effective changes at various stages in this process might be helpful after acute stroke. For example, by complementing professional judgement with predictions from prognostic models, clinicians could provide information that is more accurate. Decision aids that are personalized may be helpful. Further qualitative research can provide clinicians with a better understanding of patient values and factors influencing this at different time points after a stroke. The evaluation of this tool in its success to achieve outcomes consistent with patients' values may require more than one clinical trial.

Uncertainty, imprecision, and the precautionary principle in climate change assessment.

PubMed

Borsuk, M E; Tomassini, L

2005-01-01

Statistical decision theory can provide useful support for climate change decisions made under conditions of uncertainty. However, the probability distributions used to calculate expected costs in decision theory are themselves subject to uncertainty, disagreement, or ambiguity in their specification. This imprecision can be described using sets of probability measures, from which upper and lower bounds on expectations can be calculated. However, many representations, or classes, of probability measures are possible. We describe six of the more useful classes and demonstrate how each may be used to represent climate change uncertainties. When expected costs are specified by bounds, rather than precise values, the conventional decision criterion of minimum expected cost is insufficient to reach a unique decision. Alternative criteria are required, and the criterion of minimum upper expected cost may be desirable because it is consistent with the precautionary principle. Using simple climate and economics models as an example, we determine the carbon dioxide emissions levels that have minimum upper expected cost for each of the selected classes. There can be wide differences in these emissions levels and their associated costs, emphasizing the need for care when selecting an appropriate class.

Air Traffic Management Research at NASA Ames Research Center

NASA Technical Reports Server (NTRS)

Lee, Katharine

2005-01-01

Since the late 1980's, NASA Ames researchers have been investigating ways to improve the air transportation system through the development of decision support automation. These software advances, such as the Center-TRACON Automation System (eTAS) have been developed with teams of engineers, software developers, human factors experts, and air traffic controllers; some ASA Ames decision support tools are currently operational in Federal Aviation Administration (FAA) facilities and some are in use by the airlines. These tools have provided air traffic controllers and traffic managers the capabilities to help reduce overall delays and holding, and provide significant cost savings to the airlines as well as more manageable workload levels for air traffic service providers. NASA is continuing to collaborate with the FAA, as well as other government agencies, to plan and develop the next generation of decision support tools that will support anticipated changes in the air transportation system, including a projected increase to three times today's air-traffic levels by 2025. The presentation will review some of NASA Ames' recent achievements in air traffic management research, and discuss future tool developments and concepts currently under consideration.

Behavioral change in rural practice: improving patient motivation in primary care.

PubMed

Clark, Karen; Weir, Christine

2013-01-01

As the disparities in rural healthcare have become better understood, the need to adjust and compensate for these unique challenges becomes a priority. This manuscript suggests three constructs that can be readily integrated into rural care providers' daily work to improve treatment outcomes. Autonomy support, relational support, and competence support are among the motivational constructs discussed with a special consideration for the unique cultural and environmental influences of rural West Virginia residents. The overall objective of this review is to renew the basic tenants of shared decision making as they related to successful behavioral change in primary care.

Evaluating the State of Water Management in the Rio Grande/Bravo Basin

NASA Astrophysics Data System (ADS)

Ortiz Partida, Jose Pablo; Sandoval-Solis, Samuel; Diaz Gomez, Romina

2017-04-01

Water resource modeling tools have been developed for many different regions and sub-basins of the Rio Grande/Bravo (RGB). Each of these tools has specific objectives, whether it is to explore drought mitigation alternatives, conflict resolution, climate change evaluation, tradeoff and economic synergies, water allocation, reservoir operations, or collaborative planning. However, there has not been an effort to integrate different available tools, or to link models developed for specific reaches into a more holistic watershed decision-support tool. This project outlines promising next steps to meet long-term goals of improved decision support tools and modeling. We identify, describe, and synthesize water resources management practices in the RGB basin and available water resources models and decision support tools that represent the RGB and the distribution of water for human and environmental uses. The extent body of water resources modeling is examined from a perspective of environmental water needs and water resources management and thereby allows subsequent prioritization of future research and monitoring needs for the development of river system modeling tools. This work communicates the state of the RGB science to diverse stakeholders, researchers, and decision-makers. The products of this project represent a planning tool to support an integrated water resources management framework to maximize economic and social welfare without compromising vital ecosystems.

Distributed collaborative decision support environments for predictive awareness

NASA Astrophysics Data System (ADS)

McQuay, William K.; Stilman, Boris; Yakhnis, Vlad

2005-05-01

The past decade has produced significant changes in the conduct of military operations: asymmetric warfare, the reliance on dynamic coalitions, stringent rules of engagement, increased concern about collateral damage, and the need for sustained air operations. Mission commanders need to assimilate a tremendous amount of information, rapidly assess the enemy"s course of action (eCOA) or possible actions and promulgate their own course of action (COA) - a need for predictive awareness. Decision support tools in a distributed collaborative environment offer the capability of decomposing complex multitask processes and distributing them over a dynamic set of execution assets that include modeling, simulations, and analysis tools. Revolutionary new approaches to strategy generation and assessment such as Linguistic Geometry (LG) permit the rapid development of COA vs. enemy COA (eCOA). LG tools automatically generate and permit the operators to take advantage of winning strategies and tactics for mission planning and execution in near real-time. LG is predictive and employs deep "look-ahead" from the current state and provides a realistic, reactive model of adversary reasoning and behavior. Collaborative environments provide the framework and integrate models, simulations, and domain specific decision support tools for the sharing and exchanging of data, information, knowledge, and actions. This paper describes ongoing research efforts in applying distributed collaborative environments to decision support for predictive mission awareness.

Anxiety and Decision-Making

PubMed Central

Hartley, Catherine A.; Phelps, Elizabeth A.

2013-01-01

While the everyday decision-making of clinically anxious individuals is clearly influenced by their excessive fear and worry, the relationship between anxiety and decision-making remains relatively unexplored in neuroeconomic studies. In this review, we attempt to explore the role of anxiety in decision-making using a neuroeconomic approach. We first review the neural systems mediating fear and anxiety, which overlap with a network of brain regions implicated in studies of economic decision-making. We then discuss the potential influence of cognitive biases associated with anxiety upon economic choice, focusing on a set of decision-making biases involving choice in the face of potential aversive outcomes. We propose that the neural circuitry supporting fear learning and regulation may mediate the influence of anxiety upon choice, and suggest that techniques for altering fear and anxiety may also change decisions. PMID:22325982

Progress in and prospects for fluvial flood modelling.

PubMed

Wheater, H S

2002-07-15

Recent floods in the UK have raised public and political awareness of flood risk. There is an increasing recognition that flood management and land-use planning are linked, and that decision-support modelling tools are required to address issues of climate and land-use change for integrated catchment management. In this paper, the scientific context for fluvial flood modelling is discussed, current modelling capability is considered and research challenges are identified. Priorities include (i) appropriate representation of spatial precipitation, including scenarios of climate change; (ii) development of a national capability for continuous hydrological simulation of ungauged catchments; (iii) improved scientific understanding of impacts of agricultural land-use and land-management change, and the development of new modelling approaches to represent those impacts; (iv) improved representation of urban flooding, at both local and catchment scale; (v) appropriate parametrizations for hydraulic simulation of in-channel and flood-plain flows, assimilating available ground observations and remotely sensed data; and (vi) a flexible decision-support modelling framework, incorporating developments in computing, data availability, data assimilation and uncertainty analysis.

Unintended adverse consequences of a clinical decision support system: two cases.

PubMed

Stone, Erin G

2018-05-01

Many institutions have implemented clinical decision support systems (CDSSs). While CDSS research papers have focused on benefits of these systems, there is a smaller body of literature showing that CDSSs may also produce unintended adverse consequences (UACs). Detailed here are 2 cases of UACs resulting from a CDSS. Both of these cases were related to external systems that fed data into the CDSS. In the first case, lack of knowledge of data categorization in an external pharmacy system produced a UAC; in the second case, the change of a clinical laboratory instrument produced the UAC. CDSSs rely on data from many external systems. These systems are dynamic and may have changes in hardware, software, vendors, or processes. Such changes can affect the accuracy of CDSSs. These cases point to the need for the CDSS team to be familiar with these external systems. This team (manager and alert builders) should include members in specific clinical specialties with deep knowledge of these external systems.

Improving the relevance and impact of decision support research: A co-production framework and water management case study

NASA Astrophysics Data System (ADS)

Smith, R.; Kasprzyk, J. R.; Dilling, L.; Basdekas, L.; Kaatz, L.

2016-12-01

In light of the unpredictable effects of climate change and population shifts, responsible resource management will require new types of information and strategies going forward. For water utilities, this means that water supply infrastructure systems must be expanded and/or managed for changes in overall supply and increased extremes. Utilities have begun seeking innovative tools and methods to support planning and decision making, but there are limited channels through which they can gain exposure to emerging tools from the research world, and for researchers to uptake important real-world planning and decision context. A transdisciplinary team of engineers, social and climate scientists, and water managers designed this study to develop and apply a co-production framework which explores the potential of an emerging decision support tool to enhance flexibility and adaptability in water utility planning. It also demonstrates how to improve the link between research and practice in the water sector. In this study we apply the co-production framework to the use of Multiobjective Evolutionary Algorithms (MOEAs). MOEAs have shown promise in being able to generate and evaluate new planning alternatives but they have had little testing or application in water utilities. Anchored by two workshops, this study (1) elicited input from water managers from six water suppliers on the Front Range of Colorado, USA, to create a testbed MOEA application, and (2) evaluated the managers' responses to multiobjective optimization results. The testbed consists of a Front Range-relevant hypothetical water supply model, the Borg MOEA, hydrology and demand scenarios, and a set of planning decisions and performance objectives that drive the link between the algorithm and the model. In this presentation we describe researcher-manager interactions at the initial workshop that served to establish relationships and provide in-depth information to researchers about regional water management context. We also describe the development of, and experiences from, the second workshop which included activities for water managers to interact directly with MOEA testbed results. Finally, we evaluate the co-production framework itself and the potential for the feedback from managers to shape future development of decision support tools.

The use of data-mining techniques for developing effective decisionsupport systems: A case study of simulating the effects ofclimate change on coastal salinity intrusion

USGS Publications Warehouse

Conrads, Paul; Edwin Roehl, Jr.

2017-01-01

Natural-resource managers and stakeholders face difficult challenges when managing interactions between natural and societal systems. Potential changes in climate could alter interactions between environmental and societal systems and adversely affect the availability of water resources in many coastal communities. The availability of freshwater in coastal streams can be threatened by saltwater intrusion. Even though the collective interests and computer skills of the community of managers, scientists and other stakeholders are quite varied, there is an overarching need for equal access by all to the scientific knowledge needed to make the best possible decisions. This paper describes a decision support system, PRISM-2, developed to evaluate salinity intrusion due to potential climate change along the South Carolina coast in southeastern USA. The decision support system is disseminated as a spreadsheet application and integrates the output of global circulation models, watershed models and salinity intrusion models with real-time databases for simulation, graphical user interfaces, and streaming displays of results. The results from PRISM-2 showed that a 31-cm and 62-cm increase in sea level reduced the daily availability of freshwater supply to a coastal municipal intake by 4% and 12% of the time, respectively. Future climate change projections by a global circulation model showed a seasonal change in salinity intrusion events from the summer to the fall for the majority of events.

Nursing implications of personalized and precision medicine.

PubMed

Vorderstrasse, Allison A; Hammer, Marilyn J; Dungan, Jennifer R

2014-05-01

Identify and discuss the nursing implications of personalized and precision oncology care. PubMed, CINAHL. The implications in personalized and precision cancer nursing care include interpretation and clinical use of novel and personalized information including genetic testing; patient advocacy and support throughout testing, anticipation of results and treatment; ongoing chronic monitoring; and support for patient decision-making. Attention must also be given to the family and ethical implications of a personalized approach to care. Nurses face increasing challenges and opportunities in communication, support, and advocacy for patients given the availability of advanced testing, care and treatment in personalized and precision medicine. Nursing education and continuing education, clinical decision support, and health systems changes will be necessary to provide personalized multidisciplinary care to patients, in which nurses play a key role. Copyright © 2014 Elsevier Inc. All rights reserved.

A Framework for Categorizing the Relative Vulnerability of Threatened and Endangered Species to Climate Change (External Review Draft)

EPA Science Inventory

NCEA/ORD has developed an evaluative framework that may be used to categorize the relative vulnerability of species to climate change. This framework is intended to provide information to ecosystem and resource managers to support their decision making about management actions th...

Simulation of climate change impacts on grain sorghum production grown under free air CO2 enrichment

USDA-ARS?s Scientific Manuscript database

Potential impacts of global climate change on crop productivity have drawn much attention in recent years. To investigate these impacts on grain sorghum [Sorghum bicolor (L.) Möench] productivity, we calibrated the CERES-Sorghum model in the Decision Support System for Agrotechnology Transfer (DSSAT...

Super's Career Stages and the Decision to Change Careers.

ERIC Educational Resources Information Center

Smart, Roslyn; Peterson, Candida

1997-01-01

Australians (n=226) in one of four stages of a second career (contemplating, choosing a field, implementing, change completed) were compared with 81 nonchangers. Job satisfaction varied as a function of stage. Results supported Super's theory that career changers cycle through the full set of career stages a second time. (SK)

What is a good medical decision? A research agenda guided by perspectives from multiple stakeholders

PubMed Central

Hamilton, Jada G.; Lillie, Sarah E.; Alden, Dana L.; Scherer, Laura; Oser, Megan; Rini, Christine; Tanaka, Miho; Baleix, John; Brewster, Mikki; Lee, Simon Craddock; Goldstein, Mary K.; Jacobson, Robert M.; Myers, Ronald E.; Zikmund-Fisher, Brian J.; Waters, Erika A.

2016-01-01

Informed and shared decision making are critical aspects of patient-centered care, which has contributed to an emphasis on decision support interventions to promote good medical decision making. However, researchers and healthcare providers have not reached a consensus on what defines a good decision, nor how to evaluate it. This position paper, informed by conference sessions featuring diverse stakeholders held at the 2015 Society of Behavioral Medicine and Society for Medical Decision Making annual meetings, describes key concepts that influence the decision making process itself and that may change what it means to make a good decision: interpersonal factors, structural constraints, affective influences, and values clarification methods. This paper also proposes specific research questions within each of these priority areas, with the goal of moving medical decision making research to a more comprehensive definition of a good medical decision, and enhancing the ability to measure and improve the decision making process. PMID:27566316

The Dynamic Landscape of Higher Education: The Role of Big Data and Analytics

ERIC Educational Resources Information Center

Mahroeian, Hamidreza; Daniel, Ben Kei

2016-01-01

Over the years, a number of institutions have systematically deployed new technologies to support learning and teaching. Lately, institutions have begun to explore new forms of data in order to understand and effectively address its systemic challenges, and help support effective decision-making. This paper describes the dynamic changes in the…

Economic, Educational, and Personal Implications of Implementing Computerized Guidance Information Systems. Information System for Vocational Decisions.

ERIC Educational Resources Information Center

Tiedeman, David V.

The author asserts that financial support of guidance activities, the job of the counselor, and counselors themselves will all have to change if computerized guidance support systems are to come into widespread use. The potential costs, benefits, and operating economics are discussed. Needed educational reorganization is dealt with on several…

Decision Support | Solar Research | NREL

Science.gov Websites

informed solar decision making with credible, objective, accessible, and timely resources. Solar Energy Decision Support Decision Support NREL provides technical and analytical support to support provide unbiased information on solar policies and issues for state and local government decision makers

Decision Support in Diabetes Care: The Challenge of Supporting Patients in Their Daily Living Using a Mobile Glucose Predictor.

PubMed

Pérez-Gandía, Carmen; García-Sáez, Gema; Subías, David; Rodríguez-Herrero, Agustín; Gómez, Enrique J; Rigla, Mercedes; Hernando, M Elena

2018-03-01

In type 1 diabetes mellitus (T1DM), patients play an active role in their own care and need to have the knowledge to adapt decisions to their daily living conditions. Artificial intelligence applications can help people with type 1 diabetes in decision making and allow them to react at time scales shorter than the scheduled face-to-face visits. This work presents a decision support system (DSS), based on glucose prediction, to assist patients in a mobile environment. The system's impact on therapeutic corrective actions has been evaluated in a randomized crossover pilot study focused on interprandial periods. Twelve people with type 1 diabetes treated with insulin pump participated in two phases: In the experimental phase (EP) patients used the DSS to modify initial corrective decisions in presence of hypoglycemia or hyperglycemia events. In the control phase (CP) patients were asked to follow decisions without knowing the glucose prediction. A telemedicine platform allowed participants to register monitoring data and decisions and allowed endocrinologists to supervise data at the hospital. The study period was defined as a postprediction (PP) time window. After knowing the glucose prediction, participants modified the initial decision in 20% of the situations. No statistically significant differences were found in the PP Kovatchev's risk index change (-1.23 ± 11.85 in EP vs -0.56 ± 6.06 in CP). Participants had a positive opinion about the DSS with an average score higher than 7 in a usability questionnaire. The DSS had a relevant impact in the participants' decision making while dealing with T1DM and showed a high confidence of patients in the use of glucose prediction.

Producing More Actionable Science Isn't the Problem; It's Providing Decision-Makers with Access to Right Actionable Knowledge

NASA Astrophysics Data System (ADS)

Trexler, M.

2017-12-01

Policy-makers today have almost infinite climate-relevant scientific and other information available to them. The problem for climate change decision-making isn't missing science or inadequate knowledge of climate risks; the problem is that the "right" climate change actionable knowledge isn't getting to the right decision-maker, or is getting there too early or too late to effectively influence her decision-making. Actionable knowledge is not one-size-fit-all, and for a given decision-maker might involve scientific, economic, or risk-based information. Simply producing more and more information as we are today is not the solution, and actually makes it harder for individual decision-makers to access "their" actionable knowledge. The Climatographers began building the Climate Web five years ago to test the hypothesis that a knowledge management system could help navigate the gap between infinite information and individual actionable knowledge. Today the Climate Web's more than 1,500 index terms allow instant access to almost any climate change topic. It is a curated public-access knowledgebase of more than 1,000 books, 2,000 videos, 15,000 reports and articles, 25,000 news stories, and 3,000 websites. But it is also much more, linking together tens of thousands of individually extracted ideas and graphics, and providing Deep Dives into more than 100 key topics from changing probability distributions of extreme events to climate communications best practices to cognitive dissonance in climate change decision-making. The public-access Climate Web is uniquely able to support cross-silo learning, collaboration, and actionable knowledge dissemination. The presentation will use the Climate Web to demonstrate why knowledge management should be seen as a critical component of science and policy-making collaborations.

Barriers to and facilitators of implementing shared decision making and decision support in a paediatric hospital: A descriptive study.

PubMed

Boland, Laura; McIsaac, Daniel I; Lawson, Margaret L

2016-04-01

To explore multiple stakeholders' perceived barriers to and facilitators of implementing shared decision making and decision support in a tertiary paediatric hospital. An interpretive descriptive qualitative study was conducted using focus groups and interviews to examine senior hospital administrators', clinicians', parents' and youths' perceived barriers to and facilitators of shared decision making and decision support implementation. Data were analyzed using inductive thematic analysis. Fifty-seven stakeholders participated. Six barrier and facilitator themes emerged. The main barrier was gaps in stakeholders' knowledge of shared decision making and decision support. Facilitators included compatibility between shared decision making and the hospital's culture and ideal practices, perceptions of positive patient and family outcomes associated with shared decision making, and positive attitudes regarding shared decision making and decision support. However, youth attitudes regarding the necessity and usefulness of a decision support program were a barrier. Two themes were both a barrier and a facilitator. First, stakeholder groups were uncertain which clinical situations are suitable for shared decision making (eg, new diagnoses, chronic illnesses, complex decisions or urgent decisions). Second, the clinical process may be hindered if shared decision making and decision support decrease efficiency and workflow; however, shared decision making may reduce repeat visits and save time over the long term. Specific knowledge translation strategies that improve shared decision making knowledge and match specific barriers identified by each stakeholder group may be required to promote successful shared decision making and decision support implementation in the authors' paediatric hospital.

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

Integrating cost information with health management support system: an enhanced methodology to assess health care quality drivers.

PubMed

Kohli, R; Tan, J K; Piontek, F A; Ziege, D E; Groot, H

1999-08-01

Changes in health care delivery, reimbursement schemes, and organizational structure have required health organizations to manage the costs of providing patient care while maintaining high levels of clinical and patient satisfaction outcomes. Today, cost information, clinical outcomes, and patient satisfaction results must become more fully integrated if strategic competitiveness and benefits are to be realized in health management decision making, especially in multi-entity organizational settings. Unfortunately, traditional administrative and financial systems are not well equipped to cater to such information needs. This article presents a framework for the acquisition, generation, analysis, and reporting of cost information with clinical outcomes and patient satisfaction in the context of evolving health management and decision-support system technology. More specifically, the article focuses on an enhanced costing methodology for determining and producing improved, integrated cost-outcomes information. Implementation issues and areas for future research in cost-information management and decision-support domains are also discussed.

A few scenarios still do not fit all

NASA Astrophysics Data System (ADS)

Schweizer, Vanessa

2018-05-01

For integrated climate change research, the Scenario Matrix Architecture provides a tractable menu of possible emissions trajectories, socio-economic futures and policy environments. However, the future of decision support may lie in searchable databases.

Performance evaluation of the machine learning algorithms used in inference mechanism of a medical decision support system.

PubMed

Bal, Mert; Amasyali, M Fatih; Sever, Hayri; Kose, Guven; Demirhan, Ayse

2014-01-01

The importance of the decision support systems is increasingly supporting the decision making process in cases of uncertainty and the lack of information and they are widely used in various fields like engineering, finance, medicine, and so forth, Medical decision support systems help the healthcare personnel to select optimal method during the treatment of the patients. Decision support systems are intelligent software systems that support decision makers on their decisions. The design of decision support systems consists of four main subjects called inference mechanism, knowledge-base, explanation module, and active memory. Inference mechanism constitutes the basis of decision support systems. There are various methods that can be used in these mechanisms approaches. Some of these methods are decision trees, artificial neural networks, statistical methods, rule-based methods, and so forth. In decision support systems, those methods can be used separately or a hybrid system, and also combination of those methods. In this study, synthetic data with 10, 100, 1000, and 2000 records have been produced to reflect the probabilities on the ALARM network. The accuracy of 11 machine learning methods for the inference mechanism of medical decision support system is compared on various data sets.

Land Use, climate change and BIOdiversity in cultural landscapes (LUBIO): Assessing feedbacks and promoting land-use strategies towards a viable future

NASA Astrophysics Data System (ADS)

Dullinger, Iwona; Bohner, Andreas; Dullinger, Stefan; Essl, Franz; Gaube, Veronika; Haberl, Helmut; Mayer, Andreas; Plutzar, Christoph; Remesch, Alexander

2016-04-01

Land-use and climate change are important, pervasive drivers of global environmental change and pose major threats to global biodiversity. Research to date has mostly focused either on land-use change or on climate change, but rarely on the interactions between both drivers, even though it is expected that systemic feedbacks between changes in climate and land use will have important effects on biodiversity. In particular, climate change will not only alter the pool of plant and animal species capable of thriving in a specific area, it will also force land owners to reconsider their land use decisions. Such changes in land-use practices may have major additional effects on local and regional species composition and abundance. In LUBIO, we will explore the anticipated systemic feedbacks between (1) climate change, (2) land owner's decisions on land use, (3) land-use change, and (4) changes in biodiversity patterns during the coming decades in a regional context which integrates a broad range of land use practices and intensity gradients. To achieve this goal, an integrated socioecological model will be designed and implemented, consisting of three principal components: (1) an agent based model (ABM) that simulates decisions of important actors, (2) a spatially explicit GIS model that translates these decisions into changes in land cover and land use patterns, and (3) a species distribution model (SDM) that calculates changes in biodiversity patterns following from both changes in climate and the land use decisions as simulated in the ABM. Upon integration of these three components, the coupled socioecological model will be used to generate scenarios of future land-use decisions of landowners under climate change and, eventually, the combined effects of climate and land use changes on biodiversity. Model development of the ABM will be supported by a participatory process intended to collect regional and expert knowledge through a series of expert interviews, a series of transdisciplinary participatory modelling workshops, and a questionnaire-based survey targeted at regional farmers. Beside the integrated socioecological model a catalogue of recommended actions will be developed in order to distribute the insights of the research to the most relevant regional stakeholder groups.

Using Co-production to Enhance Co-production: Cultivating institutional capacity through exchange between climate science, social science, and practice

NASA Astrophysics Data System (ADS)

Kalafatis, S.

2015-12-01

Many climate scientists and boundary organizations have accumulated years of experience providing decision support for climate adaptation related to landscape change. The Great Lakes Integrated Sciences + Assessments (GLISA) is one such organization that has developed a reputation for providing stakeholders with climate change decision support throughout the Great Lakes region of North America. After five years of applied outreach, GLISA climate scientists working with practitioners identified three common limitations across projects that were slowing down the use of information, describing them as mismatched terminology, unrealistic expectations, and disordered integration. Discussions with GLISA-affiliated social scientists revealed compelling parallels between these observations and the existing social science literature on the persistent "usability gap" in information use as well as opportunities to preemptively overcome these barriers. The discovery of these overlaps between the climate scientists' experience of barriers and the social science literature as well as strategies to systematically address them demonstrate the potential for boundary organizations to act as incubators of more and more efficient co-production over time. To help illustrate these findings, this presentation also provides an example of decision-making for adaptation in the face of landscape change in which GLISA scientists assisted Isle Royale National Park with assessing the implications of future ecological transitions for current wildlife management efforts.

Clarity versus complexity: land-use modeling as a practical tool for decision-makers

USGS Publications Warehouse

Sohl, Terry L.; Claggett, Peter

2013-01-01

The last decade has seen a remarkable increase in the number of modeling tools available to examine future land-use and land-cover (LULC) change. Integrated modeling frameworks, agent-based models, cellular automata approaches, and other modeling techniques have substantially improved the representation of complex LULC systems, with each method using a different strategy to address complexity. However, despite the development of new and better modeling tools, the use of these tools is limited for actual planning, decision-making, or policy-making purposes. LULC modelers have become very adept at creating tools for modeling LULC change, but complicated models and lack of transparency limit their utility for decision-makers. The complicated nature of many LULC models also makes it impractical or even impossible to perform a rigorous analysis of modeling uncertainty. This paper provides a review of land-cover modeling approaches and the issues causes by the complicated nature of models, and provides suggestions to facilitate the increased use of LULC models by decision-makers and other stakeholders. The utility of LULC models themselves can be improved by 1) providing model code and documentation, 2) through the use of scenario frameworks to frame overall uncertainties, 3) improving methods for generalizing key LULC processes most important to stakeholders, and 4) adopting more rigorous standards for validating models and quantifying uncertainty. Communication with decision-makers and other stakeholders can be improved by increasing stakeholder participation in all stages of the modeling process, increasing the transparency of model structure and uncertainties, and developing user-friendly decision-support systems to bridge the link between LULC science and policy. By considering these options, LULC science will be better positioned to support decision-makers and increase real-world application of LULC modeling results.

Application of a web-based Decision Support System in risk management

NASA Astrophysics Data System (ADS)

Aye, Zar Chi; Jaboyedoff, Michel; Derron, Marc-Henri

2013-04-01

Increasingly, risk information is widely available with the help of advanced technologies such as earth observation satellites, global positioning technologies, coupled with hazard modeling and analysis, and geographical information systems (GIS). Even though it exists, no effort will be put into action if it is not properly presented to the decision makers. These information need to be communicated clearly and show its usefulness so that people can make better informed decision. Therefore, communicating available risk information has become an important challenge and decision support systems have been one of the significant approaches which can help not only in presenting risk information to the decision makers but also in making efficient decisions while reducing human resources and time needed. In this study, the conceptual framework of an internet-based decision support system is presented to highlight its importance role in risk management framework and how it can be applied in case study areas chosen. The main purpose of the proposed system is to facilitate the available risk information in risk reduction by taking into account of the changes in climate, land use and socio-economic along with the risk scenarios. It allows the users to formulate, compare and select risk reduction scenarios (mainly for floods and landslides) through an enhanced participatory platform with diverse stakeholders' involvement in the decision making process. It is based on the three-tier (client-server) architecture which integrates web-GIS plus DSS functionalities together with cost benefit analysis and other supporting tools. Embedding web-GIS provides its end users to make better planning and informed decisions referenced to a geographical location, which is the one of the essential factors in disaster risk reduction programs. Different risk reduction measures of a specific area (local scale) will be evaluated using this web-GIS tool, available risk scenarios obtained from Probabilistic Risk Assessment (PRA) model and the knowledge collected from experts. The visualization of the risk reduction scenarios can also be shared among the users on the web to support the on-line participatory process. In addition, cost-benefit ratios of the different risk reduction scenarios can be prepared in order to serve as inputs for high-level decision makers. The most appropriate risk reduction scenarios will be chosen using Multi-Criteria Evaluation (MCE) method by weighting different parameters according to the preferences and criteria defined by the users. The role of public participation has been changing from one-way communication between authorities, experts, stakeholders and citizens towards more intensive two-way interaction. Involving the affected public and interest groups can enhance the level of legitimacy, transparency, and confidence in the decision making process. Due to its important part in decision making, online participatory tool is included in the DSS in order to allow the involved stakeholders interactively in risk reduction and be aware of the existing vulnerability conditions of the community. Moreover, it aims to achieve a more transparent and better informed decision-making process. The system is under in progress and the first tools implemented will be presented showing the wide possibilities of new web technologies which can have a great impact on the decision making process. It will be applied in four pilot areas in Europe: French Alps, North Eastern Italy, Romania and Poland. Nevertheless, the framework will be designed and implemented in a way to be applicable in any other regions.

Investigation assessing the publicly available evidence supporting postmarketing withdrawals, revocations and suspensions of marketing authorisations in the EU since 2012

PubMed Central

Lynn, Elizabeth; Shakir, Saad

2018-01-01

Objectives To assess the sources of publicly available evidence supporting withdrawal, revocation or suspension of marketing authorisations (‘regulatory actions’) due to safety reasons in the EU since 2012 and to investigate the time taken since initial marketing authorisation to reach these regulatory decisions. Setting This investigation examined the sources of evidence supporting 18 identified prescription medicinal products which underwent regulatory action due to safety reasons within the EU in the period 1 July 2012 to 31 December 2016. Results Eighteen single or combined active substances (‘medicinal products’) withdrawn, revoked or suspended within the EU for safety reasons between 2012 and 2016 met the inclusion criteria. Case reports were most commonly cited, supporting 94.4% of regulatory actions (n=17), followed by randomised controlled trial, meta-analyses, animal and in vitro, ex vivo or in silico study designs, each cited in 72.2% of regulatory actions (n=13). Epidemiological study designs were least commonly cited (n=8, 44.4%). Multiple sources of evidence contributed to 94.4% of regulatory decisions (n=17). Death was the most common adverse drug reaction leading to regulatory action (n=5; 27.8%), with four of these related to medication error or overdose. Median (IQR) time taken to reach a decision from the start of regulatory review was found to be 204.5 days (143, 535 days) and decreased across the study period. Duration of marketing prior to regulatory action, from the medicinal product’s authorisation date, increased across the period 2012–2016. Conclusions The sources of evidence supporting pharmacovigilance regulatory activities appear to have changed since implementation of Directive 2010/84/EU and Regulation (EU) No. 1235/2010. This, together with a small improvement in regulatory efficiency, suggests progress towards more rapid regulatory decisions based on more robust evidence. Future research should continue to monitor sources of evidence supporting regulatory decisions and the time taken to reach these decisions over time. PMID:29362275

An Environment for Guideline-based Decision Support Systems for Outpatients Monitoring.

PubMed

Zini, Elisa M; Lanzola, Giordano; Bossi, Paolo; Quaglini, Silvana

2017-08-11

We propose an architecture for monitoring outpatients that relies on mobile technologies for acquiring data. The goal is to better control the onset of possible side effects between the scheduled visits at the clinic. We analyze the architectural components required to ensure a high level of abstraction from data. Clinical practice guidelines were formalized with Alium, an authoring tool based on the PROforma language, using SNOMED-CT as a terminology standard. The Alium engine is accessible through a set of APIs that may be leveraged for implementing an application based on standard web technologies to be used by doctors at the clinic. Data sent by patients using mobile devices need to be complemented with those already available in the Electronic Health Record to generate personalized recommendations. Thus a middleware pursuing data abstraction is required. To comply with current standards, we adopted the HL7 Virtual Medical Record for Clinical Decision Support Logical Model, Release 2. The developed architecture for monitoring outpatients includes: (1) a guideline-based Decision Support System accessible through a web application that helps the doctors with prevention, diagnosis and treatment of therapy side effects; (2) an application for mobile devices, which allows patients to regularly send data to the clinic. In order to tailor the monitoring procedures to the specific patient, the Decision Support System also helps physicians with the configuration of the mobile application, suggesting the data to be collected and the associated collection frequency that may change over time, according to the individual patient's conditions. A proof of concept has been developed with a system for monitoring the side effects of chemo-radiotherapy in head and neck cancer patients. Our environment introduces two main innovation elements with respect to similar works available in the literature. First, in order to meet the specific patients' needs, in our work the Decision Support System also helps the physicians in properly configuring the mobile application. Then the Decision Support System is also continuously fed by patient-reported outcomes.

Effects of category-specific costs on neural systems for perceptual decision-making.

PubMed

Fleming, Stephen M; Whiteley, Louise; Hulme, Oliver J; Sahani, Maneesh; Dolan, Raymond J

2010-06-01

Perceptual judgments are often biased by prospective losses, leading to changes in decision criteria. Little is known about how and where sensory evidence and cost information interact in the brain to influence perceptual categorization. Here we show that prospective losses systematically bias the perception of noisy face-house images. Asymmetries in category-specific cost were associated with enhanced blood-oxygen-level-dependent signal in a frontoparietal network. We observed selective activation of parahippocampal gyrus for changes in category-specific cost in keeping with the hypothesis that loss functions enact a particular task set that is communicated to visual regions. Across subjects, greater shifts in decision criteria were associated with greater activation of the anterior cingulate cortex (ACC). Our results support a hypothesis that costs bias an intermediate representation between perception and action, expressed via general effects on frontal cortex, and selective effects on extrastriate cortex. These findings indicate that asymmetric costs may affect a neural implementation of perceptual decision making in a similar manner to changes in category expectation, constituting a step toward accounting for how prospective losses are flexibly integrated with sensory evidence in the brain.

Efficient GIS-based model-driven method for flood risk management and its application in central China

NASA Astrophysics Data System (ADS)

Liu, Y.; Zhou, J.; Song, L.; Zou, Q.; Guo, J.; Wang, Y.

2014-02-01

In recent years, an important development in flood management has been the focal shift from flood protection towards flood risk management. This change greatly promoted the progress of flood control research in a multidisciplinary way. Moreover, given the growing complexity and uncertainty in many decision situations of flood risk management, traditional methods, e.g., tight-coupling integration of one or more quantitative models, are not enough to provide decision support for managers. Within this context, this paper presents a beneficial methodological framework to enhance the effectiveness of decision support systems, through the dynamic adaptation of support regarding the needs of the decision-maker. In addition, we illustrate a loose-coupling technical prototype for integrating heterogeneous elements, such as multi-source data, multidisciplinary models, GIS tools and existing systems. The main innovation is the application of model-driven concepts, which put the system in a state of continuous iterative optimization. We define the new system as a model-driven decision support system (MDSS ). Two characteristics that differentiate the MDSS are as follows: (1) it is made accessible to non-technical specialists; and (2) it has a higher level of adaptability and compatibility. Furthermore, the MDSS was employed to manage the flood risk in the Jingjiang flood diversion area, located in central China near the Yangtze River. Compared with traditional solutions, we believe that this model-driven method is efficient, adaptable and flexible, and thus has bright prospects of application for comprehensive flood risk management.

Assessment of the quality of antenatal care services provided by health workers using a mobile phone decision support application in northern Nigeria: a pre/post-intervention study.

PubMed

McNabb, Marion; Chukwu, Emeka; Ojo, Oluwayemisi; Shekhar, Navendu; Gill, Christopher J; Salami, Habeeb; Jega, Farouk

2015-01-01

Given the shortage of skilled healthcare providers in Nigeria, frontline community health extension workers (CHEWs) are commonly tasked with providing maternal and child health services at primary health centers. In 2012, we introduced a mobile case management and decision support application in twenty primary health centers in northern Nigeria, and conducted a pre-test/post-test study to assess whether the introduction of the app had an effect on the quality of antenatal care services provided by this lower-level cadre. Using the CommCare mobile platform, the app dynamically guides CHEWs through antenatal care protocols and collects client data in real time. Thirteen health education audio clips are also embedded in the app for improving and standardizing client counseling. To detect changes in quality, we developed an evidence-based quality score consisting of 25 indicators, and conducted a total of 266 client exit interviews. We analyzed baseline and endline data to assess changes in the overall quality score as well as changes in the provision of key elements of antenatal care. Overall, the quality score increased from 13.3 at baseline to 17.2 at endline (p<0.0001), out of a total possible score of 25, with the most significant improvements related to health counseling, technical services provided, and quality of health education. These study results suggest that the introduction of a low-cost mobile case management and decision support application can spur behavior change and improve the quality of services provided by a lower level cadre of healthcare workers. Future research should employ a more rigorous experimental design to explore potential longer-term effects on client health outcomes.

Data Model for Multi Hazard Risk Assessment Spatial Support Decision System

NASA Astrophysics Data System (ADS)

Andrejchenko, Vera; Bakker, Wim; van Westen, Cees

2014-05-01

The goal of the CHANGES Spatial Decision Support System is to support end-users in making decisions related to risk reduction measures for areas at risk from multiple hydro-meteorological hazards. The crucial parts in the design of the system are the user requirements, the data model, the data storage and management, and the relationships between the objects in the system. The implementation of the data model is carried out entirely with an open source database management system with a spatial extension. The web application is implemented using open source geospatial technologies with PostGIS as the database, Python for scripting, and Geoserver and javascript libraries for visualization and the client-side user-interface. The model can handle information from different study areas (currently, study areas from France, Romania, Italia and Poland are considered). Furthermore, the data model handles information about administrative units, projects accessible by different types of users, user-defined hazard types (floods, snow avalanches, debris flows, etc.), hazard intensity maps of different return periods, spatial probability maps, elements at risk maps (buildings, land parcels, linear features etc.), economic and population vulnerability information dependent on the hazard type and the type of the element at risk, in the form of vulnerability curves. The system has an inbuilt database of vulnerability curves, but users can also add their own ones. Included in the model is the management of a combination of different scenarios (e.g. related to climate change, land use change or population change) and alternatives (possible risk-reduction measures), as well as data-structures for saving the calculated economic or population loss or exposure per element at risk, aggregation of the loss and exposure using the administrative unit maps, and finally, producing the risk maps. The risk data can be used for cost-benefit analysis (CBA) and multi-criteria evaluation (SMCE). The data model includes data-structures for CBA and SMCE. The model is at the stage where risk and cost-benefit calculations can be stored but the remaining part is currently under development. Multi-criteria information, user management and the relation of these with the rest of the model is our next step. Having a carefully designed data model plays a crucial role in the development of the whole system for rapid development, keeping the data consistent, and in the end, support the end-user in making good decisions in risk-reduction measures related to multiple natural hazards. This work is part of the EU FP7 Marie Curie ITN "CHANGES"project (www.changes-itn.edu)

How to deal with climate change uncertainty in the planning of engineering systems

NASA Astrophysics Data System (ADS)

Spackova, Olga; Dittes, Beatrice; Straub, Daniel

2016-04-01

The effect of extreme events such as floods on the infrastructure and built environment is associated with significant uncertainties: These include the uncertain effect of climate change, uncertainty on extreme event frequency estimation due to limited historic data and imperfect models, and, not least, uncertainty on future socio-economic developments, which determine the damage potential. One option for dealing with these uncertainties is the use of adaptable (flexible) infrastructure that can easily be adjusted in the future without excessive costs. The challenge is in quantifying the value of adaptability and in finding the optimal sequence of decision. Is it worth to build a (potentially more expensive) adaptable system that can be adjusted in the future depending on the future conditions? Or is it more cost-effective to make a conservative design without counting with the possible future changes to the system? What is the optimal timing of the decision to build/adjust the system? We develop a quantitative decision-support framework for evaluation of alternative infrastructure designs under uncertainties, which: • probabilistically models the uncertain future (trough a Bayesian approach) • includes the adaptability of the systems (the costs of future changes) • takes into account the fact that future decisions will be made under uncertainty as well (using pre-posterior decision analysis) • allows to identify the optimal capacity and optimal timing to build/adjust the infrastructure. Application of the decision framework will be demonstrated on an example of flood mitigation planning in Bavaria.

Creating and sharing clinical decision support content with Web 2.0: Issues and examples.

PubMed

Wright, Adam; Bates, David W; Middleton, Blackford; Hongsermeier, Tonya; Kashyap, Vipul; Thomas, Sean M; Sittig, Dean F

2009-04-01

Clinical decision support is a powerful tool for improving healthcare quality and patient safety. However, developing a comprehensive package of decision support interventions is costly and difficult. If used well, Web 2.0 methods may make it easier and less costly to develop decision support. Web 2.0 is characterized by online communities, open sharing, interactivity and collaboration. Although most previous attempts at sharing clinical decision support content have worked outside of the Web 2.0 framework, several initiatives are beginning to use Web 2.0 to share and collaborate on decision support content. We present case studies of three efforts: the Clinfowiki, a world-accessible wiki for developing decision support content; Partners Healthcare eRooms, web-based tools for developing decision support within a single organization; and Epic Systems Corporation's Community Library, a repository for sharing decision support content for customers of a single clinical system vendor. We evaluate the potential of Web 2.0 technologies to enable collaborative development and sharing of clinical decision support systems through the lens of three case studies; analyzing technical, legal and organizational issues for developers, consumers and organizers of clinical decision support content in Web 2.0. We believe the case for Web 2.0 as a tool for collaborating on clinical decision support content appears strong, particularly for collaborative content development within an organization.

A Conceptual Analytics Model for an Outcome-Driven Quality Management Framework as Part of Professional Healthcare Education.

PubMed

Hervatis, Vasilis; Loe, Alan; Barman, Linda; O'Donoghue, John; Zary, Nabil

2015-10-06

Preparing the future health care professional workforce in a changing world is a significant undertaking. Educators and other decision makers look to evidence-based knowledge to improve quality of education. Analytics, the use of data to generate insights and support decisions, have been applied successfully across numerous application domains. Health care professional education is one area where great potential is yet to be realized. Previous research of Academic and Learning analytics has mainly focused on technical issues. The focus of this study relates to its practical implementation in the setting of health care education. The aim of this study is to create a conceptual model for a deeper understanding of the synthesizing process, and transforming data into information to support educators' decision making. A deductive case study approach was applied to develop the conceptual model. The analytics loop works both in theory and in practice. The conceptual model encompasses the underlying data, the quality indicators, and decision support for educators. The model illustrates how a theory can be applied to a traditional data-driven analytics approach, and alongside the context- or need-driven analytics approach.

A Conceptual Analytics Model for an Outcome-Driven Quality Management Framework as Part of Professional Healthcare Education

PubMed Central

Loe, Alan; Barman, Linda; O'Donoghue, John; Zary, Nabil

2015-01-01

Background Preparing the future health care professional workforce in a changing world is a significant undertaking. Educators and other decision makers look to evidence-based knowledge to improve quality of education. Analytics, the use of data to generate insights and support decisions, have been applied successfully across numerous application domains. Health care professional education is one area where great potential is yet to be realized. Previous research of Academic and Learning analytics has mainly focused on technical issues. The focus of this study relates to its practical implementation in the setting of health care education. Objective The aim of this study is to create a conceptual model for a deeper understanding of the synthesizing process, and transforming data into information to support educators’ decision making. Methods A deductive case study approach was applied to develop the conceptual model. Results The analytics loop works both in theory and in practice. The conceptual model encompasses the underlying data, the quality indicators, and decision support for educators. Conclusions The model illustrates how a theory can be applied to a traditional data-driven analytics approach, and alongside the context- or need-driven analytics approach. PMID:27731840

Barriers to and facilitators of implementing shared decision making and decision support in a paediatric hospital: A descriptive study

PubMed Central

Boland, Laura; McIsaac, Daniel I; Lawson, Margaret L

2016-01-01

OBJECTIVE: To explore multiple stakeholders’ perceived barriers to and facilitators of implementing shared decision making and decision support in a tertiary paediatric hospital. METHODS: An interpretive descriptive qualitative study was conducted using focus groups and interviews to examine senior hospital administrators’, clinicians’, parents’ and youths’ perceived barriers to and facilitators of shared decision making and decision support implementation. Data were analyzed using inductive thematic analysis. RESULTS: Fifty-seven stakeholders participated. Six barrier and facilitator themes emerged. The main barrier was gaps in stakeholders’ knowledge of shared decision making and decision support. Facilitators included compatibility between shared decision making and the hospital’s culture and ideal practices, perceptions of positive patient and family outcomes associated with shared decision making, and positive attitudes regarding shared decision making and decision support. However, youth attitudes regarding the necessity and usefulness of a decision support program were a barrier. Two themes were both a barrier and a facilitator. First, stakeholder groups were uncertain which clinical situations are suitable for shared decision making (eg, new diagnoses, chronic illnesses, complex decisions or urgent decisions). Second, the clinical process may be hindered if shared decision making and decision support decrease efficiency and workflow; however, shared decision making may reduce repeat visits and save time over the long term. CONCLUSIONS: Specific knowledge translation strategies that improve shared decision making knowledge and match specific barriers identified by each stakeholder group may be required to promote successful shared decision making and decision support implementation in the authors’ paediatric hospital. PMID:27398058

A systematic review of patient reported factors associated with uptake and completion of cardiovascular lifestyle behaviour change.

PubMed

Murray, Jenni; Craigs, Cheryl Leanne; Hill, Kate Mary; Honey, Stephanie; House, Allan

2012-12-08

Healthy lifestyles are an important facet of cardiovascular risk management. Unfortunately many individuals fail to engage with lifestyle change programmes. There are many factors that patients report as influencing their decisions about initiating lifestyle change. This is challenging for health care professionals who may lack the skills and time to address a broad range of barriers to lifestyle behaviour. Guidance on which factors to focus on during lifestyle consultations may assist healthcare professionals to hone their skills and knowledge leading to more productive patient interactions with ultimately better uptake of lifestyle behaviour change support. The aim of our study was to clarify which influences reported by patients predict uptake and completion of formal lifestyle change programmes. A systematic narrative review of quantitative observational studies reporting factors (influences) associated with uptake and completion of lifestyle behaviour change programmes. Quantitative observational studies involving patients at high risk of cardiovascular events were identified through electronic searching and screened against pre-defined selection criteria. Factors were extracted and organised into an existing qualitative framework. 374 factors were extracted from 32 studies. Factors most consistently associated with uptake of lifestyle change related to support from family and friends, transport and other costs, and beliefs about the causes of illness and lifestyle change. Depression and anxiety also appear to influence uptake as well as completion. Many factors show inconsistent patterns with respect to uptake and completion of lifestyle change programmes. There are a small number of factors that consistently appear to influence uptake and completion of cardiovascular lifestyle behaviour change. These factors could be considered during patient consultations to promote a tailored approach to decision making about the most suitable type and level lifestyle behaviour change support.

An Innovative Approach to Effective Climate Science Application through Stakeholder Participation in Great Plains Grasslands

NASA Astrophysics Data System (ADS)

Athearn, N.; Broska, J.

2015-12-01

For natural resource managers and other Great Plains stakeholders, climate uncertainties further confound decision-making on a highly altered landscape. Partner organizations comprising the Great Plains Landscape Conservation Cooperative (GPLCC) acknowledge climate change as a high-priority threat to grasslands and associated habitats, affecting water availability, species composition, and other factors. Despite its importance, incorporation of climate change impacts into planning is hindered by high uncertainty and lack of translation to a tangible outcome: effects on species and their habitats. In 2014, the GPLCC initiated a Landscape Conservation Design (LCD) process to ultimately improve the size and connectivity of grasslands - informing land managers of the landscape-scale impacts of local decisions about where to restore, enhance, protect, and develop lands. Defining this goal helped stakeholders envision a tangible product. High resolution land cover data recently completed for Texas and Oklahoma represent current grassland locations. By focusing climate change models to project changes in these land cover datasets, resulting land cover projections can be directly incorporated into LCD-based models to focus restoration where future climates will support grasslands. Broad organizational cooperation has been critical for this USGS-led project, which uses downscaled climate data and other support from the South Central Climate Science Center Consortium and builds on existing work including LCD efforts of the Playa Lakes Joint Venture and the Bureau of Land Management's Southern Great Plains Rapid Ecological Assessment. Ongoing stakeholder guidance through an advisory team ensures effective application of a product that will be both relevant to and understood by decision makers, for whom the primary role of research is to reduce uncertainties and clear the path for more efficient decision-making in the face of climatic uncertainty.

An integrated crop model and GIS decision support system for assisting agronomic decision making under climate change.

PubMed

Kadiyala, M D M; Nedumaran, S; Singh, Piara; S, Chukka; Irshad, Mohammad A; Bantilan, M C S

2015-07-15

The semi-arid tropical (SAT) regions of India are suffering from low productivity which may be further aggravated by anticipated climate change. The present study analyzes the spatial variability of climate change impacts on groundnut yields in the Anantapur district of India and examines the relative contribution of adaptation strategies. For this purpose, a web based decision support tool that integrates crop simulation model and Geographical Information System (GIS) was developed to assist agronomic decision making and this tool can be scalable to any location and crop. The climate change projections of five global climate models (GCMs) relative to the 1980-2010 baseline for Anantapur district indicates an increase in rainfall activity to the tune of 10.6 to 25% during Mid-century period (2040-69) with RCP 8.5. The GCMs also predict warming exceeding 1.4 to 2.4°C by 2069 in the study region. The spatial crop responses to the projected climate indicate a decrease in groundnut yields with four GCMs (MPI-ESM-MR, MIROC5, CCSM4 and HadGEM2-ES) and a contrasting 6.3% increase with the GCM, GFDL-ESM2M. The simulation studies using CROPGRO-Peanut model reveals that groundnut yields can be increased on average by 1.0%, 5.0%, 14.4%, and 20.2%, by adopting adaptation options of heat tolerance, drought tolerant cultivars, supplemental irrigation and a combination of drought tolerance cultivar and supplemental irrigation respectively. The spatial patterns of relative benefits of adaptation options were geographically different and the greatest benefits can be achieved by adopting new cultivars having drought tolerance and with the application of one supplemental irrigation at 60days after sowing. Copyright © 2015 Elsevier B.V. All rights reserved.

Employee responsibility in benefit change.

PubMed

Hart, Deb; Arian, Mark

2007-01-01

If employers want to move employees beyond superficial acceptance of benefit changes, organizations need to increase the focus on how they manage the change process and support employee decision making. This article describes how employers can help workers understand changes and, through effective change management and communication, successfully navigate in an evolving benefits world. Using recent survey research about large employer and employee attitudes, the authors demonstrate tangible proof that these efforts pay off, both in financial and cultural terms.

AERIS : Eco-Vehicle Speed Control at Signalized Intersections Using I2V Communication

DOT National Transportation Integrated Search

2012-06-01

This report concentrates on a velocity advisory tool, or decision support system, for vehicles approaching an intersection using communication capabilities between the infrastructure and vehicles. The system uses available signal change information, ...

Cultivating Conformists or Raising Rebels? Connecting Parental Control and Autonomy Support to Adolescent Delinquency.

PubMed

Brauer, Jonathan R

2017-06-01

This study investigates short-term and long-term associations between parenting in early adolescence and delinquency throughout adolescence using data from the National Longitudinal Surveys. Multilevel longitudinal Poisson regressions show that behavioral control, psychological control, and decision-making autonomy in early adolescence (ages 10-11) are associated with delinquency trajectories throughout adolescence (ages 10-17). Path analyses reveal support for three mediation hypotheses. Parental monitoring (behavioral control) is negatively associated with delinquency in the short term and operates partly through changes in self-control. Parental pressure (psychological control) shows immediate and long-lasting associations with delinquency through changes in self-control and delinquent peer pressures. Decision-making autonomy is negatively associated with delinquency in the long term, yet may exacerbate delinquency in early adolescence by increasing exposure to delinquent peers. © 2016 The Author. Journal of Research on Adolescence © 2016 Society for Research on Adolescence.

Climate Risk Assessment: Technical Guidance Manual for DoD Installations and Built Environment

DTIC Science & Technology

2016-09-06

climate change risks to DoD installations and the built environment. The approach, which we call “decision-scaling,” reveals the core sensitivity of...DoD installations to climate change . It is designed to illuminate the sensitivity of installations and their supporting infrastructure systems...including water and energy, to climate changes and other uncertainties without dependence on climate change projections. In this way the analysis and

Implementation of a cystic fibrosis lung transplant referral patient decision aid in routine clinical practice: an observational study.

PubMed

Stacey, Dawn; Vandemheen, Katherine L; Hennessey, Rosamund; Gooyers, Tracy; Gaudet, Ena; Mallick, Ranjeeta; Salgado, Josette; Freitag, Andreas; Berthiaume, Yves; Brown, Neil; Aaron, Shawn D

2015-02-07

The decision to have lung transplantation as treatment for end-stage lung disease from cystic fibrosis (CF) has benefits and serious risks. Although patient decision aids are effective interventions for helping patients reach a quality decision, little is known about implementing them in clinical practice. Our study evaluated a sustainable approach for implementing a patient decision aid for adults with CF considering referral for lung transplantation. A prospective pragmatic observational study was guided by the Knowledge-to-Action Framework. Healthcare professionals in all 23 Canadian CF clinics were eligible. We surveyed participants regarding perceived barriers and facilitators to patient decision aid use. Interventions tailored to address modifiable identified barriers included training, access to decision aids, and conference calls. The primary outcome was >80% use of the decision aid in year 2. Of 23 adult CF clinics, 18 participated (78.2%) and 13 had healthcare professionals attend training. Baseline barriers were healthcare professionals' inadequate knowledge for supporting patients making decisions (55%), clarifying patients' values for outcomes of options (58%), and helping patients handle conflicting views of others (71%). Other barriers were lack of time (52%) and needing to change how transplantation is discussed (42%). Baseline facilitators were healthcare professionals feeling comfortable discussing bad transplantation outcomes (74%), agreeing the decision aid would be easy to experiment with (71%) and use in the CF clinic (87%), and agreeing that using the decision aid would not require reorganization of the CF clinic (90%). After implementing the decision aid with interventions tailored to the barriers, decision aid use increased from 29% at baseline to 85% during year 1 and 92% in year 2 (p < 0.001). Compared to baseline, more healthcare professionals at the end of the study were confident in supporting decision-making (p = 0.03) but continued to feel inadequate ability with supporting patients to handle conflicting views (p = 0.01). Most Canadian CF clinics agreed to participate in the study. Interventions were used to target identified modifiable barriers to using the patient decision aid in routine CF clinical practice. CF clinics reported using it with almost all patients in the second year.

Parental decision-making for medically complex infants and children: an integrated literature review.

PubMed

Allen, Kimberly A

2014-09-01

Many children with life-threatening conditions who would have died at birth are now surviving months to years longer than previously expected. Understanding how parents make decisions is necessary to prevent parental regret about decision-making, which can lead to psychological distress, decreased physical health, and decreased quality of life for the parents. The aim of this integrated literature review was to describe possible factors that affect parental decision-making for medically complex children. The critical decisions included continuation or termination of a high-risk pregnancy, initiation of life-sustaining treatments such as resuscitation, complex cardiothoracic surgery, use of experimental treatments, end-of-life care, and limitation of care or withdrawal of support. PubMed, Cumulative Index of Nursing and Allied Health Literature, and PsycINFO were searched using the combined key terms 'parents and decision-making' to obtain English language publications from 2000 to June 2013. The findings from each of the 31 articles retained were recorded. The strengths of the empirical research reviewed are that decisions about initiating life support and withdrawing life support have received significant attention. Researchers have explored how many different factors impact decision-making and have used multiple different research designs and data collection methods to explore the decision-making process. These initial studies lay the foundation for future research and have provided insight into parental decision-making during times of crisis. Studies must begin to include both parents and providers so that researchers can evaluate how decisions are made for individual children with complex chronic conditions to understand the dynamics between parents and parent-provider relationships. The majority of studies focused on one homogenous diagnostic group of premature infants and children with complex congenital heart disease. Thus comparisons across other child illness categories cannot be made. Most studies also used cross-sectional and/or retrospective research designs, which led to researchers and clinicians having limited understanding of how factors change over time for parents. Copyright © 2014 Elsevier Ltd. All rights reserved.

Patient decision making among older individuals with cancer.

PubMed

Strohschein, Fay J; Bergman, Howard; Carnevale, Franco A; Loiselle, Carmen G

2011-07-01

Patient decision making is an area of increasing inquiry. For older individuals experiencing cancer, variations in health and functional status, physiologic aspects of aging, and tension between quality and quantity of life present unique challenges to treatment-related decision making. We used the pragmatic utility method to analyze the concept of patient decision making in the context of older individuals with cancer. We first evaluated its maturity in existing literature and then posed analytical questions to clarify aspects found to be only partially mature. In this context, we found patient decision making to be an ongoing process, changing with time, reflecting individual and relational components, as well as analytical and emotional ones. Assumptions frequently associated with patient decision making were not consistent with the empirical literature. Careful attention to the multifaceted components of patient decision making among older individuals with cancer provides guidance for research, supportive interventions, and targeted follow-up care.

Serious Simulation Role-Playing Games for Transformative Climate Change Education: "World Climate" and "Future Climate"

NASA Astrophysics Data System (ADS)

Rooney-Varga, J. N.; Sterman, J.; Sawin, E.; Jones, A.; Merhi, H.; Hunt, C.

2012-12-01

Climate change, its mitigation, and adaption to its impacts are among the greatest challenges of our times. Despite the importance of societal decisions in determining climate change outcomes, flawed mental models about climate change remain widespread, are often deeply entrenched, and present significant barriers to understanding and decision-making around climate change. Here, we describe two simulation role-playing games that combine active, affective, and analytical learning to enable shifts of deeply held conceptions about climate change. The games, World Climate and Future Climate, use a state-of-the-art decision support simulation, C-ROADS (Climate Rapid Overview and Decision Support) to provide users with immediate feedback on the outcomes of their mitigation strategies at the national level, including global greenhouse gas (GHG) emissions and concentrations, mean temperature changes, sea level rise, and ocean acidification. C-ROADS outcomes are consistent with the atmosphere-ocean general circulation models (AOGCMS), such as those used by the IPCC, but runs in less than one second on ordinary laptops, providing immediate feedback to participants on the consequences of their proposed policies. Both World Climate and Future Climate role-playing games provide immersive, situated learning experiences that motivate active engagement with climate science and policy. In World Climate, participants play the role of United Nations climate treaty negotiators. Participant emissions reductions proposals are continually assessed through interactive exploration of the best available science through C-ROADS. Future Climate focuses on time delays in the climate and energy systems. Participants play the roles of three generations: today's policymakers, today's youth, and 'just born.' The game unfolds in three rounds 25 simulated years apart. In the first round, only today's policymakers make decisions; In the next round, the young become the policymakers and inherit the results of the earlier decisions, as simulated by C-ROADS. Preliminary evaluations show that both exercises have the potential to provide powerful learning experiences. University students who played World Climate in a climate change course cited it as one of the course activities "promoting the most learning." Students' responses on anonymous surveys and open-ended questions revealed that the experience affected them at visceral, as well as intellectual levels. All of the students recommended that the exercise be continued in future years and many felt that it was the most important learning experience of the semester. Similarly, understanding of climate change and the dynamics of the climate improved for the majority of Future Climate participants, and 90% of participants stated that they were more likely to take action to address climate change on a personal level because of their experience.

Mainstreaming Climate Change: Recent and Ongoing Efforts to Understand, Improve, and Expand Consideration of Climate Change in Federal Water Resources Planning

NASA Astrophysics Data System (ADS)

Ferguson, I. M.; McGuire, M.; Broman, D.; Gangopadhyay, S.

2017-12-01

The Bureau of Reclamation is a Federal agency tasked with developing and managing water supply and hydropower projects in the Western U.S. Climate and hydrologic variability and change significantly impact management actions and outcomes across Reclamation's programs and initiatives, including water resource planning and operations, infrastructure design and maintenance, hydropower generation, and ecosystem restoration, among others. Planning, design, and implementation of these programs therefore requires consideration of future climate and hydrologic conditions will impact program objectives. Over the past decade, Reclamation and other Federal agencies have adopted new guidelines, directives, and mandates that require consideration of climate change in water resources planning and decision making. Meanwhile, the scientific community has developed a large number of climate projections, along with an array of models, methods, and tools to facilitate consideration of climate projections in planning and decision making. However, water resources engineers, planners, and decision makers continue to face challenges regarding how best to use the available data and tools to support major decisions, including decisions regarding infrastructure investments and long-term operating criteria. This presentation will discuss recent and ongoing research towards understanding, improving, and expanding consideration of climate projections and related uncertainties in Federal water resources planning and decision making. These research efforts address a variety of challenges, including: How to choose between available climate projection datasets and related methods, models, and tools—many of which are considered experimental or research tools? How to select an appropriate decision framework when design or operating alternatives may differ between climate scenarios? How to effectively communicate results of a climate impacts analysis to decision makers? And, how to improve robustness and resilience of water resources systems in the face of significant uncertainty? Discussion will focus on the intersection between technical challenges and decision making paradigms and the need for improved scientist-decision maker engagement through the lens of this Federal water management agency.

On Their Own: The Meaning of Change Experienced by Female Entrepreneurs as They Initiate New Business Ventures.

ERIC Educational Resources Information Center

Coyle, H. Elizabeth; Ellinger, Andrea

2003-01-01

Cases of four female entrepreneurs produced seven themes related to the meaning of change resulting from business start-up: definition of the transition experience within a connected self, precursors and readiness, support of informal networks, traits, risk-taking behaviors, motivations, and decision making. The results imply that entrepreneurship…

75 FR 55792 - Decision To Evaluate a Petition To Designate a Class of Employees From the Wah Chang Facility...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-09-14

... warranted by the evaluation, is as follows: Facility: Wah Chang. Location: Albany, Oregon. Job Titles and/or Job Duties: All employees who worked in any buildings. Period of Employment: Operational period from... of Compensation Analysis and Support, National Institute for Occupational Safety and Health (NIOSH...

Improving the role of vulnerability assessments In decision support for effective climate adaptation

Treesearch

Linda A. Joyce; Constance I. Millar

2014-01-01

Vulnerability assessments (VA) have been proposed as an initial step in a process to develop and implement adaptation management for climate change in forest ecosystems. Scientific understanding of the effects of climate change is an ever-accumulating knowledge base. Synthesizing information from this knowledge base in the context of our understanding of ecosystem...

Decision support for evaluating landscape departure and prioritizing forest management activities in a changing environment

Treesearch

S. Gärtner; K.M. Reynolds; P.F. Hessburg; S.S. Hummel; M. Twery

2008-01-01

We evaluated changes (hereafter, departures) in spatial patterns of various patch types of forested landscapes in two subwatersheds ("east" and "west") in eastern Washington, USA, from the patterns of two sets of reference conditions; one representing the broad variability of pre-management era (~1900) conditions, and another representing the broad...

Climate change and European forests: what do we know, what are the uncertainties, and what are the implications for forest management?

PubMed

Lindner, Marcus; Fitzgerald, Joanne B; Zimmermann, Niklaus E; Reyer, Christopher; Delzon, Sylvain; van der Maaten, Ernst; Schelhaas, Mart-Jan; Lasch, Petra; Eggers, Jeannette; van der Maaten-Theunissen, Marieke; Suckow, Felicitas; Psomas, Achilleas; Poulter, Benjamin; Hanewinkel, Marc

2014-12-15

The knowledge about potential climate change impacts on forests is continuously expanding and some changes in growth, drought induced mortality and species distribution have been observed. However despite a significant body of research, a knowledge and communication gap exists between scientists and non-scientists as to how climate change impact scenarios can be interpreted and what they imply for European forests. It is still challenging to advise forest decision makers on how best to plan for climate change as many uncertainties and unknowns remain and it is difficult to communicate these to practitioners and other decision makers while retaining emphasis on the importance of planning for adaptation. In this paper, recent developments in climate change observations and projections, observed and projected impacts on European forests and the associated uncertainties are reviewed and synthesised with a view to understanding the implications for forest management. Current impact assessments with simulation models contain several simplifications, which explain the discrepancy between results of many simulation studies and the rapidly increasing body of evidence about already observed changes in forest productivity and species distribution. In simulation models uncertainties tend to cascade onto one another; from estimating what future societies will be like and general circulation models (GCMs) at the global level, down to forest models and forest management at the local level. Individual climate change impact studies should not be uncritically used for decision-making without reflection on possible shortcomings in system understanding, model accuracy and other assumptions made. It is important for decision makers in forest management to realise that they have to take long-lasting management decisions while uncertainty about climate change impacts are still large. We discuss how to communicate about uncertainty - which is imperative for decision making - without diluting the overall message. Considering the range of possible trends and uncertainties in adaptive forest management requires expert knowledge and enhanced efforts for providing science-based decision support. Copyright © 2014 Elsevier Ltd. All rights reserved.

Supporting end of life decision making: Case studies of relational closeness in supported decision making for people with severe or profound intellectual disability.

PubMed

Watson, Joanne; Wilson, Erin; Hagiliassis, Nick

2017-11-01

The United Nations Convention on the Rights of Persons with Disabilities (UNCRPD) promotes the use of supported decision making in lieu of substitute decision making. To date, there has been a lack of focus on supported decision making for people with severe or profound intellectual disability, including for end of life decisions. Five people with severe or profound intellectual disability's experiences of supported decision making were examined. This article is particularly focused on one participant's experiences at the end of his life. All five case studies identified that supporters were most effective in providing decision-making support for participants when they were relationally close to the person and had knowledge of the person's life story, particularly in relation to events that demonstrated preference. Findings from this study provide new understandings of supported decision making for people with severe or profound intellectual disability and have particular relevance for supporting decision making at the end of life. © 2017 John Wiley & Sons Ltd.

Neuro-Oncology Branch patient emotional support services | Center for Cancer Research

Cancer.gov

Emotional Support Services The diagnosis of a brain tumor elicits many different and sometimes difficult emotions, not only for the patient, but also for their family members. Patients may encounter changes in cognitive functioning and language, a diminished ability to focus or make decisions, or short-term memory loss, all of which can greatly affect their personal and

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.

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

The future of intelligent assistive technologies for cognition: devices under development to support independent living and aging-with-choice.

PubMed

Boger, Jennifer; Mihailidis, Alex

2011-01-01

A person's ability to be independent is dependent on his or her overall health, mobility, and ability to complete activities of daily living. Intelligent assistive technologies (IATs) are devices that incorporate context into their decision-making process, which enables them to provide customised and dynamic assistance in an appropriate manner. IATs have tremendous potential to support people with cognitive impairments as they can be used to support many facets of well-being; from augmenting memory and decision making tasks to providing autonomous and early detection of possible changes in health. This paper presents IATs that are currently in development in the research community to support tasks that can be impacted by compromised cognition. While they are not yet ready for the general public, these devices showcase the capabilities of technologies one can expect to see in the consumer marketplace in the near future.

Decision Making in Rangelands: An Integrated Modeling Approach to Resilience and Change

NASA Astrophysics Data System (ADS)

Galvin, K. A.; Ojima, D. S.; Boone, R. B.

2007-12-01

Rangelands comprise approximately 25% of the earth's surface and these landscapes support more than 20 million people and most of the world's charismatic megafauna. Most of the people who live in these regions of the world herd domestic livestock and some do limited cultivation so they are dependent directly on the environment for their livelihoods. But change is rapidly changing the environments upon which these people depend through such factors as population pressures, land use and land tenure changes, climate variability, and policy changes which fragment their resources and thus their ability to earn a living. How can we understand change in this linked human-environment system? The study of complex biophysical and human systems can be greatly assisted by appropriate simulation models that integrate what is known about ecological and human decision-making processes. We have developed an integrated modeling system for Kajiado, Kenya where land use management decisions have implications for economics and the ecosystem. In this paper we look at how land use decisions, that is, livestock movement patterns have implications for societal economics and ecosystem services. Research that focuses on local behavior is important because it is at that level where fundamental decisions are made regarding events like extreme climate and changes such as land tenure policy and it is here where resilience is manifested. The notion that broad recommendation domains can be identified for a broad set of people and large regions coping with change is becoming increasingly hard to trust given the spatial and temporal heterogeneity of the systems we are looking at, and the complexity of the world we now live in. Why is this important? The only way the research community is going to make great progress in attaining objectives that do confer resilience (on social and ecological systems) is through much better targeting ability, a large part of which seem to be intimately entwined with understanding how make decisions are made at the local level.

Decision making in a multidisciplinary cancer team: does team discussion result in better quality decisions?

PubMed

Kee, Frank; Owen, Tracy; Leathem, Ruth

2004-01-01

To establish whether treatment recommendations made by clinicians concur with the best outcomes predicted from their prognostic estimates and whether team discussion improves the quality or outcome of their decision making, the authors studied real-time decision making by a lung cancer team. Clinicians completed pre- and postdiscussion questionnaires for 50 newly diagnosed patients. For each patient/doctor pairing, a decision model determined the expected patient outcomes from the clinician's prognostic estimates. The difference between the expected utility of the recommended treatment and the maximum utility derived from the clinician's predictions of the outcomes (the net utility loss) following all potential treatment modalities was calculated as an indicator of quality of the decision. The proportion of treatment decisions changed by the multidisciplinary team discussion was also calculated. Insofar as the change in net utility loss brought about by multidisciplinary team discussion was not significantly different from zero, team discussion did not improve the quality of decision making overall. However, given the modest power of the study, these findings must be interpreted with caution. In only 23 of 87 instances (26%) in which an individual specialist's initial treatment preference differed from the final group judgment did the specialist finally concur with the group treatment choice after discussion. This study does not support the theory that team discussion improves decision making by closing a knowledge gap.

Coastal livelihood transitions under globalization with implications for trans-ecosystem interactions.

PubMed

Kramer, Daniel B; Stevens, Kara; Williams, Nicholas E; Sistla, Seeta A; Roddy, Adam B; Urquhart, Gerald R

2017-01-01

Anthropogenic threats to natural systems can be exacerbated due to connectivity between marine, freshwater, and terrestrial ecosystems, complicating the already daunting task of governance across the land-sea interface. Globalization, including new access to markets, can change social-ecological, land-sea linkages via livelihood responses and adaptations by local people. As a first step in understanding these trans-ecosystem effects, we examined exit and entry decisions of artisanal fishers and smallholder farmers on the rapidly globalizing Caribbean coast of Nicaragua. We found that exit and entry decisions demonstrated clear temporal and spatial patterns and that these decisions differed by livelihood. In addition to household characteristics, livelihood exit and entry decisions were strongly affected by new access to regional and global markets. The natural resource implications of these livelihood decisions are potentially profound as they provide novel linkages and spatially-explicit feedbacks between terrestrial and marine ecosystems. Our findings support the need for more scientific inquiry in understanding trans-ecosystem tradeoffs due to linked-livelihood transitions as well as the need for a trans-ecosystem approach to natural resource management and development policy in rapidly changing coastal regions.

Hurricane Imaging Radiometer (HIRAD) Wind Speed Retrieval Assessment with Dropsondes

NASA Technical Reports Server (NTRS)

Cecil, Daniel J.; Biswas, Sayak K.

2017-01-01

Map surface wind speed over wide swath (approximately 50-60 km, for aircraft greater than FL600) in hurricanes. Provide research data for understanding hurricane structure, and intensity change. Enable improved forecasts, warnings, and decision support.

Influence of change in psychosocial work characteristics on sickness absence: The Whitehall II Study.

PubMed

Head, Jenny; Kivimäki, Mika; Martikainen, Pekka; Vahtera, Jussi; Ferrie, Jane E; Marmot, Michael G

2006-01-01

To study the influence of change in self perceived psychosocial work characteristics on subsequent rates of sickness absence. Prospective cohort study of British civil service employees. Job control, job demands, and work social supports were measured in 1985/88 and in 1991/93. Analyses included 3817 British civil servants with sickness absence records at baseline (1985-89) and for two follow up periods, early (1994-95) and later follow up (1996-98). Change in work characteristics predicted subsequent incidence of long spells of sickness absence (>7 days) in the early follow up period after adjustment for covariates including baseline work characteristics, health status, and sickness absence. Adjusted rate ratios were 1.23 (95% CI 1.03 to 1.46) for decreased compared with stable decision latitude; 1.17 (95% CI 1.01 to 1.36) for increased compared with stable job demands and 0.79 (95% CI 0.67 to 0.93) for increased compared with stable work social support. These associations were also seen in a sub-sample who did not change employment grade. In the later follow up period, associations between work change and long spells of sickness absence were similar for decision latitude, less pronounced for job demands, and no longer apparent for social supports. Changes in work characteristics were not associated with subsequent short spells of sickness absence (

An informatics strategy for cancer care

PubMed Central

Wright, J; Shogan, A; McCune, J; Stevens, S

2008-01-01

Whether transitioning from paper to electronic records or attempting to leverage data from existing systems for outcome studies, oncology practices face many challenges in defining and executing an informatics strategy. With the increasing costs of oncology treatments and expected changes in reimbursement rules, including requirements for evidence that supports physician decisions, it will become essential to collect data on treatment decisions and treatment efficacy to run a successful program. This study evaluates the current state of informatics systems available for use in oncology programs and focuses on developing an informatics strategy to meet the challenges introduced by expected changes in reimbursement rules and in medical and information technologies. PMID:21611003

Real options analysis for photovoltaic project under climate uncertainty

NASA Astrophysics Data System (ADS)

Kim, Kyeongseok; Kim, Sejong; Kim, Hyoungkwan

2016-08-01

The decision on photovoltaic project depends on the level of climate environments. Changes in temperature and insolation affect photovoltaic output. It is important for investors to consider future climate conditions for determining investments on photovoltaic projects. We propose a real options-based framework to assess economic feasibility of photovoltaic project under climate change. The framework supports investors to evaluate climate change impact on photovoltaic projects under future climate uncertainty.

A multistage decision support framework to guide tree species management under climate change via habitat suitability and colonization models, and a knowledge-based scoring system

Treesearch

Anantha M. Prasad; Louis R. Iverson; Stephen N. Matthews; Matthew P. Peters

2016-01-01

Context. No single model can capture the complex species range dynamics under changing climates--hence the need for a combination approach that addresses management concerns. Objective. A multistage approach is illustrated to manage forested landscapes under climate change. We combine a tree species habitat model--DISTRIB II, a species colonization model--SHIFT, and...

Realizing the potential of ecosystem services: a framework for relating ecological changes to economic benefits.

PubMed

Wainger, Lisa; Mazzotta, Marisa

2011-10-01

Increasingly government agencies are seeking to quantify the outcomes of proposed policy options in terms of ecosystem service benefits, yet conflicting definitions and ad hoc approaches to measuring ecosystem services have created confusion regarding how to rigorously link ecological change to changes in human well-being. Here, we describe a step-by-step framework for producing ecological models and metrics that can effectively serve an economic-benefits assessment of a proposed change in policy or management. A focus of the framework is developing comparable units of ecosystem goods and services to support decision-making, even if outcomes cannot be monetized. Because the challenges to translating ecological changes to outcomes appropriate for economic analyses are many, we discuss examples that demonstrate practical methods and approaches to overcoming data limitations. The numerous difficult decisions that government agencies must make to fairly use and allocate natural resources provides ample opportunity for interdisciplinary teams of natural and social scientists to improve methods for quantifying changes in ecosystem services and their effects on human well-being. This framework is offered with the intent of promoting the success of such teams as they support managers in evaluating the equivalency of ecosystem service offsets and trades, establishing restoration and preservation priorities, and more generally, in developing environmental policy that effectively balances multiple perspectives.

Implementing interactive decision support: A case for combining cyberinfrastructure, data fusion, and social process to mobilize scientific knowledge in sustainability problems

NASA Astrophysics Data System (ADS)

Pierce, S. A.

2014-12-01

Geosciences are becoming increasingly data intensive, particularly in relation to sustainability problems, which are multi-dimensional, weakly structured and characterized by high levels of uncertainty. In the case of complex resource management problems, the challenge is to extract meaningful information from data and make sense of it. Simultaneously, scientific knowledge alone is insufficient to change practice. Creating tools, and group decision support processes for end users to interact with data are key challenges to transforming science-based information into actionable knowledge. The ENCOMPASS project began as a multi-year case study in the Atacama Desert of Chile to design and implement a knowledge transfer model for energy-water-mining conflicts in the region. ENCOMPASS combines the use of cyberinfrastructure (CI), automated data collection, interactive interfaces for dynamic decision support, and participatory modelling to support social learning. A pilot version of the ENCOMPASS CI uses open source systems and serves as a structure to integrate and store multiple forms of data and knowledge, such as DEM, meteorological, water quality, geomicrobiological, energy demand, and groundwater models. In the case study, informatics and data fusion needs related to scientific uncertainty around deep groundwater flowpaths and energy-water connections. Users may upload data from field sites with handheld devices or desktops. Once uploaded, data assets are accessible for a variety of uses. To address multi-attributed decision problems in the Atacama region a standalone application with touch-enabled interfaces was created to improve real-time interactions with datasets by groups. The tool was used to merge datasets from the ENCOMPASS CI to support exploration among alternatives and build shared understanding among stakeholders. To date, the project has increased technical capacity among stakeholders, resulted in the creation of both for-profit and non-profit entities, enabled cross-sector collaboration with mining-indigenous stakeholders, and produced an interactive application for group decision support. ENCOMPASS leverages advances in computational tools to deliver data and models for group decision support applied to sustainability science problems.

Factors influencing decision of general practitioners and managers to train and employ a nurse practitioner or physician assistant in primary care: a qualitative study.

PubMed

van der Biezen, Mieke; Derckx, Emmy; Wensing, Michel; Laurant, Miranda

2017-02-07

Due to the increasing demand on primary care, it is not only debated whether there are enough general practitioners (GPs) to comply with these demands but also whether specific tasks can be performed by other care providers. Although changing the workforce skill mix care by employing Physician Assistants (PAs) and Nurse Practitioners (NPs) has proven to be both effective and safe, the implementation of those professionals differs widely between and within countries. To support policy making regarding PAs/NPs in primary care, the aim of this study is to provide insight into factors influencing the decision of GPs and managers to train and employ a PA/NP within their organisation. A qualitative study was conducted in 2014 in which 7 managers of out-of-hours primary care services and 32 GPs who owned a general practice were interviewed. Three main topic areas were covered in the interviews: the decision-making process in the organisation, considerations and arguments to train and employ a PA/NP, and the tasks and responsibilities of a PA/NP. Employment of PAs/NPs in out-of-hours services was intended to substitute care for minor ailments in order to decrease GPs' caseload or to increase service capacity. Mangers formulated long-term planning and role definitions when changing workforce skill mix. Lastly, out-of-hours services experienced difficulties with creating team support among their members regarding the employment of PAs/NPs. In general practices during office hours, GPs indented both substitution and supplementation for minor ailments and/or target populations through changing the skill mix. Supplementation was aimed at improving quality of care and extending the range of services to patients. The decision-making in general practices was accompanied with little planning and role definition. The willingness to employ PAs/NPs was highly influenced by an employees' motivation to start the master's programme and GPs' prior experience with PAs/NPs. Knowledge about the PA/NP profession and legislations was often lacking. Role standardisations, long-term political planning and support from professional associations are needed to support policy makers in implementing skill mix in primary care.

Sustained Large-Scale Collective Climate Action Supported by Effective Climate Change Education Practice

NASA Astrophysics Data System (ADS)

Niepold, F., III; Crim, H.; Fiorile, G.; Eldadah, S.

2017-12-01

Since 2012, the Climate and Energy Literacy community have realized that as cities, nations and the international community seek solutions to global climate change over the coming decades, a more comprehensive, interdisciplinary approach to climate literacy—one that includes economic and social considerations—will play a vital role in knowledgeable planning, decision-making, and governance. City, county and state leaders are now leading the American response to a changing climate by incubating social innovation to prevail in the face of unprecedented change. Cities are beginning to realize the importance of critical investments to support the policies and strategies that will foster the climate literacy necessary for citizens to understand the urgency of climate actions and to succeed in a resilient post-carbon economy and develop the related workforce. Over decade of federal and non-profit Climate Change Education effective methods have been developed that can support municipality's significant educational capabilities for the purpose of strengthening and scaling city, state, business, and education actions designed to sustain and effectively address this significant social change. Looking to foster the effective and innovative strategies that will enable their communities several networks have collaborated to identify recommendations for effective education and communication practices when working with different types of audiences. U.S. National Science Foundation funded Climate Change Education Partnership (CCEP) Alliance, the National Wildlife Federation, NOAA Climate Program Office, Tri-Agency Climate Change Education Collaborative and the Climate Literacy and Energy Awareness Network (CLEAN) are working to develop a new web portal that will highlight "effective" practices that includes the acquisition and use of climate change knowledge to inform decision-making. The purpose of the web portal is to transfer effective practice to support communities to be empowered to address the challenges of a new climate reality and ensure that all people are capable of taking an active role in shaping a sustainable future.

Advances in Medical Analytics Solutions for Autonomous Medical Operations on Long-Duration Missions

NASA Technical Reports Server (NTRS)

Thompson, David E.; Lindsey, Antonia Edward

2017-01-01

A review will be presented on the progress made under STMDGame Changing Development Program Funding towards the development of a Medical Decision Support System for augmenting crew capabilities during long-duration missions, such as Mars Transit. To create an MDSS, initial work requires acquiring images and developing models that analyze and assess the features in such medical biosensor images that support medical assessment of pathologies. For FY17, the project has focused on ultrasound images towards cardiac pathologies: namely, evaluation and assessment of pericardial effusion identification and discrimination from related pneumothorax and even bladder-induced infections that cause inflammation around the heart. This identification is substantially changed due to uncertainty due to conditions of fluid behavior under space-microgravity. This talk will present and discuss the work-to-date in this Project, recognizing conditions under which various machine learning technologies, deep-learning via convolutional neural nets, and statistical learning methods for feature identification and classification can be employed and conditioned to graphical format in preparation for attachment to an inference engine that eventually creates decision support recommendations to remote crew in a triage setting.

Disaster Response Modeling Through Discrete-Event Simulation

NASA Technical Reports Server (NTRS)

Wang, Jeffrey; Gilmer, Graham

2012-01-01

Organizations today are required to plan against a rapidly changing, high-cost environment. This is especially true for first responders to disasters and other incidents, where critical decisions must be made in a timely manner to save lives and resources. Discrete-event simulations enable organizations to make better decisions by visualizing complex processes and the impact of proposed changes before they are implemented. A discrete-event simulation using Simio software has been developed to effectively analyze and quantify the imagery capabilities of domestic aviation resources conducting relief missions. This approach has helped synthesize large amounts of data to better visualize process flows, manage resources, and pinpoint capability gaps and shortfalls in disaster response scenarios. Simulation outputs and results have supported decision makers in the understanding of high risk locations, key resource placement, and the effectiveness of proposed improvements.

Integrated Data & Analysis in Support of Informed and Transparent Decision Making

NASA Astrophysics Data System (ADS)

Guivetchi, K.

2012-12-01

The California Water Plan includes a framework for improving water reliability, environmental stewardship, and economic stability through two initiatives - integrated regional water management to make better use of local water sources by integrating multiple aspects of managing water and related resources; and maintaining and improving statewide water management systems. The Water Plan promotes ways to develop a common approach for data standards and for understanding, evaluating, and improving regional and statewide water management systems, and for common ways to evaluate and select from alternative management strategies and projects. The California Water Plan acknowledges that planning for the future is uncertain and that change will continue to occur. It is not possible to know for certain how population growth, land use decisions, water demand patterns, environmental conditions, the climate, and many other factors that affect water use and supply may change by 2050. To anticipate change, our approach to water management and planning for the future needs to consider and quantify uncertainty, risk, and sustainability. There is a critical need for information sharing and information management to support over-arching and long-term water policy decisions that cross-cut multiple programs across many organizations and provide a common and transparent understanding of water problems and solutions. Achieving integrated water management with multiple benefits requires a transparent description of dynamic linkages between water supply, flood management, water quality, land use, environmental water, and many other factors. Water Plan Update 2013 will include an analytical roadmap for improving data, analytical tools, and decision-support to advance integrated water management at statewide and regional scales. It will include recommendations for linking collaborative processes with technical enhancements, providing effective analytical tools, and improving and sharing data and information. Specifically, this includes achieving better integration and consistency with other planning activities; obtaining consensus on quantitative deliverables; building a common conceptual understanding of the water management system; developing common schematics of the water management system; establishing modeling protocols and standards; and improving transparency and exchange of Water Plan information.

Northern Eurasia Future Initiative: Facing the Challenges of Global Change in the 21st century

NASA Astrophysics Data System (ADS)

Groisman, P. Y.; Gulev, S.; Maksyutov, S. S.; Qi, J.

2015-12-01

During the past 10 years, the Northern Eurasia Earth Science Partnership Initiative (NEESPI) - an interdisciplinary program of internationally-supported Earth systems and science research - has addressed large-scale and long-term manifestations of climate and environmental changes over Northern Eurasia and their impact on the Global Earth system. With more than 1480 peer-reviewed journal publications and 40 books to its credit, NEESPI's activities resulted in significant scientific outreach. This created a new research realm through self-organization of NEESPI scientists in a broad research network, accumulation of knowledge while developing new tools (observations, models, and collaborative networks) and producing new, exciting results that can be applied to directly support decision-making for societal needs. This realm was summed up at the Synthesis NEESPI Workshop in Prague, Czech Republic (April 9-12, 2015) where it was decided to shift gradually the foci of regional studies in Northern Eurasia towards applications with the following major Science Question: " What dynamic and interactive change(s) will affect societal well-being, activities, and health, and what might be the mitigation and adaptation strategies that could support sustainable development and decision-making activities in Northern Eurasia?". To answer this question requires a stronger socio-economic component in the ongoing and future regional studies focused on sustainable societal development under changing climatic and environmental conditions, especially, under conditions when societal decision-making impacts and feeds back on the environment. This made the NEESPI studies closer to the ICSU research initiative "Future Earth". Accordingly, the NEESPI Research Team decided to reorganize in the nearest future NEESPI into "Northern Eurasia Future Initiative" (NEFI) and began development of its Programmatic White Paper (in preparation at the time of this abstract submission). The NEFI research foci emerged in discussions within the NEESPI community during the past 12 months. Presentation will provide justification of these foci and approach examples addressing them. The societal challenges, particularly the socio-economic challenges are the top priority in most of them. .

Turning Points in the Lives of Youth of With/Without ADHD: Are They Linked to Changes in Substance Use?

PubMed

Jensen, Peter S; Yuki, Kumi; Murray, Desiree; Mitchell, John T; Weisner, Thomas; Hinshaw, Steven; Molina, Brooke; Swanson, James; Arnold, L Eugene; Hechtman, Lily; Wells, Karen

2017-04-01

This study examines the behavior beliefs, social supports, and turning points in individuals with/without ADHD related to their substance use/abuse (SU/A) decisions. The coded interviews from 60 participants with/without ADHD were compared for their SU/A decisions and precipitants with these decisions among abstainers, persisters, and desisters. ADHD participants reported fewer social advantages to avoid SU/A than non-ADHD participants. Desisters and persisters reported more social advantages of using drugs than abstainers. Persisters reported both more negative and positive psychological/physiological effects of SU/A. ADHD participants reported fewer positive role models in their lives. Non-ADHD patients reported more positive turning points than ADHD participants, regardless of SU/A status. ADHD individuals face challenges in making healthy decisions about SU/A due to lack of positive role models. Reinforcing accurate behavioral beliefs may be important to change behaviors in individuals with SU/A or to prevent SU/A initiation in ADHD individuals.

Development of the Supported Decision Making Inventory System.

PubMed

Shogren, Karrie A; Wehmeyer, Michael L; Uyanik, Hatice; Heidrich, Megan

2017-12-01

Supported decision making has received increased attention as an alternative to guardianship and a means to enable people with intellectual and developmental disabilities to exercise their right to legal capacity. Assessments are needed that can used by people with disabilities and their systems of supports to identify and plan for needed supports to enable decision making. This article describes the steps taken to develop such an assessment tool, the Supported Decision Making Inventory System (SDMIS), and initial feedback received from self-advocates with intellectual disability. The three sections of the SDMIS (Supported Decision Making Personal Factors Inventory, Supported Decision Making Environmental Demands Inventory, and Decision Making Autonomy Inventory) are described and implications for future research, policy, and practice are discussed.

Posterior cingulate cortex mediates outcome-contingent allocation of behavior

PubMed Central

Hayden, Benjamin Y.; Nair, Amrita C.; McCoy, Allison N.; Platt, Michael L.

2008-01-01

SUMMARY Adaptive decision making requires selecting an action and then monitoring its consequences to improve future decisions. The neuronal mechanisms supporting action evaluation and subsequent behavioral modification, however, remain poorly understood. To investigate the contribution of posterior cingulate cortex (CGp) to these processes, we recorded activity of single neurons in monkeys performing a gambling task in which the reward outcome of each choice strongly influenced subsequent choices. We found that CGp neurons signaled reward outcomes in a nonlinear fashion, and that outcome-contingent modulations in firing rate persisted into subsequent trials. Moreover, firing rate on any one trial predicted switching to the alternative option on the next trial. Finally, microstimulation in CGp following risky choices promoted a preference reversal for the safe option on the following trial. Collectively, these results demonstrate that CGp directly contributes to the evaluative processes that support dynamic changes in decision making in volatile environments. PMID:18940585

Heat and Health in a Changing Climate: Building a Decision Support Tool for California Public Health Officials

NASA Astrophysics Data System (ADS)

Steinberg, N.

2017-12-01

There is considerable interest in overlaying climate projections with social vulnerability maps as a mechanism for targeting community adaptation efforts. Yet the identification of relevant factors for adaptation- and resilience-based decisions remain a challenge. Our findings show that successful adaptation interventions are more likely when factors are grouped and spatially represented. By designing a decision-support tool that is focused on informing long-term planning to mitigate the public health impacts of extreme heat, communities can more easily integrate climate, land use, and population characteristics into local planning processes. The ability to compare risks and potential health impacts across census tracts may also position local practitioners to leverage scarce resources. This presentation will discuss the information gaps identified by planners and public health practitioners throughout California and illustrate the spatial variations of key health risk factors.

A Wireless Sensor Network-Based Approach with Decision Support for Monitoring Lake Water Quality.

PubMed

Huang, Xiaoci; Yi, Jianjun; Chen, Shaoli; Zhu, Xiaomin

2015-11-19

Online monitoring and water quality analysis of lakes are urgently needed. A feasible and effective approach is to use a Wireless Sensor Network (WSN). Lake water environments, like other real world environments, present many changing and unpredictable situations. To ensure flexibility in such an environment, the WSN node has to be prepared to deal with varying situations. This paper presents a WSN self-configuration approach for lake water quality monitoring. The approach is based on the integration of a semantic framework, where a reasoner can make decisions on the configuration of WSN services. We present a WSN ontology and the relevant water quality monitoring context information, which considers its suitability in a pervasive computing environment. We also propose a rule-based reasoning engine that is used to conduct decision support through reasoning techniques and context-awareness. To evaluate the approach, we conduct usability experiments and performance benchmarks.

Workplace bullying in risk and safety professionals.

PubMed

Brewer, Gayle; Holt, Barry; Malik, Shahzeb

2018-02-01

Previous research demonstrates that workplace bullying impacts the welfare of victimized employees, with further consequences for the organization and profession. There is, however, a paucity of information relating to the bullying directed at risk and safety professionals. The present study was conducted to address this issue. Risk and safety professionals (N=420) completed the Negative Acts Questionnaire - Revised and Brief Cope, and reported the extent to which they had been pressured to make or amend a risk or safety based decision. Those experiencing workplace bullying were more likely to engage in a range of coping behaviors, with exposure to work-related and personal bullying particularly influential. Workplace bullying also predicted pressure to make or change a risk or safety based decision. Work related and physically intimidating bullying were particularly important for this aspect of professional practice. Findings are discussed with regard to current practice and the support available to risk and safety professionals. Risk and safety professionals require additional support in relation to workplace bullying and specifically guidance to resist pressure to make or change a risk or safety based decision. Copyright © 2017 National Safety Council and Elsevier Ltd. All rights reserved.

Suggestions for Designers of Navy Electronic Equipment. 1989 Edition. Revision B

DTIC Science & Technology

1989-07-01

his design and the weak links in the reliability chain. From this information, he can make more reasonable decisions as to the need for design changes...SYSTEMS CENTER San Diego. Caifornl 92152-5000 ~89 12 12 084 It is a pleasure to make available this 1989 -Suggestions for Designers of Navy Electronic...the costs of supporting equipment for mission operations. The factors relate to early design decisions . Design deficiencies or design weaknesses in

Building University Capacity to Visualize Solutions to Complex Problems in the Arctic

NASA Astrophysics Data System (ADS)

Broderson, D.; Veazey, P.; Raymond, V. L.; Kowalski, K.; Prakash, A.; Signor, B.

2016-12-01

Rapidly changing environments are creating complex problems across the globe, which are particular magnified in the Arctic. These worldwide challenges can best be addressed through diverse and interdisciplinary research teams. It is incumbent on such teams to promote co-production of knowledge and data-driven decision-making by identifying effective methods to communicate their findings and to engage with the public. Decision Theater North (DTN) is a new semi-immersive visualization system that provides a space for teams to collaborate and develop solutions to complex problems, relying on diverse sets of skills and knowledge. It provides a venue to synthesize the talents of scientists, who gather information (data); modelers, who create models of complex systems; artists, who develop visualizations; communicators, who connect and bridge populations; and policymakers, who can use the visualizations to develop sustainable solutions to pressing problems. The mission of Decision Theater North is to provide a cutting-edge visual environment to facilitate dialogue and decision-making by stakeholders including government, industry, communities and academia. We achieve this mission by adopting a multi-faceted approach reflected in the theater's design, technology, networking capabilities, user support, community relationship building, and strategic partnerships. DTN is a joint project of Alaska's National Science Foundation Experimental Program to Stimulate Competitive Research (NSF EPSCoR) and the University of Alaska Fairbanks (UAF), who have brought the facility up to full operational status and are now expanding its development space to support larger team science efforts. Based in Fairbanks, Alaska, DTN is uniquely poised to address changes taking place in the Arctic and subarctic, and is connected with a larger network of decision theaters that include the Arizona State University Decision Theater Network and the McCain Institute in Washington, DC.

Sea Level Rise Decision Support Tools for Adaptation Planning in Vulnerable Coastal Communities

NASA Astrophysics Data System (ADS)

Rozum, J. S.; Marcy, D.

2015-12-01

NOAA is involved in a myriad of climate related research and projects that help decision makers and the public understand climate science as well as climate change impacts. The NOAA Office for Coastal Management (OCM) provides data, tools, trainings and technical assistance to coastal resource managers. Beginning in 2011, NOAA OCM began developing a sea level rise and coastal flooding impacts viewer which provides nationally consistent data sets and analyses to help communities with coastal management goals such as: understanding and communicating coastal flood hazards, performing vulnerability assessments and increasing coastal resilience, and prioritizing actions for different inundation/flooding scenarios. The Viewer is available on NOAA's Digital Coast platform: (coast.noaa.gov/ditgitalcoast/tools/slr). In this presentation we will share the lessons learned from our work with coastal decision-makers on the role of coastal flood risk data and tools in helping to shape future land use decisions and policies. We will also focus on a recent effort in California to help users understand the similarities and differences of a growing array of sea level rise decision support tools. NOAA staff and other partners convened a workshop entitled, "Lifting the Fog: Bringing Clarity to Sea Level Rise and Shoreline Change Models and Tools," which was attended by tool develops, science translators and coastal managers with the goal to create a collaborative communication framework to help California coastal decision-makers navigate the range of available sea level rise planning tools, and to inform tool developers of future planning needs. A sea level rise tools comparison matrix will be demonstrated. This matrix was developed as part of this effort and has been expanded to many other states via a partnership with NOAA, Climate Central, and The Nature Conservancy.

LandCaRe DSS--an interactive decision support system for climate change impact assessment and the analysis of potential agricultural land use adaptation strategies.

PubMed

Wenkel, Karl-Otto; Berg, Michael; Mirschel, Wilfried; Wieland, Ralf; Nendel, Claas; Köstner, Barbara

2013-09-01

Decision support to develop viable climate change adaptation strategies for agriculture and regional land use management encompasses a wide range of options and issues. Up to now, only a few suitable tools and methods have existed for farmers and regional stakeholders that support the process of decision-making in this field. The interactive model-based spatial information and decision support system LandCaRe DSS attempts to close the existing methodical gap. This system supports interactive spatial scenario simulations, multi-ensemble and multi-model simulations at the regional scale, as well as the complex impact assessment of potential land use adaptation strategies at the local scale. The system is connected to a local geo-database and via the internet to a climate data server. LandCaRe DSS uses a multitude of scale-specific ecological impact models, which are linked in various ways. At the local scale (farm scale), biophysical models are directly coupled with a farm economy calculator. New or alternative simulation models can easily be added, thanks to the innovative architecture and design of the DSS. Scenario simulations can be conducted with a reasonable amount of effort. The interactive LandCaRe DSS prototype also offers a variety of data analysis and visualisation tools, a help system for users and a farmer information system for climate adaptation in agriculture. This paper presents the theoretical background, the conceptual framework, and the structure and methodology behind LandCaRe DSS. Scenario studies at the regional and local scale for the two Eastern German regions of Uckermark (dry lowlands, 2600 km(2)) and Weißeritz (humid mountain area, 400 km(2)) were conducted in close cooperation with stakeholders to test the functionality of the DSS prototype. The system is gradually being transformed into a web version (http://www.landcare-dss.de) to ensure the broadest possible distribution of LandCaRe DSS to the public. The system will be continuously developed, updated and used in different research projects and as a learning and knowledge-sharing tool for students. The main objective of LandCaRe DSS is to provide information on the complex long-term impacts of climate change and on potential management options for adaptation by answering "what-if" type questions. Copyright © 2013 Elsevier Ltd. All rights reserved.

Carbon Cycle Science in Support of Decision-Making

NASA Astrophysics Data System (ADS)

Brown, M. E.; West, T. O.; McGlynn, E.; Gurwick, N. P.; Duren, R. M.; Ocko, I.; Paustian, K.

2016-12-01

There has been an extensive amount of basic and applied research conducted on biogeochemical cycles, land cover change, watershed to earth system modeling, climate change, and energy efficiency. Concurrently, there continues to be interest in how to best reduce net carbon emissions, including maintaining or augmenting global carbon stocks and decreasing fossil fuel emissions. Decisions surrounding reductions in net emissions should be grounded in, and informed by, existing scientific knowledge and analyses in order to be most effective. The translation of scientific research to decision-making is rarely direct, and often requires coordination of objectives or intermediate research steps. For example, complex model output may need to be simplified to provide mean estimates for given activities; biogeochemical models used for climate change prediction may need to be altered to estimate net carbon flux associated with particular activities; or scientific analyses may need to aggregate and analyze data in a different manner to address specific questions. In the aforementioned cases, expertise and capabilities of researchers and decision-makers are both needed, and early coordination and communication is most effective. Initial analysis of existing science and current decision-making needs indicate that (a) knowledge that is co-produced by scientists and decision-makers has a higher probability of being usable for decision making, (b) scientific work in the past decade to integrate activity data into models has resulted in more usable information for decision makers, (c) attribution and accounting of carbon cycle fluxes is key to using carbon cycle science for decision-making, and (d) stronger, long-term links among research on climate and management of carbon-related sectors (e.g., energy, land use, industry, and buildings) are needed to adequately address current issues.

Decision Making For Sustainable Futures In A Rapidly Changing Arctic

NASA Astrophysics Data System (ADS)

Chabay, I.

2016-12-01

Observing, understanding, and predicting effects of rapid climate change in the Arctic are crucial as the circumpolar region becomes more accessible and demand grows for commercial development and resource extraction. Climate change effects - including changes in ocean ice coverage, Arctic weather patterns, permafrost conditions, and coastal erosion - are a consequence of fossil fuel use outside the Arctic, while at the same time the changes open greater access to the Arctic's rich resources, including oil and gas. This offers new opportunities for livelihoods and development of Arctic communities, but inevitably also introduces substantially increased environmental, social, and economic risks. I will outline the rationale for and the process of our transdisciplinary project in engaging with a wide range of actors in the Arctic and beyond. The purpose of the project is to support informed and effective decision making for sustainable futures that is contextually appropriate through co-design and co-production of knowledge with rights-holders and stakeholders.

Supporting End of Life Decision Making: Case Studies of Relational Closeness in Supported Decision Making for People with Severe or Profound Intellectual Disability

ERIC Educational Resources Information Center

Watson, Joanne; Wilson, Erin; Hagiliassis, Nick

2017-01-01

Background: The United Nations Convention on the Rights of Persons with Disabilities (UNCRPD) promotes the use of supported decision making in lieu of substitute decision making. To date, there has been a lack of focus on supported decision making for people with severe or profound intellectual disability, including for end of life decisions.…

A web platform for integrated surface water - groundwater modeling and data management

NASA Astrophysics Data System (ADS)

Fatkhutdinov, Aybulat; Stefan, Catalin; Junghanns, Ralf

2016-04-01

Model-based decision support systems are considered to be reliable and time-efficient tools for resources management in various hydrology related fields. However, searching and acquisition of the required data, preparation of the data sets for simulations as well as post-processing, visualization and publishing of the simulations results often requires significantly more work and time than performing the modeling itself. The purpose of the developed software is to combine data storage facilities, data processing instruments and modeling tools in a single platform which potentially can reduce time required for performing simulations, hence decision making. The system is developed within the INOWAS (Innovative Web Based Decision Support System for Water Sustainability under a Changing Climate) project. The platform integrates spatially distributed catchment scale rainfall - runoff, infiltration and groundwater flow models with data storage, processing and visualization tools. The concept is implemented in a form of a web-GIS application and is build based on free and open source components, including the PostgreSQL database management system, Python programming language for modeling purposes, Mapserver for visualization and publishing the data, Openlayers for building the user interface and others. Configuration of the system allows performing data input, storage, pre- and post-processing and visualization in a single not disturbed workflow. In addition, realization of the decision support system in the form of a web service provides an opportunity to easily retrieve and share data sets as well as results of simulations over the internet, which gives significant advantages for collaborative work on the projects and is able to significantly increase usability of the decision support system.

Measurement-based care for refractory depression: a clinical decision support model for clinical research and practice.

PubMed

Trivedi, Madhukar H; Daly, Ella J

2007-05-01

Despite years of antidepressant drug development and patient and provider education, suboptimal medication dosing and duration of exposure resulting in incomplete remission of symptoms remains the norm in the treatment of depression. Additionally, since no one treatment is effective for all patients, optimal implementation focusing on the measurement of symptoms, side effects, and function is essential to determine effective sequential treatment approaches. There is a need for a paradigm shift in how clinical decision making is incorporated into clinical practice and for a move away from the trial-and-error approach that currently determines the "next best" treatment. This paper describes how our experience with the Texas Medication Algorithm Project (TMAP) and the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial has confirmed the need for easy-to-use clinical support systems to ensure fidelity to guidelines. To further enhance guideline fidelity, we have developed an electronic decision support system that provides critical feedback and guidance at the point of patient care. We believe that a measurement-based care (MBC) approach is essential to any decision support system, allowing physicians to individualize and adapt decisions about patient care based on symptom progress, tolerability of medication, and dose optimization. We also believe that successful integration of sequential algorithms with MBC into real-world clinics will facilitate change that will endure and improve patient outcomes. Although we use major depression to illustrate our approach, the issues addressed are applicable to other chronic psychiatric conditions including comorbid depression and substance use disorder as well as other medical illnesses.

Measurement-Based Care for Refractory Depression: A Clinical Decision Support Model for Clinical Research and Practice

PubMed Central

Trivedi, Madhukar H.; Daly, Ella J.

2009-01-01

Despite years of antidepressant drug development and patient and provider education, suboptimal medication dosing and duration of exposure resulting in incomplete remission of symptoms remains the norm in the treatment of depression. Additionally, since no one treatment is effective for all patients, optimal implementation focusing on the measurement of symptoms, side effects, and function is essential to determine effective sequential treatment approaches. There is a need for a paradigm shift in how clinical decision making is incorporated into clinical practice and for a move away from the trial-and-error approach that currently determines the “next best” treatment. This paper describes how our experience with the Texas Medication Algorithm Project (TMAP) and the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial has confirmed the need for easy-to-use clinical support systems to ensure fidelity to guidelines. To further enhance guideline fidelity, we have developed an electronic decision support system that provides critical feedback and guidance at the point of patient care. We believe that a measurement-based care (MBC) approach is essential to any decision support system, allowing physicians to individualize and adapt decisions about patient care based on symptom progress, tolerability of medication, and dose optimization. We also believe that successful integration of sequential algorithms with MBC into real-world clinics will facilitate change that will endure and improve patient outcomes. Although we use major depression to illustrate our approach, the issues addressed are applicable to other chronic psychiatric conditions including comorbid depression and substance use disorder as well as other medical illnesses. PMID:17320312

Decision support for clinical laboratory capacity planning.

PubMed

van Merode, G G; Hasman, A; Derks, J; Goldschmidt, H M; Schoenmaker, B; Oosten, M

1995-01-01

The design of a decision support system for capacity planning in clinical laboratories is discussed. The DSS supports decisions concerning the following questions: how should the laboratory be divided into job shops (departments/sections), how should staff be assigned to workstations and how should samples be assigned to workstations for testing. The decision support system contains modules for supporting decisions at the overall laboratory level (concerning the division of the laboratory into job shops) and for supporting decisions at the job shop level (assignment of staff to workstations and sample scheduling). Experiments with these modules are described showing both the functionality and the validity.

Features of computerized clinical decision support systems supportive of nursing practice: a literature review.

PubMed

Lee, Seonah

2013-10-01

This study aimed to organize the system features of decision support technologies targeted at nursing practice into assessment, problem identification, care plans, implementation, and outcome evaluation. It also aimed to identify the range of the five stage-related sequential decision supports that computerized clinical decision support systems provided. MEDLINE, CINAHL, and EMBASE were searched. A total of 27 studies were reviewed. The system features collected represented the characteristics of each category from patient assessment to outcome evaluation. Several features were common across the reviewed systems. For the sequential decision support, all of the reviewed systems provided decision support in sequence for patient assessment and care plans. Fewer than half of the systems included problem identification. There were only three systems operating in an implementation stage and four systems in outcome evaluation. Consequently, the key steps for sequential decision support functions were initial patient assessment, problem identification, care plan, and outcome evaluation. Providing decision support in such a full scope will effectively help nurses' clinical decision making. By organizing the system features, a comprehensive picture of nursing practice-oriented computerized decision support systems was obtained; however, the development of a guideline for better systems should go beyond the scope of a literature review.

An Overview Of The Ecosystem Services Research Program Decision Support Framework

EPA Science Inventory

There is an increasing understanding that top-down regulatory and technology driven responses are not sufficient to address current and emerging environmental challenges such as climate change, sustainable communities, and environmental justice. Such problems require ways to dee...

Deploying temporary networks for upscaling of sparse network stations

USDA-ARS?s Scientific Manuscript database

Soil observations networks at the national scale play an integral role in hydrologic modeling, drought assessment, agricultural decision support, and our ability to understand climate change. Understanding soil moisture variability is necessary to apply these measurements to model calibration, busin...

Remote Sensing for Climate and Environmental Change

NASA Technical Reports Server (NTRS)

Evans, Diane

2011-01-01

Remote sensing is being used more and more for decision-making and policy development. Specific examples are: (1) Providing constraints on climate models used in IPCC assessments (2) Framing discussions about greenhouse gas monitoring (3) Providing support for hazard assessment and recovery.

INTRODUCING CHANGES TO QUALITY SYSTEMS IN LARGE, ESTABLISHED ORGANIZATIONS

EPA Science Inventory

To achieve the agency's mission of having defensible and reliable scientific data with which to make informed decisions, the EPA Quality Assurance (QA) community must continue its successful efforts in increasing support for QA activities through personal communication and carefu...

Monitoring Drought Conditions in the Navajo Nation Using NASA Earth Observations

NASA Technical Reports Server (NTRS)

Ly, Vickie; Gao, Michael; Cary, Cheryl; Turnbull-Appell, Sophie; Surunis, Anton

2016-01-01

The Navajo Nation, a 65,700 sq km Native American territory located in the southwestern United States, has been increasingly impacted by severe drought events and changes in climate. These events are coupled with a lack of domestic water infrastructure and economic resources, leaving approximately one-third of the population without access to potable water in their homes. Current methods of monitoring drought are dependent on state-based monthly Standardized Precipitation Index value maps calculated by the Western Regional Climate Center. However, these maps do not provide the spatial resolution needed to illustrate differences in drought severity across the vast Nation. To better understand and monitor drought events and drought regime changes in the Navajo Nation, this project created a geodatabase of historical climate information specific to the area, and a decision support tool to calculate average Standardized Precipitation Index values for user-specified areas. The tool and geodatabase use Tropical Rainfall Monitoring Mission (TRMM) and Global Precipitation Monitor (GPM) observed precipitation data and Parameter-elevation Relationships on Independent Slopes Model modeled historical precipitation data, as well as NASA's modeled Land Data Assimilation Systems deep soil moisture, evaporation, and transpiration data products. The geodatabase and decision support tool will allow resource managers in the Navajo Nation to utilize current and future NASA Earth observation data for increased decision-making capacity regarding future climate change impact on water resources.

Updating beliefs and combining evidence in adaptive forest management under climate change: a case study of Norway spruce (Picea abies L. Karst) in the Black Forest, Germany.

PubMed

Yousefpour, Rasoul; Temperli, Christian; Bugmann, Harald; Elkin, Che; Hanewinkel, Marc; Meilby, Henrik; Jacobsen, Jette Bredahl; Thorsen, Bo Jellesmark

2013-06-15

We study climate uncertainty and how managers' beliefs about climate change develop and influence their decisions. We develop an approach for updating knowledge and beliefs based on the observation of forest and climate variables and illustrate its application for the adaptive management of an even-aged Norway spruce (Picea abies L. Karst) forest in the Black Forest, Germany. We simulated forest development under a range of climate change scenarios and forest management alternatives. Our analysis used Bayesian updating and Dempster's rule of combination to simulate how observations of climate and forest variables may influence a decision maker's beliefs about climate development and thereby management decisions. While forest managers may be inclined to rely on observed forest variables to infer climate change and impacts, we found that observation of climate state, e.g. temperature or precipitation is superior for updating beliefs and supporting decision-making. However, with little conflict among information sources, the strongest evidence would be offered by a combination of at least two informative variables, e.g., temperature and precipitation. The success of adaptive forest management depends on when managers switch to forward-looking management schemes. Thus, robust climate adaptation policies may depend crucially on a better understanding of what factors influence managers' belief in climate change. Copyright © 2013 Elsevier Ltd. All rights reserved.

New methods in hydrologic modeling and decision support for culvert flood risk under climate change

NASA Astrophysics Data System (ADS)

Rosner, A.; Letcher, B. H.; Vogel, R. M.; Rees, P. S.

2015-12-01

Assessing culvert flood vulnerability under climate change poses an unusual combination of challenges. We seek a robust method of planning for an uncertain future, and therefore must consider a wide range of plausible future conditions. Culverts in our case study area, northwestern Massachusetts, USA, are predominantly found in small, ungaged basins. The need to predict flows both at numerous sites and under numerous plausible climate conditions requires a statistical model with low data and computational requirements. We present a statistical streamflow model that is driven by precipitation and temperature, allowing us to predict flows without reliance on reference gages of observed flows. The hydrological analysis is used to determine each culvert's risk of failure under current conditions. We also explore the hydrological response to a range of plausible future climate conditions. These results are used to determine the tolerance of each culvert to future increases in precipitation. In a decision support context, current flood risk as well as tolerance to potential climate changes are used to provide a robust assessment and prioritization for culvert replacements.

Optimizing Decision Support for Tailored Health Behavior Change Applications.

PubMed

Kukafka, Rita; Jeong, In cheol; Finkelstein, Joseph

2015-01-01

The Tailored Lifestyle Change Decision Aid (TLC DA) system was designed to provide support for a person to make an informed choice about which behavior change to work on when multiple unhealthy behaviors are present. TLC DA can be delivered via web, smartphones and tablets. The system collects a significant amount of information that is used to generate tailored messages to consumers to persuade them in certain healthy lifestyles. One limitation is the necessity to collect vast amounts of information from users who manually enter. By identifying an optimal set of self-reported parameters we will be able to minimize the data entry burden of the app users. The study was to identify primary determinants of health behavior choices made by patients after using the system. Using discriminant analysis an optimal set of predictors was identified. The resulting set included smoking status, smoking cessation success estimate, self-efficacy, body mass index and diet status. Predicting smoking cessation choice was the most accurate, followed by weight management. Physical activity and diet choices were better identified in a combined cluster.

Decision-making in geriatric oncology: systemic treatment considerations for older adults with colon cancer.

PubMed

Moth, Erin B; Vardy, Janette; Blinman, Prunella

2016-12-01

Colon cancer is common and can be considered a disease of older adults with more than half of cases diagnosed in patients aged over 70 years. Decision-making about treatment with chemotherapy for older adults may be complicated by age-related physiological changes, impaired functional status, limited social supports, concerns regarding the occurrence of and ability to tolerate treatment toxicity, and the presence of comorbidities. This is compounded by a lack of high quality evidence guiding cancer treatment decisions for older adults. Areas covered: This narrative review evaluates the evidence for adjuvant and palliative systemic therapy in older adults with colon cancer. The value of an adequate assessment prior to making a treatment decision is addressed, with emphasis on the geriatric assessment. Guidance in making a treatment decision is provided. Expert commentary: Treatment decisions should consider goals of care, a patient's treatment preferences, and weigh up relative benefits and harms.

Dynamic Integration of Value Information into a Common Probability Currency as a Theory for Flexible Decision Making

PubMed Central

Christopoulos, Vassilios; Schrater, Paul R.

2015-01-01

Decisions involve two fundamental problems, selecting goals and generating actions to pursue those goals. While simple decisions involve choosing a goal and pursuing it, humans evolved to survive in hostile dynamic environments where goal availability and value can change with time and previous actions, entangling goal decisions with action selection. Recent studies suggest the brain generates concurrent action-plans for competing goals, using online information to bias the competition until a single goal is pursued. This creates a challenging problem of integrating information across diverse types, including both the dynamic value of the goal and the costs of action. We model the computations underlying dynamic decision-making with disparate value types, using the probability of getting the highest pay-off with the least effort as a common currency that supports goal competition. This framework predicts many aspects of decision behavior that have eluded a common explanation. PMID:26394299

HUMAN HEALTH METRICS FOR ENVIRONMENTAL DECISION SUPPORT TOOLS: LESSONS FROM HEALTH ECONOMICS AND DECISION ANALYSIS: PUBLISHED REPORT

EPA Science Inventory

NRMRL-CIN-1351A Hofstetter**, P., and Hammitt, J. K. Human Health Metrics for Environmental Decision Support Tools: Lessons from Health Economics and Decision Analysis. EPA/600/R-01/104 (NTIS PB2002-102119). Decision makers using environmental decision support tools are often ...

Governing therapy choices: power/knowledge in the treatment of progressive renal failure.

PubMed

Holmes, Dave; Perron, Amélie M; Savoie, Marc

2006-12-04

This article outlines the struggle between the power of the health care professional and the rights of the individual to choose freely a modality of treatment. Nurses are instrumental in assisting patients in making the best decision for a therapy they will have to assume for the rest of their lives. In guiding patients' decision, nurses must take into account these unavoidable contingencies: changes in lifestyle, nutritional restrictions, level of acceptance, compliance issues, ease of training and availability of support/facilities. Ensuring that the patient makes an informed decision is therefore an ongoing challenge for nurses as they are taking part in a delicate balancing act between not directly influencing the patient's decision while making sure the patient is accurately informed.

Governing therapy choices: Power/Knowledge in the treatment of progressive renal failure

PubMed Central

Holmes, Dave; Perron, Amélie M; Savoie, Marc

2006-01-01

This article outlines the struggle between the power of the health care professional and the rights of the individual to choose freely a modality of treatment. Nurses are instrumental in assisting patients in making the best decision for a therapy they will have to assume for the rest of their lives. In guiding patients' decision, nurses must take into account these unavoidable contingencies: changes in lifestyle, nutritional restrictions, level of acceptance, compliance issues, ease of training and availability of support/facilities. Ensuring that the patient makes an informed decision is therefore an ongoing challenge for nurses as they are taking part in a delicate balancing act between not directly influencing the patient's decision while making sure the patient is accurately informed. PMID:17144913

Biasing moral decisions by exploiting the dynamics of eye gaze.

PubMed

Pärnamets, Philip; Johansson, Petter; Hall, Lars; Balkenius, Christian; Spivey, Michael J; Richardson, Daniel C

2015-03-31

Eye gaze is a window onto cognitive processing in tasks such as spatial memory, linguistic processing, and decision making. We present evidence that information derived from eye gaze can be used to change the course of individuals' decisions, even when they are reasoning about high-level, moral issues. Previous studies have shown that when an experimenter actively controls what an individual sees the experimenter can affect simple decisions with alternatives of almost equal valence. Here we show that if an experimenter passively knows when individuals move their eyes the experimenter can change complex moral decisions. This causal effect is achieved by simply adjusting the timing of the decisions. We monitored participants' eye movements during a two-alternative forced-choice task with moral questions. One option was randomly predetermined as a target. At the moment participants had fixated the target option for a set amount of time we terminated their deliberation and prompted them to choose between the two alternatives. Although participants were unaware of this gaze-contingent manipulation, their choices were systematically biased toward the target option. We conclude that even abstract moral cognition is partly constituted by interactions with the immediate environment and is likely supported by gaze-dependent decision processes. By tracking the interplay between individuals, their sensorimotor systems, and the environment, we can influence the outcome of a decision without directly manipulating the content of the information available to them.

Success matters: Recasting the relationship among geophysical, biological, and behavioral scientists to support decision making on major environmental challenges

NASA Astrophysics Data System (ADS)

Knopman, Debra S.

2006-03-01

Coping with global change, providing clean water for growing populations, and disposing of nuclear waste are some of the most difficult public policy challenges of our time. Unknowns in the physical sciences are one source of the difficulty. Real difficulties in meeting these challenges also arise in the behavioral sciences. A potentially rich vein of transdisciplinary research is to integrate the psychology of decision making, known as "judgment and decision making," or JDM, with the development of technical information and decision support tools for complex, long-term environmental problems. Practitioners of JDM conduct research on how individuals and groups respond to uncertainty and ambiguity, hedge against risks, anchor decisions to the status quo, compare relative risks and rewards of alternative strategies, and cope with other classes of decisions. Practitioners use a variety of stimuli, chance devices, hypothetical and real choices involving small stakes, scenarios, and questionnaires to measure (directly and indirectly) preferences under varying conditions. These kinds of experiments can help guide choices about the level of complexity required for different types of decision-making processes, the value of new data collection efforts, and the ways in which uncertainty in model outcomes can be cast to minimize decision-making paralysis. They can also provide a scientific basis for interacting with decision makers throughout the model development process, designing better ways of eliciting and combining opinions and of communicating information relevant to public policy issues with the goal of improving the value of the scientific contribution to the social decision.

Effects of Category-Specific Costs on Neural Systems for Perceptual Decision-Making

PubMed Central

Whiteley, Louise; Hulme, Oliver J.; Sahani, Maneesh; Dolan, Raymond J.

2010-01-01

Perceptual judgments are often biased by prospective losses, leading to changes in decision criteria. Little is known about how and where sensory evidence and cost information interact in the brain to influence perceptual categorization. Here we show that prospective losses systematically bias the perception of noisy face-house images. Asymmetries in category-specific cost were associated with enhanced blood-oxygen-level-dependent signal in a frontoparietal network. We observed selective activation of parahippocampal gyrus for changes in category-specific cost in keeping with the hypothesis that loss functions enact a particular task set that is communicated to visual regions. Across subjects, greater shifts in decision criteria were associated with greater activation of the anterior cingulate cortex (ACC). Our results support a hypothesis that costs bias an intermediate representation between perception and action, expressed via general effects on frontal cortex, and selective effects on extrastriate cortex. These findings indicate that asymmetric costs may affect a neural implementation of perceptual decision making in a similar manner to changes in category expectation, constituting a step toward accounting for how prospective losses are flexibly integrated with sensory evidence in the brain. PMID:20357071

From Global Climate Model Projections to Local Impacts Assessments: Analyses in Support of Planning for Climate Change

NASA Astrophysics Data System (ADS)

Snover, A. K.; Littell, J. S.; Mantua, N. J.; Salathe, E. P.; Hamlet, A. F.; McGuire Elsner, M.; Tohver, I.; Lee, S.

2010-12-01

Assessing and planning for the impacts of climate change require regionally-specific information. Information is required not only about projected changes in climate but also the resultant changes in natural and human systems at the temporal and spatial scales of management and decision making. Therefore, climate impacts assessment typically results in a series of analyses, in which relatively coarse-resolution global climate model projections of changes in regional climate are downscaled to provide appropriate input to local impacts models. This talk will describe recent examples in which coarse-resolution (~150 to 300km) GCM output was “translated” into information requested by decision makers at relatively small (watershed) and large (multi-state) scales using regional climate modeling, statistical downscaling, hydrologic modeling, and sector-specific impacts modeling. Projected changes in local air temperature, precipitation, streamflow, and stream temperature were developed to support Seattle City Light’s assessment of climate change impacts on hydroelectric operations, future electricity load, and resident fish populations. A state-wide assessment of climate impacts on eight sectors (agriculture, coasts, energy, forests, human health, hydrology and water resources, salmon, and urban stormwater infrastructure) was developed for Washington State to aid adaptation planning. Hydro-climate change scenarios for approximately 300 streamflow locations in the Columbia River basin and selected coastal drainages west of the Cascades were developed in partnership with major water management agencies in the Pacific Northwest to allow planners to consider how hydrologic changes may affect management objectives. Treatment of uncertainty in these assessments included: using “bracketing” scenarios to describe a range of impacts, using ensemble averages to characterize the central estimate of future conditions (given an emissions scenario), and explicitly assessing the impacts of multiple GCM ensemble members. The implications of various approaches to dealing with uncertainty, such as these, must be carefully communicated to decision makers in order for projected climate impacts to be viewed as credible and used appropriately.

Evaluating the effectiveness of the Emergency Neurological Life Support educational framework in low-income countries

PubMed Central

McCredie, Victoria A; Shrestha, Gentle S; Acharya, Subhash; Bellini, Antonio; Singh, Jeffrey M; Hemphill, J Claude; Goffi, Alberto

2018-01-01

Abstract Background The Emergency Neurological Life Support (ENLS) is an educational initiative designed to improve the acute management of neurological injuries. However, the applicability of the course in low-income countries in unknown. We evaluated the impact of the course on knowledge, decision-making skills and preparedness to manage neurological emergencies in a resource-limited country. Methods A prospective cohort study design was implemented for the first ENLS course held in Asia. Knowledge and decision-making skills for neurological emergencies were assessed at baseline, post-course and at 6 months following course completion. To determine perceived knowledge and preparedness, data were collected using surveys administered immediately post-course and 6 months later. Results A total of 34 acute care physicians from across Nepal attended the course. Knowledge and decision-making skills significantly improved following the course (p=0.0008). Knowledge and decision-making skills remained significantly improved after 6 months, compared with before the course (p=0.02), with no significant loss of skills immediately following the course to the 6-month follow-up (p=0.16). At 6 months, the willingness to participate in continuing medical education activities remained evident, with 77% (10/13) of participants reporting a change in their clinical practice and decision-making, with the repeated use of ENLS protocols as the main driver of change. Conclusions Using the ENLS framework, neurocritical care education can be delivered in low-income countries to improve knowledge uptake, with evidence of knowledge retention up to 6 months. PMID:29506188

Reconciling uncertain costs and benefits in bayes nets for invasive species management

USGS Publications Warehouse

Burgman, M.A.; Wintle, B.A.; Thompson, C.A.; Moilanen, A.; Runge, M.C.; Ben-Haim, Y.

2010-01-01

Bayes nets are used increasingly to characterize environmental systems and formalize probabilistic reasoning to support decision making. These networks treat probabilities as exact quantities. Sensitivity analysis can be used to evaluate the importance of assumptions and parameter estimates. Here, we outline an application of info-gap theory to Bayes nets that evaluates the sensitivity of decisions to possibly large errors in the underlying probability estimates and utilities. We apply it to an example of management and eradication of Red Imported Fire Ants in Southern Queensland, Australia and show how changes in management decisions can be justified when uncertainty is considered. ?? 2009 Society for Risk Analysis.

SANDS: an architecture for clinical decision support in a National Health Information Network.

PubMed

Wright, Adam; Sittig, Dean F

2007-10-11

A new architecture for clinical decision support called SANDS (Service-oriented Architecture for NHIN Decision Support) is introduced and its performance evaluated. The architecture provides a method for performing clinical decision support across a network, as in a health information exchange. Using the prototype we demonstrated that, first, a number of useful types of decision support can be carried out using our architecture; and, second, that the architecture exhibits desirable reliability and performance characteristics.

Scientists and Stakeholders in the Chesapeake Bay: How the Mid-Atlantic RISA Strengthens Climate Resilience Through Participatory Decision-Making Processes

NASA Astrophysics Data System (ADS)

Knopman, D.; Berg, N.

2017-12-01

The NOAA Mid-Atlantic Regional Integrated Sciences and Assessments (MARISA) program was formed in September 2016 to increase climate resilience in the Mid-Atlantic, with an initial focus on the Chesapeake Bay Watershed. In this talk, we will discuss how the program's unique structure and approach are designed to advance resilience to a changing climate through improved data, place-based decision support, and public engagement. Emphasis will be placed on MARISA's approach to integrating stakeholder perspectives from the onset of decision scoping, through the creation of actionable data sets, and concluding with the co-development of adaptation strategies between the scientific community, decision-makers, and stakeholders. Specific examples of this process involving climate-sensitive decisions and investments regarding water resources, land management, and urban corridors will be discussed.

Future of electronic health records: implications for decision support.

PubMed

Rothman, Brian; Leonard, Joan C; Vigoda, Michael M

2012-01-01

The potential benefits of the electronic health record over traditional paper are many, including cost containment, reductions in errors, and improved compliance by utilizing real-time data. The highest functional level of the electronic health record (EHR) is clinical decision support (CDS) and process automation, which are expected to enhance patient health and healthcare. The authors provide an overview of the progress in using patient data more efficiently and effectively through clinical decision support to improve health care delivery, how decision support impacts anesthesia practice, and how some are leading the way using these systems to solve need-specific issues. Clinical decision support uses passive or active decision support to modify clinician behavior through recommendations of specific actions. Recommendations may reduce medication errors, which would result in considerable savings by avoiding adverse drug events. In selected studies, clinical decision support has been shown to decrease the time to follow-up actions, and prediction has proved useful in forecasting patient outcomes, avoiding costs, and correctly prompting treatment plan modifications by clinicians before engaging in decision-making. Clinical documentation accuracy and completeness is improved by an electronic health record and greater relevance of care data is delivered. Clinical decision support may increase clinician adherence to clinical guidelines, but educational workshops may be equally effective. Unintentional consequences of clinical decision support, such as alert desensitization, can decrease the effectiveness of a system. Current anesthesia clinical decision support use includes antibiotic administration timing, improved documentation, more timely billing, and postoperative nausea and vomiting prophylaxis. Electronic health record implementation offers data-mining opportunities to improve operational, financial, and clinical processes. Using electronic health record data in real-time for decision support and process automation has the potential to both reduce costs and improve the quality of patient care. © 2012 Mount Sinai School of Medicine.

Introduction of human papillomavirus (HPV) vaccination into national immunisation schedules in Europe: Results of the VENICE 2007 survey.

PubMed

King, L A; Lévy-Bruhl, D; O'Flanagan, D; Bacci, S; Lopalco, P L; Kudjawu, Y; Salmaso, S

2008-08-14

The European Union Member States are simultaneously considering introducing HPV vaccination into their national immunisation schedules. The Vaccine European New Integrated Collaboration Effort (VENICE) project aims to develop a collaborative European vaccination network. A survey was undertaken to describe the decision status and the decision-making process regarding the potential introduction of human papillomavirus (HPV) vaccination in to their national immunisation schedules. A web-based questionnaire was developed and completed online in 2007 by 28 countries participating in VENICE. As of 31 October 2007,five countries had decided to introduce HPV vaccination into the national immunisation schedule, while another seven had started the decision-making process with a recommendation favouring introduction. Varying target populations were selected by the five countries which had introduced the vaccination. Half of the surveyed countries had undertaken at least one ad hoc study to support the decision-making process. According to an update of the decision-status from January 2008, the number of countries which had made a decision or recommendation changed to 10 and 5 respectively. This survey demonstrates the rapidly evolving nature of HPV vaccine introduction in Europe and the existence of expertise and experience among EU Member States. The VENICE network is capable of following this process and supporting countries in making vaccine introduction decisions. A VENICE collaborative web-space is being developed as a European resource for the decision-making process for vaccine introduction.

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.

Clinical Decision Support Reduces Overuse of Red Blood Cell Transfusions: Interrupted Time Series Analysis.

PubMed

Kassakian, Steven Z; Yackel, Thomas R; Deloughery, Thomas; Dorr, David A

2016-06-01

Red blood cell transfusion is the most common procedure in hospitalized patients in the US. Growing evidence suggests that a sizeable percentage of these transfusions are inappropriate, putting patients at significant risk and increasing costs to the health care system. We performed a retrospective quasi-experimental study from November 2008 until November 2014 in a 576-bed tertiary care hospital. The intervention consisted of an interruptive clinical decision support alert shown to a provider when a red blood cell transfusion was ordered in a patient whose most recent hematocrit was ≥21%. We used interrupted time series analysis to determine whether our primary outcome of interest, rate of red blood cell transfusion in patients with hematocrit ≥21% per 100 patient (pt) days, was reduced by the implementation of the clinical decision support tool. The rate of platelet transfusions was used as a nonequivalent dependent control variable. A total of 143,000 hospital admissions were included in our analysis. Red blood cell transfusions decreased from 9.4 to 7.8 per 100 pt days after the clinical decision support intervention was implemented. Interrupted time series analysis showed that significant decline of 0.05 (95% confidence interval [CI], 0.03-0.07; P < .001) units of red blood cells transfused per 100 pt days per month was already underway in the preintervention period. This trend accelerated to 0.1 (95% CI, 0.09-0.12; P < .001) units of red blood cells transfused per 100 pt days per month following the implementation of the clinical decision support tool. There was no statistical change in the rate of platelet transfusion resulting from the intervention. The implementation of an evidence-based clinical decision support tool was associated with a significant decline in the overuse of red blood cell transfusion. We believe this intervention could be easily replicated in other hospitals using commercial electronic health records and a similar reduction in overuse of red blood cell transfusions achieved. Copyright © 2016 Elsevier Inc. All rights reserved.

Interventions for supporting pregnant women's decision-making about mode of birth after a caesarean.

PubMed

Horey, Dell; Kealy, Michelle; Davey, Mary-Ann; Small, Rhonda; Crowther, Caroline A

2013-07-30

Pregnant women who have previously had a caesarean birth and who have no contraindication for vaginal birth after caesarean (VBAC) may need to decide whether to choose between a repeat caesarean birth or to commence labour with the intention of achieving a VBAC. Women need information about their options and interventions designed to support decision-making may be helpful. Decision support interventions can be implemented independently, or shared with health professionals during clinical encounters or used in mediated social encounters with others, such as telephone decision coaching services. Decision support interventions can include decision aids, one-on-one counselling, group information or support sessions and decision protocols or algorithms. This review considers any decision support intervention for pregnant women making birth choices after a previous caesarean birth. To examine the effectiveness of interventions to support decision-making about vaginal birth after a caesarean birth.Secondary objectives are to identify issues related to the acceptability of any interventions to parents and the feasibility of their implementation. We searched the Cochrane Pregnancy and Childbirth Group's Trials Register (30 June 2013), Current Controlled Trials (22 July 2013), the WHO International Clinical Trials Registry Platform Search Portal (ICTRP) (22 July 2013) and reference lists of retrieved articles. We also conducted citation searches of included studies to identify possible concurrent qualitative studies. All published, unpublished, and ongoing randomised controlled trials (RCTs) and quasi-randomised trials with reported data of any intervention designed to support pregnant women who have previously had a caesarean birth make decisions about their options for birth. Studies using a cluster-randomised design were eligible for inclusion but none were identified. Studies using a cross-over design were not eligible for inclusion. Studies published in abstract form only would have been eligible for inclusion if data were able to be extracted. Two review authors independently applied the selection criteria and carried out data extraction and quality assessment of studies. Data were checked for accuracy. We contacted authors of included trials for additional information. All included interventions were classified as independent, shared or mediated decision supports. Consensus was obtained for classifications. Verification of the final list of included studies was undertaken by three review authors. Three randomised controlled trials involving 2270 women from high-income countries were eligible for inclusion in the review. Outcomes were reported for 1280 infants in one study. The interventions assessed in the trials were designed to be used either independently by women or mediated through the involvement of independent support. No studies looked at shared decision supports, that is, interventions designed to facilitate shared decision-making with health professionals during clinical encounters.We found no difference in planned mode of birth: VBAC (risk ratio (RR) 1.03, 95% confidence interval (CI) 0.97 to 1.10; I² = 0%) or caesarean birth (RR 0.96, 95% CI 0.84 to 1.10; I² = 0%). The proportion of women unsure about preference did not change (RR 0.87, 95% CI 0.62 to 1.20; I² = 0%).There was no difference in adverse outcomes reported between intervention and control groups (one trial, 1275 women/1280 babies): permanent (RR 0.66, 95% CI 0.32 to 1.36); severe (RR 1.02, 95% CI 0.77 to 1.36); unclear (0.66, 95% CI 0.27, 1.61). Overall, 64.8% of those indicating preference for VBAC achieved it, while 97.1% of those planning caesarean birth achieved this mode of birth. We found no difference in the proportion of women achieving congruence between preferred and actual mode of birth (RR 1.02, 95% CI 0.96 to 1.07) (three trials, 1921 women).More women had caesarean births (57.3%), including 535 women where it was unplanned (42.6% all caesarean deliveries and 24.4% all births). We found no difference in actual mode of birth between groups, (average RR 0.97, 95% CI 0.89 to 1.06) (three trials, 2190 women).Decisional conflict about preferred mode of birth was lower (less uncertainty) for women with decisional support (standardised mean difference (SMD) -0.25, 95% CI -0.47 to -0.02; two trials, 787 women; I² = 48%). There was also a significant increase in knowledge among women with decision support compared with those in the control group (SMD 0.74, 95% CI 0.46 to 1.03; two trials, 787 women; I² = 65%). However, there was considerable heterogeneity between the two studies contributing to this outcome ( I² = 65%) and attrition was greater than 15 per cent and the evidence for this outcome is considered to be moderate quality only. There was no difference in satisfaction between women with decision support and those without it (SMD 0.06, 95% CI -0.09 to 0.20; two trials, 797 women; I² = 0%). No study assessed decisional regret or whether women's information needs were met.Qualitative data gathered in interviews with women and health professionals provided information about acceptability of the decision support and its feasibility of implementation. While women liked the decision support there was concern among health professionals about their impact on their time and workload. Evidence is limited to independent and mediated decision supports. Research is needed on shared decision support interventions for women considering mode of birth in a pregnancy after a caesarean birth to use with their care providers.

Toward a Multilingual, Experiential Environment for Learning Decision Technology.

ERIC Educational Resources Information Center

Yeo, Gee Kin; Tan, Seng Teen

1999-01-01

Describes work at the National University of Singapore on the Internet in expanding a simulation game used in supporting a course in decision technology. Topics include decision support systems, multilingual support for cross-cultural decision studies, process support in a World Wide Web-enhanced multiuser domain (MUD) learning environment, and…

Maintenance and operations decision support tool : Clarus regional demonstrations.

DOT National Transportation Integrated Search

2011-01-01

Weather affects almost all maintenance activity decisions. The Federal Highway Administration (FHWA) tested a new decision support system for maintenance in Iowa, Indiana, and Illinois called the Maintenance and Operations Decision Support System (MO...

Northern Eurasia Future Initiative: Facing the Challenges of Global Change in the 21st century

NASA Astrophysics Data System (ADS)

Groisman, Pavel; Gutman, Garik; Gulev, Sergey; Maksyutov, Shamil; Qi, Jiaguo

2016-04-01

During the past 12 years, the Northern Eurasia Earth Science Partnership Initiative (NEESPI) - an interdisciplinary program of internationally-supported Earth systems and science research - has addressed large-scale and long-term manifestations of climate and environmental changes over Northern Eurasia and their impact on the Global Earth system. With more than 1500 peer-reviewed journal publications and 40 books to its credit, NEESPI's activities resulted in significant scientific outreach. This created a new research realm through self-organization of NEESPI scientists in a broad research network, accumulation of knowledge while developing new tools (observations, models, and collaborative networks) and producing new, exciting results that can be applied to directly support decision-making for societal needs. This realm was summed up at the Synthesis NEESPI Workshop in Prague, Czech Republic (April 9-12, 2015) where it was decided to shift gradually the foci of regional studies in Northern Eurasia towards applications with the following major Science Question: " What dynamic and interactive change(s) will affect societal well-being, activities, and health, and what might be the mitigation and adaptation strategies that could support sustainable development and decision-making activities in Northern Eurasia?". To answer this question requires a stronger socio-economic component in the ongoing and future regional studies focused on sustainable societal development under changing climatic and environmental conditions, especially, under conditions when societal decision-making impacts and feeds back on the environment. This made the NEESPI studies closer to the ICSU research initiative "Future Earth". Accordingly, the NEESPI Research Team decided to reorganize in the nearest future NEESPI into "Northern Eurasia Future Initiative" (NEFI) and began development of its Programmatic White Paper (in preparation at the time of this abstract submission). The NEFI research foci emerged in discussions within the NEESPI community during the past 20 months. Presentation will provide justification of these foci and approach examples addressing them. The societal challenges, particularly the socio-economic challenges are the top priority in most of them. Throughout the NEESP Initiative duration, support for it studies has been provided by different national and international Agencies of the United States (in particular, the NASA Land Cover and Land Use Change Program), the Russian Federation (in particular, the Ministry of Education and Science, e.g., mega-grant 14.B25.31.0026), European Union, Japan, and China. After the NEFI White Paper release, we anticipate a similar kind of support for this new Initiative.

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.

Combining communication technology utilization and organizational innovation: evidence from Canadian healthcare decision makers.

PubMed

Jbilou, Jalila; Landry, Réjean; Amara, Nabil; El Adlouni, Salaheddine

2009-08-01

Information and Communication Technology (ICT) and Organizational Innovation (OI) are seen as the miracle of post-modernity in organizations. In this way, they are supposed to resolve most organizational problems, efficiently and rapidly. OI is highly dependent on the capacity and the investment in knowledge management (internal and external) to support decision making process and to implement significant changes. We know what explains ICT utilization (ICTU) and what determines OI development (OID) in healthcare services. Moreover, the literature tends to link ICTU to OID and vice versa. However, this dependency has never been explored empirically through the lens of roles combination. To identify the existing combined roles profiles of ICTU and OID among healthcare decision makers and determine factors of the shift from a profile to another. We did the following: (1) a structured review of the literature on healthcare management by focusing on ICTU and OID which allowed us to build two indexes and a comprehensive framework; (2) a copula methodology to identify with high precision the thresholds for ICTU and OID; and (3) a cross-sectional study based on a survey done with a sample of 942 decision makers from Canadian healthcare organizations through a multinomial logit model to identify determinants of the shift. ICTU and OID are correlated at 22% (Kendal's Tau). The joint distribution (combination) of ICTU and OID shows that four major profiles exist among decision makers in Canadian healthcare organizations: the traditional decision maker, the innovative decision maker, the technologic decision maker and the contemporary decision maker. We found out that classic factors act as barriers to the shift from one profile to the desired profile (from 1 to 4, from 2 to 4 and from 3 to 4). We have identified that the attitude toward research and relational capital are transversal barriers of shift. We have also found that some factors have a specific impact such as engaging in activities of research acquisition, the administrative position (being a manager), the preference for applied research results as source of information, the degree of novelty of research results, and the gender. Modern Canadian healthcare organizations need contemporary decision makers who use ICT and develop OI, if performance is the target. Our results let us suggest that the isolated administrative agents profile is no more effective in a dynamic and changing world. Contemporary decision makers need to be more active intellectually and to take risks in their decisions. Relying exclusively on research results and on their social network is no more helpful for a real shift. Moreover, the traditional factors, i.e. organization size, time, experience ... are no more effective, especially when we consider combined roles. We propose some practical and theoretical recommendations to support these changes.

The Role of Health Care Provider and Partner Decisional Support in Patients' Cancer Treatment Decision-Making Satisfaction.

PubMed

Palmer-Wackerly, Angela L; Krieger, Janice L; Rhodes, Nancy D

2017-01-01

Cancer patients rely on multiple sources of support when making treatment decisions; however, most research studies examine the influence of health care provider support while the influence of family member support is understudied. The current study fills this gap by examining the influence of health care providers and partners on decision-making satisfaction. In a cross-sectional study via an online Qualtrics panel, we surveyed cancer patients who reported that they had a spouse or romantic partner when making cancer treatment decisions (n = 479). Decisional support was measured using 5-point, single-item scales for emotional support, informational support, informational-advice support, and appraisal support. Decision-making satisfaction was measured using Holmes-Rovner and colleagues' (1996) Satisfaction With Decision Scale. We conducted a mediated regression analysis to examine treatment decision-making satisfaction for all participants and a moderated mediation analysis to examine treatment satisfaction among those patients offered a clinical trial. Results indicated that partner support significantly and partially mediated the relationship between health care provider support and patients' decision-making satisfaction but that results did not vary by enrollment in a clinical trial. This study shows how and why decisional support from partners affects communication between health care providers and cancer patients.

Making cognitive decision support work: Facilitating adoption, knowledge and behavior change through QI.

PubMed

Weir, Charlene; Brunker, Cherie; Butler, Jorie; Supiano, Mark A

2017-07-01

This paper evaluates the role of facilitation in the successful implementation of Computerized Decision Support (CDS). Facilitation processes include education, specialized computerized decision support, and work process reengineering. These techniques, as well as modeling and feedback enhance self-efficacy, which we propose is one of the factors that mediate the effectiveness of any CDS. In this study, outpatient clinics implemented quality improvement (QI) projects focused on improving geriatric care. Quality Improvement is the systematic process of improving quality through continuous measurement and targeted actions. The program, entitled "Advancing Geriatric Education through Quality Improvement" (AGE QI), consisted of a 6-month, QI based, intervention: (1) 2h didactic session, (2) 1h QI planning session, (3) computerized decision support design and implementation, (4) QI facilitation activities, (5) outcome feedback, and (6) 20h of CME. Specifically, we examined the impact of the QI based program on clinician's perceived self-efficacy in caring for older adults and the relationship of implementation support and facilitation on perceived success. The intervention was implemented at 3 institutions, 27 community healthcare system clinics, and 134 providers. This study reports the results of pre/post surveys for the forty-nine clinicians who completed the full CME program. Self-efficacy ratings for specific clinical behaviors related to care of older adults were assessed using a Likert based instrument. Self-ratings of efficacy improved across the following domains (depression, falls, end-of-life, functional status and medication management) and specifically in QI targeted domains and were associated with overall clinic improvements. Published by Elsevier Inc.

Erroneous knowledge of results affects decision and memory processes on timing tasks.

PubMed

Ryan, Lawrence J; Fritz, Matthew S

2007-12-01

On mental timing tasks, erroneous knowledge of results (KR) leads to incorrect performance accompanied by the subjective judgment of accurate performance. Using the start-stop technique (an analogue of the peak interval procedure) with both reproduction and production timing tasks, the authors analyze what processes erroneous KR alters. KR provides guidance (performance error information) that lowers decision thresholds. Erroneous KR also provides targeting information that alters response durations proportionately to the magnitude of the feedback error. On the production task, this shift results from changes in the reference memory, whereas on the reproduction task this shift results from changes in the decision threshold for responding. The idea that erroneous KR can alter different cognitive processes on related tasks is supported by the authors' demonstration that the learned strategies can transfer from the reproduction task to the production task but not visa versa. Thus effects of KR are both task and context dependent.

The influence of emotion regulation on social interactive decision-making.

PubMed

van't Wout, Mascha; Chang, Luke J; Sanfey, Alan G

2010-12-01

Although adequate emotion regulation is considered to be essential in every day life, it is especially important in social interactions. However, the question as to what extent two different regulation strategies are effective in changing decision-making in a consequential socially interactive context remains unanswered. We investigated the effect of expressive suppression and emotional reappraisal on strategic decision-making in a social interactive task, that is, the Ultimatum Game. As hypothesized, participants in the emotional reappraisal condition accepted unfair offers more often than participants in the suppression and no-regulation condition. Additionally, the effect of emotional reappraisal influenced the amount of money participants proposed during a second interaction with partners that had treated them unfairly in a previous interaction. These results support and extend previous findings that emotional reappraisal as compared to expressive suppression, is a powerful regulation strategy that influences and changes how we interact with others even in the face of inequity.

The influence of emotion regulation on social interactive decision-making

PubMed Central

van ’t Wout, Mascha; Chang, Luke J.; Sanfey, Alan G.

2010-01-01

Although adequate emotion regulation is considered to be essential in every day life, it is especially important in social interactions. However, the question as to what extent two different regulation strategies are effective in changing decision-making in a consequential socially interactive context remains unanswered. We investigated the effect of expressive suppression and emotional reappraisal on strategic decision-making in a social interactive task, i.e. the Ultimatum Game. As hypothesized, participants in the emotional reappraisal condition accepted unfair offers more often than participants in the suppression and no-regulation condition. Additionally, the effect of emotional reappraisal influenced the amount of money participants proposed during a second interaction with partners that had treated them unfairly in a previous interaction. These results support and extend previous findings that emotional reappraisal as compared to expressive suppression, is a powerful regulation strategy that influences and changes how we interact with others even in the face of inequity. PMID:21171756

Overcoming Indecision by Changing the Decision Boundary

PubMed Central

2017-01-01

The dominant theoretical framework for decision making asserts that people make decisions by integrating noisy evidence to a threshold. It has recently been shown that in many ecologically realistic situations, decreasing the decision boundary maximizes the reward available from decisions. However, empirical support for decreasing boundaries in humans is scant. To investigate this problem, we used an ideal observer model to identify the conditions under which participants should change their decision boundaries with time to maximize reward rate. We conducted 6 expanded-judgment experiments that precisely matched the assumptions of this theoretical model. In this paradigm, participants could sample noisy, binary evidence presented sequentially. Blocks of trials were fixed in duration, and each trial was an independent reward opportunity. Participants therefore had to trade off speed (getting as many rewards as possible) against accuracy (sampling more evidence). Having access to the actual evidence samples experienced by participants enabled us to infer the slope of the decision boundary. We found that participants indeed modulated the slope of the decision boundary in the direction predicted by the ideal observer model, although we also observed systematic deviations from optimality. Participants using suboptimal boundaries do so in a robust manner, so that any error in their boundary setting is relatively inexpensive. The use of a normative model provides insight into what variable(s) human decision makers are trying to optimize. Furthermore, this normative model allowed us to choose diagnostic experiments and in doing so we present clear evidence for time-varying boundaries. PMID:28406682

Bringing the ecosystem services concept into marine management decisions, supporting ecosystems-based management.

NASA Astrophysics Data System (ADS)

Tweddle, J. F.; Byg, A.; Davies, I.; Gubbins, M.; Irvine, K.; Kafas, A.; Kenter, J.; MacDonald, A.; Murray, R. B. O.; Potts, T.; Slater, A. M.; Wright, K.; Scott, B. E.

2016-02-01

The marine environment is under increasing use, putting pressure on marine ecosystems and increasing competition for space. New activities (e.g. renewable energy developments), evolving marine policies (e.g. implementation of marine protected areas), and climate change may drive changes in biodiversity and resulting ecosystem services (ES) that society and business utilise from coastal and marine systems. A process is needed that integrates ecological assessment of changes with stakeholder perceptions and valuation of ES, whilst balancing ease of application with the ability to deal with complex social-economic-ecological issues. The project "Cooperative participatory assessment of the impact of renewable technology on ecosystem services: CORPORATES" involved natural and social scientists, law and policy experts, and marine managers, with the aim of promoting more integrated decision making using ES concepts in marine management. CORPORATES developed a process to bring ES concepts into stakeholders' awareness. The interactive process, involving 2 workshops, employs interludes of knowledge exchange by experts on ecological processes underpinning ES and on law and policy. These enable mapping of benefits linked to activities, participatory system modelling, and deliberation of policy impacts on different sectors. The workshops were attended by industry representatives, regulatory/advisory partners, and other stakeholders (NGOs, SMEs, recreationalists, local government). Mixed sector groups produced new insights into links between activities and ES, and highlighted cross-sector concerns. Here we present the aspects of the process that successfully built shared understanding between industry and stakeholders of inter-linkages and interactions between ES, benefits, activities, and economic and cultural values. These methods provide an ES-based decision-support model for exchanging societal-ecological knowledge and providing stakeholder interaction in marine planning, supporting ecosystem-based management.

Bringing the ecosystem services concept into marine management decisions, supporting ecosystems-based management.

NASA Astrophysics Data System (ADS)

Tweddle, J. F.; Byg, A.; Davies, I.; Gubbins, M.; Irvine, K.; Kafas, A.; Kenter, J.; MacDonald, A.; Murray, R. B. O.; Potts, T.; Slater, A. M.; Wright, K.; Scott, B. E.

2016-12-01

The marine environment is under increasing use, putting pressure on marine ecosystems and increasing competition for space. New activities (e.g. renewable energy developments), evolving marine policies (e.g. implementation of marine protected areas), and climate change may drive changes in biodiversity and resulting ecosystem services (ES) that society and business utilise from coastal and marine systems. A process is needed that integrates ecological assessment of changes with stakeholder perceptions and valuation of ES, whilst balancing ease of application with the ability to deal with complex social-economic-ecological issues. The project "Cooperative participatory assessment of the impact of renewable technology on ecosystem services: CORPORATES" involved natural and social scientists, law and policy experts, and marine managers, with the aim of promoting more integrated decision making using ES concepts in marine management. CORPORATES developed a process to bring ES concepts into stakeholders' awareness. The interactive process, involving 2 workshops, employs interludes of knowledge exchange by experts on ecological processes underpinning ES and on law and policy. These enable mapping of benefits linked to activities, participatory system modelling, and deliberation of policy impacts on different sectors. The workshops were attended by industry representatives, regulatory/advisory partners, and other stakeholders (NGOs, SMEs, recreationalists, local government). Mixed sector groups produced new insights into links between activities and ES, and highlighted cross-sector concerns. Here we present the aspects of the process that successfully built shared understanding between industry and stakeholders of inter-linkages and interactions between ES, benefits, activities, and economic and cultural values. These methods provide an ES-based decision-support model for exchanging societal-ecological knowledge and providing stakeholder interaction in marine planning, supporting ecosystem-based management.

Diabetes-Related Behavior Change Knowledge Transfer to Primary Care Practitioners and Patients: Implementation and Evaluation of a Digital Health Platform

PubMed Central

Vallis, Michael; Piccinini-Vallis, Helena; Imran, Syed Ali; Abidi, Syed Sibte Raza

2018-01-01

Background Behavioral science is now being integrated into diabetes self-management interventions. However, the challenge that presents itself is how to translate these knowledge resources during care so that primary care practitioners can use them to offer evidence-informed behavior change support and diabetes management recommendations to patients with diabetes. Objective The aim of this study was to develop and evaluate a computerized decision support platform called “Diabetes Web-Centric Information and Support Environment” (DWISE) that assists primary care practitioners in applying standardized behavior change strategies and clinical practice guidelines–based recommendations to an individual patient and empower the patient with the skills and knowledge required to self-manage their diabetes through planned, personalized, and pervasive behavior change strategies. Methods A health care knowledge management approach is used to implement DWISE so that it features the following functionalities: (1) assessment of primary care practitioners’ readiness to administer validated behavior change interventions to patients with diabetes; (2) educational support for primary care practitioners to help them offer behavior change interventions to patients; (3) access to evidence-based material, such as the Canadian Diabetes Association’s (CDA) clinical practice guidelines, to primary care practitioners; (4) development of personalized patient self-management programs to help patients with diabetes achieve healthy behaviors to meet CDA targets for managing type 2 diabetes; (5) educational support for patients to help them achieve behavior change; and (6) monitoring of the patients’ progress to assess their adherence to the behavior change program and motivating them to ensure compliance with their program. DWISE offers these functionalities through an interactive Web-based interface to primary care practitioners, whereas the patient’s self-management program and associated behavior interventions are delivered through a mobile patient diary via mobile phones and tablets. DWISE has been tested for its usability, functionality, usefulness, and acceptance through a series of qualitative studies. Results For the primary care practitioner tool, most usability problems were associated with the navigation of the tool and the presentation, formatting, understandability, and suitability of the content. For the patient tool, most issues were related to the tool’s screen layout, design features, understandability of the content, clarity of the labels used, and navigation across the tool. Facilitators and barriers to DWISE use in a shared decision-making environment have also been identified. Conclusions This work has provided a unique electronic health solution to translate complex health care knowledge in terms of easy-to-use, evidence-informed, point-of-care decision aids for primary care practitioners. Patients’ feedback is now being used to make necessary modification to DWISE. PMID:29669705

Diabetes-Related Behavior Change Knowledge Transfer to Primary Care Practitioners and Patients: Implementation and Evaluation of a Digital Health Platform.

PubMed

Abidi, Samina; Vallis, Michael; Piccinini-Vallis, Helena; Imran, Syed Ali; Abidi, Syed Sibte Raza

2018-04-18

Behavioral science is now being integrated into diabetes self-management interventions. However, the challenge that presents itself is how to translate these knowledge resources during care so that primary care practitioners can use them to offer evidence-informed behavior change support and diabetes management recommendations to patients with diabetes. The aim of this study was to develop and evaluate a computerized decision support platform called "Diabetes Web-Centric Information and Support Environment" (DWISE) that assists primary care practitioners in applying standardized behavior change strategies and clinical practice guidelines-based recommendations to an individual patient and empower the patient with the skills and knowledge required to self-manage their diabetes through planned, personalized, and pervasive behavior change strategies. A health care knowledge management approach is used to implement DWISE so that it features the following functionalities: (1) assessment of primary care practitioners' readiness to administer validated behavior change interventions to patients with diabetes; (2) educational support for primary care practitioners to help them offer behavior change interventions to patients; (3) access to evidence-based material, such as the Canadian Diabetes Association's (CDA) clinical practice guidelines, to primary care practitioners; (4) development of personalized patient self-management programs to help patients with diabetes achieve healthy behaviors to meet CDA targets for managing type 2 diabetes; (5) educational support for patients to help them achieve behavior change; and (6) monitoring of the patients' progress to assess their adherence to the behavior change program and motivating them to ensure compliance with their program. DWISE offers these functionalities through an interactive Web-based interface to primary care practitioners, whereas the patient's self-management program and associated behavior interventions are delivered through a mobile patient diary via mobile phones and tablets. DWISE has been tested for its usability, functionality, usefulness, and acceptance through a series of qualitative studies. For the primary care practitioner tool, most usability problems were associated with the navigation of the tool and the presentation, formatting, understandability, and suitability of the content. For the patient tool, most issues were related to the tool's screen layout, design features, understandability of the content, clarity of the labels used, and navigation across the tool. Facilitators and barriers to DWISE use in a shared decision-making environment have also been identified. This work has provided a unique electronic health solution to translate complex health care knowledge in terms of easy-to-use, evidence-informed, point-of-care decision aids for primary care practitioners. Patients' feedback is now being used to make necessary modification to DWISE. ©Samina Abidi, Michael Vallis, Helena Piccinini-Vallis, Syed Ali Imran, Syed Sibte Raza Abidi. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 18.04.2018.

Uncertainty and probability in wildfire management decision support: An example from the United States [Chapter 4

Treesearch

Matthew Thompson; David Calkin; Joe H. Scott; Michael Hand

2017-01-01

Wildfire risk assessment is increasingly being adopted to support federal wildfire management decisions in the United States. Existing decision support systems, specifically the Wildland Fire Decision Support System (WFDSS), provide a rich set of probabilistic and risk‐based information to support the management of active wildfire incidents. WFDSS offers a wide range...

Interprofessional practice and decision support: an organizational framework applied to a mental health setting.

PubMed

Campbell, Susan; Stowe, Karen; Ozanne, Elissa M

2011-11-01

Decision support as a means to assist people in making healthcare decisions has been discussed extensively in the medical literature. However, the potential for use of decision support and decision aids with people with psychiatric disabilities in order to promote recovery has only begun to be researched and discussed in the mental health literature. Organizational factors that foster interprofessional practice within a decision support environment focused on mental health issues are examined in this paper.

From products to processes: Academic events to foster interdisciplinary and iterative dialogue in a changing climate

NASA Astrophysics Data System (ADS)

Addor, Nans; Ewen, Tracy; Johnson, Leigh; Ćöltekin, Arzu; Derungs, Curdin; Muccione, Veruska

2015-08-01

In the context of climate change, both climate researchers and decision makers deal with uncertainties, but these uncertainties differ in fundamental ways. They stem from different sources, cover different temporal and spatial scales, might or might not be reducible or quantifiable, and are generally difficult to characterize and communicate. Hence, a mutual understanding between current and future climate researchers and decision makers must evolve for adaptation strategies and planning to progress. Iterative two-way dialogue can help to improve the decision making process by bridging current top-down and bottom-up approaches. One way to cultivate such interactions is by providing venues for these actors to interact and exchange on the uncertainties they face. We use a workshop-seminar series involving academic researchers, students, and decision makers as an opportunity to put this idea into practice and evaluate it. Seminars, case studies, and a round table allowed participants to reflect upon and experiment with uncertainties. An opinion survey conducted before and after the workshop-seminar series allowed us to qualitatively evaluate its influence on the participants. We find that the event stimulated new perspectives on research products and communication processes, and we suggest that similar events may ultimately contribute to the midterm goal of improving support for decision making in a changing climate. Therefore, we recommend integrating bridging events into university curriculum to foster interdisciplinary and iterative dialogue among researchers, decision makers, and students.

Examining Challenges Related to the Production of Actionable Climate Knowledge for Adaptation Decision-Making: A Focus on Climate Knowledge System Producers

NASA Astrophysics Data System (ADS)

Ernst, K.; Preston, B. L.; Tenggren, S.; Klein, R.; Gerger-Swartling, Å.

2017-12-01

Many challenges to adaptation decision-making and action have been identified across peer-reviewed and gray literature. These challenges have primarily focused on the use of climate knowledge for adaptation decision-making, the process of adaptation decision-making, and the needs of the decision-maker. Studies on climate change knowledge systems often discuss the imperative role of climate knowledge producers in adaptation decision-making processes and stress the need for producers to engage in knowledge co-production activities and to more effectively meet decision-maker needs. While the influence of climate knowledge producers on the co-production of science for adaptation decision-making is well-recognized, hardly any research has taken a direct approach to analyzing the challenges that climate knowledge producers face when undertaking science co-production. Those challenges can influence the process of knowledge production and may hinder the creation, utilization, and dissemination of actionable knowledge for adaptation decision-making. This study involves semi-structured interviews, focus groups, and participant observations to analyze, identify, and contextualize the challenges that climate knowledge producers in Sweden face as they endeavor to create effective climate knowledge systems for multiple contexts, scales, and levels across the European Union. Preliminary findings identify complex challenges related to education, training, and support; motivation, willingness, and culture; varying levels of prioritization; professional roles and responsibilities; the type and amount of resources available; and professional incentive structures. These challenges exist at varying scales and levels across individuals, organizations, networks, institutions, and disciplines. This study suggests that the creation of actionable knowledge for adaptation decision-making is not supported across scales and levels in the climate knowledge production landscape. Additionally, enabling the production of actionable knowledge for adaptation decision-making requires multi-level effort beyond the individual level.

Water and life from snow: A trillion dollar science question

NASA Astrophysics Data System (ADS)

Sturm, Matthew; Goldstein, Michael A.; Parr, Charles

2017-05-01

Snow provides essential resources/services in the form of water for human use, and climate regulation in the form of enhanced cooling of the Earth. In addition, it supports a thriving winter outdoor recreation industry. To date, the financial evaluation of the importance of snow is incomplete and hence the need for accelerated snow research is not as clear as it could be. With snow cover changing worldwide in several worrisome ways, there is pressing need to determine global, regional, and local rates of snow cover change, and to link these to financial analyses that allow for rational decision making, as risks related to those decisions involve trillions of dollars.

Implementation of workflow engine technology to deliver basic clinical decision support functionality.

PubMed

Huser, Vojtech; Rasmussen, Luke V; Oberg, Ryan; Starren, Justin B

2011-04-10

Workflow engine technology represents a new class of software with the ability to graphically model step-based knowledge. We present application of this novel technology to the domain of clinical decision support. Successful implementation of decision support within an electronic health record (EHR) remains an unsolved research challenge. Previous research efforts were mostly based on healthcare-specific representation standards and execution engines and did not reach wide adoption. We focus on two challenges in decision support systems: the ability to test decision logic on retrospective data prior prospective deployment and the challenge of user-friendly representation of clinical logic. We present our implementation of a workflow engine technology that addresses the two above-described challenges in delivering clinical decision support. Our system is based on a cross-industry standard of XML (extensible markup language) process definition language (XPDL). The core components of the system are a workflow editor for modeling clinical scenarios and a workflow engine for execution of those scenarios. We demonstrate, with an open-source and publicly available workflow suite, that clinical decision support logic can be executed on retrospective data. The same flowchart-based representation can also function in a prospective mode where the system can be integrated with an EHR system and respond to real-time clinical events. We limit the scope of our implementation to decision support content generation (which can be EHR system vendor independent). We do not focus on supporting complex decision support content delivery mechanisms due to lack of standardization of EHR systems in this area. We present results of our evaluation of the flowchart-based graphical notation as well as architectural evaluation of our implementation using an established evaluation framework for clinical decision support architecture. We describe an implementation of a free workflow technology software suite (available at http://code.google.com/p/healthflow) and its application in the domain of clinical decision support. Our implementation seamlessly supports clinical logic testing on retrospective data and offers a user-friendly knowledge representation paradigm. With the presented software implementation, we demonstrate that workflow engine technology can provide a decision support platform which evaluates well against an established clinical decision support architecture evaluation framework. Due to cross-industry usage of workflow engine technology, we can expect significant future functionality enhancements that will further improve the technology's capacity to serve as a clinical decision support platform.

An integrated decision support system for diagnosing and managing patients with community-acquired pneumonia.

PubMed Central

Aronsky, D.; Haug, P. J.

1999-01-01

Decision support systems that integrate guidelines have become popular applications to reduce variation and deliver cost-effective care. However, adverse characteristics of decision support systems, such as additional and time-consuming data entry or manually identifying eligible patients, result in a "behavioral bottleneck" that prevents decision support systems to become part of the clinical routine. This paper describes the design and the implementation of an integrated decision support system that explores a novel approach for bypassing the behavioral bottleneck. The real-time decision support system does not require health care providers to enter additional data and consists of a diagnostic and a management component. Images Fig. 1 Fig. 2 Fig. 3 PMID:10566348

Identification of Relevant Costs in the Decision to Consolidate or Maintain Two Marine Corps Recruit Training Depots

DTIC Science & Technology

2015-06-01

Martial Arts Program MCRD Marine Corps Recruit Depot PCO Property Control Office PSC permanent change of station PSE personnel support...office supplies and materials required for the operations office to function. The Property Control Office ( PCO ) is another cost under the base...operations subcategory. PCO supports the Marines with non-deployable equipment. PCO Garrison Property, PSE, collateral equipment (CE) and food preparation

Telephone Support During Overseas Deployment for Military Spouses

DTIC Science & Technology

2017-12-01

other provision of law, no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a...negotiating roles and relationships; changes during deployment; strategies to support the spouse and the service member; and cues to alert spouses when to...14 o Table 4. Decision Making When Service Member (SM) Home and Deployed ............. 15 • Spouse Deployed Contents – Elearning modules

Cyborg practices: call-handlers and computerised decision support systems in urgent and emergency care.

PubMed

Pope, Catherine; Halford, Susan; Turnbull, Joanne; Prichard, Jane

2014-06-01

This article draws on data collected during a 2-year project examining the deployment of a computerised decision support system. This computerised decision support system was designed to be used by non-clinical staff for dealing with calls to emergency (999) and urgent care (out-of-hours) services. One of the promises of computerised decisions support technologies is that they can 'hold' vast amounts of sophisticated clinical knowledge and combine it with decision algorithms to enable standardised decision-making by non-clinical (clerical) staff. This article draws on our ethnographic study of this computerised decision support system in use, and we use our analysis to question the 'automated' vision of decision-making in healthcare call-handling. We show that embodied and experiential (human) expertise remains central and highly salient in this work, and we propose that the deployment of the computerised decision support system creates something new, that this conjunction of computer and human creates a cyborg practice.

Development of a decision support system for analysis and solutions of prolonged standing in the workplace.

PubMed

Halim, Isa; Arep, Hambali; Kamat, Seri Rahayu; Abdullah, Rohana; Omar, Abdul Rahman; Ismail, Ahmad Rasdan

2014-06-01

Prolonged standing has been hypothesized as a vital contributor to discomfort and muscle fatigue in the workplace. The objective of this study was to develop a decision support system that could provide systematic analysis and solutions to minimize the discomfort and muscle fatigue associated with prolonged standing. The integration of object-oriented programming and a Model Oriented Simultaneous Engineering System were used to design the architecture of the decision support system. Validation of the decision support system was carried out in two manufacturing companies. The validation process showed that the decision support system produced reliable results. The decision support system is a reliable advisory tool for providing analysis and solutions to problems related to the discomfort and muscle fatigue associated with prolonged standing. Further testing of the decision support system is suggested before it is used commercially.

Development of a Decision Support System for Analysis and Solutions of Prolonged Standing in the Workplace

PubMed Central

Halim, Isa; Arep, Hambali; Kamat, Seri Rahayu; Abdullah, Rohana; Omar, Abdul Rahman; Ismail, Ahmad Rasdan

2014-01-01

Background Prolonged standing has been hypothesized as a vital contributor to discomfort and muscle fatigue in the workplace. The objective of this study was to develop a decision support system that could provide systematic analysis and solutions to minimize the discomfort and muscle fatigue associated with prolonged standing. Methods The integration of object-oriented programming and a Model Oriented Simultaneous Engineering System were used to design the architecture of the decision support system. Results Validation of the decision support system was carried out in two manufacturing companies. The validation process showed that the decision support system produced reliable results. Conclusion The decision support system is a reliable advisory tool for providing analysis and solutions to problems related to the discomfort and muscle fatigue associated with prolonged standing. Further testing of the decision support system is suggested before it is used commercially. PMID:25180141

A Customized Drought Decision Support Tool for Hsinchu Science Park

NASA Astrophysics Data System (ADS)

Huang, Jung; Tien, Yu-Chuan; Lin, Hsuan-Te; Liu, Tzu-Ming; Tung, Ching-Pin

2016-04-01

Climate change creates more challenges for water resources management. Due to the lack of sufficient precipitation in Taiwan in fall of 2014, many cities and counties suffered from water shortage during early 2015. Many companies in Hsinchu Science Park were significantly influenced and realized that they need a decision support tool to help them managing water resources. Therefore, a customized computer program was developed, which is capable of predicting the future status of public water supply system and water storage of factories when the water rationing is announced by the government. This program presented in this study for drought decision support (DDSS) is a customized model for a semiconductor company in the Hsinchu Science Park. The DDSS is programmed in Java which is a platform-independent language. System requirements are any PC with the operating system above Windows XP and an installed Java SE Runtime Environment 7. The DDSS serves two main functions. First function is to predict the future storage of Baoshan Reservoir and Second Baoshan Reservoir, so to determine the time point of water use restriction in Hsinchu Science Park. Second function is to use the results to help the company to make decisions to trigger their response plans. The DDSS can conduct real-time scenario simulations calculating the possible storage of water tank for each factory with pre-implementation and post-implementation of those response plans. In addition, DDSS can create reports in Excel to help decision makers to compare results between different scenarios.

Developing the U.S. Wildland Fire Decision Support System

Treesearch

Erin Noonan-Wright; Tonja S. Opperman; Mark A. Finney; Tom Zimmerman; Robert C. Seli; Lisa M. Elenz; David E. Calkin; John R. Fiedler

2011-01-01

A new decision support tool, the Wildland Fire Decision Support System (WFDSS) has been developed to support risk-informed decision-making for individual fires in the United States. WFDSS accesses national weather data and forecasts, fire behavior prediction, economic assessment, smoke management assessment, and landscape databases to efficiently formulate and apply...

Decision Support for Ecosystem Management (Chapter 28)

Treesearch

Keith Reynolds; Jennifer Bjork; Rachel Riemann Hershey; Dan Schmoldt; John Payne; Susan King; Lee DeCola; Mark J. Twery; Pat Cunningham

1999-01-01

This chapter presents a management perspective on decision support for ecosystem management.The Introduction provides a brief historical overview of decision support technology as it has been used in natural resource management, discusses the role of decision support in ecosystem management as we see it, and summarizes the current state of the technology.

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.

A Changing Information Environment Challenges Public Administrations.

ERIC Educational Resources Information Center

Otten, Klaus W.

1989-01-01

Describes ways in which information handling techniques will eventually be used in public administration, focusing on technologies that automate routine administrative processes and support decision making. The need to develop a long range concept for continued full employment of administrative staff is discussed. (two references) (CLB)

Two decades of change in transportation reflections from transportation statistics annual reports 1994-2014.

DOT National Transportation Integrated Search

2015-01-01

The Bureau of Transportation Statistics (BTS) : provides information to support understanding : and decision-making related to the transportation : system, including the size and extent of the : system, how it is used, how well it works, and its : co...

The Student Affairs Committee. Effective Committees. Board Basics.

ERIC Educational Resources Information Center

Goodale, Thomas G.

1997-01-01

Responsibilities of the college or university governing board's student affairs committee include representing students' interests in all policy decisions, ensuring provision of adequate financial resources to support a comprehensive student affairs program, ensuring that board policies keep pace with students' diverse and changing needs, and…

Municipal Solid Waste - Sustainable Materials Management

EPA Science Inventory

The MSW DST was initially developed in the 1990s and has evolved over the years to better account for changes in waste management practices, waste composition, and improvements in decision support tool design and functionality. The most recent version of the tool is publicly ava...

The Effect of a Supreme Court Decision Regarding Gay Marriage on Social Norms and Personal Attitudes.

PubMed

Tankard, Margaret E; Paluck, Elizabeth Levy

2017-09-01

We propose that institutions such as the U.S. Supreme Court can lead individuals to update their perceptions of social norms, in contrast to the mixed evidence on whether institutions shape individuals' personal opinions. We studied reactions to the June 2015 U.S. Supreme Court ruling in favor of same-sex marriage. In a controlled experimental setting, we found that a favorable ruling, when presented as likely, shifted perceived norms and personal attitudes toward increased support for gay marriage and gay people. Next, a five-wave longitudinal time-series study using a sample of 1,063 people found an increase in perceived social norms supporting gay marriage after the ruling but no change in personal attitudes. This pattern was replicated in a separate between-subjects data set. These findings provide the first experimental evidence that an institutional decision can change perceptions of social norms, which have been shown to guide behavior, even when individual opinions are unchanged.

Diagnosing, monitoring and managing behavioural variant frontotemporal dementia.

PubMed

Piguet, Olivier; Kumfor, Fiona; Hodges, John

2017-09-02

Behavioural variant frontotemporal dementia is characterised by insidious changes in personality and interpersonal conduct that reflect progressive disintegration of the neural circuits involved in social cognition, emotion regulation, motivation and decision making. The underlying pathology is heterogeneous and classified according to the presence of intraneuronal inclusions of tau, TDP-43 or, occasionally, fused in sarcoma proteins. Biomarkers to detect these histopathological changes in life are increasingly important with the development of disease-modifying drugs. A number of gene abnormalities have been identified, the most common being an expansion in the C9orf72 gene, which together account for most familial cases. The 2011 international consensus criteria propose three levels of diagnostic certainty: possible, probable and definite. Detailed history taking from family members to elicit behavioural features underpins the diagnostic process, with support from neuropsychological testing designed to detect impairment in decision making, emotion processing and social cognition. Brain imaging is important for increasing the level of diagnosis certainty over time. Carer education and support remain of paramount importance.

SANDS: a service-oriented architecture for clinical decision support in a National Health Information Network.

PubMed

Wright, Adam; Sittig, Dean F

2008-12-01

In this paper, we describe and evaluate a new distributed architecture for clinical decision support called SANDS (Service-oriented Architecture for NHIN Decision Support), which leverages current health information exchange efforts and is based on the principles of a service-oriented architecture. The architecture allows disparate clinical information systems and clinical decision support systems to be seamlessly integrated over a network according to a set of interfaces and protocols described in this paper. The architecture described is fully defined and developed, and six use cases have been developed and tested using a prototype electronic health record which links to one of the existing prototype National Health Information Networks (NHIN): drug interaction checking, syndromic surveillance, diagnostic decision support, inappropriate prescribing in older adults, information at the point of care and a simple personal health record. Some of these use cases utilize existing decision support systems, which are either commercially or freely available at present, and developed outside of the SANDS project, while other use cases are based on decision support systems developed specifically for the project. Open source code for many of these components is available, and an open source reference parser is also available for comparison and testing of other clinical information systems and clinical decision support systems that wish to implement the SANDS architecture. The SANDS architecture for decision support has several significant advantages over other architectures for clinical decision support. The most salient of these are:

Working memory retrieval as a decision process

PubMed Central

Pearson, Benjamin; Raškevičius, Julius; Bays, Paul M.; Pertzov, Yoni; Husain, Masud

2014-01-01

Working memory (WM) is a core cognitive process fundamental to human behavior, yet the mechanisms underlying it remain highly controversial. Here we provide a new framework for understanding retrieval of information from WM, conceptualizing it as a decision based on the quality of internal evidence. Recent findings have demonstrated that precision of WM decreases with memory load. If WM retrieval uses a decision process that depends on memory quality, systematic changes in response time distribution should occur as a function of WM precision. We asked participants to view sample arrays and, after a delay, report the direction of change in location or orientation of a probe. As WM precision deteriorated with increasing memory load, retrieval time increased systematically. Crucially, the shape of reaction time distributions was consistent with a linear accumulator decision process. Varying either task relevance of items or maintenance duration influenced memory precision, with corresponding shifts in retrieval time. These results provide strong support for a decision-making account of WM retrieval based on noisy storage of items. Furthermore, they show that encoding, maintenance, and retrieval in WM need not be considered as separate processes, but may instead be conceptually unified as operations on the same noise-limited, neural representation. PMID:24492597

Seasonality in communication and collective decision-making in ants.

PubMed

Stroeymeyt, N; Jordan, C; Mayer, G; Hovsepian, S; Giurfa, M; Franks, N R

2014-04-07

The ability of animals to adjust their behaviour according to seasonal changes in their ecology is crucial for their fitness. Eusocial insects display strong collective behavioural seasonality, yet the mechanisms underlying such changes are poorly understood. We show that nest preference by emigrating Temnothorax albipennis ant colonies is influenced by a season-specific modulatory pheromone that may help tune decision-making according to seasonal constraints. The modulatory pheromone triggers aversion towards low-quality nests and enhances colony cohesion in summer and autumn, but not after overwintering-in agreement with reports that field colonies split in spring and reunite in summer. Interestingly, we show that the pheromone acts by downgrading the perceived value of marked nests by informed and naive individuals. This contrasts with theories of collective intelligence, stating that accurate collective decision-making requires independent evaluation of options by individuals. The violation of independence highlighted here was accordingly shown to increase error rate during emigrations. However, this is counterbalanced by enhanced cohesion and the transmission of valuable information through the colony. Our results support recent claims that optimal decisions are not necessarily those that maximize accuracy. Other criteria-such as cohesion or reward rate-may be more relevant in animal decision-making.

Coastal livelihood transitions under globalization with implications for trans-ecosystem interactions

PubMed Central

Stevens, Kara; Williams, Nicholas E.; Sistla, Seeta A.; Roddy, Adam B.; Urquhart, Gerald R.

2017-01-01

Anthropogenic threats to natural systems can be exacerbated due to connectivity between marine, freshwater, and terrestrial ecosystems, complicating the already daunting task of governance across the land-sea interface. Globalization, including new access to markets, can change social-ecological, land-sea linkages via livelihood responses and adaptations by local people. As a first step in understanding these trans-ecosystem effects, we examined exit and entry decisions of artisanal fishers and smallholder farmers on the rapidly globalizing Caribbean coast of Nicaragua. We found that exit and entry decisions demonstrated clear temporal and spatial patterns and that these decisions differed by livelihood. In addition to household characteristics, livelihood exit and entry decisions were strongly affected by new access to regional and global markets. The natural resource implications of these livelihood decisions are potentially profound as they provide novel linkages and spatially-explicit feedbacks between terrestrial and marine ecosystems. Our findings support the need for more scientific inquiry in understanding trans-ecosystem tradeoffs due to linked-livelihood transitions as well as the need for a trans-ecosystem approach to natural resource management and development policy in rapidly changing coastal regions. PMID:29077748

Age-related quantitative and qualitative changes in decision making ability.

PubMed

Isella, Valeria; Mapelli, Cristina; Morielli, Nadia; Pelati, Oriana; Franceschi, Massimo; Appollonio, Ildebrando Marco

2008-01-01

The "frontal aging hypothesis" predicts that brain senescence affects predominantly the prefrontal regions. Preliminary evidence has recently been gathered in favour of an age-related change in a typically frontal process, i.e. decision making, using the Iowa Gambling Task (IGT), but overall findings have been conflicting. Following the traditional scoring method, coupled with a qualitative analysis, in the present study we compared IGT performance of 40 young (mean age: 27.9+/-4.7) and 40 old (mean age: 65.4+/-8.6) healthy adults and of 18 patients affected by frontal lobe dementia of mild severity (mean age: 65.1+/-7.4, mean MMSE score: 24.1+/-3.9). Quantitative findings support the notion that decision making ability declines with age; moreover, it approximates the impairment observed in executive dysfunction due to neurodegeneration. Results of the qualitative analysis did not reach statistical significance for the motivational and learning decision making components considered, but approached significance for the attentional component for elderly versus young normals, suggesting a possible decrease in the ability to maintain sustained attention during complex and prolonged tasks as the putative deficit underlying impaired decision making in normal aging.

Working memory retrieval as a decision process.

PubMed

Pearson, Benjamin; Raskevicius, Julius; Bays, Paul M; Pertzov, Yoni; Husain, Masud

2014-02-03

Working memory (WM) is a core cognitive process fundamental to human behavior, yet the mechanisms underlying it remain highly controversial. Here we provide a new framework for understanding retrieval of information from WM, conceptualizing it as a decision based on the quality of internal evidence. Recent findings have demonstrated that precision of WM decreases with memory load. If WM retrieval uses a decision process that depends on memory quality, systematic changes in response time distribution should occur as a function of WM precision. We asked participants to view sample arrays and, after a delay, report the direction of change in location or orientation of a probe. As WM precision deteriorated with increasing memory load, retrieval time increased systematically. Crucially, the shape of reaction time distributions was consistent with a linear accumulator decision process. Varying either task relevance of items or maintenance duration influenced memory precision, with corresponding shifts in retrieval time. These results provide strong support for a decision-making account of WM retrieval based on noisy storage of items. Furthermore, they show that encoding, maintenance, and retrieval in WM need not be considered as separate processes, but may instead be conceptually unified as operations on the same noise-limited, neural representation.

Heart rate variability indicates emotional value during pro-social economic laboratory decisions with large external validity.

PubMed

Fooken, Jonas

2017-03-10

The present study investigates the external validity of emotional value measured in economic laboratory experiments by using a physiological indicator of stress, heart rate variability (HRV). While there is ample evidence supporting the external validity of economic experiments, there is little evidence comparing the magnitude of internal levels of emotional stress during decision making with external stress. The current study addresses this gap by comparing the magnitudes of decision stress experienced in the laboratory with the stress from outside the laboratory. To quantify a large change in HRV, measures observed in the laboratory during decision-making are compared to the difference between HRV during a university exam and other mental activity for the same individuals in and outside of the laboratory. The results outside the laboratory inform about the relevance of laboratory findings in terms of their relative magnitude. Results show that psychologically induced HRV changes observed in the laboratory, particularly in connection with social preferences, correspond to large effects outside. This underscores the external validity of laboratory findings and shows the magnitude of emotional value connected to pro-social economic decisions in the laboratory.

Enhancing Participation in the U.S. Global Change Research Program

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

Washington, Warren; Lee, Kai; Arent, Doug

2016-02-29

The US Global Change Research Program (USGCRP) is a collection of 13 Federal entities charged by law to assist the United States and the world to understand, assess, predict, and respond to human-induced and natural processes of global change. As the understanding of global change has evolved over the past decades and as demand for scientific information on global change has increased, the USGCRP has increasingly focused on research that can inform decisions to cope with current climate variability and change, to reduce the magnitude of future changes, and to prepare for changes projected over coming decades. Overall, the currentmore » breadth and depth of research in these agencies is insufficient to meet the country's needs, particularly to support decision makers. This report provides a rationale for evaluating current program membership and capabilities and identifying potential new agencies and departments in the hopes that these changes will enable the program to more effectively inform the public and prepare for the future. It also offers actionable recommendations for adjustments to the methods and procedures that will allow the program to better meet its stated goals.« less

Toward the Modularization of Decision Support Systems

NASA Astrophysics Data System (ADS)

Raskin, R. G.

2009-12-01

Decision support systems are typically developed entirely from scratch without the use of modular components. This “stovepiped” approach is inefficient and costly because it prevents a developer from leveraging the data, models, tools, and services of other developers. Even when a decision support component is made available, it is difficult to know what problem it solves, how it relates to other components, or even that the component exists, The Spatial Decision Support (SDS) Consortium was formed in 2008 to organize the body of knowledge in SDS within a common portal. The portal identifies the canonical steps in the decision process and enables decision support components to be registered, categorized, and searched. This presentation describes how a decision support system can be assembled from modular models, data, tools and services, based on the needs of the Earth science application.

Incorporating population viability models into species status assessment and listing decisions under the U.S. Endangered Species Act

USGS Publications Warehouse

McGowan, Conor P.; Allan, Nathan; Servoss, Jeff; Hedwall, Shaula J.; Wooldridge, Brian

2017-01-01

Assessment of a species' status is a key part of management decision making for endangered and threatened species under the U.S. Endangered Species Act. Predicting the future state of the species is an essential part of species status assessment, and projection models can play an important role in developing predictions. We built a stochastic simulation model that incorporated parametric and environmental uncertainty to predict the probable future status of the Sonoran desert tortoise in the southwestern United States and North Central Mexico. Sonoran desert tortoise was a Candidate species for listing under the Endangered Species Act, and decision makers wanted to use model predictions in their decision making process. The model accounted for future habitat loss and possible effects of climate change induced droughts to predict future population growth rates, abundances, and quasi-extinction probabilities. Our model predicts that the population will likely decline over the next few decades, but there is very low probability of quasi-extinction less than 75 years into the future. Increases in drought frequency and intensity may increase extinction risk for the species. Our model helped decision makers predict and characterize uncertainty about the future status of the species in their listing decision. We incorporated complex ecological processes (e.g., climate change effects on tortoises) in transparent and explicit ways tailored to support decision making processes related to endangered species.

Women's health nursing in the context of the National Health Information Infrastructure.

PubMed

Jenkins, Melinda L; Hewitt, Caroline; Bakken, Suzanne

2006-01-01

Nurses must be prepared to participate in the evolving National Health Information Infrastructure and the changes that will consequently occur in health care practice and documentation. Informatics technologies will be used to develop electronic health records with integrated decision support features that will likely lead to enhanced health care quality and safety. This paper provides a summary of the National Health Information Infrastructure and highlights electronic health records and decision support systems within the context of evidence-based practice. Activities at the Columbia University School of Nursing designed to prepare nurses with the necessary informatics competencies to practice in a National Health Information Infrastructure-enabled health care system are described. Data are presented from electronic (personal digital assistant) encounter logs used in our Women's Health Nurse Practitioner program to support evidence-based advanced practice nursing care. Implications for nursing practice, education, and research in the evolving National Health Information Infrastructure are discussed.

A "simulation chain" to define a Multidisciplinary Decision Support System for landslide risk management in pyroclastic soils

NASA Astrophysics Data System (ADS)

Damiano, E.; Mercogliano, P.; Netti, N.; Olivares, L.

2012-04-01

This paper proposes a Multidisciplinary Decision Support System (MDSS) as an approach to manage rainfall-induced shallow landslides of the flow type (flowslides) in pyroclastic deposits. We stress the need to combine information from the fields of meteorology, geology, hydrology, geotechnics and economics to support the agencies engaged in land monitoring and management. The MDSS consists of a "simulation chain" to link rainfall to effects in terms of infiltration, slope stability and vulnerability. This "simulation chain" was developed at the Euro-Mediterranean Centre for Climate Change (CMCC) (meteorological aspects), at the Geotechnical Laboratory of the Second University of Naples (hydrological and geotechnical aspects) and at the Department of Economics of the University of Naples "Federico II" (economic aspects). The results obtained from the application of this simulation chain in the Cervinara area during eleven years of research allowed in-depth analysis of the mechanisms underlying a flowslide in pyroclastic soil.

Assessing Climate-Induced Change in River Flow Using Satellite Remote Sensing and Process Modeling in High Mountain Asia

NASA Astrophysics Data System (ADS)

McDonald, K. C.

2017-12-01

Snow- and glacier-fed river systems originating from High Mountain Asia (HMA) support diverse ecosystems and provide the basis for food and energy production for more than a billion people living downstream. Climate-driven changes in the melting of snow and glaciers and in precipitation patterns are expected to significantly alter the flow of the rivers in the HMA region at various temporal scales, which in turn could heavily affect the socioeconomics of the region. Hence, climate change effects on seasonal and long-term hydrological conditions may have far reaching economic impact annually and over the century. We are developing a decision support tool utilizing integrated microwave remote sensing datasets, process modeling and economic models to inform water resource management decisions and ecosystem sustainability as related to the High Mountain Asia (HMA) region's response to climate change. The availability of consistent time-series microwave remote sensing datasets from Earth-orbiting scatterometers, radiometers and synthetic aperture radar (SAR) imagery provides the basis for the observational framework of this monitoring system. We discuss the assembly, processing and application of scatterometer and SAR data sets from the Advanced Scatterometer (ASCAT) and Sentinal-1 SARs, and the enlistment of these data to monitor seasonal melt and thaw status of glacier-dominated and surrounding regions. We present current status and future plans for this effort. Our team's study emphasizes processes and economic modeling within the Trishuli basin; our remote sensing analysis supports analyses across the HiMAT domain.

Probabilistic Decision Tools for Determining Impacts of Agricultural Development Policy on Household Nutrition

NASA Astrophysics Data System (ADS)

Whitney, Cory W.; Lanzanova, Denis; Muchiri, Caroline; Shepherd, Keith D.; Rosenstock, Todd S.; Krawinkel, Michael; Tabuti, John R. S.; Luedeling, Eike

2018-03-01

Governments around the world have agreed to end hunger and food insecurity and to improve global nutrition, largely through changes to agriculture and food systems. However, they are faced with a lot of uncertainty when making policy decisions, since any agricultural changes will influence social and biophysical systems, which could yield either positive or negative nutrition outcomes. We outline a holistic probability modeling approach with Bayesian Network (BN) models for nutritional impacts resulting from agricultural development policy. The approach includes the elicitation of expert knowledge for impact model development, including sensitivity analysis and value of information calculations. It aims at a generalizable methodology that can be applied in a wide range of contexts. To showcase this approach, we develop an impact model of Vision 2040, Uganda's development strategy, which, among other objectives, seeks to transform the country's agricultural landscape from traditional systems to large-scale commercial agriculture. Model results suggest that Vision 2040 is likely to have negative outcomes for the rural livelihoods it intends to support; it may have no appreciable influence on household hunger but, by influencing preferences for and access to quality nutritional foods, may increase the prevalence of micronutrient deficiency. The results highlight the trade-offs that must be negotiated when making decisions regarding agriculture for nutrition, and the capacity of BNs to make these trade-offs explicit. The work illustrates the value of BNs for supporting evidence-based agricultural development decisions.

Coping with Inflammatory Bowel Disease: Engaging with Information to Inform Health-Related Decision Making in Daily Life.

PubMed

Restall, Gayle J; Simms, Alexandria M; Walker, John R; Haviva, Clove; Graff, Lesley A; Sexton, Kathryn A; Miller, Norine; Targownik, Laura E; Bernstein, Charles N

2017-08-01

People with inflammatory bowel disease (IBD) require disease and lifestyle information to make health-related decisions in their daily lives. Derived from a larger qualitative study of the lived experiences of people with IBD, we report on findings that explored how people with IBD engage with health-related information in their daily lives. Participants were recruited primarily from the Manitoba IBD Cohort Study. We used purposive sampling to select people with a breadth of characteristics and experiences. Individual interviews were audio-recorded and transcribed verbatim. Data were analyzed using inductive qualitative methods consistent with a phenomenological approach. Forty-five people with IBD participated; 51% were women. Findings highlighted the temporal and contextual influences on engagement with health-related information. Temporal influences were described as the changing need for health-related information over time. Participants identified 6 contextual factors influencing engagement with information to make health decisions: (1) emotional and attitudinal responses, (2) perceived benefits and risks, (3) trust in the source of the information, (4) knowledge and skills to access and use information, (5) availability of evidence to support decisions, and (6) social and economic environments. Findings illustrate the changing needs for health-related information over the course of IBD, and with evolving health and life circumstances. Practitioners can be responsive to information needs of people with IBD by having high-quality information available at the right time in a variety of formats and by supporting the incorporation of information in daily life.

Supporting Coral Reef Ecosystem Management Decisions Appropriate to Climate Change

NASA Astrophysics Data System (ADS)

Hendee, J. C.; Fletcher, P.; Shein, K. A.

2013-05-01

There has been a perception that the myriad of environmental information products derived from satellite and other instrumental sources means ipso facto that there is a direct use for them by environmental managers. Trouble is, as information providers, for the most part we don't really know what decisions managers face daily, nor is it a trivial matter to ascertain the effect of management decisions on the environment, at least in a time frame that facilitates timely maintenance and enhancement of decision support software. To bridge this gap in understanding, we conducted a Needs Assessment (using methodology from the NOAA/Coastal Services Center's Product Design and Evaluation training program) from December, 2011 through May, 2012, in which we queried 15 resource managers in southeast Florida to identify the types of climate data and information products they needed to understand the effects of climate change in their region of purview, and how best these products should be delivered and subsequently enhanced or corrected. Our intent has been to develop a suite of software and information products customized specifically for environmental managers. This report summarizes our success to date, including a report on the development of software for gathering and presenting specific types of climate data, and a narrative about how some U.S. government sponsored efforts, such as Giovanni and TerraVis, as well as non-governmental sponsored efforts such as Marxan, Zonation, SimCLIM, and other off-the-shelf software might be customized for use in specific regions.

Systematic Review of Medical Informatics-Supported Medication Decision Making.

PubMed

Melton, Brittany L

2017-01-01

This systematic review sought to assess the applications and implications of current medical informatics-based decision support systems related to medication prescribing and use. Studies published between January 2006 and July 2016 which were indexed in PubMed and written in English were reviewed, and 39 studies were ultimately included. Most of the studies looked at computerized provider order entry or clinical decision support systems. Most studies examined decision support systems as a means of reducing errors or risk, particularly associated with medication prescribing, whereas a few studies evaluated the impact medical informatics-based decision support systems have on workflow or operations efficiency. Most studies identified benefits associated with decision support systems, but some indicate there is room for improvement.

Patterns of out-of-home placement decision-making in child welfare.

PubMed

Chor, Ka Ho Brian; McClelland, Gary M; Weiner, Dana A; Jordan, Neil; Lyons, John S

2013-10-01

Out-of-home placement decision-making in child welfare is founded on the best interest of the child in the least restrictive setting. After a child is removed from home, however, little is known about the mechanism of placement decision-making. This study aims to systematically examine the patterns of out-of-home placement decisions made in a state's child welfare system by comparing two models of placement decision-making: a multidisciplinary team decision-making model and a clinically based decision support algorithm. Based on records of 7816 placement decisions representing 6096 children over a 4-year period, hierarchical log-linear modeling characterized concordance or agreement, and discordance or disagreement when comparing the two models and accounting for age-appropriate placement options. Children aged below 16 had an overall concordance rate of 55.7%, most apparent in the least restrictive (20.4%) and the most restrictive placement (18.4%). Older youth showed greater discordant distributions (62.9%). Log-linear analysis confirmed the overall robustness of concordance (odd ratios [ORs] range: 2.9-442.0), though discordance was most evident from small deviations from the decision support algorithm, such as one-level under-placement in group home (OR=5.3) and one-level over-placement in residential treatment center (OR=4.8). Concordance should be further explored using child-level clinical and placement stability outcomes. Discordance might be explained by dynamic factors such as availability of placements, caregiver preferences, or policy changes and could be justified by positive child-level outcomes. Empirical placement decision-making is critical to a child's journey in child welfare and should be continuously improved to effect positive child welfare outcomes. Copyright © 2013 Elsevier Ltd. All rights reserved.

A Prototype Indicators System for U.S. Climate Changes, Impacts, Vulnerabilities, and Responses

NASA Astrophysics Data System (ADS)

Kenney, M. A.; Janetos, A.; Gerst, M.; Lloyd, A.; Wolfinger, J. F.; Reyes, J. J.; Anderson, S. M.; Pouyat, R. V.

2015-12-01

Indicators are observations or calculations that are used to systematically report or forecast social and biophysical conditions over time. When the purpose of indicators is to, in part, provide complex scientific information that is understood by non-scientists and included in decision processes, the choice of indicators requires a structured process that includes co-production among a range of actors, including scientists, decision-makers, and a range of stakeholders. Here we describe recommendations on a vision and a prototype created for an indicators system, we term the National Climate Indicators System (NCIS). The goal of the NCIS is to create a system of physical, natural, and societal indicators to communicate and inform decisions about climate changes, impacts, vulnerabilities, and responses. The process of generating the indicator system involved input from over 200 subject-matter experts. Organized into 13 teams, experts created conceptual models of their respective sectors to generate an initial recommended set of indicators. A subset of indicators, which could be immediately implemented, were prototyped for the U.S. Global Change Research Program (USGCRP) a Federal program that coordinates and supports integration of global change research across the government. USGCRP reviewed the recommendations (Kenney et al., 2014) and prototypes provided by the scientific experts, and recently launched 14 indicators as proof-of-concept in support of a sustained National Climate Assessment and to solicit feedback from the users. Social science research is currently being undertaken in order to evaluate how well the prototype indicators communicate science to non-scientists, the usability of indicator system portal by scientists and decision-makers, and the development of information visualization guidelines to improve visual communication effectiveness. The goal of such efforts would be to provide input into the development of a more comprehensive USGCRP indicator set, building on recommendations from Kenney et al. (2014), and improve our understanding of the comprehension and use of indicators by non-scientists.

Development of climate risk services under climate change scenarios in the North Adriatic coast (Italy).

NASA Astrophysics Data System (ADS)

Valentina, Gallina; Silvia, Torresan; Anna, Sperotto; Elisa, Furlan; Andrea, Critto; Antonio, Marcomini

2014-05-01

Nowadays, the challenge for coastal stakeholders and decision makers is to incorporate climate change in land and policy planning in order to ensure a sustainable integrated coastal zone management aimed at preserve coastal environments and socio-economic activities. Consequently, an increasing amount of information on climate variability and its impact on human and natural ecosystem is requested. Climate risk services allows to bridge the gap between climate experts and decision makers communicating timely science-based information about impacts and risks related to climate change that could be incorporated into land planning, policy and practice. Within the CLIM-RUN project (FP7), a participatory Regional Risk Assessment (RRA) methodology was applied for the evaluation of water-related hazards in coastal areas (i.e. pluvial flood and sea-level rise inundation risks) taking into consideration future climate change scenarios in the case study of the North Adriatic Sea for the period 2040-2050. Specifically, through the analysis of hazard, exposure, vulnerability and risk and the application of Multi-Criteria Decision Analysis (MCDA), the RRA methodology allowed to identify and prioritize targets (i.e. residential and commercial-industrial areas, beaches, infrastructures, wetlands, agricultural typology) and sub-areas that are more likely to be affected by pluvial flood and sea-level rise impacts in the same region. From the early stages of the climate risk services development and application, the RRA followed a bottom-up approach taking into account the needs, knowledge and perspectives of local stakeholders dealing with the Integrated Coastal Zone Management (ICZM), by means of questionnaires, workshops and focus groups organized within the project. Specifically, stakeholders were asked to provide their needs in terms of time scenarios, geographical scale and resolution, choice of receptors, vulnerability factors and thresholds that were considered in the implementation of the RRA methodology. The main output of the analysis are climate risk products produced with the DEcision support SYstem for COastal climate change impact assessment (DESYCO) and represented by GIS-based maps and statistics of hazard, exposure, physical and environmental vulnerability, risk and damage. These maps are useful to transfer information about climate change impacts to stakeholders and decision makers, to allow the classification and prioritization of areas that are likely to be affected by climate change impacts more severely than others in the same region, and therefore to support the identification of suitable areas for infrastructure, economic activities and human settlements toward the development of regional adaptation plans. The climate risk products and the results of North Adriatic case study will be here presented and discussed.

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.

Energy Decision Science and Informatics | Integrated Energy Solutions |

Science.gov Websites

Science Advanced decision science methods include multi-objective and multi-criteria decision support. Our decision science methods, including multi-objective and multi-criteria decision support. For example, we

A Decision Analysis Tool for Climate Impacts, Adaptations, and Vulnerabilities

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

Omitaomu, Olufemi A; Parish, Esther S; Nugent, Philip J

Climate change related extreme events (such as flooding, storms, and drought) are already impacting millions of people globally at a cost of billions of dollars annually. Hence, there are urgent needs for urban areas to develop adaptation strategies that will alleviate the impacts of these extreme events. However, lack of appropriate decision support tools that match local applications is limiting local planning efforts. In this paper, we present a quantitative analysis and optimization system with customized decision support modules built on geographic information system (GIS) platform to bridge this gap. This platform is called Urban Climate Adaptation Tool (Urban-CAT). Formore » all Urban-CAT models, we divide a city into a grid with tens of thousands of cells; then compute a list of metrics for each cell from the GIS data. These metrics are used as independent variables to predict climate impacts, compute vulnerability score, and evaluate adaptation options. Overall, the Urban-CAT system has three layers: data layer (that contains spatial data, socio-economic and environmental data, and analytic data), middle layer (that handles data processing, model management, and GIS operation), and application layer (that provides climate impacts forecast, adaptation optimization, and site evaluation). The Urban-CAT platform can guide city and county governments in identifying and planning for effective climate change adaptation strategies.« less

The Distribution of Climate Change Public Opinion in Canada.

PubMed

Mildenberger, Matto; Howe, Peter; Lachapelle, Erick; Stokes, Leah; Marlon, Jennifer; Gravelle, Timothy

2016-01-01

While climate scientists have developed high resolution data sets on the distribution of climate risks, we still lack comparable data on the local distribution of public climate change opinions. This paper provides the first effort to estimate local climate and energy opinion variability outside the United States. Using a multi-level regression and post-stratification (MRP) approach, we estimate opinion in federal electoral districts and provinces. We demonstrate that a majority of the Canadian public consistently believes that climate change is happening. Belief in climate change's causes varies geographically, with more people attributing it to human activity in urban as opposed to rural areas. Most prominently, we find majority support for carbon cap and trade policy in every province and district. By contrast, support for carbon taxation is more heterogeneous. Compared to the distribution of US climate opinions, Canadians believe climate change is happening at higher levels. This new opinion data set will support climate policy analysis and climate policy decision making at national, provincial and local levels.

The Advertising Marketplace and the Media Planning Course.

ERIC Educational Resources Information Center

Lloyd, Carla V.; Slater, Jan; Robbs, Brett

2000-01-01

Surveys media professionals as to how major marketplace changes are affecting the way media planning courses should be taught. Offers recommendations to teach students to: think conceptually, critically, and creatively; use numbers to determine and support their media decisions; contend with audience fragmentation and advertising clutter;…

Bush School Capstone course support : the regional impact of climate change on transportation infrastructure and decision making.

DOT National Transportation Integrated Search

2009-09-01

The Master of Public Service and Administration program at Texas A&Ms Bush School of Government : and Public Service requires that all second year graduate students participate in a two semester Capstone : course. These courses represent the pract...

SUSTAINABILITY AND ITS IMPACT ON SOLID WASTE MANAGEMENT

EPA Science Inventory

The MSW DST was initially developed in the 1990s and has evolved over the years to better account for changes in waste management practices, waste composition, and improvements in decision support tool design and functionality. The most recent version of the tool is publicly ava...

Ecosystem informaties for natural history data - Developing an integrated framework for biological and geographic data

EPA Science Inventory

Threats to the ecological integrity of marine and estuarine systems operate over many spatial scales, from nutrient enrichment at watershed/estuarine linkages to invasive species and climate change at regional/global scales. Decision support tools and information systems needed t...

EnviroAtlas: Two Use Cases in the EnviroAtlas

EPA Science Inventory

EnviroAtlas is an online spatial decision support tool for viewing and analyzing the supply, demand, and drivers of change related to natural and built infrastructure at multiple scales for the nation. To maximize usefulness to a broad range of users, EnviroAtlas contains trainin...

EnviroAtlas: Incorporation of Community-Scale Data for Additional Communities

EPA Science Inventory

EnviroAtlas is ORD’s online spatial decision support tool for viewing and analyzing the supply, demand, and drivers of change related to natural and built infrastructure at multiple scales for the nation. Maps and text identify known relationships between the goods and services ...

Supporting tribal agriculture and natural resources in a changing climate working group

USDA-ARS?s Scientific Manuscript database

The U.S. Department of Agriculture (USDA) Climate Hubs were created in 2014 to deliver science-based, region-specific information and technologies to enable climate-informed decision-making. Our stakeholders include agricultural and natural resource managers (i.e. farmers, ranchers, forest land mana...

NASA Earth Observations Informing Renewable Energy Management and Policy Decision Making

NASA Technical Reports Server (NTRS)

Eckman, Richard S.; Stackhouse, Paul W., Jr.

2008-01-01

The NASA Applied Sciences Program partners with domestic and international governmental organizations, universities, and private entities to improve their decisions and assessments. These improvements are enabled by using the knowledge generated from research resulting from spacecraft observations and model predictions conducted by NASA and providing these as inputs to the decision support and scenario assessment tools used by partner organizations. The Program is divided into eight societal benefit areas, aligned in general with the Global Earth Observation System of Systems (GEOSS) themes. The Climate Application of the Applied Sciences Program has as one of its focuses, efforts to provide for improved decisions and assessments in the areas of renewable energy technologies, energy efficiency, and climate change impacts. The goals of the Applied Sciences Program are aligned with national initiatives such as the U.S. Climate Change Science and Technology Programs and with those of international organizations including the Group on Earth Observations (GEO) and the Committee on Earth Observation Satellites (CEOS). Activities within the Program are funded principally through proposals submitted in response to annual solicitations and reviewed by peers.

Does physician communication style impact patient report of decision quality for breast cancer treatment?

PubMed

Martinez, Kathryn A; Resnicow, Ken; Williams, Geoffrey C; Silva, Marlene; Abrahamse, Paul; Shumway, Dean A; Wallner, Lauren P; Katz, Steven J; Hawley, Sarah T

2016-12-01

Provider communication that supports patient autonomy has been associated with numerous positive patient outcomes. However, to date, no research has examined the relationship between perceived provider communication style and patient-assessed decision quality in breast cancer. Using a population-based sample of women with localized breast cancer, we assessed patient perceptions of autonomy-supportive communication from their surgeons and medical oncologists, as well as patient-reported decision quality. We used multivariable linear regression to examine the association between autonomy-supportive communication and subjective decision quality for surgery and chemotherapy decisions, controlling for sociodemographic and clinical factors, as well as patient-reported communication preference (non-directive or directive). Among the 1690 women included in the overall sample, patient-reported decision quality scores were positively associated with higher levels of perceived autonomy-supportive communication from surgeons (β=0.30; p<0.001) and medical oncologists (β=0.26; p<0.001). Patient communication style preference moderated the association between physician communication style received and perceived decision quality. Autonomy-supportive communication by physicians was associated with higher subjective decision quality among women with localized breast cancer. These results support future efforts to design interventions that enhance autonomy-supportive communication. Autonomy-supportive communication by cancer doctors can improve patients' perceived decision quality. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Does physician communication style impact patient report of decision quality for breast cancer treatment?

PubMed Central

Resnicow, Ken; Williams, Geoffrey C.; Silva, Marlene; Abrahamse, Paul; Shumway, Dean; Wallner, Lauren; Katz, Steven; Hawley, Sarah

2016-01-01

Objective Provider communication that supports patient autonomy has been associated with numerous positive patient outcomes. However, to date, no research has examined the relationship between perceived provider communication style and patient-assessed decision quality in breast cancer. Methods Using a population-based sample of women with localized breast cancer, we assessed patient perceptions of autonomy-supportive communication from their surgeons and medical oncologists, as well as patient-reported decision quality. We used multivariable linear regression to examine the association between autonomy-supportive communication and subjective decision quality for surgery and chemotherapy decisions, controlling for sociodemographic and clinical factors, as well as patient-reported communication preference (non-directive or directive). Results Among the 1,690 women included in the overall sample, patient-reported decision quality scores were positively associated with higher levels of perceived autonomy-supportive communication from surgeons (β=0.30; p<0.001) and medical oncologists (β=0.26; p<0.001). Patient communication style preference moderated the association between physician communication style received and perceived decision quality. Conclusion Autonomy-supportive communication by physicians was associated with higher subjective decision quality among women with localized breast cancer. These results support future efforts to design interventions that enhance autonomy-supportive communication. Practice Implications Autonomy-supportive communication by cancer doctors can improve patients’ perceived decision quality. PMID:27395750

Climate Literacy in the Classroom: Supporting Teachers in the Transition to NGSS

NASA Astrophysics Data System (ADS)

Rogers, M. J. B.; Merrill, J.; Harcourt, P.; Petrone, C.; Shea, N.; Mead, H.

2014-12-01

Meeting the challenge of climate change will clearly require 'deep learning' - learning that motivates a search for underlying meaning, a willingness to exert the sustained effort needed to understand complex problems, and innovative problem-solving. This type of learning is dependent on the level of the learner's engagement with the material, their intrinsic motivation to learn, intention to understand, and relevance of the material to the learner. Here, we present evidence for deep learning about climate change through a simulation-based role-playing exercise, World Climate. The exercise puts participants into the roles of delegates to the United Nations climate negotiations and asks them to create an international climate deal. They find out the implications of their decisions, according to the best available science, through the same decision-support computer simulation used to provide feedback for the real-world negotiations, C-ROADS. World Climate provides an opportunity for participants have an immersive, social experience in which they learn first-hand about both the social dynamics of climate change decision-making, through role-play, and the dynamics of the climate system, through an interactive computer simulation. Evaluation results so far have shown that the exercise is highly engaging and memorable and that it motivates large majorities of participants (>70%) to take action on climate change. In addition, we have found that it leads to substantial gains in understanding key systems thinking concepts (e.g., the stock-flow behavior of atmospheric CO2), as well as improvements in understanding of climate change causes and impacts. While research is still needed to better understand the impacts of simulation-based role-playing exercises like World Climate on behavior change, long-term understanding, transfer of systems thinking skills across topics, and the importance of social learning during the exercise, our results to date indicate that it is a powerful, active learning tool that has strong potential to foster deep learning about climate change.

Embedding climate change risk assessment within a governance context

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

Preston, Benjamin L

Climate change adaptation is increasingly being framed in the context of climate risk management. This has contributed to the proliferation of climate change vulnerability and/or risk assessments as means of supporting institutional decision-making regarding adaptation policies and measures. To date, however, little consideration has been given to how such assessment projects and programs interact with governance systems to facilitate or hinder the implementation of adaptive responses. An examination of recent case studies involving Australian local governments reveals two key linkages between risk assessment and the governance of adaptation. First, governance systems influence how risk assessment processes are conducted, by whommore » they are conducted, and whom they are meant to inform. Australia s governance system emphasizes evidence-based decision-making that reinforces a knowledge deficit model of decision support. Assessments are often carried out by external experts on behalf of local government, with limited participation by relevant stakeholders and/or civil society. Second, governance systems influence the extent to which the outputs from risk assessment activities are translated into adaptive responses and outcomes. Technical information regarding risk is often stranded by institutional barriers to adaptation including poor uptake of information, competition on the policy agenda, and lack of sufficient entitlements. Yet, risk assessments can assist in bringing such barriers to the surface, where they can be debated and resolved. In fact, well-designed risk assessments can contribute to multi-loop learning by institutions, and that reflexive problem orientation may be one of the more valuable benefits of assessment.« less

Variance adaptation in navigational decision making

NASA Astrophysics Data System (ADS)

Gershow, Marc; Gepner, Ruben; Wolk, Jason; Wadekar, Digvijay

Drosophila larvae navigate their environments using a biased random walk strategy. A key component of this strategy is the decision to initiate a turn (change direction) in response to declining conditions. We modeled this decision as the output of a Linear-Nonlinear-Poisson cascade and used reverse correlation with visual and fictive olfactory stimuli to find the parameters of this model. Because the larva responds to changes in stimulus intensity, we used stimuli with uncorrelated normally distributed intensity derivatives, i.e. Brownian processes, and took the stimulus derivative as the input to our LNP cascade. In this way, we were able to present stimuli with 0 mean and controlled variance. We found that the nonlinear rate function depended on the variance in the stimulus input, allowing larvae to respond more strongly to small changes in low-noise compared to high-noise environments. We measured the rate at which the larva adapted its behavior following changes in stimulus variance, and found that larvae adapted more quickly to increases in variance than to decreases, consistent with the behavior of an optimal Bayes estimator. Supported by NIH Grant 1DP2EB022359 and NSF Grant PHY-1455015.

Towards ethical decision support and knowledge management in neonatal intensive care.

PubMed

Yang, L; Frize, M; Eng, P; Walker, R; Catley, C

2004-01-01

Recent studies in neonatal medicine, clinical nursing, and cognitive psychology have indicated the need to augment current decision-making practice in neonatal intensive care units with computerized, intelligent decision support systems. Rapid progress in artificial intelligence and knowledge management facilitates the design of collaborative ethical decision-support tools that allow clinicians to provide better support for parents facing inherently difficult choices, such as when to withdraw aggressive treatment. The appropriateness of using computers to support ethical decision-making is critically analyzed through research and literature review. In ethical dilemmas, multiple diverse participants need to communicate and function as a team to select the best treatment plan. In order to do this, physicians require reliable estimations of prognosis, while parents need a highly useable tool to help them assimilate complex medical issues and address their own value system. Our goal is to improve and structuralize the ethical decision-making that has become an inevitable part of modern neonatal care units. The paper contributes to clinical decision support by outlining the needs and basis for ethical decision support and justifying the proposed development efforts.

Implementation of workflow engine technology to deliver basic clinical decision support functionality

PubMed Central

2011-01-01

Background Workflow engine technology represents a new class of software with the ability to graphically model step-based knowledge. We present application of this novel technology to the domain of clinical decision support. Successful implementation of decision support within an electronic health record (EHR) remains an unsolved research challenge. Previous research efforts were mostly based on healthcare-specific representation standards and execution engines and did not reach wide adoption. We focus on two challenges in decision support systems: the ability to test decision logic on retrospective data prior prospective deployment and the challenge of user-friendly representation of clinical logic. Results We present our implementation of a workflow engine technology that addresses the two above-described challenges in delivering clinical decision support. Our system is based on a cross-industry standard of XML (extensible markup language) process definition language (XPDL). The core components of the system are a workflow editor for modeling clinical scenarios and a workflow engine for execution of those scenarios. We demonstrate, with an open-source and publicly available workflow suite, that clinical decision support logic can be executed on retrospective data. The same flowchart-based representation can also function in a prospective mode where the system can be integrated with an EHR system and respond to real-time clinical events. We limit the scope of our implementation to decision support content generation (which can be EHR system vendor independent). We do not focus on supporting complex decision support content delivery mechanisms due to lack of standardization of EHR systems in this area. We present results of our evaluation of the flowchart-based graphical notation as well as architectural evaluation of our implementation using an established evaluation framework for clinical decision support architecture. Conclusions We describe an implementation of a free workflow technology software suite (available at http://code.google.com/p/healthflow) and its application in the domain of clinical decision support. Our implementation seamlessly supports clinical logic testing on retrospective data and offers a user-friendly knowledge representation paradigm. With the presented software implementation, we demonstrate that workflow engine technology can provide a decision support platform which evaluates well against an established clinical decision support architecture evaluation framework. Due to cross-industry usage of workflow engine technology, we can expect significant future functionality enhancements that will further improve the technology's capacity to serve as a clinical decision support platform. PMID:21477364

Volatile decision dynamics: experiments, stochastic description, intermittency control and traffic optimization

NASA Astrophysics Data System (ADS)

Helbing, Dirk; Schönhof, Martin; Kern, Daniel

2002-06-01

The coordinated and efficient distribution of limited resources by individual decisions is a fundamental, unsolved problem. When individuals compete for road capacities, time, space, money, goods, etc, they normally make decisions based on aggregate rather than complete information, such as TV news or stock market indices. In related experiments, we have observed a volatile decision dynamics and far-from-optimal payoff distributions. We have also identified methods of information presentation that can considerably improve the overall performance of the system. In order to determine optimal strategies of decision guidance by means of user-specific recommendations, a stochastic behavioural description is developed. These strategies manage to increase the adaptibility to changing conditions and to reduce the deviation from the time-dependent user equilibrium, thereby enhancing the average and individual payoffs. Hence, our guidance strategies can increase the performance of all users by reducing overreaction and stabilizing the decision dynamics. These results are highly significant for predicting decision behaviour, for reaching optimal behavioural distributions by decision support systems and for information service providers. One of the promising fields of application is traffic optimization.

An Internationally Consented Standard for Nursing Process-Clinical Decision Support Systems in Electronic Health Records.

PubMed

Müller-Staub, Maria; de Graaf-Waar, Helen; Paans, Wolter

2016-11-01

Nurses are accountable to apply the nursing process, which is key for patient care: It is a problem-solving process providing the structure for care plans and documentation. The state-of-the art nursing process is based on classifications that contain standardized concepts, and therefore, it is named Advanced Nursing Process. It contains valid assessments, nursing diagnoses, interventions, and nursing-sensitive patient outcomes. Electronic decision support systems can assist nurses to apply the Advanced Nursing Process. However, nursing decision support systems are missing, and no "gold standard" is available. The study aim is to develop a valid Nursing Process-Clinical Decision Support System Standard to guide future developments of clinical decision support systems. In a multistep approach, a Nursing Process-Clinical Decision Support System Standard with 28 criteria was developed. After pilot testing (N = 29 nurses), the criteria were reduced to 25. The Nursing Process-Clinical Decision Support System Standard was then presented to eight internationally known experts, who performed qualitative interviews according to Mayring. Fourteen categories demonstrate expert consensus on the Nursing Process-Clinical Decision Support System Standard and its content validity. All experts agreed the Advanced Nursing Process should be the centerpiece for the Nursing Process-Clinical Decision Support System and should suggest research-based, predefined nursing diagnoses and correct linkages between diagnoses, evidence-based interventions, and patient outcomes.

Understanding nurses' decision-making when managing weaning from mechanical ventilation: a study of novice and experienced critical care nurses in Scotland and Greece.

PubMed

Kydonaki, Kalliopi; Huby, Guro; Tocher, Jennifer; Aitken, Leanne M

2016-02-01

To examine how nurses collect and use cues from respiratory assessment to inform their decisions as they wean patients from ventilatory support. Prompt and accurate identification of the patient's ability to sustain reduction of ventilatory support has the potential to increase the likelihood of successful weaning. Nurses' information processing during the weaning from mechanical ventilation has not been well-described. A descriptive ethnographic study exploring critical care nurses' decision-making processes when weaning mechanically ventilated patients from ventilatory support in the real setting. Novice and expert Scottish and Greek nurses from two tertiary intensive care units were observed in real practice of weaning mechanical ventilation and were invited to participate in reflective interviews near the end of their shift. Data were analysed thematically using concept maps based on information processing theory. Ethics approval and informed consent were obtained. Scottish and Greek critical care nurses acquired patient-centred objective physiological and subjective information from respiratory assessment and previous knowledge of the patient, which they clustered around seven concepts descriptive of the patient's ability to wean. Less experienced nurses required more encounters of cues to attain the concepts with certainty. Subjective criteria were intuitively derived from previous knowledge of patients' responses to changes of ventilatory support. All nurses used focusing decision-making strategies to select and group cues in order to categorise information with certainty and reduce the mental strain of the decision task. Nurses used patient-centred information to make a judgment about the patients' ability to wean. Decision-making strategies that involve categorisation of patient-centred information can be taught in bespoke educational programmes for mechanical ventilation and weaning. Advanced clinical reasoning skills and accurate detection of cues in respiratory assessment by critical care nurses will ensure optimum patient management in weaning mechanical ventilation. © 2016 John Wiley & Sons Ltd.

Use of volunteers' information to support proactive inspection of hydraulic structures

NASA Astrophysics Data System (ADS)

Cortes Arevalo, Juliette; Sterlacchini, Simone; Bogaard, Thom; Frigerio, Simone; Junier, Sandra; Schenato, Luca; van den Giesen, Nick

2016-04-01

Proactive management is particularly important to deal with the increasing occurrence of hydro-meteorological hazards in mountain areas were threats are often caused by multiple and sudden onset hazards such as debris flows. Citizen volunteers can be involved in supporting technicians on inspecting the structures' functional status. Such collaborative effort between managing organizations and local volunteers becomes more important under limited resources. To consider volunteers' information in support of proactive inspection of hydraulic structures, we developed a methodology applicable in day-to-day risk management. At first, in collaboration with technicians-in-charge, a data collection approach was developed for first level or pre-screening visual inspections that can be performed by volunteers. Methods comprise of a data collection exercise, an inspection forms and a learning session based on existent procedures in the FVG region and neighbouring regions. To systematically evaluate the individual inspection reports, we designed a support method by means of a multi-criteria method with fuzzy terms. The method allows the technicians-in-charge to categorize the reports in one of three levels, each corresponding with a course of action. To facilitate the evaluation of inspection reports, we transformed the decision support method into a prototype Web-GIS application. The design process of the Web-GIS framework followed a user-centred approach. The conceptual design incorporates four modules for managing the inspection reports: 1) Registered users, 2) Inspection planning; 3) Available reports and 4) Evaluation of reports. The development of the prototype focused on the evaluation module and was implemented based on standard and interoperable open source tools. Finally, we organized a workshop with technicians in the study area to test the decision support method and get insights about the usefulness of the Web-GIS framework. Participants that took part of the workshop included technicians that were not involved in previous research activities. The involvement of new technicians was important due to their fresh perspectives. We looked at the effect of the quality of the input reports on the output of the decision support method. In addition, we compared the differences in the participants' advice during the inspection and the output from the decision support method. Participants' feedback led to a set of suggested improvements in the decision support method and the web-GIS application. We hope that the knowledge, theory and concept behind this decision support method can be developed into a full-scale web-GIS application. The advantage of using this decision support method is that it allows inspections to be carried out by either skilled volunteers or technicians while ensuring technicians-in-charge that they can systematically evaluate the collected reports. Volunteers can become skilled inspectors by teaming up with technicians for the inspection of hydraulic structures. Technicians can become more aware about local impacts and changes in the structures' status by teaming up with volunteers.

Effect of clinical decision rules, patient cost and malpractice information on clinician brain CT image ordering: a randomized controlled trial.

PubMed

Gimbel, Ronald W; Pirrallo, Ronald G; Lowe, Steven C; Wright, David W; Zhang, Lu; Woo, Min-Jae; Fontelo, Paul; Liu, Fang; Connor, Zachary

2018-03-12

The frequency of head computed tomography (CT) imaging for mild head trauma patients has raised safety and cost concerns. Validated clinical decision rules exist in the published literature and on-line sources to guide medical image ordering but are often not used by emergency department (ED) clinicians. Using simulation, we explored whether the presentation of a clinical decision rule (i.e. Canadian CT Head Rule - CCHR), findings from malpractice cases related to clinicians not ordering CT imaging in mild head trauma cases, and estimated patient out-of-pocket cost might influence clinician brain CT ordering. Understanding what type and how information may influence clinical decision making in the ordering advanced medical imaging is important in shaping the optimal design and implementation of related clinical decision support systems. Multi-center, double-blinded simulation-based randomized controlled trial. Following standardized clinical vignette presentation, clinicians made an initial imaging decision for the patient. This was followed by additional information on decision support rules, malpractice outcome review, and patient cost; each with opportunity to modify their initial order. The malpractice and cost information differed by assigned group to test the any temporal relationship. The simulation closed with a second vignette and an imaging decision. One hundred sixteen of the 167 participants (66.9%) initially ordered a brain CT scan. After CCHR presentation, the number of clinicians ordering a CT dropped to 76 (45.8%), representing a 21.1% reduction in CT ordering (P = 0.002). This reduction in CT ordering was maintained, in comparison to initial imaging orders, when presented with malpractice review information (p = 0.002) and patient cost information (p = 0.002). About 57% of clinicians changed their order during study, while 43% never modified their imaging order. This study suggests that ED clinician brain CT imaging decisions may be influenced by clinical decision support rules, patient out-of-pocket cost information and findings from malpractice case review. NCT03449862 , February 27, 2018, Retrospectively registered.

Public Key Infrastructure Increment 2 (PKI Inc 2)

DTIC Science & Technology

2016-03-01

DoD - Department of Defense DoDAF - DoD Architecture Framework FD - Full Deployment FDD - Full Deployment Decision FY - Fiscal Year IA...experienced due to a delay in achieving the FDD . The Critical Change Report was provided to Congress on July 11, 2014. Firm, Fixed-Price Feasibility...to a delay in achieving the FDD . To support the Critical Change Report, the NSA Cost Estimating organization prepared a cost estimate that was

The role of medial prefrontal cortex in memory and decision making.

PubMed

Euston, David R; Gruber, Aaron J; McNaughton, Bruce L

2012-12-20

Some have claimed that the medial prefrontal cortex (mPFC) mediates decision making. Others suggest mPFC is selectively involved in the retrieval of remote long-term memory. Yet others suggests mPFC supports memory and consolidation on time scales ranging from seconds to days. How can all these roles be reconciled? We propose that the function of the mPFC is to learn associations between context, locations, events, and corresponding adaptive responses, particularly emotional responses. Thus, the ubiquitous involvement of mPFC in both memory and decision making may be due to the fact that almost all such tasks entail the ability to recall the best action or emotional response to specific events in a particular place and time. An interaction between multiple memory systems may explain the changing importance of mPFC to different types of memories over time. In particular, mPFC likely relies on the hippocampus to support rapid learning and memory consolidation. Copyright © 2012 Elsevier Inc. All rights reserved.

Artificial Intelligence (AI), Operations Research (OR), and Decision Support Systems (DSS): A conceptual framework

NASA Technical Reports Server (NTRS)

Parnell, Gregory S.; Rowell, William F.; Valusek, John R.

1987-01-01

In recent years there has been increasing interest in applying the computer based problem solving techniques of Artificial Intelligence (AI), Operations Research (OR), and Decision Support Systems (DSS) to analyze extremely complex problems. A conceptual framework is developed for successfully integrating these three techniques. First, the fields of AI, OR, and DSS are defined and the relationships among the three fields are explored. Next, a comprehensive adaptive design methodology for AI and OR modeling within the context of a DSS is described. These observations are made: (1) the solution of extremely complex knowledge problems with ill-defined, changing requirements can benefit greatly from the use of the adaptive design process, (2) the field of DSS provides the focus on the decision making process essential for tailoring solutions to these complex problems, (3) the characteristics of AI, OR, and DSS tools appears to be converging rapidly, and (4) there is a growing need for an interdisciplinary AI/OR/DSS education.

Flood Forecast Accuracy and Decision Support System Approach: the Venice Case

NASA Astrophysics Data System (ADS)

Canestrelli, A.; Di Donato, M.

2016-02-01

In the recent years numerical models for weather predictions have experienced continuous advances in technology. As a result, all the disciplines making use of weather forecasts have made significant steps forward. In the case of the Safeguard of Venice, a large effort has been put in order to improve the forecast of tidal levels. In this context, the Istituzione Centro Previsioni e Segnalazioni Maree (ICPSM) of the Venice Municipality has developed and tested many different forecast models, both of the statistical and deterministic type, and has shown to produce very accurate forecasts. For Venice, the maximum admissible forecast error should be (ideally) of the order of ten centimeters at 24 hours. The entity of the forecast error clearly affects the decisional process, which mainly consists of alerting the population, activating the movable barriers installed at the three tidal inlets and contacting the port authority. This process becomes more challenging whenever the weather predictions, and therefore the water level forecasts, suddenly change. These new forecasts have to be quickly transformed into operational tasks. Therefore, it is of the utter importance to set up scheduled alerts and emergency plans by means of easy-to-follow procedures. On this direction, Technital has set up a Decision Support System based on expert procedures that minimizes the human mistakes and, as a consequence, reduces the risk of flooding of the historical center. Moreover, the Decision Support System can communicate predefined alerts to all the interested subjects. The System uses the water levels forecasts produced by the ICPSM by taking into account the accuracy at different leading times. The Decision Support System has been successfully tested with 8 years of data, 6 of them in real time. Venice experience shows that the Decision Support System is an essential tool which assesses the risks associated with a particular event, provides clear operational procedures and minimizes the impact of natural floods on human lives, private properties and historical monuments.

Military Medical Decision Support for Homeland Defense During Emergency

DTIC Science & Technology

2004-12-01

abstraction hierarchy, three levels of information requirement for designing emergency training interface are recognized. These are epistemological ...support human decision making process is considered to be decision-centric. A typical decision-centric interface is supported by at least four design ... Designing Emergency Training Interface ......................................................................................... 5 Epistemological

A three-talk model for shared decision making: multistage consultation process

PubMed Central

Durand, Marie Anne; Song, Julia; Aarts, Johanna; Barr, Paul J; Berger, Zackary; Cochran, Nan; Frosch, Dominick; Galasiński, Dariusz; Gulbrandsen, Pål; Han, Paul K J; Härter, Martin; Kinnersley, Paul; Lloyd, Amy; Mishra, Manish; Perestelo-Perez, Lilisbeth; Scholl, Isabelle; Tomori, Kounosuke; Trevena, Lyndal; Witteman, Holly O; Van der Weijden, Trudy

2017-01-01

Objectives To revise an existing three-talk model for learning how to achieve shared decision making, and to consult with relevant stakeholders to update and obtain wider engagement. Design Multistage consultation process. Setting Key informant group, communities of interest, and survey of clinical specialties. Participants 19 key informants, 153 member responses from multiple communities of interest, and 316 responses to an online survey from medically qualified clinicians from six specialties. Results After extended consultation over three iterations, we revised the three-talk model by making changes to one talk category, adding the need to elicit patient goals, providing a clear set of tasks for each talk category, and adding suggested scripts to illustrate each step. A new three-talk model of shared decision making is proposed, based on “team talk,” “option talk,” and “decision talk,” to depict a process of collaboration and deliberation. Team talk places emphasis on the need to provide support to patients when they are made aware of choices, and to elicit their goals as a means of guiding decision making processes. Option talk refers to the task of comparing alternatives, using risk communication principles. Decision talk refers to the task of arriving at decisions that reflect the informed preferences of patients, guided by the experience and expertise of health professionals. Conclusions The revised three-talk model of shared decision making depicts conversational steps, initiated by providing support when introducing options, followed by strategies to compare and discuss trade-offs, before deliberation based on informed preferences. PMID:29109079

PubMed Central

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

2014-01-01

Background: 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 decisionmaking by patients with cancer within the context of treatment, survivorship, and palliation. We also aimed to summarize emergent concepts within a preliminary conceptual framework. Methods: 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. Results: 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 informationseeking 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. Interpretation: 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 theorybased decision-support programs that are responsive to patients' beliefs and preferences. PMID:25009685

Stress Causing Factors Among Teachers in Elementary Schools and Their Relationship with Demographic and Job Characteristics.

PubMed

Agai-Demjaha, Teuta; Minov, Jordan; Stoleski, Sasho; Zafirova, Beti

2015-09-15

Once high levels of work-related stress among teachers were confirmed many studies concentrated on identifying and investigating key stress factors among school teachers. Unfortunately there are very few researches made on stress causing factors among teachers in Republic of Macedonia. To determine the most frequent stress causing factors among teachers in elementary schools and to investigate their relationship with demographic and job characteristics. We performed a descriptive-analytical model of a cross-sectional study which involved 300 teachers employed in nine elementary schools. Evaluation of examined subjects included completion of a specially designed questionnaire. Among six categories of factors that generate work related stress (job demands, control, relationships, role, changes and support) control and support had the highest mean scores. Within the control category the highest levels of perceived teacher's work-related stress were caused by the following factors - changes in terms and conditions without consultation and given responsibility without the authority to take decisions. 141 out of the interviewed teachers (47%) have mentioned changes in terms and conditions without consultation as very stressful, while another 50 (16.67%) have reported it as stressful. 123 out of interviewed teachers (41%) have stated given responsibility without the authority to take decisions as very stressful, with another 105 (35%) have reported it as stressful. In the category support the highest levels of perceived teacher's work-related stress were caused by stress factors - lack of funds/resources to do the job and limited or no access to training. Out of 300 interviewed teachers, 179 (59.67%) have reported lack of funds/resources to do the job as very stressful, while another 50 (16.67%) as stressful. There is no significant relationship between the stress factor limited or no access to training and demographic and job characteristics. Our findings confirm that within the control category, the highest levels of perceived teacher's work-related stress were caused by changes in terms and conditions without consultation and given responsibility without the authority to take decisions, while in the category support, the same was true for stress factors lack of funds/resources to do the job and limited or no access to training. We have also concluded that the lower-grade school teachers, female teachers, teachers for whom this is the first job and teachers with university education perceive more often the lack of authority to take decisions as a very stressful factor than the upper-grade school teachers, male teachers, teachers previously employed in another workplace, and those with high education. The lower-grade school teachers, older teachers and teachers with university education perceive more often changes in education as a very stressful factor than the upper grade school teachers, younger teachers and those with high education.

Avoiding harm and supporting autonomy are under-prioritised in cancer-screening policies and practices.

PubMed

Parker, Lisa; Carter, Stacy; Williams, Jane; Pickles, Kristen; Barratt, Alexandra

2017-11-01

The ethical principles of avoiding harm and supporting autonomy are relevant to cancer-screening policy. We argue that more attention needs to be given to implementing them. Cancer screening may deliver excessive harms due to low-value or outdated screening programs and from poorly communicated screening options that leave people with heavy burdens of decision-making. Autonomy is inadequately supported due to limited opportunities for people to understand downsides of screening and because of institutional and societal pressures in favour of screening. Members of screening policy committees may have differing ideas about the goals of screening or have conflicts of interest that prevent them from addressing policy questions in a neutral way. We recommend the following: 1. Committees should be required to discern and discuss the values of individual members and the wider public; 2. Committee membership and voting procedures should be more carefully constructed to reduce the likelihood that committee members' interests are placed above public interests; 3. Committees should explain their policy decisions with reference to values as well as evidence, so that values considered in decision-making can be interrogated and challenged if necessary. These changes would increase the likelihood that cancer-screening policy decisions are in keeping with public views about what is important. Copyright © 2017 Elsevier Ltd. All rights reserved.

Physical mechanism of mind changes and tradeoffs among speed, accuracy, and energy cost in brain decision making: Landscape, flux, and path perspectives

NASA Astrophysics Data System (ADS)

Han, Yan; Kun, Zhang; Jin, Wang

2016-07-01

Cognitive behaviors are determined by underlying neural networks. Many brain functions, such as learning and memory, have been successfully described by attractor dynamics. For decision making in the brain, a quantitative description of global attractor landscapes has not yet been completely given. Here, we developed a theoretical framework to quantify the landscape associated with the steady state probability distributions and associated steady state curl flux, measuring the degree of non-equilibrium through the degree of detailed balance breaking for decision making. We quantified the decision-making processes with optimal paths from the undecided attractor states to the decided attractor states, which are identified as basins of attractions, on the landscape. Both landscape and flux determine the kinetic paths and speed. The kinetics and global stability of decision making are explored by quantifying the landscape topography through the barrier heights and the mean first passage time. Our theoretical predictions are in agreement with experimental observations: more errors occur under time pressure. We quantitatively explored two mechanisms of the speed-accuracy tradeoff with speed emphasis and further uncovered the tradeoffs among speed, accuracy, and energy cost. Our results imply that there is an optimal balance among speed, accuracy, and the energy cost in decision making. We uncovered the possible mechanisms of changes of mind and how mind changes improve performance in decision processes. Our landscape approach can help facilitate an understanding of the underlying physical mechanisms of cognitive processes and identify the key factors in the corresponding neural networks. Project supported by the National Natural Science Foundation of China (Grant Nos. 21190040, 91430217, and 11305176).

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.

Content-specific evidence accumulation in inferior temporal cortex during perceptual decision-making

PubMed Central

Tremel, Joshua J.; Wheeler, Mark E.

2015-01-01

During a perceptual decision, neuronal activity can change as a function of time-integrated evidence. Such neurons may serve as decision variables, signaling a choice when activity reaches a boundary. Because the signals occur on a millisecond timescale, translating to human decision-making using functional neuroimaging has been challenging. Previous neuroimaging work in humans has identified patterns of neural activity consistent with an accumulation account. However, the degree to which the accumulating neuroimaging signals reflect specific sources of perceptual evidence is unknown. Using an extended face/house discrimination task in conjunction with cognitive modeling, we tested whether accumulation signals, as measured using functional magnetic resonance imaging (fMRI), are stimulus-specific. Accumulation signals were defined as a change in the slope of the rising edge of activation corresponding with response time (RT), with higher slopes associated with faster RTs. Consistent with an accumulation account, fMRI activity in face- and house-selective regions in the inferior temporal cortex increased at a rate proportional to decision time in favor of the preferred stimulus. This finding indicates that stimulus-specific regions perform an evidence integrative function during goal-directed behavior and that different sources of evidence accumulate separately. We also assessed the decision-related function of other regions throughout the brain and found that several regions were consistent with classifications from prior work, suggesting a degree of domain generality in decision processing. Taken together, these results provide support for an integration-to-boundary decision mechanism and highlight possible roles of both domain-specific and domain-general regions in decision evidence evaluation. PMID:25562821

The role of academic institutions in leveraging engagement and action on climate change

NASA Astrophysics Data System (ADS)

Hill, T. M.; Palca, J.

2016-12-01

Growing global concern over the impact of climate change places climate scientists at the forefront of communicating risks, impacts, and adaptation strategies to non-scientists. Academic institutions can play a leadership role in providing support, incentives, and structures that encourage scientific engagement on this, and other, complex societal and scientific issues. This presentation will focus on `best practices' in supporting university scientists in communicating their science and engaging in thoughtful dialogue with decision makers, managers, media, and public audiences. For example, institutions that can provide significant administrative support for science communication (press officers, training workshops) may decrease barriers between academic science and public knowledge. Additionally, financial (or similar) support in the form of teaching releases and institutional awards can be utilized to acknowledge the time and effort spent in engagement. This presentation will feature examples from universities, professional societies and other institutions where engagement on climate science is structurally encouraged and supported.

Semantic Clinical Guideline Documents

PubMed Central

Eriksson, Henrik; Tu, Samson W.; Musen, Mark

2005-01-01

Decision-support systems based on clinical practice guidelines can support physicians and other health-care personnel in the process of following best practice consistently. A knowledge-based approach to represent guidelines makes it possible to encode computer-interpretable guidelines in a formal manner, perform consistency checks, and use the guidelines directly in decision-support systems. Decision-support authors and guideline users require guidelines in human-readable formats in addition to computer-interpretable ones (e.g., for guideline review and quality assurance). We propose a new document-oriented information architecture that combines knowledge-representation models with electronic and paper documents. The approach integrates decision-support modes with standard document formats to create a combined clinical-guideline model that supports on-line viewing, printing, and decision support. PMID:16779037

The changing nature of ICU charge nurses' decision making: from supervision of care delivery to unit resource management.

PubMed

Miller, Anne; Buerhaus, Peter I

2013-01-01

Recent findings that variations in nursing workload may affect inpatient outcomes now highlight nurse workload management and the need for an updated analysis of the role of the charge nurse (CN). Observational data for eight CNs, each at one of eight ICUs in a not-for-profit Level 1 Trauma Center, coded to capture interprofessional interactions, decision making, team coordination phases, and support tools. A researcher shadowed each participant for 12 hours. Each shift began and ended with a face-to-face handoff that included summaries of each patient's condition; the current bed census; anticipated admissions, discharges, and transfers; and the number of nurses available to work the current and coming two shifts. The researcher, using a notebook, recorded the substantive content of all work conversations initiated by or directed to the CN from physicians, staff nurses, allied health workers, other employees, and patients/families. The tools used to support conversations were collected as blank forms or computer screen prints and annotated to describe how they were used, when, and for what purpose. Statistically significant three-way interactions suggest that CNs' conversations with colleagues depend on the team coordination phase and the decision-making level, and that the support tools that CNs use when talking to colleagues depend on the decision-making level and the team coordination phase. The role of ICU CNs appears to be continuing to evolve, now encompassing unit resource management in addition to supervising care delivery. Effective support tools, together with education that would enhance communication and resource management skills, will be essential to CNs' ability to support unit resilience and adaptability in an increasingly complex environment.

Using Best Practices to Extract, Organize, and Reuse Embedded Decision Support Content Knowledge Rules from Mature Clinical Systems.

PubMed

DesAutels, Spencer J; Fox, Zachary E; Giuse, Dario A; Williams, Annette M; Kou, Qing-Hua; Weitkamp, Asli; Neal R, Patel; Bettinsoli Giuse, Nunzia

2016-01-01

Clinical decision support (CDS) knowledge, embedded over time in mature medical systems, presents an interesting and complex opportunity for information organization, maintenance, and reuse. To have a holistic view of all decision support requires an in-depth understanding of each clinical system as well as expert knowledge of the latest evidence. This approach to clinical decision support presents an opportunity to unify and externalize the knowledge within rules-based decision support. Driven by an institutional need to prioritize decision support content for migration to new clinical systems, the Center for Knowledge Management and Health Information Technology teams applied their unique expertise to extract content from individual systems, organize it through a single extensible schema, and present it for discovery and reuse through a newly created Clinical Support Knowledge Acquisition and Archival Tool (CS-KAAT). CS-KAAT can build and maintain the underlying knowledge infrastructure needed by clinical systems.

Medication-related clinical decision support in computerized provider order entry systems: a review.

PubMed

Kuperman, Gilad J; Bobb, Anne; Payne, Thomas H; Avery, Anthony J; Gandhi, Tejal K; Burns, Gerard; Classen, David C; Bates, David W

2007-01-01

While medications can improve patients' health, the process of prescribing them is complex and error prone, and medication errors cause many preventable injuries. Computer provider order entry (CPOE) with clinical decision support (CDS), can improve patient safety and lower medication-related costs. To realize the medication-related benefits of CDS within CPOE, one must overcome significant challenges. Healthcare organizations implementing CPOE must understand what classes of CDS their CPOE systems can support, assure that clinical knowledge underlying their CDS systems is reasonable, and appropriately represent electronic patient data. These issues often influence to what extent an institution will succeed with its CPOE implementation and achieve its desired goals. Medication-related decision support is probably best introduced into healthcare organizations in two stages, basic and advanced. Basic decision support includes drug-allergy checking, basic dosing guidance, formulary decision support, duplicate therapy checking, and drug-drug interaction checking. Advanced decision support includes dosing support for renal insufficiency and geriatric patients, guidance for medication-related laboratory testing, drug-pregnancy checking, and drug-disease contraindication checking. In this paper, the authors outline some of the challenges associated with both basic and advanced decision support and discuss how those challenges might be addressed. The authors conclude with summary recommendations for delivering effective medication-related clinical decision support addressed to healthcare organizations, application and knowledge base vendors, policy makers, and researchers.

Research on web-based decision support system for sports competitions

NASA Astrophysics Data System (ADS)

Huo, Hanqiang

2010-07-01

This paper describes the system architecture and implementation technology of the decision support system for sports competitions, discusses the design of decision-making modules, management modules and security of the system, and proposes the development idea of building a web-based decision support system for sports competitions.

The story of rising voices: Facilitating collaboration between indigenous and western ways of knowing

USGS Publications Warehouse

Maldonado, Julie; Lazrus, Heather; Bennett, Shiloh-Kay; Chief, Karletta; Dhillon, Carla May; Gough, Bob; Kruger, Linda; Morisette, Jeffrey T.; Petrovic, Stefan; Whyte, Kyle P.; Companion, Michele; Chaiken, Miriam S.

2016-01-01

Indigenous community self-determination, cultures, and ways of life are at high risk from climate change impacts and ecological dispossession. Partnerships between experts with backgrounds in Indigenous and western knowledge may be productive and effective ways to reduce vulnerability and foster resilience. This chapter examines collaborations among scientific and Native American, Alaska Native, and Pacific Island communities to support climate solutions. We draw examples from the "Rising Voices: Collaborative Science with Indigenous Knowledge for Climate Solutions" program (Rising Voices) to examine how boundary organizations function cross-culturally to increase communities' adaptive capacity through knowledge exchange, as well as building the decision-making capacity needed to exercise sovereignty and make adaptive decisions in a changing climate.

Cross-scale phenological data integration to benefit resource management and monitoring

USGS Publications Warehouse

Richardson, Andrew D.; Weltzin, Jake F.; Morisette, Jeffrey T.

2017-01-01

Climate change is presenting new challenges for natural resource managers charged with maintaining sustainable ecosystems and landscapes. Phenology, a branch of science dealing with seasonal natural phenomena (bird migration or plant flowering in response to weather changes, for example), bridges the gap between the biosphere and the climate system. Phenological processes operate across scales that span orders of magnitude—from leaf to globe and from days to seasons—making phenology ideally suited to multiscale, multiplatform data integration and delivery of information at spatial and temporal scales suitable to inform resource management decisions.A workshop report: Workshop held June 2016 to investigate opportunities and challenges facing multi-scale, multi-platform integration of phenological data to support natural resource management decision-making.

The Department of the Interior Southeast Climate Science Center synthesis report 2011–15—Projects, products, and science priorities

USGS Publications Warehouse

Varela Minder, Elda; Lascurain, Aranzazu R.; McMahon, Gerard

2016-09-28

IntroductionIn 2009, the U.S. Department of the Interior (DOI) Secretary Ken Salazar established a network of eight regional Climate Science Centers (CSCs) that, along with the Landscape Conservation Cooperatives (LCCs), would help define and implement the Department's climate adaptation response. The Southeast Climate Science Center (SE CSC) was established at North Carolina State University (NCSU) in Raleigh, North Carolina, in 2010, under a 5-year cooperative agreement with the U.S. Geological Survey (USGS), to identify and address the regional challenges presented by climate change and variability in the Southeastern United States. All eight regional CSC hosts, including NCSU, were selected through a competitive process.Since its opening, the focus of the SE CSC has been on working with partners in the identification and development of research-based information that can assist managers, including cultural and natural resource managers, in adapting to global change processes, such as climate and land use change, that operate at local to global scales and affect resources important to the DOI mission. The SE CSC was organized to accomplish three goals:Provide co-produced, researched based, actionable science that supports transparent global change adaptation decisions.Convene conversations among decision makers, scientists, and managers to identify key ecosystem adaptation decisions driven by climate and land use change, the values and objectives that will be used to make decisions, and the research-based information needed to assess adaptation options.Build the capacity of natural resource professionals, university faculty, and students to understand and frame natural resource adaptation decisions and develop and use research-based information to make adaptation decisions.This report provides an overview of the SE CSC and the projects developed by the SE CSC since its inception. An important goal of this report is to provide a framework for understanding the evolution of the SE CSC science agenda, which has evolved over the first 5 years of the Center’s operation.

Preserving professional credibility: grounded theory study of medical trainees' requests for clinical support.

PubMed

Kennedy, Tara J T; Regehr, Glenn; Baker, G Ross; Lingard, Lorelei

2009-02-09

To develop a conceptual framework of the influences on medical trainees' decisions regarding requests for clinical support from a supervisor. Phase 1: members of teaching teams in internal and emergency medicine were observed during regular clinical activities (216 hours) and subsequently completed brief interviews. Phase 2: 36 in depth interviews were conducted using videotaped vignettes to probe tacit influences on decisions to request support. Data collection and analysis used grounded theory methods. Three teaching hospitals in an urban setting in Canada. 124 members of teaching teams on general internal medicine wards and in the emergency department, comprising 31 attending physicians, 57 junior and senior residents, 28 medical students, and eight nurses. Purposeful sampling to saturation was conducted. Trainees' decisions about whether or not to seek clinical support were influenced by three issues: the clinical question (clinical importance, scope of practice), supervisor factors (availability, approachability), and trainee factors (skill, desire for independence, evaluation). Trainees perceived that requesting frequent/inappropriate support threatened their credibility and used rhetorical strategies to preserve credibility. These strategies included building a case for the importance of requests, saving requests for opportune moments, making a plan before requesting support, and targeting requests to specific team members. Trainees consider not only clinical implications but also professional credibility when requesting support from clinical supervisors. Exposing the complexity of this process provides the opportunity to make changes to training programmes to promote timely supervision and provides a framework for further exploration of the impact of clinical training on quality of care of patients.

The Human-Electronic Crew: Is the Team Maturing? Joint GAF/RAF/USAF workshop on Human-Electronic Crew Teamwork (2nd) Held in Ingolstadt, Germany on September 25-28, 1990

DTIC Science & Technology

1992-07-10

a way ahead for future work to explore the cognitive nature of the whole command and control task and a decision support environment . Introduction...existing inferior approach. Second, the nature of how tasks are performed changes in a dynamic environment . For example, the decision-making process...the system must be designed to perform in its expected operational environment . It includes tasks performed by the aircraft, its systems, and each of

THE USE OF SCENARIO ANALYSIS TO ASSESS LANDSCAPE CHANGE ON WATERSHED CONDITION IN THE PACKIFIC NORTHWEST (USA)

EPA Science Inventory

The ability to assess, report, and forecast the life support functions of ecosystems is absolutely critical to our capacity to make informed decisions which will maintain the sustainable nature of our environmental services and secure these resources into the future. Scenario ana...

Defining ecohydrological function to support low impact development in coastal South Carolina

Treesearch

Daniel Hitchcock; A.D. Jayakaran; T. H. Epps; J.A. Palazzolo; T.M. Williams; D.M. Amatya

2016-01-01

In the face of dual pressures in coastal South Carolina - residential and commercial development, along with potential climate change impacts - stakeholders need clear, accurate, relevant, and easily-accessible information for effective decision-making for watershed management and natural resource protection.

Strategic Enrollment Management (SEM) Decisions and Geographic Information Systems (GIS) for Community Colleges

ERIC Educational Resources Information Center

Baldin, Antoinette M.

2013-01-01

With the changing landscape in enrollment options for potential community college students, community college administrators are looking for ways to forecast enrollment by using strategic enrollment management models. Today, community colleges' administration is challenged to develop, use, and implement enrollment models that support their…

PREDICT: Pattern Representation and Evaluation of Data through Integration, Correlation, and Transformation

DTIC Science & Technology

2015-10-01

overview visualization to help clinicians identify patients that are changing and inserted these indices into the sepsis specific decision support...visualization, 4) Created a sepsis identification visualization tool to help clinicians identify patients headed for septic shock, and 5) Generated a...5 Sepsis Visualization

Technology Enhanced Analytics (TEA) in Higher Education

ERIC Educational Resources Information Center

Daniel, Ben Kei; Butson, Russell

2013-01-01

This paper examines the role of Big Data Analytics in addressing contemporary challenges associated with current changes in institutions of higher education. The paper first explores the potential of Big Data Analytics to support instructors, students and policy analysts to make better evidence based decisions. Secondly, the paper presents an…

Multi-profile analysis of soil moisture within the U.S. Climate Reference Network

USDA-ARS?s Scientific Manuscript database

Soil moisture estimates are crucial for hydrologic modeling and agricultural decision-support efforts. These measurements are also pivotal for long-term inquiries regarding the impacts of climate change and the resulting droughts over large spatial and temporal scales. However, it has only been t...

What Can Local Foundations Do to Support Youth Service System Change Efforts?

ERIC Educational Resources Information Center

Weah, Wokie; Pope, Marcus

2013-01-01

Making sound decisions in funding youth-serving organizations can be greatly enhanced by implementing a comprehensive and inclusive learning process that embraces the perspectives of and input from a variety of stakeholders, including program staff and leadership, various community partners, and, most important, the youth. Youthprise effectively…

Decision support: Vulnerability, conservation, and restoration (Chapter 8)

Treesearch

Megan M. Friggens; Jeremiah R. Pinto; R. Kasten Dumroese; Nancy L. Shaw

2012-01-01

Current predictive tools, management options, restoration paradigms, and conservation programs are insufficient to meet the challenges of climate change in western North America. Scientific and management capabilities and resources will be sapped trying to identify risks to genetic resources and ecosystems and determine new approaches for mitigating and managing...

Query Modification through External Sources to Support Clinical Decisions

DTIC Science & Technology

2014-11-01

takes no medications. Physical examination is normal. The EKG shows nonspecific changes. Summary 58-year-old woman with hypertension and obesity presents...algorithm for suffix stripping. Program, 14:130–137, 1980. Reprinted in Readings in Information Retrieval, pages 313–316, 1997. M. S. Simpson, E

Growing Student Voice in Curriculum Decisions at the University

ERIC Educational Resources Information Center

Rojas Pernia, Susana; Haya Salmón, Ignacio; Susinos Rada, Teresa

2016-01-01

This paper is a result of the development of the R+D Project "Schools that are moving towards inclusive education: working with the local community, the student voice and educational support for promoting change" in conjunction with the Innovation Project "Building Bridges. An Educational Innovation Project in the European Higher…

Strengthening Resiliency in Coastal Watersheds: An Ecosystem Services and Ecological Integrity Decision Support System.

EPA Science Inventory

To promote and strengthen the resiliency of coastal watersheds in the face of climate change and development, ecological outcomes as well as economic, social, and environmental justice issues need to be considered. An integrated assessment framework is being developed to help wat...

Scenario-based carbon footprint inventory tool for urban sustainable development decision support: The Cincinnati Case Study

EPA Science Inventory

Rapid growing of travel demand and transportation activities and co-occurring land use changes have resulted in traffic congestion and negative impacts on the environment, energy consumption and green house gas (GHG) emissions in an urban environment. The challenge lies in quanti...

Changing Perceptions of Teacher Candidates in High-Needs Schools

ERIC Educational Resources Information Center

DeJarnette, Nancy K.

2016-01-01

Candidates enter teacher education programs with established beliefs about diversity and urban education. These belief systems impact decisions that teacher candidates make both now and in the future. Providing opportunities for candidates to spend quality time in an urban Professional Development School (PDS) setting with the support and guidance…

A Distributed Information Strategy. AIR Forum 1982 Paper. Preliminary Paper.

ERIC Educational Resources Information Center

Baker, Michael E.

Planning issues and computing technology changes are reviewed and decision support systems are examined as a means of providing an appropriate information system for the university institutional research office. Examples of formative attempts to provide such systems at Carnegie-Mellon University (CMU) and other institutions are considered. The…

The Use of Office Automation by Managers: A Survey.

ERIC Educational Resources Information Center

Fleischer, Mitchell; Morell, Jonathan A.

1988-01-01

Describes a survey that examined office automation use by managers and the impact on managerial roles. The factors discussed include the impact on decision making, changes in work activities, sources of support, training, and different uses between managerial ranks. Recommendations are offered for improving use of office automation. (13…

[End-of-life decisions and practices in critically ill patients in the cardiac intensive care unit. A nationwide survey].

PubMed

Schimmer, C; Hamouda, K; Oezkur, M; Sommer, S-P; Leistner, M; Leyh, R

2016-03-01

Ethical and medical criteria in the decision-making process of withholding or withdrawal of life support therapy in critically ill patients present a great challenge in intensive care medicine. The purpose of this work was to assess medical and ethical criteria that influence the decision-making process for changing the aim of therapy in critically ill cardiac surgery patients. A questionnaire was distributed to all German cardiac surgery centers (n = 79). All clinical directors, intensive care unit (ICU) consultants and ICU head nurses were asked to complete questionnaires (n = 237). In all, 86 of 237 (36.3 %) questionnaires were returned. Medical reasons which influence the decision-making process for changing the aim of therapy were cranial computed tomography (cCT) with poor prognosis (91.9 %), multi-organ failure (70.9 %), and failure of assist device therapy (69.8 %). Concerning ethical reasons, poor expected quality of life (48.8 %) and the presumed patient's wishes (40.7 %) were reported. There was a significant difference regarding the perception of the three different professional groups concerning medical and ethical criteria as well as the involvement in the decision-making process. In critically ill cardiac surgery patients, medical reasons which influence the decision-making process for changing the aim of therapy included cCT with poor prognosis, multi-organ failure, and failure of assist device therapy. Further studies are mandatory in order to be able to provide adequate answers to this difficult topic.

Integrating Climate and Risk-Informed Science to Support Critical Decisions

ScienceCinema

None

2018-01-16

The PNNL Environmental Health and Remediation Sector stewards several decision support capabilities to integrate climate- and risk-informed science to support critical decisions. Utilizing our expertise in risk and decision analysis, integrated Earth systems modeling, and remote sensing and geoinformatics, PNNL is influencing the way science informs high level decisions at national, regional and local scales to protect and preserve our most critical assets.

Integrating Climate and Risk-Informed Science to Support Critical Decisions

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

None

2016-07-27

The PNNL Environmental Health and Remediation Sector stewards several decision support capabilities to integrate climate- and risk-informed science to support critical decisions. Utilizing our expertise in risk and decision analysis, integrated Earth systems modeling, and remote sensing and geoinformatics, PNNL is influencing the way science informs high level decisions at national, regional and local scales to protect and preserve our most critical assets.

A two-stage clinical decision support system for early recognition and stratification of patients with sepsis: an observational cohort study.

PubMed

Amland, Robert C; Lyons, Jason J; Greene, Tracy L; Haley, James M

2015-10-01

To examine the diagnostic accuracy of a two-stage clinical decision support system for early recognition and stratification of patients with sepsis. Observational cohort study employing a two-stage sepsis clinical decision support to recognise and stratify patients with sepsis. The stage one component was comprised of a cloud-based clinical decision support with 24/7 surveillance to detect patients at risk of sepsis. The cloud-based clinical decision support delivered notifications to the patients' designated nurse, who then electronically contacted a provider. The second stage component comprised a sepsis screening and stratification form integrated into the patient electronic health record, essentially an evidence-based decision aid, used by providers to assess patients at bedside. Urban, 284 acute bed community hospital in the USA; 16,000 hospitalisations annually. Data on 2620 adult patients were collected retrospectively in 2014 after the clinical decision support was implemented. 'Suspected infection' was the established gold standard to assess clinical decision support clinimetric performance. A sepsis alert activated on 417 (16%) of 2620 adult patients hospitalised. Applying 'suspected infection' as standard, the patient population characteristics showed 72% sensitivity and 73% positive predictive value. A postalert screening conducted by providers at bedside of 417 patients achieved 81% sensitivity and 94% positive predictive value. Providers documented against 89% patients with an alert activated by clinical decision support and completed 75% of bedside screening and stratification of patients with sepsis within one hour from notification. A clinical decision support binary alarm system with cross-checking functionality improves early recognition and facilitates stratification of patients with sepsis.

Climate Change and Water Working Group - User Needs to Manage Hydrclimatic Risk from Days to Decades

NASA Astrophysics Data System (ADS)

Raff, D. A.; Brekke, L. D.; Werner, K.; Wood, A.; White, K. D.

2012-12-01

The Federal Climate Change Water Working Group (CCAWWG) provides engineering and scientific collaborations in support of water management. CCAWWG objectives include building working relationships across federal science and water management agencies, provide a forum to share expertise and leverage resources, develop education and training forums, to work with water managers to understand scientific needs and to foster collaborative efforts across the Federal and non-Federal water management and science communities to address those needs. Identifying and addressing water management needs has been categorized across two major time scales: days to a decade and multi-decadal, respectively. These two time periods are termed "Short-Term" and "Long-Term" in terms of the types of water management decisions they support where Short-Term roughly correlates to water management operations and Long-Term roughly correlates to planning activities. This presentation will focus on portraying the identified water management user needs across these two time periods. User Needs for Long-Term planning were identified in the 2011 Reclamation and USACE "Addressing Climate Change in Long-Term Water Resources Planning and Management: User Needs for Improving Tools and Information." User needs for Long-Term planning are identified across eight major categories: Summarize Relevant Literature, Obtain Climate Change Information, Make Decisions About How to Use the Climate Change Information, Assess Natural Systems Response, Assess Socioeconomic and Institutional Response, Assess System Risks and Evaluate Alternatives, Assess and Characterize Uncertainties, and Communicating Results and Uncertainties to Decisionmakers. User Needs for Short-Term operations are focused on needs relative to available or desired monitoring and forecast products from the hydroclimatic community. These needs are presenting in the 2012 USACE, Reclamation, and NOAA - NWS "Short-Term Water Management Decisions: User Needs for Improved Climate, Weather, and Hydrologic Information." Identified needs are presented in four categories: Monitoring, Forecasting, Understanding on Product Relationships and Utilization in Water Management, and Information Services Enterprise. These needs represent everything from continuation and enhancement of in situ monitoring products such as USGS water gages and precipitation networks to supporting product maintenance and evolution to accommodate newly developed technologies.

Socio-Ecohydrologic Agents And Services: Integrating Human And Natural Components To Address Coupled System Resilience

NASA Astrophysics Data System (ADS)

Pavao-zuckerman, M.; Pope, A.; Chan, D.; Curl, K.; Gimblett, H. R.; Hough, M.; House-Peters, L.; Lee, R.; Scott, C. A.

2012-12-01

Riparian corridors in arid regions are highly valued for their relative scarcity, and because healthy riparian systems support high levels of biodiversity, can meet human demand for water and water-related resources and functions. Our team is taking a transdiciplinary social-ecological systems approach to assessing riparian corridor resilience in two watersheds (the San Pedro River in USA and Mexico, and the Rio San Miguel in Mexico) through a project funded by the NSF CNH program ("Strengthening Resilience of Arid Region Riparian Corridors"). Multiple perspectives are integrated in the project, including hydrology, ecology, institutional dynamics, and decision making (at the level of both policy and individual choice), as well as the perspectives of various stakeholder groups and individuals in the watersheds. Here we discuss initial findings that center around linking changes in ecohydrology and livelihoods related to decisions in response to climatic, ecological, and social change. The research team is implementing two approaches to integrate the disparate disciplines participating in the research (and the varied perspectives among the stakeholders in this binational riparian context): (1) ecosystem service assessment, and (2) agent based model simulation. We are developing an ecosystem service perspective that provides a bridge between ecological dynamics in the landscape and varied stakeholder perspectives on the implications of ecohydrology for well-being (economic, cultural, ecological). Services are linked on one hand to the spatial patterns of traits of individuals within species (allowing a more predictive application of ecosystem services as they vary with community change in time), and to stakeholder perspectives (facilitating integration of ecosystem services into our understanding of decision making processes) in a case study in the San Pedro River National Conservation Area. The agent- based model (ABM) approach incorporates the influence of human decision-making on spatially-explicit landscapes in a mechanistic way, taking into account social interaction, adaptation, and decision-making at different levels, allowing individual stakeholders to make decisions based on their unique perceptions of their environment, be it economic, social, or ecological awareness. Initial parameterization of the ABM proceeds from a case study centered in the town of Rayón, Sonora, Mexico, where semi-structured interviews were used to elicit perceptions by water resource users of CNH function, change, and solutions relating to livelihood changes in response to several drivers. In both case studies, we see the potential and limitations for an approach to adaptive management and decision support related to water resources that links ecosystem services and agent-based modeling. Methodologically, synthetic approaches such as these may allow coupling of systems for improved assessment and analysis, while at the same time lack a connection to the perspectives of water users and managers on the ground. There is thus potential for a either a loss of system resilience in the face of external change, or an opportunity to increase system resilience by building off perspectives already in place within these coupled socio-ecohydrologic systems.

A new fit-for-purpose model testing framework: Decision Crash Tests

NASA Astrophysics Data System (ADS)

Tolson, Bryan; Craig, James

2016-04-01

Decision-makers in water resources are often burdened with selecting appropriate multi-million dollar strategies to mitigate the impacts of climate or land use change. Unfortunately, the suitability of existing hydrologic simulation models to accurately inform decision-making is in doubt because the testing procedures used to evaluate model utility (i.e., model validation) are insufficient. For example, many authors have identified that a good standard framework for model testing called the Klemes Crash Tests (KCTs), which are the classic model validation procedures from Klemeš (1986) that Andréassian et al. (2009) rename as KCTs, have yet to become common practice in hydrology. Furthermore, Andréassian et al. (2009) claim that the progression of hydrological science requires widespread use of KCT and the development of new crash tests. Existing simulation (not forecasting) model testing procedures such as KCTs look backwards (checking for consistency between simulations and past observations) rather than forwards (explicitly assessing if the model is likely to support future decisions). We propose a fundamentally different, forward-looking, decision-oriented hydrologic model testing framework based upon the concept of fit-for-purpose model testing that we call Decision Crash Tests or DCTs. Key DCT elements are i) the model purpose (i.e., decision the model is meant to support) must be identified so that model outputs can be mapped to management decisions ii) the framework evaluates not just the selected hydrologic model but the entire suite of model-building decisions associated with model discretization, calibration etc. The framework is constructed to directly and quantitatively evaluate model suitability. The DCT framework is applied to a model building case study on the Grand River in Ontario, Canada. A hypothetical binary decision scenario is analysed (upgrade or not upgrade the existing flood control structure) under two different sets of model building decisions. In one case, we show the set of model building decisions has a low probability to correctly support the upgrade decision. In the other case, we show evidence suggesting another set of model building decisions has a high probability to correctly support the decision. The proposed DCT framework focuses on what model users typically care about: the management decision in question. The DCT framework will often be very strict and will produce easy to interpret results enabling clear unsuitability determinations. In the past, hydrologic modelling progress has necessarily meant new models and model building methods. Continued progress in hydrologic modelling requires finding clear evidence to motivate researchers to disregard unproductive models and methods and the DCT framework is built to produce this kind of evidence. References: Andréassian, V., C. Perrin, L. Berthet, N. Le Moine, J. Lerat, C. Loumagne, L. Oudin, T. Mathevet, M.-H. Ramos, and A. Valéry (2009), Crash tests for a standardized evaluation of hydrological models. Hydrology and Earth System Sciences, 13, 1757-1764. Klemeš, V. (1986), Operational testing of hydrological simulation models. Hydrological Sciences Journal, 31 (1), 13-24.

NOAA Climate Information and Tools for Decision Support Services

NASA Astrophysics Data System (ADS)

Timofeyeva, M. M.; Higgins, W.; Strager, C.; Horsfall, F. M.

2013-12-01

NOAA is an active participant of the Global Framework for Climate Services (GFCS) contributing data, information, analytical capabilities, forecasts, and decision support services to the Climate Services Partnership (CSP). These contributions emerge from NOAA's own climate services, which have evolved to respond to the urgent and growing need for reliable, trusted, transparent, and timely climate information across all sectors of the U.S. economy. Climate services not only enhance development opportunities in many regions, but also reduce vulnerability to climate change around the world. The NOAA contribution lies within the NOAA Climate Goal mission, which is focusing its efforts on four key climate priority areas: water, extremes, coastal inundation, and marine ecosystems. In order to make progress in these areas, NOAA is exploiting its fundamental capabilities, including foundational research to advance understanding of the Earth system, observations to preserve and build the climate data record and monitor changes in climate conditions, climate models to predict and project future climate across space and time scales, and the development and delivery of decision support services focused on risk management. NOAA's National Weather Services (NWS) is moving toward provision of Decision Support Services (DSS) as a part of the Roadmap on the way to achieving a Weather Ready National (WRN) strategy. Both short-term and long-term weather, water, and climate information are critical for DSS and emergency services and have been integrated into NWS in the form of pilot projects run by National and Regional Operations Centers (NOC and ROCs respectively) as well as several local offices. Local offices with pilot projects have been focusing their efforts on provision of timely and actionable guidance for specific tasks such as DSS in support of Coastal Environments and Integrated Environmental Studies. Climate information in DSS extends the concept of climate services to provision of information that will help guide long-term preparedness for severe weather events and extreme conditions as well as climate variability and change GFCS recently summarized examples of existing initiatives to advance provision of climate services in the 2012 publication Climate ExChange. In this publication, NWS introduced the new Local Climate Analysis Tool (LCAT), a tool that is used to conduct local climate studies that are needed to create efficient and reliable guidance for DSS. LCAT allows for analyzing trends in local climate variables and identifying local impacts of climate variability (e.g., ENSO) on weather and water conditions. In addition to LCAT, NWS, working in partnership with the North East Regional Climate center, released xmACIS version 2, a climate data mining tool, for NWS field operations. During this talk we will demonstrate LCAT and xmACIS as well as outline several examples of their application to DSS and its potential use for achieving GFCS goals. The examples include LCAT-based temperature analysis for energy decisions, guidance on weather and water events leading to increased algal blooms and red tide months in advance, local climate sensitivities to droughts, probabilities of hot/cold conditions and their potential impacts on agriculture and fish kills or fish stress.

A Successful Implementation Strategy to Support Adoption of Decision Making in Mental Health Services.

PubMed

MacDonald-Wilson, Kim L; Hutchison, Shari L; Karpov, Irina; Wittman, Paul; Deegan, Patricia E

2017-04-01

Individual involvement in treatment decisions with providers, often through the use of decision support aids, improves quality of care. This study investigates an implementation strategy to bring decision support to community mental health centers (CMHC). Fifty-two CMHCs implemented a decision support toolkit supported by a 12-month learning collaborative using the Breakthrough Series model. Participation in learning collaborative activities was high, indicating feasibility of the implementation model. Progress by staff in meeting process aims around utilization of components of the toolkit improved significantly over time (p < .0001). Survey responses by individuals in service corroborate successful implementation. Community-based providers were able to successfully implement decision support in mental health services as evidenced by improved process outcomes and sustained practices over 1 year through the structure of the learning collaborative model.

Cross-sectoral optimization and visualization of transformation processes in urban water infrastructures in rural areas.

PubMed

Baron, S; Kaufmann Alves, I; Schmitt, T G; Schöffel, S; Schwank, J

2015-01-01

Predicted demographic, climatic and socio-economic changes will require adaptations of existing water supply and wastewater disposal systems. Especially in rural areas, these new challenges will affect the functionality of the present systems. This paper presents a joint interdisciplinary research project with the objective of developing an innovative software-based optimization and decision support system for the implementation of long-term transformations of existing infrastructures of water supply, wastewater and energy. The concept of the decision support and optimization tool is described and visualization methods for the presentation of results are illustrated. The model is tested in a rural case study region in the Southwest of Germany. A transformation strategy for a decentralized wastewater treatment concept and its visualization are presented for a model village.

Economics of Obesity — Learning from the Past to Contribute to a Better Future

PubMed Central

Ananthapavan, Jaithri; Sacks, Gary; Moodie, Marj; Carter, Rob

2014-01-01

The discipline of economics plays a varied role in informing the understanding of the problem of obesity and the impact of different interventions aimed at addressing it. This paper discusses the causes of the obesity epidemic from an economics perspective, and outlines various justifications for government intervention in this area. The paper then focuses on the potential contribution of health economics in supporting resource allocation decision making for obesity prevention/treatment. Although economic evaluations of single interventions provide useful information, evaluations undertaken as part of a priority setting exercise provide the greatest scope for influencing decision making. A review of several priority setting examples in obesity prevention/treatment indicates that policy (as compared with program-based) interventions, targeted at prevention (as compared with treatment) and focused “upstream” on the food environment, are likely to be the most cost-effective options for change. However, in order to further support decision makers, several methodological advances are required. These include the incorporation of intervention costs/benefits outside the health sector, the addressing of equity impacts, and the increased engagement of decision makers in the priority setting process. PMID:24736685

An education intervention to improve health literacy and decision making about supporting self-care among older Australians: a study protocol for a randomised controlled trial.

PubMed

Smith, Caroline A; Chang, Esther; Gallego, Gisselle; Balneaves, Lynda G

2017-09-26

Older Australians are high consumers of complementary and alternative medicines (CM). To help older people to take an active role in their health, we will develop and evaluate a novel educational intervention to support decision self-efficacy, and improve health literacy skills. The primary hypothesis is that participants receiving a web/DVD plus booklet intervention compared with a booklet-only group will demonstrate an increase in decision self-efficacy. This study is a randomised controlled trial. One hundred and sixty-eight people aged 65 years and older will be recruited from community settings comprising retirement villages and community groups, based in Sydney, Australia. Participants will be randomly allocated to either the education intervention delivered by the Internet or a DVD plus booklet versus a control group (booklet only). The primary outcome measure is CM decision self-efficacy. Secondary outcomes are health literacy, knowledge and attitudes, and change in health-seeking behaviour. Participants' views on the ease of using the resources, the length of the modules, the amount of information, and participant understanding of the modules will be assessed. Outcomes will be collected on completion of the intervention at 3 weeks, and at a 2-month follow up from trial entry. This trial has the potential to improve CM health literacy in older Australians. There are no educational resources designed to support decision self-efficacy and improve health literacy amongst older people related to CM. Australian New Zealand Clinical Trials Registry (ANZCTR), ACTRN12616000135415 . Registered on 5 February 2016.

Reconciling Scale Mismatch in Water Governance, Hydro-climatic Processes and Infrastructure Systems of Water Supply in Las Vegas

NASA Astrophysics Data System (ADS)

Garcia, M. E.; Alarcon, T.; Portney, K.; Islam, S.

2013-12-01

Water resource systems are a classic example of a common pool resource due to the high cost of exclusion and the subtractability of the resource; for common pool resources, the performance of governance systems primarily depends on how well matched the institutional arrangements and rules are to the biophysical conditions and social norms. Changes in water governance, hydro-climatic processes and infrastructure systems occur on disparate temporal and spatial scales. A key challenge is the gap between current climate change model resolution, and the spatial and temporal scale of urban water supply decisions. This gap will lead to inappropriate management policies if not mediated through a carefully crafted decision making process. Traditional decision support and planning methods (DSPM) such as classical decision analysis are not equipped to deal with a non-static climate. While emerging methods such as decision scaling, robust decision making and real options are designed to deal with a changing climate, governance systems have evolved under the assumption of a static climate and it is not clear if these methods are well suited to the existing governance regime. In our study, these questions are contextualized by examining an urban water utility that has made significant changes in policy to adapt to changing conditions: the Southern Nevada Water Authority (SNWA) which serves metropolitan Las Vegas. Like most desert cities, Las Vegas exists because of water; the artesian springs of the Las Vegas Valley once provided an ample water supply for Native Americans, ranchers and later a small railroad city. However, population growth has increased demands far beyond local supplies. The area now depends on the Colorado River for the majority of its water supply. Natural climate variability with periodic droughts has further challenged water providers; projected climate changes and further population growth will exacerbate these challenges. Las Vegas is selected as a case study due to the combined challenges of population growth and climate change, common in the arid west, and due its cooperative institutional response to these challenges, unprecedented in the arid west. To begin to disentangle this question we have analyzed the institutional arrangements and rules which govern water decision making in the Las Vegas Valley and evaluated the existing DSPM used by the SNWA and partner utilities. Presented here are the preliminary results from an ongoing project.

Overview of EPA tools for supporting local-, state- and regional-level decision makers addressing energy and environmental issues: NYC MARKAL Energy Systems Model and Municipal Solid Waste Decision Support Tool

EPA Science Inventory

A workshop will be conducted to demonstrate and focus on two decision support tools developed at EPA/ORD: 1. Community-scale MARKAL model: an energy-water technology evaluation tool and 2. Municipal Solid Waste Decision Support Tool (MSW DST). The Workshop will be part of Southea...

Real-time use of the iPad by third-year medical students for clinical decision support and learning: a mixed methods study.

PubMed

Nuss, Michelle A; Hill, Janette R; Cervero, Ronald M; Gaines, Julie K; Middendorf, Bruce F

2014-01-01

Despite widespread use of mobile technology in medical education, medical students' use of mobile technology for clinical decision support and learning is not well understood. Three key questions were explored in this extensive mixed methods study: 1) how medical students used mobile technology in the care of patients, 2) the mobile applications (apps) used and 3) how expertise and time spent changed overtime. This year-long (July 2012-June 2013) mixed methods study explored the use of the iPad, using four data collection instruments: 1) beginning and end-of-year questionnaires, 2) iPad usage logs, 3) weekly rounding observations, and 4) weekly medical student interviews. Descriptive statistics were generated for the questionnaires and apps reported in the usage logs. The iPad usage logs, observation logs, and weekly interviews were analyzed via inductive thematic analysis. Students predominantly used mobile technology to obtain real-time patient data via the electronic health record (EHR), to access medical knowledge resources for learning, and to inform patient care. The top four apps used were Epocrates(®), PDF Expert(®), VisualDx(®), and Micromedex(®). The majority of students indicated that their use (71%) and expertise (75%) using mobile technology grew overtime. This mixed methods study provides substantial evidence that medical students used mobile technology for clinical decision support and learning. Integrating its use into the medical student's daily workflow was essential for achieving these outcomes. Developing expertise in using mobile technology and various apps was critical for effective and efficient support of real-time clinical decisions.