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

Stakeholder views of management and decision support tools to integrate climate change into Great Lakes Lake Whitefish management

USGS Publications Warehouse

Lynch, Abigail J.; Taylor, William W.; McCright, Aaron M.

2016-01-01

Decision support tools can aid decision making by systematically incorporating information, accounting for uncertainties, and facilitating evaluation between alternatives. Without user buy-in, however, decision support tools can fail to influence decision-making processes. We surveyed fishery researchers, managers, and fishers affiliated with the Lake Whitefish Coregonus clupeaformis fishery in the 1836 Treaty Waters of Lakes Huron, Michigan, and Superior to assess opinions of current and future management needs to identify barriers to, and opportunities for, developing a decision support tool based on Lake Whitefish recruitment projections with climate change. Approximately 64% of 39 respondents were satisfied with current management, and nearly 85% agreed that science was well integrated into management programs. Though decision support tools can facilitate science integration into management, respondents suggest that they face significant implementation barriers, including lack of political will to change management and perceived uncertainty in decision support outputs. Recommendations from this survey can inform development of decision support tools for fishery management in the Great Lakes and other regions.

An exploration of pregnant teenagers' views of the future and their decisions to continue or terminate their pregnancy: implications for nursing care.

PubMed

Bell, Emily R; Glover, Lesley; Alexander, Tim

2014-09-01

To explore teenagers' views of the future in relation to their choices to continue or terminate pregnancy. Despite recent decreases in the numbers of teenage pregnancies, across the world, the teenage pregnancy rate remains high. Consideration of views of the future (future orientation) appears to play an important part in teenage girls' decisions to continue with pregnancy. To date, no study has explored this in teenage pregnant girls at the time they make their decision to continue with or terminate their pregnancy. Cross-sectional mixed methods design. Three groups were included: termination of pregnancy (n = 19), antenatal (n = 9) and never pregnant (n = 23). Participants were 13-18 years old. The termination of pregnancy and antenatal groups were interviewed, and the never pregnant group completed postal questionnaires. Groups differed in individual aspects of future orientation, that is, education, career and family, and reasons for pregnancy resolution choice. The termination group had more clearly developed and longer-term plans for the future with a focus on career. The never pregnant group shared aspects of their future orientation with both the antenatal and termination of pregnancy groups. The impact of negative discourses about teenage pregnancy from others was identified as a significant issue. How pregnant teenage girls view the future has a relationship with their decision to terminate or continue with their pregnancy. The findings suggest that working with teenage girls to clarify their views of the future may be useful both in preventing future unwanted pregnancy and in supporting teenagers in making pregnancy decisions. Supporting pregnant teenagers in distancing themselves from negative stereotypes of teenage mothers may also be beneficial. © 2013 John Wiley & Sons Ltd.

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.

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

Computer-Assisted Diagnostic Decision Support: History, Challenges, and Possible Paths Forward

ERIC Educational Resources Information Center

Miller, Randolph A.

2009-01-01

This paper presents a brief history of computer-assisted diagnosis, including challenges and future directions. Some ideas presented in this article on computer-assisted diagnostic decision support systems (CDDSS) derive from prior work by the author and his colleagues (see list in Acknowledgments) on the INTERNIST-1 and QMR projects. References…

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.

A big data analysis of the relationship between future thinking and decision-making.

PubMed

Thorstad, Robert; Wolff, Phillip

2018-02-20

We use big data methods to investigate how decision-making might depend on future sightedness (that is, on how far into the future people's thoughts about the future extend). In study 1, we establish a link between future thinking and decision-making at the population level in showing that US states with citizens having relatively far future sightedness, as reflected in their tweets, take fewer risks than citizens in states having relatively near future sightedness. In study 2, we analyze people's tweets to confirm a connection between future sightedness and decision-making at the individual level in showing that people with long future sightedness are more likely to choose larger future rewards over smaller immediate rewards. In study 3, we show that risk taking decreases with increases in future sightedness as reflected in people's tweets. The ability of future sightedness to predict decisions suggests that future sightedness is a relatively stable cognitive characteristic. This implication was supported in an analysis of tweets by over 38,000 people that showed that future sightedness has both state and trait characteristics (study 4). In study 5, we provide evidence for a potential mechanism by which future sightedness can affect decisions in showing that far future sightedness can make the future seem more connected to the present, as reflected in how people refer to the present, past, and future in their tweets over the course of several minutes. Our studies show how big data methods can be applied to naturalistic data to reveal underlying psychological properties and processes.

Role of Advance Care Planning in Proxy Decision Making Among Individuals With Dementia and Their Family Caregivers.

PubMed

Kwak, Jung; De Larwelle, Jessica A; Valuch, Katharine O'Connell; Kesler, Toni

2016-01-01

Health care proxies make important end-of-life decisions for individuals with dementia. A cross-sectional survey was conducted to examine the role of advance care planning in proxy decision making for 141 individuals with cognitive impairment, Alzheimer's disease, or other types of dementia. Proxies who did not know the preferences of individuals with dementia for life support treatments reported greater understanding of their values. Proxies of individuals with dementia who did not want life support treatments anticipated receiving less support and were more uncertain in decision making. The greater knowledge proxies had about dementia trajectory, family support, and trust of physicians, the more informed, clearer, and less uncertain they were in decision making. In addition to advance care planning, multiple factors influence proxy decision making, which should be considered in developing interventions and future research to support informed decision making for individuals with dementia and their families. Copyright 2016, SLACK Incorporated.

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

Fuzzy Integration of Support Vector Regression Models for Anticipatory Control of Complex Energy Systems

DOE PAGES

Alamaniotis, Miltiadis; Agarwal, Vivek

2014-04-01

Anticipatory control systems are a class of systems whose decisions are based on predictions for the future state of the system under monitoring. Anticipation denotes intelligence and is an inherent property of humans that make decisions by projecting in future. Likewise, artificially intelligent systems equipped with predictive functions may be utilized for anticipating future states of complex systems, and therefore facilitate automated control decisions. Anticipatory control of complex energy systems is paramount to their normal and safe operation. In this paper a new intelligent methodology integrating fuzzy inference with support vector regression is introduced. Our proposed methodology implements an anticipatorymore » system aiming at controlling energy systems in a robust way. Initially a set of support vector regressors is adopted for making predictions over critical system parameters. Furthermore, the predicted values are fed into a two stage fuzzy inference system that makes decisions regarding the state of the energy system. The inference system integrates the individual predictions into a single one at its first stage, and outputs a decision together with a certainty factor computed at its second stage. The certainty factor is an index of the significance of the decision. The proposed anticipatory control system is tested on a real world set of data obtained from a complex energy system, describing the degradation of a turbine. Results exhibit the robustness of the proposed system in controlling complex energy systems.« less

Decision-Making and the Interface between Human Intelligence and Artificial Intelligence. AIR 1987 Annual Forum Paper.

ERIC Educational Resources Information Center

Henard, Ralph E.

Possible future developments in artificial intelligence (AI) as well as its limitations are considered that have implications for institutional research in higher education, and especially decision making and decision support systems. It is noted that computer software programs have been developed that store knowledge and mimic the decision-making…

Ecological models supporting environmental decision making: a strategy for the future

USGS Publications Warehouse

Schmolke, Amelie; Thorbek, Pernille; DeAngelis, Donald L.; Grimm, Volker

2010-01-01

Ecological models are important for environmental decision support because they allow the consequences of alternative policies and management scenarios to be explored. However, current modeling practice is unsatisfactory. A literature review shows that the elements of good modeling practice have long been identified but are widely ignored. The reasons for this might include lack of involvement of decision makers, lack of incentives for modelers to follow good practice, and the use of inconsistent terminologies. As a strategy for the future, we propose a standard format for documenting models and their analyses: transparent and comprehensive ecological modeling (TRACE) documentation. This standard format will disclose all parts of the modeling process to scrutiny and make modeling itself more efficient and coherent.

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.

Bridging the gap: decision-making processes of women with breast cancer using complementary and alternative medicine (CAM).

PubMed

Balneaves, Lynda G; Truant, Tracy L O; Kelly, Mary; Verhoef, Marja J; Davison, B Joyce

2007-08-01

The purpose of this study was to explore the personal and social processes women with breast cancer engaged in when making decisions about complementary and alternative medicine (CAM). The overall aim was to develop a conceptual model of the treatment decision-making process specific to breast cancer care and CAM that will inform future information and decision support strategies. Grounded theory methodology explored the decisions of women with breast cancer using CAM. Semistructured interviews were conducted with 20 women diagnosed with early-stage breast cancer. Following open, axial, and selective coding, the constant comparative method was used to identify key themes in the data and develop a conceptual model of the CAM decision-making process. The final decision-making model, Bridging the Gap, was comprised of four core concepts including maximizing choices/minimizing risks, experiencing conflict, gathering and filtering information, and bridging the gap. Women with breast cancer used one of three decision-making styles to address the paradigmatic, informational, and role conflict they experienced as a result of the gap they perceived between conventional care and CAM: (1) taking it one step at a time, (2) playing it safe, and (3) bringing it all together. Women with breast cancer face conflict and anxiety when making decisions about CAM within a conventional cancer care context. Information and decision support strategies are needed to ensure women are making safe, informed treatment decisions about CAM. The model, Bridging the Gap, provides a conceptual framework for future decision support interventions.

Minimum Equipment Lists, Flight Rules and ... Past, Present and Future of Safety Pre-Determined Decisions for Operations

NASA Astrophysics Data System (ADS)

Herd, A.; Wolff, M.

2012-01-01

Extended mission operations, such as human spaceflight to Mars provide an opportunity for take current human exploration beyond Low Earth Orbit, such as the operations undertaken on the International Space Station (ISS). This opportunity also presents a challenge in terms of extending what we currently understand as "remote operations" performed on ISS, offering learning beyond that gained from the successful moon- lander expeditions. As such there is a need to assess how the existing operations concept of ground support teams directing (and supporting) on-orbit ISS operations can be applied in the extended mission concept. The current mission support concept involves three interacting operations products - a short term plan, crew procedures and flight rules. Flight rules (for ISS operations) currently provide overall planning, engineering and operations constraints (including those derived from a safety perspective) in the form of a rule book. This paper will focus specifically on flight rules, and describe the current use of them, and assess the future role of flight rules to support exploration, including the deployment of decision support tools (DSTs) to ensure flight rule compliancy for missions with minimal ground support. Taking consideration of the historical development of pre-planned decisions, and their manifestation within the operations environment, combined with the extended remoteness of human exploration missions, we will propose a future development of this product and a platform on which it could be presented.

GET SMARTE: DECISION TOOLS TO REVITALIZE BROWNFIELDS

EPA Science Inventory

SMARTe (Sustainable Management Approaches and Revitalization Tools-electronic) is an open-source, web-based, decision-support system for developing and evaluating future use scenarios for potentially contaminated sites (i.e., brownfields). It contains resources and analysis tools...

Computer-assisted diagnostic decision support: history, challenges, and possible paths forward.

PubMed

Miller, Randolph A

2009-09-01

This paper presents a brief history of computer-assisted diagnosis, including challenges and future directions. Some ideas presented in this article on computer-assisted diagnostic decision support systems (CDDSS) derive from prior work by the author and his colleagues (see list in Acknowledgments) on the INTERNIST-1 and QMR projects. References indicate the original sources of many of these ideas.

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.

Decision-support systems for forest management

Treesearch

H. Michael Rauscher

2005-01-01

The basic concept of sustainable development, formulated in the Brundtland report and applied to forest management by the Montreal Process, has focused attention on the need for formal decision processes (Brundtland. 1987). The application of decision theory is essential because meeting the needs of the present without compromising the ability of future generations to...

GET SMARTE: DECISION TOOLS TO REVITALIZE COMMUNITIES (MAY 2006)

EPA Science Inventory

SMARTe (Sustainable Management Approaches and Revitalization Tools-electronic) is an open-source, web-based, decision-support system for developing and evaluating future use scenarios for potentially contaminated sites (i.e., brownfields). It contains resources and analysis tools...

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.

Biomedical Informatics for Computer-Aided Decision Support Systems: A Survey

PubMed Central

Belle, Ashwin; Kon, Mark A.; Najarian, Kayvan

2013-01-01

The volumes of current patient data as well as their complexity make clinical decision making more challenging than ever for physicians and other care givers. This situation calls for the use of biomedical informatics methods to process data and form recommendations and/or predictions to assist such decision makers. The design, implementation, and use of biomedical informatics systems in the form of computer-aided decision support have become essential and widely used over the last two decades. This paper provides a brief review of such systems, their application protocols and methodologies, and the future challenges and directions they suggest. PMID:23431259

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.

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

PubMed

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

2018-07-01

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

Delaying investments in sensor technology: The rationality of dairy farmers' investment decisions illustrated within the framework of real options theory.

PubMed

Rutten, C J; Steeneveld, W; Oude Lansink, A G J M; Hogeveen, H

2018-05-02

The adoption rate of sensors on dairy farms varies widely. Whereas some sensors are hardly adopted, others are adopted by many farmers. A potential rational explanation for the difference in adoption may be the expected future technological progress in the sensor technology and expected future improved decision support possibilities. For some sensors not much progress can be expected because the technology has already made enormous progress in recent years, whereas for sensors that have only recently been introduced on the market, much progress can be expected. The adoption of sensors may thus be partly explained by uncertainty about the investment decision, in which uncertainty lays in the future performance of the sensors and uncertainty about whether improved informed decision support will become available. The overall aim was to offer a plausible example of why a sensor may not be adopted now. To explain this, the role of uncertainty about technological progress in the investment decision was illustrated for highly adopted sensors (automated estrus detection) and hardly adopted sensors (automated body condition score). This theoretical illustration uses the real options theory, which accounts for the role of uncertainty in the timing of investment decisions. A discrete event model, simulating a farm of 100 dairy cows, was developed to estimate the net present value (NPV) of investing now and investing in 5 yr in both sensor systems. The results show that investing now in automated estrus detection resulted in a higher NPV than investing 5 yr from now, whereas for the automated body condition score postponing the investment resulted in a higher NPV compared with investing now. These results are in line with the observation that farmers postpone investments in sensors. Also, the current high adoption of automated estrus detection sensors can be explained because the NPV of investing now is higher than the NPV of investing in 5 yr. The results confirm that uncertainty about future sensor performance and uncertainty about whether improved decision support will become available play a role in investment decisions. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Aiding Lay Decision Making Using a Cognitive Competencies Approach.

PubMed

Maule, A J; Maule, Simon

2015-01-01

Two prescriptive approaches have evolved to aid human decision making: just in time interventions that provide support as a decision is being made; and just in case interventions that educate people about future events that they may encounter so that they are better prepared to make an informed decision when these events occur. We review research on these two approaches developed in the context of supporting everyday decisions such as choosing an apartment, a financial product or a medical procedure. We argue that the lack of an underlying prescriptive theory has limited the development and evaluation of these interventions. We draw on recent descriptive research on the cognitive competencies that underpin human decision making to suggest new ways of interpreting how and why existing decision aids may be effective and suggest a different way of evaluating their effectiveness. We also briefly outline how our approach has the potential to develop new interventions to support everyday decision making and highlight the benefits of drawing on descriptive research when developing and evaluating interventions.

Aiding Lay Decision Making Using a Cognitive Competencies Approach

PubMed Central

Maule, A. J.; Maule, Simon

2016-01-01

Two prescriptive approaches have evolved to aid human decision making: just in time interventions that provide support as a decision is being made; and just in case interventions that educate people about future events that they may encounter so that they are better prepared to make an informed decision when these events occur. We review research on these two approaches developed in the context of supporting everyday decisions such as choosing an apartment, a financial product or a medical procedure. We argue that the lack of an underlying prescriptive theory has limited the development and evaluation of these interventions. We draw on recent descriptive research on the cognitive competencies that underpin human decision making to suggest new ways of interpreting how and why existing decision aids may be effective and suggest a different way of evaluating their effectiveness. We also briefly outline how our approach has the potential to develop new interventions to support everyday decision making and highlight the benefits of drawing on descriptive research when developing and evaluating interventions. PMID:26779052

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 Ecosystem Services Indices with EnviroAtlas Metrics

EPA Science Inventory

To support the well-being of future generations, ecosystem services (ES) need to be fully understood and evaluated by decision-makers. Geospatial tools, such as the EnviroAtlas, allow decision-makers, urban planners, public health professionals, and other stakeholders to view and...

Optimal data systems: the future of clinical predictions and decision support.

PubMed

Celi, Leo A; Csete, Marie; Stone, David

2014-10-01

The purpose of the review is to describe the evolving concept and role of data as it relates to clinical predictions and decision-making. Critical care medicine is, as an especially data-rich specialty, becoming acutely cognizant not only of its historic deficits in data utilization but also of its enormous potential for capturing, mining, and leveraging such data into well-designed decision support modalities as well as the formulation of robust best practices. Modern electronic medical records create an opportunity to design complete and functional data systems that can support clinical care to a degree never seen before. Such systems are often referred to as 'data-driven,' but a better term is 'optimal data systems' (ODS). Here we discuss basic features of an ODS and its benefits, including the potential to transform clinical prediction and decision support.

Developing genomic knowledge bases and databases to support clinical management: current perspectives.

PubMed

Huser, Vojtech; Sincan, Murat; Cimino, James J

2014-01-01

Personalized medicine, the ability to tailor diagnostic and treatment decisions for individual patients, is seen as the evolution of modern medicine. We characterize here the informatics resources available today or envisioned in the near future that can support clinical interpretation of genomic test results. We assume a clinical sequencing scenario (germline whole-exome sequencing) in which a clinical specialist, such as an endocrinologist, needs to tailor patient management decisions within his or her specialty (targeted findings) but relies on a genetic counselor to interpret off-target incidental findings. We characterize the genomic input data and list various types of knowledge bases that provide genomic knowledge for generating clinical decision support. We highlight the need for patient-level databases with detailed lifelong phenotype content in addition to genotype data and provide a list of recommendations for personalized medicine knowledge bases and databases. We conclude that no single knowledge base can currently support all aspects of personalized recommendations and that consolidation of several current resources into larger, more dynamic and collaborative knowledge bases may offer a future path forward.

Developing genomic knowledge bases and databases to support clinical management: current perspectives

PubMed Central

Huser, Vojtech; Sincan, Murat; Cimino, James J

2014-01-01

Personalized medicine, the ability to tailor diagnostic and treatment decisions for individual patients, is seen as the evolution of modern medicine. We characterize here the informatics resources available today or envisioned in the near future that can support clinical interpretation of genomic test results. We assume a clinical sequencing scenario (germline whole-exome sequencing) in which a clinical specialist, such as an endocrinologist, needs to tailor patient management decisions within his or her specialty (targeted findings) but relies on a genetic counselor to interpret off-target incidental findings. We characterize the genomic input data and list various types of knowledge bases that provide genomic knowledge for generating clinical decision support. We highlight the need for patient-level databases with detailed lifelong phenotype content in addition to genotype data and provide a list of recommendations for personalized medicine knowledge bases and databases. We conclude that no single knowledge base can currently support all aspects of personalized recommendations and that consolidation of several current resources into larger, more dynamic and collaborative knowledge bases may offer a future path forward. PMID:25276091

Management of Forested Landscapes: Simulations of three alternatives

Treesearch

Stephen G. Boyce; W. Henry McNab

1994-01-01

Forested landscapes can be managed to support variouscombinations of timber, biological diversity,esthetic values, and habitats. However, all such management decisions arechoices basedon opinions about future events. Opinions underlie managementdecisionsbecause thereis no way to jump into the future, verify a future event, jump back to the present, and make a...

Decision support models for solid waste management: Review and game-theoretic approaches

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

Karmperis, Athanasios C., E-mail: athkarmp@mail.ntua.gr; Army Corps of Engineers, Hellenic Army General Staff, Ministry of Defence; Aravossis, Konstantinos

Highlights: ► The mainly used decision support frameworks for solid waste management are reviewed. ► The LCA, CBA and MCDM models are presented and their strengths, weaknesses, similarities and possible combinations are analyzed. ► The game-theoretic approach in a solid waste management context is presented. ► The waste management bargaining game is introduced as a specific decision support framework. ► Cooperative and non-cooperative game-theoretic approaches to decision support for solid waste management are discussed. - Abstract: This paper surveys decision support models that are commonly used in the solid waste management area. Most models are mainly developed within three decisionmore » support frameworks, which are the life-cycle assessment, the cost–benefit analysis and the multi-criteria decision-making. These frameworks are reviewed and their strengths and weaknesses as well as their critical issues are analyzed, while their possible combinations and extensions are also discussed. Furthermore, the paper presents how cooperative and non-cooperative game-theoretic approaches can be used for the purpose of modeling and analyzing decision-making in situations with multiple stakeholders. Specifically, since a waste management model is sustainable when considering not only environmental and economic but also social aspects, the waste management bargaining game is introduced as a specific decision support framework in which future models can be developed.« less

Human-Computer Interaction with Medical Decisions Support Systems

NASA Technical Reports Server (NTRS)

Adolf, Jurine A.; Holden, Kritina L.

1994-01-01

Decision Support Systems (DSSs) have been available to medical diagnosticians for some time, yet their acceptance and use have not increased with advances in technology and availability of DSS tools. Medical DSSs will be necessary on future long duration space missions, because access to medical resources and personnel will be limited. Human-Computer Interaction (HCI) experts at NASA's Human Factors and Ergonomics Laboratory (HFEL) have been working toward understanding how humans use DSSs, with the goal of being able to identify and solve the problems associated with these systems. Work to date consists of identification of HCI research areas, development of a decision making model, and completion of two experiments dealing with 'anchoring'. Anchoring is a phenomenon in which the decision maker latches on to a starting point and does not make sufficient adjustments when new data are presented. HFEL personnel have replicated a well-known anchoring experiment and have investigated the effects of user level of knowledge. Future work includes further experimentation on level of knowledge, confidence in the source of information and sequential decision making.

New Directions in Health Risk Assessment: A REACH for the Future?

EPA Science Inventory

Health risk assessments have been used to support many decisions in the US to reduce risks from pollutant exposures. These decisions have been highly successful in protecting public health despite uncertainty due to gaps in knowledge and methodological limitations. In recent yea...

[Medical expert systems and clinical needs].

PubMed

Buscher, H P

1991-10-18

The rapid expansion of computer-based systems for problem solving or decision making in medicine, the so-called medical expert systems, emphasize the need for reappraisal of their indication and value. Where specialist knowledge is required, in particular where medical decisions are susceptible to error these systems will probably serve as a valuable support. In the near future computer-based systems should be able to aid the interpretation of findings of technical investigations and the control of treatment, especially where rapid reactions are necessary despite the need of complex analysis of investigated parameters. In the distant future complete support of diagnostic procedures from the history to final diagnosis is possible. It promises to be particularly attractive for the diagnosis of seldom diseases, for difficult differential diagnoses, and in the decision making in the case of expensive, risky or new diagnostic or therapeutic methods. The physician needs to be aware of certain dangers, ranging from misleading information up to abuse. Patient information depends often on subjective reports and error-prone observations. Although basing on problematic knowledge computer-born decisions may have an imperative effect on medical decision making. Also it must be born in mind that medical decisions should always combine the rational with a consideration of human motives.

The anatomy of decision support during inpatient care provider order entry (CPOE): Empirical observations from a decade of CPOE experience at Vanderbilt

PubMed Central

Miller, Randolph A.; Waitman, Lemuel R.; Chen, Sutin; Rosenbloom, S. Trent

2006-01-01

The authors describe a pragmatic approach to the introduction of clinical decision support at the point of care, based on a decade of experience in developing and evolving Vanderbilt’s inpatient “WizOrder” care provider order entry (CPOE) system. The inpatient care setting provides a unique opportunity to interject CPOE-based decision support features that restructure clinical workflows, deliver focused relevant educational materials, and influence how care is delivered to patients. From their empirical observations, the authors have developed a generic model for decision support within inpatient CPOE systems. They believe that the model’s utility extends beyond Vanderbilt, because it is based on characteristics of end-user workflows and on decision support considerations that are common to a variety of inpatient settings and CPOE systems. The specific approach to implementing a given clinical decision support feature within a CPOE system should involve evaluation along three axes: what type of intervention to create (for which the authors describe 4 general categories); when to introduce the intervention into the user’s workflow (for which the authors present 7 categories), and how disruptive, during use of the system, the intervention might be to end-users’ workflows (for which the authors describe 6 categories). Framing decision support in this manner may help both developers and clinical end-users plan future alterations to their systems when needs for new decision support features arise. PMID:16290243

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.

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.

Automation in future air traffic management: effects of decision aid reliability on controller performance and mental workload.

PubMed

Metzger, Ulla; Parasuraman, Raja

2005-01-01

Future air traffic management concepts envisage shared decision-making responsibilities between controllers and pilots, necessitating that controllers be supported by automated decision aids. Even as automation tools are being introduced, however, their impact on the air traffic controller is not well understood. The present experiments examined the effects of an aircraft-to-aircraft conflict decision aid on performance and mental workload of experienced, full-performance level controllers in a simulated Free Flight environment. Performance was examined with both reliable (Experiment 1) and inaccurate automation (Experiment 2). The aid improved controller performance and reduced mental workload when it functioned reliably. However, detection of a particular conflict was better under manual conditions than under automated conditions when the automation was imperfect. Potential or actual applications of the results include the design of automation and procedures for future air traffic control systems.

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.

Enabling Autonomous Space Mission Operations with Artificial Intelligence

NASA Technical Reports Server (NTRS)

Frank, Jeremy

2017-01-01

For over 50 years, NASA's crewed missions have been confined to the Earth-Moon system, where speed-of-light communications delays between crew and ground are practically nonexistent. This ground-centered mode of operations, with a large, ground-based support team, is not sustainable for NASAs future human exploration missions to Mars. Future astronauts will need smarter tools employing Artificial Intelligence (AI) techniques make decisions without inefficient communication back and forth with ground-based mission control. In this talk we will describe several demonstrations of astronaut decision support tools using AI techniques as a foundation. These demonstrations show that astronauts tasks ranging from living and working to piloting can benefit from AI technology development.

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 ...

A Participants' DSS for a Management Game with a DSS Generator.

ERIC Educational Resources Information Center

Yeo, Gee Kin; Nah, Fui Hoon

1992-01-01

Describes the design of a decision support system (DSS) for a management game called MAGNUS (Management Game for National University of Singapore). Built-in models for performance analysis and decision making are explained; database query and model building are described; and future work is discussed. (11 references) (LRW)

A methodology and decision support tool for informing state-level bioenergy policymaking: New Jersey biofuels as a case study

NASA Astrophysics Data System (ADS)

Brennan-Tonetta, Margaret

This dissertation seeks to provide key information and a decision support tool that states can use to support long-term goals of fossil fuel displacement and greenhouse gas reductions. The research yields three outcomes: (1) A methodology that allows for a comprehensive and consistent inventory and assessment of bioenergy feedstocks in terms of type, quantity, and energy potential. Development of a standardized methodology for consistent inventorying of biomass resources fosters research and business development of promising technologies that are compatible with the state's biomass resource base. (2) A unique interactive decision support tool that allows for systematic bioenergy analysis and evaluation of policy alternatives through the generation of biomass inventory and energy potential data for a wide variety of feedstocks and applicable technologies, using New Jersey as a case study. Development of a database that can assess the major components of a bioenergy system in one tool allows for easy evaluation of technology, feedstock and policy options. The methodology and decision support tool is applicable to other states and regions (with location specific modifications), thus contributing to the achievement of state and federal goals of renewable energy utilization. (3) Development of policy recommendations based on the results of the decision support tool that will help to guide New Jersey into a sustainable renewable energy future. The database developed in this research represents the first ever assessment of bioenergy potential for New Jersey. It can serve as a foundation for future research and modifications that could increase its power as a more robust policy analysis tool. As such, the current database is not able to perform analysis of tradeoffs across broad policy objectives such as economic development vs. CO2 emissions, or energy independence vs. source reduction of solid waste. Instead, it operates one level below that with comparisons of kWh or GGE generated by different feedstock/technology combinations at the state and county level. Modification of the model to incorporate factors that will enable the analysis of broader energy policy issues as those mentioned above, are recommended for future research efforts.

Decision Modeling Framework to Minimize Arrival Delays from Ground Delay Programs

NASA Astrophysics Data System (ADS)

Mohleji, Nandita

Convective weather and other constraints create uncertainty in air transportation, leading to costly delays. A Ground Delay Program (GDP) is a strategy to mitigate these effects. Systematic decision support can increase GDP efficacy, reduce delays, and minimize direct operating costs. In this study, a decision analysis (DA) model is constructed by combining a decision tree and Bayesian belief network. Through a study of three New York region airports, the DA model demonstrates that larger GDP scopes that include more flights in the program, along with longer lead times that provide stakeholders greater notice of a pending program, trigger the fewest average arrival delays. These findings are demonstrated to result in a savings of up to $1,850 per flight. Furthermore, when convective weather is predicted, forecast weather confidences remain the same level or greater at least 70% of the time, supporting more strategic decision making. The DA model thus enables quantification of uncertainties and insights on causal relationships, providing support for future GDP decisions.

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.

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.

Integrated Decision Support, Sensor Networks and Adaptive Control for Wireless Site-specific Sprinkler Irrigation

USDA-ARS?s Scientific Manuscript database

The development of site-specific sprinkler irrigation water management systems will be a major factor in future efforts to improve the various efficiencies of water-use and to support a sustainable irrigated environment. The challenge is to develop fully integrated management systems with supporting...

Integrated decision support, sensor networks and adaptive control for wireless site-specific sprinkler irrigation

USDA-ARS?s Scientific Manuscript database

The development of site-specific sprinkler irrigation water management systems will be a major factor in future efforts to improve the various efficiencies of water-use and to support a sustainable irrigated environment. The challenge is to develop fully integrated management systems with supporting...

Using future thinking to reduce temporal discounting: Under what circumstances are the medial temporal lobes critical?

PubMed

Palombo, D J; Keane, M M; Verfaellie, M

2016-08-01

The capacity to envision the future plays an important role in many aspects of cognition, including our ability to make optimal, adaptive choices. Past work has shown that the medial temporal lobe (MTL) is necessary for decisions that draw on episodic future thinking. By contrast, little is known about the role of the MTL in decisions that draw on semantic future thinking. Accordingly, the present study investigated whether the MTL contributes to one form of decision making, namely intertemporal choice, when such decisions depend on semantic consideration of the future. In an intertemporal choice task, participants must select either a smaller amount of money that is available in the present or a larger amount of money that would be available at a future date. Amnesic individuals with MTL damage and healthy control participants performed such a task in which, prior to making a choice, they engaged in a semantic generation exercise, wherein they generated items that they would purchase with the future reward. In experiment 1, we found that, relative to a baseline condition involving standard intertemporal choice, healthy individuals were more inclined to select a larger, later reward over a smaller, present reward after engaging in semantic future thinking. By contrast, amnesic participants were paradoxically less inclined to wait for a future reward following semantic future thinking. This finding suggests that amnesics may have had difficulty "tagging" the generated item(s) as belonging to the future. Critically, experiment 2 showed that when the generated items were presented alongside the intertemporal choices, both controls and amnesic participants shifted to more patient choices. These findings suggest that the MTL is not needed for making optimal decisions that draw on semantic future thinking as long as scaffolding is provided to support accurate time tagging. Together, these findings stand to better clarify the role of the MTL in decision making. Published by Elsevier Ltd.

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.

Episodic Future Thinking: Mechanisms and Functions.

PubMed

Schacter, Daniel L; Benoit, Roland G; Szpunar, Karl K

2017-10-01

Episodic future thinking refers to the capacity to imagine or simulate experiences that might occur in one's personal future. Cognitive, neuropsychological, and neuroimaging research concerning episodic future thinking has accelerated during recent years. This article discusses research that has delineated cognitive and neural mechanisms that support episodic future thinking as well as the functions that episodic future thinking serves. Studies focused on mechanisms have identified a core brain network that underlies episodic future thinking and have begun to tease apart the relative contributions of particular regions in this network, and the specific cognitive processes that they support. Studies concerned with functions have identified several domains in which episodic future thinking produces performance benefits, including decision making, emotion regulation, prospective memory, and spatial navigation.

Robust Decision Making to Support Water Quality Climate Adaptation: a Case Study in the Chesapeake Bay Watershed

NASA Astrophysics Data System (ADS)

Fischbach, J. R.; Lempert, R. J.; Molina-Perez, E.

2017-12-01

The U.S. Environmental Protection Agency (USEPA), together with state and local partners, develops watershed implementation plans designed to meet water quality standards. Climate uncertainty, along with uncertainty about future land use changes or the performance of water quality best management practices (BMPs), may make it difficult for these implementation plans to meet water quality goals. In this effort, we explored how decision making under deep uncertainty (DMDU) methods such as Robust Decision Making (RDM) could help USEPA and its partners develop implementation plans that are more robust to future uncertainty. The study focuses on one part of the Chesapeake Bay watershed, the Patuxent River, which is 2,479 sq km in area, highly urbanized, and has a rapidly growing population. We simulated the contribution of stormwater contaminants from the Patuxent to the overall Total Maximum Daily Load (TMDL) for the Chesapeake Bay under multiple scenarios reflecting climate and other uncertainties. Contaminants considered included nitrogen, phosphorus, and sediment loads. The assessment included a large set of scenario simulations using the USEPA Chesapeake Bay Program's Phase V watershed model. Uncertainties represented in the analysis included 18 downscaled climate projections (based on 6 general circulation models and 3 emissions pathways), 12 land use scenarios with different population projections and development patterns, and alternative assumptions about BMP performance standards and efficiencies associated with different suites of stormwater BMPs. Finally, we developed cost estimates for each of the performance standards and compared cost to TMDL performance as a key tradeoff for future water quality management decisions. In this talk, we describe how this research can help inform climate-related decision support at USEPA's Chesapeake Bay Program, and more generally how RDM and other DMDU methods can support improved water quality management under climate uncertainty.

GODDESS: A Goal-Directed Decision Structuring System.

DTIC Science & Technology

1980-06-01

differ- ent support techniques. From a practical viewpoint, though, the major drawback of manual interviews is their length and cost. Since real - time ...conducting his future inquiries. A direct man-machine interface could provide three distinct advantages. First, it offers the capability of real - time ...knowledge in tree form. In many real -world applications, the decision maker may not perceive a problem in the form of a time sequence of decision

Characterization of Decision Making Behaviors Associated with Human Systems Integration (HSI) Design Tradeoffs: Subject Matter Expert Interviews

DTIC Science & Technology

2014-11-18

this research was to characterize the naturalistic decision making process used in Naval Aviation acquisition to assess cost, schedule and...Naval Aviation acquisitions can be identified, which can support the future development of new processes and tools for training and decision making...part of Department of Defense acquisition processes , HSI ensures that operator, maintainer and sustainer considerations are incorporated into

Decision Making and Cancer

PubMed Central

Reyna, Valerie F.; Nelson, Wendy L.; Han, Paul K.; Pignone, Michael P.

2014-01-01

We review decision-making along the cancer continuum in the contemporary context of informed and shared decision making, in which patients are encouraged to take a more active role in their health care. We discuss challenges to achieving informed and shared decision making, including cognitive limitations and emotional factors, but argue that understanding the mechanisms of decision making offers hope for improving decision support. Theoretical approaches to decision making that explain cognition, emotion, and their interaction are described, including classical psychophysical approaches, dual-process approaches that focus on conflicts between emotion versus cognition (or reason), and modern integrative approaches such as fuzzy-trace theory. In contrast to the earlier emphasis on rote use of numerical detail, modern approaches emphasize understanding the bottom-line gist of options (which encompasses emotion and other influences on meaning) and retrieving relevant social and moral values to apply to those gist representations. Finally, research on interventions to support better decision making in clinical settings is reviewed, drawing out implications for future research on decision making and cancer. PMID:25730718

Proceedings of the workshop "Development of biological decision support systems for resource managers": Denver, Colorado, October 27-29, 1998

USGS Publications Warehouse

Getter, James; D'Erchia, Terry D.; Root, Ralph; Getter, James; D'Erchia, Terry D.; Root, Ralph

1999-01-01

The format for this 3-day workshop (27-29 October 1998) included plenary presentations by USGS Biological Resources Division (BRD) and U.S. Fish and Wildlife Service per onnel who u e and develop decision support systems (DSS); breakout ses ions addressing DSS technical information aspect , outreach/ customer requirements, and future perspectives; and a DSS Steering Committee meeting to evaluate work hop goals and to provide guidance for fu ture efforts. Steering committee action item developed from workshop inputs were to ( I) develop a "DSS framework" document for u e in biological research. (2) develop a "proof of concept" DSS based upon the framework document, and (3) integrate decision support ystem into BRD program elements.

Clinical decision support for personalized medicine: an opportunity for pharmacist-physician collaboration.

PubMed

Barlow, Jane F

2012-06-01

Pharmacogenomics has significant potential to improve the efficacy and safety of medication therapy, but it requires new expertise and adds a new layer of complexity for all healthcare professionals. Pharmacists and pharmacy management systems can play a leading role in providing clinical decision support for the use and interpretation of pharmacogenomic tests. To serve this role effectively, pharmacists will need to expand their expertise in the emerging field of clinical pharmacogenomics. Pharmacy-based clinical programs can expedite the use of pharmacogenomic testing, help physicians interpret the test results and identify future medication risks associated with the patient's phenotype. Over time, some of these functions can be embedded in clinical decision support systems as part of the broader automation of the healthcare system.

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

PubMed

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

2015-01-23

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

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

PubMed Central

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

2015-01-01

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

Education and the Politics of Austerity.

ERIC Educational Resources Information Center

Florio, David H.

1979-01-01

The evolution of congressional support for educational programs and the impact of the present trend toward financial restraint are reviewed. Research, evaluation, and policy studies will help influence future decisions, although other factors such as the economy and interest group pressures will affect support. (MH)

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...

Managing the University Campus: Exploring Models for the Future and Supporting Today's Decisions

ERIC Educational Resources Information Center

den Heijer, Alexandra

2012-01-01

Managing contemporary campuses and taking decisions that will impact on those of tomorrow is a complex task for universities worldwide. It involves strategic, financial, functional and physical aspects as well as multiple stakeholders. This article summarises the conclusions of a comprehensive PhD research project which was enriched with lessons…

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 support tool for synchronizing technology advances with strategic mission objectives

NASA Technical Reports Server (NTRS)

Hornstein, Rhoda S.; Willoughby, John K.

1992-01-01

Successful accomplishment of the objectives of many long-range future missions in areas such as space systems, land-use planning, and natural resource management requires significant technology developments. This paper describes the development of a decision-support data-derived tool called MisTec for helping strategic planners to determine technology development alternatives and to synchronize the technology development schedules with the performance schedules of future long-term missions. Special attention is given to the operations, concept, design, and functional capabilities of the MisTec. The MisTec was initially designed for manned Mars mission, but can be adapted to support other high-technology long-range strategic planning situations, making it possible for a mission analyst, planner, or manager to describe a mission scenario, determine the technology alternatives for making the mission achievable, and to plan the R&D activity necessary to achieve the required technology advances.

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.

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.

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

PubMed

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

2013-08-01

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

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

PubMed

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

2012-10-01

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

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

PubMed

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

2015-01-01

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

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

Cost-effectiveness and value of information analysis of nutritional support for preventing pressure ulcers in high-risk patients: implement now, research later.

PubMed

Tuffaha, Haitham W; Roberts, Shelley; Chaboyer, Wendy; Gordon, Louisa G; Scuffham, Paul A

2015-04-01

Pressure ulcers are a major cause of mortality, morbidity, and increased healthcare cost. Nutritional support may reduce the incidence of pressure ulcers in hospitalised patients who are at risk of pressure ulcer and malnutrition. To evaluate the cost-effectiveness of nutritional support in preventing pressure ulcers in high-risk hospitalised patients, and to assess the value of further research to inform the decision to implement this intervention using value of information analysis (VOI). The analysis was from the perspective of Queensland Health, Australia using a decision model with evidence derived from a systematic review and meta-analysis. Resources were valued using 2014 prices and the time horizon of the analysis was one year. Monte Carlo simulation was used to estimate net monetary benefits (NB) and to calculate VOI measures. Compared with standard hospital diet, nutritional support was cost saving at AU$425 per patient, and more effective with an average 0.005 quality-adjusted life years (QALY) gained. At a willingness-to-pay of AU$50,000 per QALY, the incremental NB was AU$675 per patient, with a probability of 87 % that nutritional support is cost-effective. The expected value of perfect information was AU$5 million and the expected value of perfect parameter information was highest for the relative risk of developing a pressure ulcer at AU$2.5 million. For a future trial investigating the relative effectiveness of the interventions, the expected net benefit of research would be maximised at AU$100,000 with 1,200 patients in each arm if nutritional support was perfectly implemented. The opportunity cost of withholding the decision to implement the intervention until the results of the future study are available would be AU$14 million. Nutritional support is cost-effective in preventing pressure ulcers in high-risk hospitalised patients compared with standard diet. Future research to reduce decision uncertainty is worthwhile; however, given the opportunity losses associated with delaying the implementation, "implement and research" is the approach recommended for this intervention.

Balancing the benefits and costs of antibiotic drugs: the TREAT model.

PubMed

Leibovici, L; Paul, M; Andreassen, S

2010-12-01

TREAT is a computerized decision support system aimed at improving empirical antibiotic treatment of inpatients with suspected bacterial infections. It contains a model that balances, for each antibiotic choice (including 'no antibiotics'), expected benefit and expected costs. The main benefit afforded by appropriate, empirical, early antibiotic treatment in moderate to severe infections is a better chance of survival. Each antibiotic drug was consigned three cost components: cost of the drug and administration; cost of side effects; and costs of future resistance. 'No treatment' incurs no costs. The model worked well for decision support. Its analysis showed, yet again, that for moderate to severe infections, a model that does not include costs of resistance to future patients will always return maximum antibiotic treatment. Two major moral decisions are hidden in the model: how to take into account the limited life-expectancy and limited quality of life of old or very sick patients; and how to assign a value for a life-year of a future, unnamed patient vs. the present, individual patient. © 2010 The Authors. Clinical Microbiology and Infection © 2010 European Society of Clinical Microbiology and Infectious Diseases.

An Exploration of Closure as a Factor Influencing Group Member Satisfaction: Implications for Applications of Group Support Technology in Education.

ERIC Educational Resources Information Center

Small, Ruth V.; Venkatesh, Murali

Research that identifies factors that facilitate information processing and enhance performance without reducing group confidence and decision satisfaction may influence future development of groupwork systems. This paper contains a review of the literature on cognitive and motivational issues in both group decision-making and learning contexts…

Negotiating the Digital Library: Document Delivery.

ERIC Educational Resources Information Center

Jacobs, Neil; Morris, Anne

1999-01-01

The eLib-funded FIDDO (Focused Investigation of Document Delivery Options) project provides library managers/others with information to support policy decisions. Senior libraries were interviewed about the future of document delivery and interviews were analyzed with the support of NUD*IST (Nonnumerical Unstructured Data by Indexing, Searching and…

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.

Effect of descriptive information and experience on automation reliance.

PubMed

Yuviler-Gavish, Nirit; Gopher, Daniel

2011-06-01

The present research addresses the issue of reliance on decision support systems for the long-term (DSSLT), which help users develop decision-making strategies and long-term planning. It is argued that providing information about a system's future performance in an experiential manner, as compared with a descriptive manner, encourages users to increase their reliance level. Establishing appropriate reliance on DSSLT is contingent on the system developer's ability to provide users with information about the system's future performance. A sequence of three studies contrasts the effect on automation reliance of providing descriptive information versus experience for DSSLT with two different positive expected values of recommendations. Study I demonstrated that when automation reliance was determined solely on the basis of description, it was relatively low, but it increased significantly when a decision was made after experience with 50 training simulations. Participants were able to learn to increase their automation reliance levels when they encountered the same type of recommendation again. Study 2 showed that the absence of preliminary descriptive information did not affect the automation reliance levels obtained after experience. Study 3 demonstrated that participants were able to generalize their learning about increasing reliance levels to new recommendations. Using experience rather than description to give users information about future performance in DSSLT can help increase automation reliance levels. Implications for designing DSSLT and decision support systems in general are discussed.

Web-based Traffic Noise Control Support System for Sustainable Transportation

NASA Astrophysics Data System (ADS)

Fan, Lisa; Dai, Liming; Li, Anson

Traffic noise is considered as one of the major pollutions that will affect our communities in the future. This paper presents a framework of web-based traffic noise control support system (WTNCSS) for a sustainable transportation. WTNCSS is to provide the decision makers, engineers and publics a platform to efficiently access the information, and effectively making decisions related to traffic control. The system is based on a Service Oriented Architecture (SOA) which takes the advantages of the convenience of World Wide Web system with the data format of XML. The whole system is divided into different modules such as the prediction module, ontology-based expert module and dynamic online survey module. Each module of the system provides a distinct information service to the decision support center through the HTTP protocol.

A Flight Deck Decision Support Tool for Autonomous Airborne Operations

NASA Technical Reports Server (NTRS)

Ballin, Mark G.; Sharma, Vivek; Vivona, Robert A.; Johnson, Edward J.; Ramiscal, Ermin

2002-01-01

NASA is developing a flight deck decision support tool to support research into autonomous operations in a future distributed air/ground traffic management environment. This interactive real-time decision aid, referred to as the Autonomous Operations Planner (AOP), will enable the flight crew to plan autonomously in the presence of dense traffic and complex flight management constraints. In assisting the flight crew, the AOP accounts for traffic flow management and airspace constraints, schedule requirements, weather hazards, aircraft operational limits, and crew or airline flight-planning goals. This paper describes the AOP and presents an overview of functional and implementation design considerations required for its development. Required AOP functionality is described, its application in autonomous operations research is discussed, and a prototype software architecture for the AOP is presented.

Examination of the consumer decision process for residential energy use

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

Dinan, T.M.

1987-01-01

Numerous studies have examined the factors that influence consumers' energy-using behavior. A comprehensive review of these studies was conducted in which articles from different research disciplines (economics, sociology, psychology, and marketing) were examined. This paper provides a discussion of a subset of these studies, and based on findings of the review, offers recommendations for future research. The literature review revealed a need to develop an integrated framework for examining consumers' energy-using behavior. This integrated framework should simultaneously consider both price and nonprice related factors which underlie energy use decisions. It should also examined the process by which decisions are made,more » as well as the factors that affect the decision outcome. This paper provides a suggested integrated framework for future research and discusses the data required to support this framework. 23 references, 3 figures.« less

Multiple Criteria Decision Analysis for Health Care Decision Making--Emerging Good Practices: Report 2 of the ISPOR MCDA Emerging Good Practices Task Force.

PubMed

Marsh, Kevin; IJzerman, Maarten; Thokala, Praveen; Baltussen, Rob; Boysen, Meindert; Kaló, Zoltán; Lönngren, Thomas; Mussen, Filip; Peacock, Stuart; Watkins, John; Devlin, Nancy

2016-01-01

Health care decisions are complex and involve confronting trade-offs between multiple, often conflicting objectives. Using structured, explicit approaches to decisions involving multiple criteria can improve the quality of decision making. A set of techniques, known under the collective heading, multiple criteria decision analysis (MCDA), are useful for this purpose. In 2014, ISPOR established an Emerging Good Practices Task Force. The task force's first report defined MCDA, provided examples of its use in health care, described the key steps, and provided an overview of the principal methods of MCDA. This second task force report provides emerging good-practice guidance on the implementation of MCDA to support health care decisions. The report includes: a checklist to support the design, implementation and review of an MCDA; guidance to support the implementation of the checklist; the order in which the steps should be implemented; illustrates how to incorporate budget constraints into an MCDA; provides an overview of the skills and resources, including available software, required to implement MCDA; and future research directions. Copyright © 2016 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. 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.

The next generation of command post computing

NASA Astrophysics Data System (ADS)

Arnold, Ross D.; Lieb, Aaron J.; Samuel, Jason M.; Burger, Mitchell A.

2015-05-01

The future of command post computing demands an innovative new solution to address a variety of challenging operational needs. The Command Post of the Future is the Army's primary command and control decision support system, providing situational awareness and collaborative tools for tactical decision making, planning, and execution management from Corps to Company level. However, as the U.S. Army moves towards a lightweight, fully networked battalion, disconnected operations, thin client architecture and mobile computing become increasingly essential. The Command Post of the Future is not designed to support these challenges in the coming decade. Therefore, research into a hybrid blend of technologies is in progress to address these issues. This research focuses on a new command and control system utilizing the rich collaboration framework afforded by Command Post of the Future coupled with a new user interface consisting of a variety of innovative workspace designs. This new system is called Tactical Applications. This paper details a brief history of command post computing, presents the challenges facing the modern Army, and explores the concepts under consideration for Tactical Applications that meet these challenges in a variety of innovative ways.

Guidance on Data Quality Assessment for Life Cycle Inventory Data

EPA Science Inventory

Data quality within Life Cycle Assessment (LCA) is a significant issue for the future support and development of LCA as a decision support tool and its wider adoption within industry. In response to current data quality standards such as the ISO 14000 series, various entities wit...

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...

"Choose the Future Wisely": Supporting Better Ethics through Critical Thinking

ERIC Educational Resources Information Center

Meisel, Steven I.; Fearon, David S.

2006-01-01

Most people learn and internalize their sense of ethical behavior many years before they assume positions of organizational responsibility. Continued training in ethics helps to develop new understanding and supports ethical behavior. It is also useful to increase the cognitive skills of executives making decisions affecting firms and…

Coping strategies and immune neglect in affective forecasting: Direct evidence and key moderators

PubMed Central

Hoerger, Michael

2012-01-01

Affective forecasting skills have important implications for decision making. However, recent research suggests that immune neglect – the tendency to overlook coping strategies that reduce future distress – may lead to affective forecasting problems. Prior evidence for immune neglect has been indirect. More direct evidence and a deeper understanding of immune neglect are vital to informing the design of future decision-support interventions. In the current study, young adults (N = 325) supplied predicted, actual, and recollected reactions to an emotionally-evocative interpersonal event, Valentine’s Day. Based on participants’ qualitative descriptions of the holiday, a team of raters reliably coded the effectiveness of their coping strategies. Supporting the immune neglect hypothesis, participants overlooked the powerful role of coping strategies when predicting their emotional reactions. Immune neglect was present not only for those experiencing the holiday negatively (non-daters) but also for those experiencing it positively (daters), suggesting that the bias may be more robust than originally theorized. Immune neglect was greater for immediate emotional reactions than more enduring reactions. Further, immune neglect was conspicuously absent from recollected emotional reactions. Implications for decision-support interventions are discussed. PMID:22375161

Decision making and cancer.

PubMed

Reyna, Valerie F; Nelson, Wendy L; Han, Paul K; Pignone, Michael P

2015-01-01

We review decision making along the cancer continuum in the contemporary context of informed and shared decision making in which patients are encouraged to take a more active role in their health care. We discuss challenges to achieving informed and shared decision making, including cognitive limitations and emotional factors, but argue that understanding the mechanisms of decision making offers hope for improving decision support. Theoretical approaches to decision making that explain cognition, emotion, and their interaction are described, including classical psychophysical approaches, dual-process approaches that focus on conflicts between emotion versus cognition (or reason), and modern integrative approaches such as fuzzy-trace theory. In contrast to the earlier emphasis on rote use of numerical detail, modern approaches emphasize understanding the bottom-line gist of options (which encompasses emotion and other influences on meaning) and retrieving relevant social and moral values to apply to those gist representations. Finally, research on interventions to support better decision making in clinical settings is reviewed, drawing out implications for future research on decision making and cancer. PsycINFO Database Record (c) 2015 APA, all rights reserved.

Questioning the Relevance of Model-Based Probability Statements on Extreme Weather and Future Climate

NASA Astrophysics Data System (ADS)

Smith, L. A.

2007-12-01

We question the relevance of climate-model based Bayesian (or other) probability statements for decision support and impact assessment on spatial scales less than continental and temporal averages less than seasonal. Scientific assessment of higher resolution space and time scale information is urgently needed, given the commercial availability of "products" at high spatiotemporal resolution, their provision by nationally funded agencies for use both in industry decision making and governmental policy support, and their presentation to the public as matters of fact. Specifically we seek to establish necessary conditions for probability forecasts (projections conditioned on a model structure and a forcing scenario) to be taken seriously as reflecting the probability of future real-world events. We illustrate how risk management can profitably employ imperfect models of complicated chaotic systems, following NASA's study of near-Earth PHOs (Potentially Hazardous Objects). Our climate models will never be perfect, nevertheless the space and time scales on which they provide decision- support relevant information is expected to improve with the models themselves. Our aim is to establish a set of baselines of internal consistency; these are merely necessary conditions (not sufficient conditions) that physics based state-of-the-art models are expected to pass if their output is to be judged decision support relevant. Probabilistic Similarity is proposed as one goal which can be obtained even when our models are not empirically adequate. In short, probabilistic similarity requires that, given inputs similar to today's empirical observations and observational uncertainties, we expect future models to produce similar forecast distributions. Expert opinion on the space and time scales on which we might reasonably expect probabilistic similarity may prove of much greater utility than expert elicitation of uncertainty in parameter values in a model that is not empirically adequate; this may help to explain the reluctance of experts to provide information on "parameter uncertainty." Probability statements about the real world are always conditioned on some information set; they may well be conditioned on "False" making them of little value to a rational decision maker. In other instances, they may be conditioned on physical assumptions not held by any of the modellers whose model output is being cast as a probability distribution. Our models will improve a great deal in the next decades, and our insight into the likely climate fifty years hence will improve: maintaining the credibility of the science and the coherence of science based decision support, as our models improve, require a clear statement of our current limitations. What evidence do we have that today's state-of-the-art models provide decision-relevant probability forecasts? What space and time scales do we currently have quantitative, decision-relevant information on for 2050? 2080?

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

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.

Towards the ecotourism: a decision support model for the assessment of sustainability of mountain huts in the Alps.

PubMed

Stubelj Ars, Mojca; Bohanec, Marko

2010-12-01

This paper studies mountain hut infrastructure in the Alps as an important element of ecotourism in the Alpine region. To improve the decision-making process regarding the implementation of future infrastructure and improvement of existing infrastructure in the vulnerable natural environment of mountain ecosystems, a new decision support model has been developed. The methodology is based on qualitative multi-attribute modelling supported by the DEXi software. The integrated rule-based model is hierarchical and consists of two submodels that cover the infrastructure of the mountain huts and that of the huts' surroundings. The final goal for the designed tool is to help minimize the ecological footprint of tourists in environmentally sensitive and undeveloped mountain areas and contribute to mountain ecotourism. The model has been tested in the case study of four mountain huts in Triglav National Park in Slovenia. Study findings provide a new empirical approach to evaluating existing mountain infrastructure and predicting improvements for the future. The assessment results are of particular interest for decision makers in protected areas, such as Alpine national parks managers and administrators. In a way, this model proposes an approach to the management assessment of mountain huts with the main aim of increasing the quality of life of mountain environment visitors as well as the satisfaction of tourists who may eventually become ecotourists. Copyright © 2010 Elsevier Ltd. All rights reserved.

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

PubMed

Blind, M W; Refsgaard, J C

2007-01-01

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

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.

Decision support system for health care resources allocation

PubMed Central

Sebaa, Abderrazak; Nouicer, Amina; Tari, AbdelKamel; Tarik, Ramtani; Abdellah, Ouhab

2017-01-01

Background A study about healthcare resources can improve decisions regarding the allotment and mobilization of medical resources and to better guide future investment in the health sector. Aim The aim of this work was to design and implement a decision support system to improve medical resources allocation of Bejaia region. Methods To achieve the retrospective cohort study, we integrated existing clinical databases from different Bejaia department health sector institutions (an Algerian department) to collect information about patients from January 2015 through December 2015. Data integration was performed in a data warehouse using the multi-dimensional model and OLAP cube. During implementation, we used Microsoft SQL server 2012 and Microsoft Excel 2010. Results A medical decision support platform was introduced, and was implemented during the planning stages allowing the management of different medical orientations, it provides better apportionment and allotment of medical resources, and ensures that the allocation of health care resources has optimal effects on improving health. Conclusion In this study, we designed and implemented a decision support system which would improve health care in Bejaia department to especially assist in the selection of the optimum location of health center and hospital, the specialty of the health center, the medical equipment and the medical staff. PMID:28848645

Decision support system for health care resources allocation.

PubMed

Sebaa, Abderrazak; Nouicer, Amina; Tari, AbdelKamel; Tarik, Ramtani; Abdellah, Ouhab

2017-06-01

A study about healthcare resources can improve decisions regarding the allotment and mobilization of medical resources and to better guide future investment in the health sector. The aim of this work was to design and implement a decision support system to improve medical resources allocation of Bejaia region. To achieve the retrospective cohort study, we integrated existing clinical databases from different Bejaia department health sector institutions (an Algerian department) to collect information about patients from January 2015 through December 2015. Data integration was performed in a data warehouse using the multi-dimensional model and OLAP cube. During implementation, we used Microsoft SQL server 2012 and Microsoft Excel 2010. A medical decision support platform was introduced, and was implemented during the planning stages allowing the management of different medical orientations, it provides better apportionment and allotment of medical resources, and ensures that the allocation of health care resources has optimal effects on improving health. In this study, we designed and implemented a decision support system which would improve health care in Bejaia department to especially assist in the selection of the optimum location of health center and hospital, the specialty of the health center, the medical equipment and the medical staff.

SMARTe 2008

EPA Science Inventory

Sustainable Management Approaches and Revitalization Tools - electronic (SMARTe), is an open-source, web-based, decision support system for developing and evaluating future reuse scenarios for potentially contaminated land. SMARTe contains resources and analysis tools for all asp...

SMARTe 2011

EPA Science Inventory

Sustainable Management Approaches and Revitalization Tools - electronic (SMARTe), is an open-source, web-based, decisions support system for developing and evaluating future reuse scenarios for potentially contaminated land. SMARTe contains resources and analysis tools for all a...

SMARTE 2007

EPA Science Inventory

Sustainable Management Approaches and Revitalization Tools-electronic (SMARTe), is an open-source, web-based, decision support system for developing and evaluating future reuse scenarios for potentially contaminated land. SMARTe contains guidance and analysis tools for all aspect...

Accommodating complexity and human behaviors in decision analysis.

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

Backus, George A.; Siirola, John Daniel; Schoenwald, David Alan

2007-11-01

This is the final report for a LDRD effort to address human behavior in decision support systems. One sister LDRD effort reports the extension of this work to include actual human choices and additional simulation analyses. Another provides the background for this effort and the programmatic directions for future work. This specific effort considered the feasibility of five aspects of model development required for analysis viability. To avoid the use of classified information, healthcare decisions and the system embedding them became the illustrative example for assessment.

Towards public health decision support: a systematic review of bidirectional communication approaches.

PubMed

Dixon, Brian E; Gamache, Roland E; Grannis, Shaun J

2013-05-01

To summarize the literature describing computer-based interventions aimed at improving bidirectional communication between clinical and public health. A systematic review of English articles using MEDLINE and Google Scholar. Search terms included public health, epidemiology, electronic health records, decision support, expert systems, and decision-making. Only articles that described the communication of information regarding emerging health threats from public health agencies to clinicians or provider organizations were included. Each article was independently reviewed by two authors. Ten peer-reviewed articles highlight a nascent but promising area of research and practice related to alerting clinicians about emerging threats. Current literature suggests that additional research and development in bidirectional communication infrastructure should focus on defining a coherent architecture, improving interoperability, establishing clear governance, and creating usable systems that will effectively deliver targeted, specific information to clinicians in support of patient and population decision-making. Increasingly available clinical information systems make it possible to deliver timely, relevant knowledge to frontline clinicians in support of population health. Future work should focus on developing a flexible, interoperable infrastructure for bidirectional communications capable of integrating public health knowledge into clinical systems and workflows.

A prototype knowledge-based decision support system for industrial waste management. Part 1: The decision support system

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

Boyle, C.A.; Baetz, B.W.

1998-12-31

Although there are a number of expert systems available which are designed to assist in resolving environmental problems, there is still a need for a system which would assist managers in determining waste management options for all types of wastes from one or more industrial plants, giving priority to sustainable use of resources, reuse and recycling. A prototype model was developed to determine the potentials for reuse and recycling of waste materials, to select the treatments needed to recycle waste materials or for treatment before disposal, and to determine potentials for co-treatment of wastes. A knowledge-based decision support system wasmore » then designed using this model. This paper describes the prototype model, the developed knowledge-based decision support system, the input and storage of data within the system and the inference engine developed for the system to determine the treatment options for the wastes. Options for sorting and selecting treatment trains are described, along with a discussion of the limitations of the approach and future developments needed for the system.« less

Modelling and evaluating municipal solid waste management strategies in a mega-city: the case of Ho Chi Minh City.

PubMed

ThiKimOanh, Le; Bloemhof-Ruwaard, Jacqueline M; van Buuren, Joost Cl; van der Vorst, Jack Gaj; Rulkens, Wim H

2015-04-01

Ho Chi Minh City is a large city that will become a mega-city in the near future. The city struggles with a rapidly increasing flow of municipal solid waste and a foreseeable scarcity of land to continue landfilling, the main treatment of municipal solid waste up to now. Therefore, additional municipal solid waste treatment technologies are needed. The objective of this article is to support decision-making towards more sustainable and cost-effective municipal solid waste strategies in developing countries, in particular Vietnam. A quantitative decision support model is developed to optimise the distribution of municipal solid waste from population areas to treatment plants, the treatment technologies and their capacities for the near future given available infrastructure and cost factors. © The Author(s) 2015.

Preserving the Finger Lakes for the Future: A Prototype Decision Support System for Water Resource Management, Open Space, and Agricultural Protection

NASA Technical Reports Server (NTRS)

Brower, Robert

2004-01-01

This report summarizes the activity conducted under NASA Grant NAG13-02059 entitled "Preserving the Finger Lakes for the Future" A Prototype Decision Support System for Water Resources Management, Open Space and Agricultural Protection, for the period of September 26, 2003 to September 25, 2004. The RACNE continues to utilize the services of its affiliate, the Institute for the Application of Geospatial Technology at Cayuga Community College, Inc. (IAGT), for the purposes of this project under its permanent operating agreement with IAGT. IAGT is a 501(c)(3) not-for-profit Corporation created by the RACNE for the purpose of carrying out its programmatic and administrative mission. The "Preserving the Finger Lakes for the Future" project has progressed and evolved as planned, with the continuation or initiation of a number of program facets at programmatic, technical, and inter-agency levels. The project has grown, starting with the well received core concept of the Virtual Management Operations Center (VMOC), to the functional Watershed Virtual Management Operations Center (W-VMOC) prototype, to the more advanced Finger Lakes Decision Support System (FLDSS) prototype, deployed for evaluation and assessment to a wide variety of agencies and organizations in the Finger Lakes region and beyond. This suite of tools offers the advanced, compelling functionality of interactive 3D visualization interfaced with 2D mapping, all accessed via Internet or virtually any kind of distributed computer network.

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.

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.

Improving medical decisions for incapacitated persons: does focusing on "accurate predictions" lead to an inaccurate picture?

PubMed

Kim, Scott Y H

2014-04-01

The Patient Preference Predictor (PPP) proposal places a high priority on the accuracy of predicting patients' preferences and finds the performance of surrogates inadequate. However, the quest to develop a highly accurate, individualized statistical model has significant obstacles. First, it will be impossible to validate the PPP beyond the limit imposed by 60%-80% reliability of people's preferences for future medical decisions--a figure no better than the known average accuracy of surrogates. Second, evidence supports the view that a sizable minority of persons may not even have preferences to predict. Third, many, perhaps most, people express their autonomy just as much by entrusting their loved ones to exercise their judgment than by desiring to specifically control future decisions. Surrogate decision making faces none of these issues and, in fact, it may be more efficient, accurate, and authoritative than is commonly assumed.

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...

Biomedical wellness challenges and opportunities

NASA Astrophysics Data System (ADS)

Tangney, John F.

2012-06-01

The mission of ONR's Human and Bioengineered Systems Division is to direct, plan, foster, and encourage Science and Technology in cognitive science, computational neuroscience, bioscience and bio-mimetic technology, social/organizational science, training, human factors, and decision making as related to future Naval needs. This paper highlights current programs that contribute to future biomedical wellness needs in context of humanitarian assistance and disaster relief. ONR supports fundamental research and related technology demonstrations in several related areas, including biometrics and human activity recognition; cognitive sciences; computational neurosciences and bio-robotics; human factors, organizational design and decision research; social, cultural and behavioral modeling; and training, education and human performance. In context of a possible future with automated casualty evacuation, elements of current science and technology programs are illustrated.

Reviewing model application to support animal health decision making.

PubMed

Singer, Alexander; Salman, Mo; Thulke, Hans-Hermann

2011-04-01

Animal health is of societal importance as it affects human welfare, and anthropogenic interests shape decision making to assure animal health. Scientific advice to support decision making is manifold. Modelling, as one piece of the scientific toolbox, is appreciated for its ability to describe and structure data, to give insight in complex processes and to predict future outcome. In this paper we study the application of scientific modelling to support practical animal health decisions. We reviewed the 35 animal health related scientific opinions adopted by the Animal Health and Animal Welfare Panel of the European Food Safety Authority (EFSA). Thirteen of these documents were based on the application of models. The review took two viewpoints, the decision maker's need and the modeller's approach. In the reviewed material three types of modelling questions were addressed by four specific model types. The correspondence between tasks and models underpinned the importance of the modelling question in triggering the modelling approach. End point quantifications were the dominating request from decision makers, implying that prediction of risk is a major need. However, due to knowledge gaps corresponding modelling studies often shed away from providing exact numbers. Instead, comparative scenario analyses were performed, furthering the understanding of the decision problem and effects of alternative management options. In conclusion, the most adequate scientific support for decision making - including available modelling capacity - might be expected if the required advice is clearly stated. Copyright © 2011 Elsevier B.V. All rights reserved.

The Future of the Office of the Future.

DTIC Science & Technology

1980-01-01

OFFICE HOWARD L. MORCAN d -%1-@32 p THE FUTURE OF THE OFFICE OF THE FUTURE Howard L. Morgan 80-01-02 - i : Department of Decision Sciences The Wharton...School University of Pennsylvania Philadelphia, PA 19104 This paper will be presented at the Office Automation Conference to be held March 3-5, 1980...in Atlanta, Georgia. Research supported in part by the Office of Naval Research under Contract N00014-75-C-0462. 80 3 13 00 ., , !1 COjNzTY CL

Future Water Management in the South Platte River Basin: Impacts of Hydraulic Fracturing, Population, Agriculture, and Climate Change in a Semi-Arid Region.

NASA Astrophysics Data System (ADS)

Walker, E. L.; Hogue, T. S.; Anderson, A. M.; Read, L.

2015-12-01

In semi-arid basins across the world, the gap between water supply and demand is growing due to climate change, population growth, and shifts in agriculture and unconventional energy development. Water conservation efforts among residential and industrial water users, recycling and reuse techniques and innovative regulatory frameworks for water management strive to mitigate this gap, however, the extent of these strategies are often difficult to quantify and not included in modeling water allocations. Decision support systems (DSS) are purposeful for supporting water managers in making informed decisions when competing demands create the need to optimize water allocation between sectors. One region of particular interest is the semi-arid region of the South Platte River basin in northeastern Colorado, where anthropogenic and climatic effects are expected to increase the gap between water supply and demand in the near future. Specifically, water use in the South Platte is impacted by several high-intensity activities, including unconventional energy development, i.e. hydraulic fracturing, and large withdrawals for agriculture; these demands are in addition to a projected population increase of 100% by 2050. The current work describes the development of a DSS for the South Platte River basin, using the Water Evaluation and Planning system software (WEAP) to explore scenarios of how variation in future water use in the energy, agriculture, and municipal sectors will impact water allocation decisions. Detailed data collected on oil and gas water use in the Niobrara shale play will be utilized to predict future sector use. We also employ downscaled climate projections for the region to quantify the potential range of water availability in the basin under each scenario, and observe whether or not, and to what extent, climate may impact management decisions at the basin level.

"I've never been a yes person": Decision-making participation and self-conceptualization after severe traumatic brain injury.

PubMed

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

2017-11-01

Although adults who sustain a severe traumatic brain injury (TBI) require support to make decisions in their lives, little is known about their experience of this process. The aim of this study was to explore how participation in decision making contributes to self-conceptualization in adults with severe TBI. We used constructivist grounded theory methods. Data included 20 in-depth interviews with adults with severe TBI. Through a process of constant comparison, analysis involved open and focused coding until clear categories emerged and data saturation was achieved. Self-conceptualization emerged as a complex and multifaceted process, as individuals with TBI aimed to reestablish a sense of autonomy. We describe a recursive relationship in which decision-making participation assists the dynamic construction of self, and self-concept contributes to the experience of making decisions. The role of an individual's social support network in acting as a bridge between participation and self-conceptualization is presented. Findings emphasize that contributing to decisions about one's own goals across a range of life areas can reinforce a positive self-concept. It is vital that supporters understand that participation in decision making provides a pathway to conceptualizing self and aim to maximize the person's participation in the decision-making process. Implications for Rehabilitation Previous research has identified that the experience of sustaining TBI has a significant impact on a person's conceptualization of self. This study identified that decision-making experiences play an important role in the ongoing process of self-conceptualization after injury. Decision-making experiences can reinforce a person's self-concept or lead them to revise (positively or negatively) their sense of self. By maximizing the person's decision-making participation, those around them can support them to develop positive self-attributes and contribute to shaping their future goals.

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.

A Review and Analysis of Remote Sensing Capability for Air Quality Measurements as a Potential Decision Support Tool Conducted by the NASA DEVELOP Program

NASA Technical Reports Server (NTRS)

Ross, A.; Richards, A.; Keith, K.; Frew, C.; Boseck, J.; Sutton, S.; Watts, C.; Rickman, D.

2007-01-01

This project focused on a comprehensive utilization of air quality model products as decision support tools (DST) needed for public health applications. A review of past and future air quality measurement methods and their uncertainty, along with the relationship of air quality to national and global public health, is vital. This project described current and future NASA satellite remote sensing and ground sensing capabilities and the potential for using these sensors to enhance the prediction, prevention, and control of public health effects that result from poor air quality. The qualitative uncertainty of current satellite remotely sensed air quality, the ground-based remotely sensed air quality, the air quality/public health model, and the decision making process is evaluated in this study. Current peer-reviewed literature suggests that remotely sensed air quality parameters correlate well with ground-based sensor data. A satellite remote-sensed and ground-sensed data complement is needed to enhance the models/tools used by policy makers for the protection of national and global public health communities

Working with South Florida County Planners to Understand and Mitigate Uncertain Climate Risks

NASA Astrophysics Data System (ADS)

Knopman, D.; Groves, D. G.; Berg, N.

2017-12-01

This talk describes a novel approach for evaluating climate change vulnerabilities and adaptations in Southeast Florida to support long-term resilience planning. The work is unique in that it combines state-of-the-art hydrologic modeling with the region's long-term land use and transportation plans to better assess the future climate vulnerability and adaptations for the region. Addressing uncertainty in future projections is handled through the use of decisionmaking under deep uncertainty methods. Study findings, including analysis of key tradeoffs, were conveyed to the region's stakeholders through an innovative web-based decision support tool. This project leverages existing groundwater models spanning Miami-Dade and Broward Counties developed by the USGS, along with projections of land use and asset valuations for Miami-Dade and Broward County planning agencies. Model simulations are executed on virtual cloud-based servers for a highly scalable and parallelized platform. Groundwater elevations and the saltwater-freshwater interface and intrusion zones from the integrated modeling framework are analyzed under a wide range of long-term climate futures, including projected sea level rise and precipitation changes. The hydrologic hazards are then combined with current and future land use and asset valuation projections to estimate assets at risk across the range of futures. Lastly, an interactive decision support tool highlights the areas with critical climate vulnerabilities; distinguishes between vulnerability due to new development, increased climate hazards, or both; and provides guidance for adaptive management and development practices and decisionmaking in Southeast Florida.

Choice-Supportive Misremembering: A New Taxonomy and Review

PubMed Central

Lind, Martina; Visentini, Mimì; Mäntylä, Timo; Del Missier, Fabio

2017-01-01

Although the literature on the influence of memory on decisions is well developed, research on the effects of decision making on memory is rather sparse and scattered. Choice-supportive misremembering (i.e., misremembering choice-related information that boosts the chosen option and/or demotes the foregone options) has been observed in several studies and has the potential to affect future choices. Nonetheless, no attempt has been made to review the relevant literature, categorize the different types of choice-supportive misremembering observed, and critically appraise the existing evidence and proposed explanations. Thus, starting from a new theoretically motivated and empirically grounded taxonomy, we review the current research. Our taxonomy classifies choice-supportive misremembering into four conceptually distinct types: misattribution is when information is attributed to the wrong source, fact distortion when the facts are remembered in a distorted manner, false memory when items that were not part of the original decision scenarios are remembered as presented and, finally, selective forgetting is when information is selectively forgotten. After assessing the impact of various potentially moderating factors, we evaluate the evidence for each type of misremembering and conclude that the support for the phenomenon is solid in relation to misattribution when recognition memory is assessed, but significantly weaker for the other three types, and when other memory tests are used to assess memory. Finally, we review the cognitive and emotional explanations proposed for choice-supportive misremembering in the light of the available evidence and identify the main gaps in the current knowledge and the more promising avenues for future research. PMID:29255436

Episodic future thinking and episodic counterfactual thinking: intersections between memory and decisions.

PubMed

Schacter, Daniel L; Benoit, Roland G; De Brigard, Felipe; Szpunar, Karl K

2015-01-01

This article considers two recent lines of research concerned with the construction of imagined or simulated events that can provide insight into the relationship between memory and decision making. One line of research concerns episodic future thinking, which involves simulating episodes that might occur in one's personal future, and the other concerns episodic counterfactual thinking, which involves simulating episodes that could have happened in one's personal past. We first review neuroimaging studies that have examined the neural underpinnings of episodic future thinking and episodic counterfactual thinking. We argue that these studies have revealed that the two forms of episodic simulation engage a common core network including medial parietal, prefrontal, and temporal regions that also supports episodic memory. We also note that neuroimaging studies have documented neural differences between episodic future thinking and episodic counterfactual thinking, including differences in hippocampal responses. We next consider behavioral studies that have delineated both similarities and differences between the two kinds of episodic simulation. The evidence indicates that episodic future and counterfactual thinking are characterized by similarly reduced levels of specific detail compared with episodic memory, but that the effects of repeatedly imagining a possible experience have sharply contrasting effects on the perceived plausibility of those events during episodic future thinking versus episodic counterfactual thinking. Finally, we conclude by discussing the functional consequences of future and counterfactual simulations for decisions. Copyright © 2013 Elsevier Inc. All rights reserved.

Episodic future thinking and episodic counterfactual thinking: Intersections between memory and decisions

PubMed Central

Schacter, Daniel L.; Benoit, Roland G.; De Brigard, Felipe; Szpunar, Karl K.

2014-01-01

This article considers two recent lines of research concerned with the construction of imagined or simulated events that can provide insight into the relationship between memory and decision making. One line of research concerns episodic future thinking, which involves simulating episodes that might occur in one’s personal future, and the other concerns episodic counterfactual thinking, which involves simulating episodes that could have happened in one’s personal past. We first review neuroimaging studies that have examined the neural underpinnings of episodic future thinking and episodic counterfactual thinking. We argue that these studies have revealed that the two forms of episodic simulation engage a common core network including medial parietal, prefrontal, and temporal regions that also supports episodic memory. We also note that neuroimaging studies have documented neural differences between episodic future thinking and episodic counterfactual thinking, including differences in hippocampal responses. We next consider behavioral studies that have delineated both similarities and differences between the two kinds of episodic simulation. The evidence indicates that episodic future and counterfactual thinking are characterized by similarly reduced levels of specific detail compared with episodic memory, but that the effects of repeatedly imagining a possible experience have sharply contrasting effects on the perceived plausibility of those events during episodic future thinking versus episodic counterfactual thinking. Finally, we conclude by discussing the functional consequences of future and counterfactual simulations for decisions. PMID:24373942

"Many miles to go …": a systematic review of the implementation of patient decision support interventions into routine clinical practice.

PubMed

Elwyn, Glyn; Scholl, Isabelle; Tietbohl, Caroline; Mann, Mala; Edwards, Adrian G K; Clay, Catharine; Légaré, France; van der Weijden, Trudy; Lewis, Carmen L; Wexler, Richard M; Frosch, Dominick L

2013-01-01

Two decades of research has established the positive effect of using patient-targeted decision support interventions: patients gain knowledge, greater understanding of probabilities and increased confidence in decisions. Yet, despite their efficacy, the effectiveness of these decision support interventions in routine practice has yet to be established; widespread adoption has not occurred. The aim of this review was to search for and analyze the findings of published peer-reviewed studies that investigated the success levels of strategies or methods where attempts were made to implement patient-targeted decision support interventions into routine clinical settings. An electronic search strategy was devised and adapted for the following databases: ASSIA, CINAHL, Embase, HMIC, Medline, Medline-in-process, OpenSIGLE, PsycINFO, Scopus, Social Services Abstracts, and the Web of Science. In addition, we used snowballing techniques. Studies were included after dual independent assessment. After assessment, 5322 abstracts yielded 51 articles for consideration. After examining full-texts, 17 studies were included and subjected to data extraction. The approach used in all studies was one where clinicians and their staff used a referral model, asking eligible patients to use decision support. The results point to significant challenges to the implementation of patient decision support using this model, including indifference on the part of health care professionals. This indifference stemmed from a reported lack of confidence in the content of decision support interventions and concern about disruption to established workflows, ultimately contributing to organizational inertia regarding their adoption. It seems too early to make firm recommendations about how best to implement patient decision support into routine practice because approaches that use a 'referral model' consistently report difficulties. We sense that the underlying issues that militate against the use of patient decision support and, more generally, limit the adoption of shared decision making, are under-investigated and under-specified. Future reports from implementation studies could be improved by following guidelines, for example the SQUIRE proposals, and by adopting methods that would be able to go beyond the 'barriers' and 'facilitators' approach to understand more about the nature of professional and organizational resistance to these tools. The lack of incentives that reward the use of these interventions needs to be considered as a significant impediment.

“Many miles to go …”: a systematic review of the implementation of patient decision support interventions into routine clinical practice

PubMed Central

2013-01-01

Background Two decades of research has established the positive effect of using patient-targeted decision support interventions: patients gain knowledge, greater understanding of probabilities and increased confidence in decisions. Yet, despite their efficacy, the effectiveness of these decision support interventions in routine practice has yet to be established; widespread adoption has not occurred. The aim of this review was to search for and analyze the findings of published peer-reviewed studies that investigated the success levels of strategies or methods where attempts were made to implement patient-targeted decision support interventions into routine clinical settings. Methods An electronic search strategy was devised and adapted for the following databases: ASSIA, CINAHL, Embase, HMIC, Medline, Medline-in-process, OpenSIGLE, PsycINFO, Scopus, Social Services Abstracts, and the Web of Science. In addition, we used snowballing techniques. Studies were included after dual independent assessment. Results After assessment, 5322 abstracts yielded 51 articles for consideration. After examining full-texts, 17 studies were included and subjected to data extraction. The approach used in all studies was one where clinicians and their staff used a referral model, asking eligible patients to use decision support. The results point to significant challenges to the implementation of patient decision support using this model, including indifference on the part of health care professionals. This indifference stemmed from a reported lack of confidence in the content of decision support interventions and concern about disruption to established workflows, ultimately contributing to organizational inertia regarding their adoption. Conclusions It seems too early to make firm recommendations about how best to implement patient decision support into routine practice because approaches that use a ‘referral model’ consistently report difficulties. We sense that the underlying issues that militate against the use of patient decision support and, more generally, limit the adoption of shared decision making, are under-investigated and under-specified. Future reports from implementation studies could be improved by following guidelines, for example the SQUIRE proposals, and by adopting methods that would be able to go beyond the ‘barriers’ and ‘facilitators’ approach to understand more about the nature of professional and organizational resistance to these tools. The lack of incentives that reward the use of these interventions needs to be considered as a significant impediment. PMID:24625083

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. .

Uncertainty management, spatial and temporal reasoning, and validation of intelligent environmental decision support systems

USGS Publications Warehouse

Sànchez-Marrè, Miquel; Gilbert, Karina; Sojda, Rick S.; Steyer, Jean Philippe; Struss, Peter; Rodríguez-Roda, Ignasi; Voinov, A.A.; Jakeman, A.J.; Rizzoli, A.E.

2006-01-01

There are inherent open problems arising when developing and running Intelligent Environmental Decision Support Systems (IEDSS). During daily operation of IEDSS several open challenge problems appear. The uncertainty of data being processed is intrinsic to the environmental system, which is being monitored by several on-line sensors and off-line data. Thus, anomalous data values at data gathering level or even uncertain reasoning process at later levels such as in diagnosis or decision support or planning can lead the environmental process to unsafe critical operation states. At diagnosis level or even at decision support level or planning level, spatial reasoning or temporal reasoning or both aspects can influence the reasoning processes undertaken by the IEDSS. Most of Environmental systems must take into account the spatial relationships between the environmental goal area and the nearby environmental areas and the temporal relationships between the current state and the past states of the environmental system to state accurate and reliable assertions to be used within the diagnosis process or decision support process or planning process. Finally, a related issue is a crucial point: are really reliable and safe the decisions proposed by the IEDSS? Are we sure about the goodness and performance of proposed solutions? How can we ensure a correct evaluation of the IEDSS? Main goal of this paper is to analyse these four issues, review some possible approaches and techniques to cope with them, and study new trends for future research within the IEDSS field.

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.

Preliminary Work Domain Analysis for Human Extravehicular Activity

NASA Technical Reports Server (NTRS)

McGuire, Kerry; Miller, Matthew; Feigh, Karen

2015-01-01

A work domain analysis (WDA) of human extravehicular activity (EVA) is presented in this study. A formative methodology such as Cognitive Work Analysis (CWA) offers a new perspective to the knowledge gained from the past 50 years of living and working in space for the development of future EVA support systems. EVA is a vital component of human spaceflight and provides a case study example of applying a work domain analysis (WDA) to a complex sociotechnical system. The WDA presented here illustrates how the physical characteristics of the environment, hardware, and life support systems of the domain guide the potential avenues and functional needs of future EVA decision support system development.

Analysis of an Asynchronous Online Discussion as a Supportive Model for Peer Collaboration and Reflection in Teacher Education

ERIC Educational Resources Information Center

Plešec Gasparic, Romina; Pecar, Mojca

2016-01-01

Professional development of future teachers is based on connecting theory and practice with the aim of supporting and developing critical, independent, responsible decision-making and active teaching. With this aim we designed a blended learning environment with an asynchronous online discussion, enabling collaboration and reflection even when…

Social Support as a Neglected E-Learning Motivator Affecting Trainee's Decisions of Continuous Intentions of Usage

ERIC Educational Resources Information Center

Weng, Cathy; Tsai, Chin-Chung; Weng, Apollo

2015-01-01

Drawing from the social influence theory and acknowledging that the others' support within the work context affects employees' learning, values, and behaviours, an alternative framework was proposed to explain employees' learning satisfaction and future intention to participate in e-training programs in the current study. 578 survey data collected…

SARDA: An Integrated Concept for Airport Surface Operations Management

NASA Technical Reports Server (NTRS)

Gupta, Gautam; Hoang, Ty; Jung, Yoon Chul

2013-01-01

The Spot and Runway Departure Advisor (SARDA) is an integrated decision support tool for airlines and air traffic control tower enabling surface collaborative decision making (CDM) and departure metering in order to enhance efficiency of surface operations at congested airports. The presentation describes the concept and architecture of the SARDA as a CDM tool, and the results from a human-in-the-loop simulation of the tool conducted in 2012 at the FutureFlight Central, the tower simulation facility. Also, presented is the current activities and future plan for SARDA development. The presentation was given at the meeting with the FAA senior advisor of the Surface Operations Office.

SMARTE TUTORIAL CD

EPA Science Inventory

SMARTe is a web-based decision support tool intended to help revitalization practitioners find information, perform data analysis, communicate, and evaluate future reuse options for a site or area. A tutorial was developed to help users navigate SMARTe. This tutorial is approxima...

Decision support systems and methods for complex networks

DOEpatents

Huang, Zhenyu [Richland, WA; Wong, Pak Chung [Richland, WA; Ma, Jian [Richland, WA; Mackey, Patrick S [Richland, WA; Chen, Yousu [Richland, WA; Schneider, Kevin P [Seattle, WA

2012-02-28

Methods and systems for automated decision support in analyzing operation data from a complex network. Embodiments of the present invention utilize these algorithms and techniques not only to characterize the past and present condition of a complex network, but also to predict future conditions to help operators anticipate deteriorating and/or problem situations. In particular, embodiments of the present invention characterize network conditions from operation data using a state estimator. Contingency scenarios can then be generated based on those network conditions. For at least a portion of all of the contingency scenarios, risk indices are determined that describe the potential impact of each of those scenarios. Contingency scenarios with risk indices are presented visually as graphical representations in the context of a visual representation of the complex network. Analysis of the historical risk indices based on the graphical representations can then provide trends that allow for prediction of future network conditions.

Human pursuance of equality hinges on mental processes of projecting oneself into the perspectives of others and into future situations.

PubMed

Takesue, Hirofumi; Miyauchi, Carlos Makoto; Sakaiya, Shiro; Fan, Hongwei; Matsuda, Tetsuya; Kato, Junko

2017-07-19

In the pursuance of equality, behavioural scientists disagree about distinct motivators, that is, consideration of others and prospective calculation for oneself. However, accumulating data suggest that these motivators may share a common process in the brain whereby perspectives and events that did not arise in the immediate environment are conceived. To examine this, we devised a game imitating a real decision-making situation regarding redistribution among income classes in a welfare state. The neural correlates of redistributive decisions were examined under contrasting conditions, with and without uncertainty, which affects support for equality in society. The dorsal anterior cingulate cortex (dACC) and the caudate nucleus were activated by equality decisions with uncertainty but by selfless decisions without uncertainty. Activation was also correlated with subjective values. Activation in both the dACC and the caudate nucleus was associated with the attitude to prefer accordance with others, whereas activation in the caudate nucleus reflected that the expected reward involved the prospective calculation of relative income. The neural correlates suggest that consideration of others and prospective calculation for oneself may underlie the support for equality. Projecting oneself into the perspective of others and into prospective future situations may underpin the pursuance of equality.

Exploration-Related Research on the International Space Station: Connecting Science Results to the Design of Future Missions

NASA Technical Reports Server (NTRS)

Rhatigan, Jennifer L.; Robinson, Julie A.; Sawin, Charles F.; Ahlf, Peter R.

2005-01-01

In January, 2004, the US President announced a vision for space exploration, and charged NASA with utilizing the International Space Station (ISS) for research and technology targeted at supporting the US space exploration goals. This paper describes: 1) what we have learned from the first four years of research on ISS relative to the exploration mission, 2) the on-going research being conducted in this regard, 3) our current understanding of the major exploration mission risks that the ISS can be used to address, and 4) current progress in realigning NASA s research portfolio for ISS to support exploration missions. Specifically, we discuss the focus of research on solving the perplexing problems of maintaining human health on long-duration missions, and the development of countermeasures to protect humans from the space environment, enabling long duration exploration missions. The interchange between mission design and research needs is dynamic, where design decisions influence the type of research needed, and results of research influence design decisions. The fundamental challenge to science on ISS is completing experiments that answer key questions in time to shape design decisions for future exploration. In this context, exploration-relevant research must do more than be conceptually connected to design decisions-it must become a part of the mission design process.

LAMDA at TREC CDS track 2015: Clinical Decision Support Track

DTIC Science & Technology

2015-11-20

outperforms all the other vector space models supported by Elasticsearch. MetaMap is the online tool that maps biomedical text to the Metathesaurus, and...cases. The medical knowledge consists of 700,000 biomedical documents supported by the PubMed Central [3] which is online digital database freely...Science Research Program through the National Research Foundation (NRF) of Korea funded by the Ministry of Science, ICT , and Future Planning (MSIP

Robustness for slope stability modelling under deep uncertainty

NASA Astrophysics Data System (ADS)

Almeida, Susana; Holcombe, Liz; Pianosi, Francesca; Wagener, Thorsten

2015-04-01

Landslides can have large negative societal and economic impacts, such as loss of life and damage to infrastructure. However, the ability of slope stability assessment to guide management is limited by high levels of uncertainty in model predictions. Many of these uncertainties cannot be easily quantified, such as those linked to climate change and other future socio-economic conditions, restricting the usefulness of traditional decision analysis tools. Deep uncertainty can be managed more effectively by developing robust, but not necessarily optimal, policies that are expected to perform adequately under a wide range of future conditions. Robust strategies are particularly valuable when the consequences of taking a wrong decision are high as is often the case of when managing natural hazard risks such as landslides. In our work a physically based numerical model of hydrologically induced slope instability (the Combined Hydrology and Stability Model - CHASM) is applied together with robust decision making to evaluate the most important uncertainties (storm events, groundwater conditions, surface cover, slope geometry, material strata and geotechnical properties) affecting slope stability. Specifically, impacts of climate change on long-term slope stability are incorporated, accounting for the deep uncertainty in future climate projections. Our findings highlight the potential of robust decision making to aid decision support for landslide hazard reduction and risk management under conditions of deep uncertainty.

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 need for sustainability and alignment of future support for National Immunization Technical Advisory Groups (NITAGs) in low and middle-income countries.

PubMed

Howard, Natasha; Bell, Sadie; Walls, Helen; Blanchard, Laurence; Brenzel, Logan; Jit, Mark; Mounier-Jack, Sandra

2018-02-22

National Immunisation Technical Advisory Groups (NITAGs) provide independent guidance to health ministries to support evidence-based and nationally relevant immunisation decisions. We examined NITAGs' value, sustainability, and need for support in low and middle-income countries, drawing from a mixed-methods study including 130 global and national-level key informant interviews. NITAGs were particularly valued for providing independent and nationally owned evidence-based decision-making (EBDM), but needed to be integrated within national processes to effectively balance independence and influence. Participants agreed that most NITAGs, being relatively new, would need developmental and strengthening support for at least a decade. While national governments could support NITAG functioning, external support is likely needed for requisite capacity building. This might come from Gavi mechanisms and WHO, but would require alignment among stakeholders to be effective.

Nonstationary decision model for flood risk decision scaling

NASA Astrophysics Data System (ADS)

Spence, Caitlin M.; Brown, Casey M.

2016-11-01

Hydroclimatic stationarity is increasingly questioned as a default assumption in flood risk management (FRM), but successor methods are not yet established. Some potential successors depend on estimates of future flood quantiles, but methods for estimating future design storms are subject to high levels of uncertainty. Here we apply a Nonstationary Decision Model (NDM) to flood risk planning within the decision scaling framework. The NDM combines a nonstationary probability distribution of annual peak flow with optimal selection of flood management alternatives using robustness measures. The NDM incorporates structural and nonstructural FRM interventions and valuation of flows supporting ecosystem services to calculate expected cost of a given FRM strategy. A search for the minimum-cost strategy under incrementally varied representative scenarios extending across the plausible range of flood trend and value of the natural flow regime discovers candidate FRM strategies that are evaluated and compared through a decision scaling analysis (DSA). The DSA selects a management strategy that is optimal or close to optimal across the broadest range of scenarios or across the set of scenarios deemed most likely to occur according to estimates of future flood hazard. We illustrate the decision framework using a stylized example flood management decision based on the Iowa City flood management system, which has experienced recent unprecedented high flow episodes. The DSA indicates a preference for combining infrastructural and nonstructural adaptation measures to manage flood risk and makes clear that options-based approaches cannot be assumed to be "no" or "low regret."

Decision Trajectories in Dementia Care Networks: Decisions and Related Key Events.

PubMed

Groen-van de Ven, Leontine; Smits, Carolien; Oldewarris, Karen; Span, Marijke; Jukema, Jan; Eefsting, Jan; Vernooij-Dassen, Myrra

2017-10-01

This prospective multiperspective study provides insight into the decision trajectories of people with dementia by studying the decisions made and related key events. This study includes three waves of interviews, conducted between July 2010 and July 2012, with 113 purposefully selected respondents (people with beginning to advanced stages of dementia and their informal and professional caregivers) completed in 12 months (285 interviews). Our multilayered qualitative analysis consists of content analysis, timeline methods, and constant comparison. Four decision themes emerged-managing daily life, arranging support, community living, and preparing for the future. Eight key events delineate the decision trajectories of people with dementia. Decisions and key events differ between people with dementia living alone and living with a caregiver. Our study clarifies that decisions relate not only to the disease but to living with the dementia. Individual differences in decision content and sequence may effect shared decision-making and advance care planning.

Influences on Healthy-Eating Decision Making in Latino Adolescent Children of Migrant and Seasonal Agricultural Workers.

PubMed

Kilanowski, Jill F

2016-01-01

Latino children demonstrate high rates of unhealthy weight, and children of Latino migrant and seasonal agricultural workers are heavier than their Latino peers. This one-group, cross-sectional, mixed-methods pilot study explored healthy-eating decision making with 12- to 14-year-olds recruited from a Midwest summer migrant education program. Demographics, decision-making, self-efficacy, and social support survey instruments were used, along with gender-specific focus groups. In the convenience sample, which included 24 participants, students felt varying degrees of uncertainty when choosing healthy foods in social situations, and 67% made poor-quality decisions. Parents offered greater support for healthy eating compared with friends. Qualitative analyses identified three themes: healthy decision making includes fruits, vegetables, and physical activity; mothers have influence over health and healthy decisions; and friends encourage unhealthy food choices. Influences on healthy-eating decision making in Latino adolescent children of migrant and seasonal agricultural workers, which were previously missing from the literature, were identified. Future research includes development of interventions to assist these adolescents with healthy-eating decision making. Copyright © 2016 National Association of Pediatric Nurse Practitioners. Published by Elsevier Inc. All rights reserved.

Demand driven decision support for efficient water resources allocation in irrigated agriculture

NASA Astrophysics Data System (ADS)

Schuetze, Niels; Grießbach, Ulrike Ulrike; Röhm, Patric; Stange, Peter; Wagner, Michael; Seidel, Sabine; Werisch, Stefan; Barfus, Klemens

2014-05-01

Due to climate change, extreme weather conditions, such as longer dry spells in the summer months, may have an increasing impact on the agriculture in Saxony (Eastern Germany). For this reason, and, additionally, declining amounts of rainfall during the growing season the use of irrigation will be more important in future in Eastern Germany. To cope with this higher demand of water, a new decision support framework is developed which focuses on an integrated management of both irrigation water supply and demand. For modeling the regional water demand, local (and site-specific) water demand functions are used which are derived from the optimized agronomic response at farms scale. To account for climate variability the agronomic response is represented by stochastic crop water production functions (SCWPF) which provide the estimated yield subject to the minimum amount of irrigation water. These functions take into account the different soil types, crops and stochastically generated climate scenarios. By applying mathematical interpolation and optimization techniques, the SCWPF's are used to compute the water demand considering different constraints, for instance variable and fix costs or the producer price. This generic approach enables the computation for both multiple crops at farm scale as well as of the aggregated response to water pricing at a regional scale for full and deficit irrigation systems. Within the SAPHIR (SAxonian Platform for High Performance Irrigation) project a prototype of a decision support system is developed which helps to evaluate combined water supply and demand management policies for an effective and efficient utilization of water in order to meet future demands. The prototype is implemented as a web-based decision support system and it is based on a service-oriented geo-database architecture.

Comparing multi-criteria decision analysis and integrated assessment to support long-term water supply planning

PubMed Central

Maurer, Max; Lienert, Judit

2017-01-01

We compare the use of multi-criteria decision analysis (MCDA)–or more precisely, models used in multi-attribute value theory (MAVT)–to integrated assessment (IA) models for supporting long-term water supply planning in a small town case study in Switzerland. They are used to evaluate thirteen system scale water supply alternatives in four future scenarios regarding forty-four objectives, covering technical, social, environmental, and economic aspects. The alternatives encompass both conventional and unconventional solutions and differ regarding technical, spatial and organizational characteristics. This paper focuses on the impact assessment and final evaluation step of the structured MCDA decision support process. We analyze the performance of the alternatives for ten stakeholders. We demonstrate the implications of model assumptions by comparing two IA and three MAVT evaluation model layouts of different complexity. For this comparison, we focus on the validity (ranking stability), desirability (value), and distinguishability (value range) of the alternatives given the five model layouts. These layouts exclude or include stakeholder preferences and uncertainties. Even though all five led us to identify the same best alternatives, they did not produce identical rankings. We found that the MAVT-type models provide higher distinguishability and a more robust basis for discussion than the IA-type models. The needed complexity of the model, however, should be determined based on the intended use of the model within the decision support process. The best-performing alternatives had consistently strong performance for all stakeholders and future scenarios, whereas the current water supply system was outperformed in all evaluation layouts. The best-performing alternatives comprise proactive pipe rehabilitation, adapted firefighting provisions, and decentralized water storage and/or treatment. We present recommendations for possible ways of improving water supply planning in the case study and beyond. PMID:28481881

Multi-criteria decision making to support waste management: A critical review of current practices and methods.

PubMed

Goulart Coelho, Lineker M; Lange, Liséte C; Coelho, Hosmanny Mg

2017-01-01

Solid waste management is a complex domain involving the interaction of several dimensions; thus, its analysis and control impose continuous challenges for decision makers. In this context, multi-criteria decision-making models have become important and convenient supporting tools for solid waste management because they can handle problems involving multiple dimensions and conflicting criteria. However, the selection of the multi-criteria decision-making method is a hard task since there are several multi-criteria decision-making approaches, each one with a large number of variants whose applicability depends on information availability and the aim of the study. Therefore, to support researchers and decision makers, the objectives of this article are to present a literature review of multi-criteria decision-making applications used in solid waste management, offer a critical assessment of the current practices, and provide suggestions for future works. A brief review of fundamental concepts on this topic is first provided, followed by the analysis of 260 articles related to the application of multi-criteria decision making in solid waste management. These studies were investigated in terms of the methodology, including specific steps such as normalisation, weighting, and sensitivity analysis. In addition, information related to waste type, the study objective, and aspects considered was recorded. From the articles analysed it is noted that studies using multi-criteria decision making in solid waste management are predominantly addressed to problems related to municipal solid waste involving facility location or management strategy.

Towards public health decision support: a systematic review of bidirectional communication approaches

PubMed Central

Dixon, Brian E; Gamache, Roland E; Grannis, Shaun J

2013-01-01

Objective To summarize the literature describing computer-based interventions aimed at improving bidirectional communication between clinical and public health. Materials and Methods A systematic review of English articles using MEDLINE and Google Scholar. Search terms included public health, epidemiology, electronic health records, decision support, expert systems, and decision-making. Only articles that described the communication of information regarding emerging health threats from public health agencies to clinicians or provider organizations were included. Each article was independently reviewed by two authors. Results Ten peer-reviewed articles highlight a nascent but promising area of research and practice related to alerting clinicians about emerging threats. Current literature suggests that additional research and development in bidirectional communication infrastructure should focus on defining a coherent architecture, improving interoperability, establishing clear governance, and creating usable systems that will effectively deliver targeted, specific information to clinicians in support of patient and population decision-making. Conclusions Increasingly available clinical information systems make it possible to deliver timely, relevant knowledge to frontline clinicians in support of population health. Future work should focus on developing a flexible, interoperable infrastructure for bidirectional communications capable of integrating public health knowledge into clinical systems and workflows. PMID:23467470

UNDERSTANDING THE PAST, MANAGING THE FUTURE - Remotely sensed analysis of the urban sprawl of Istanbul for supporting decision making for a sustainable future

NASA Astrophysics Data System (ADS)

Altan, O.; Kemper, G.

2012-07-01

The GIS based analysis of the land use change of Istanbul delivers a huge and comprehensive database that can be used for further analysis. Trend analysis and scenarios enable a view to the future that highlights the needs for a proper planning. Also the understanding via comparison to other cities assists in order not to copy errors from other cities. GIS in combination with ancillary data open a wide field for managing the future of Istanbul.

In-vehicle decision support to reduce crashes at rural thru-stop intersections.

DOT National Transportation Integrated Search

2011-08-01

Purpose: Within the context of thru-stop intersections, investigate the feasibility and future promise of warning : systems inside the vehicle, where interfaces are best placed, and what modalities are most effective (visual versus : haptic). Methods...

SMARTE: HELPING COMMUNITIES OVERCOME OBSTACLES TO REVITALIZATION (04/23/07)

EPA Science Inventory

Sustainable Management Approaches and Revitalization Tools - electronic (SMARTe), is an open-source, web-based, decision support system for developing and evaluating future reuse scenarios for potentially contaminated land. SMARTe contains information and analysis tools for all a...

The Cognitive Impact of Past Behavior: Influences on Beliefs, Attitudes, and Future Behavioral Decisions

PubMed Central

Albarracín, Dolores; Wyer, Robert S.

2016-01-01

To study the processes by which past behavior influences future behavior, participants were led to believe that without being aware of it, they had expressed either support for or opposition to the institution of comprehensive exams. Judgment and response time data suggested that participants’ perceptions of their past behavior often influenced their decisions to repeat the behavior. This influence was partly the result of cognitive activity that influenced participants’ cognitions about specific behavioral consequences and the attitude they based on these cognitions. More generally, however, feedback about past behavior had a direct effect on participants’ attitudes and ultimate behavioral decisions that was independent of the outcome-specific cognitions. Results are discussed in terms of their implications for biased scanning of memory, dissonance reduction, self-perception, and the use of behavior as a heuristic. PMID:10909874

An Introspective Critique of Past, Present, and Future USGS Decision Support

NASA Astrophysics Data System (ADS)

Neff, B. P.; Pavlick, M.

2017-12-01

In response to increasing scrutiny of publicly funded science, the Water Mission Area of USGS is shifting its approach for informing decisions that affect the country. Historically, USGS has focused on providing sound science on cutting edge, societally relevant issues with the expectation that decision makers will take action on this information. In practice, scientists often do not understand or focus on the needs of decision makers and decision makers often cannot or do not utilize information produced by scientists. The Water Mission Area of USGS has recognized that it can better serve the taxpayer by delivering information more relevant to decision making in a form more conducive to its use. To this end, the Water Mission Area of USGS is seeking greater integration with the decision making process to better inform what information it produces. In addition, recognizing that the transfer of scientific knowledge to decision making is fundamentally a social process, USGS is embracing the use of social science to better inform how it delivers scientific information and facilitates its use. This study utilizes qualitative methods to document the evolution of decision support at USGS and provide a rationale for a shift in direction. Challenges to implementation are identified and collaborative opportunities to improve decision making are discussed.

Embedded sensor systems for health - providing the tools in future healthcare.

PubMed

Lindén, Maria; Björkman, Mats

2014-01-01

Wearable, embedded sensor systems for health applications are foreseen to be enablers in the future healthcare. They will provide ubiquitous monitoring of multiple parameters without restricting the person to stay at home or in the hospital. By following trend changes in the health status, early deteriorations will be detected and treatment can start earlier. Also health prevention will be supported. Such future healthcare requires technology development, including miniaturized sensors, smart textiles and wireless communication. The tremendous amount of data generated by these systems calls for both signal processing and decision support to guarantee the quality of data and avoid overflow of information. Safe and secure communications have to protect the integrity of the persons monitored.

Psychosocial Working Conditions and Cognitive Complaints among Swedish Employees

PubMed Central

Stenfors, Cecilia U. D.; Magnusson Hanson, Linda; Oxenstierna, Gabriel; Theorell, Töres; Nilsson, Lars-Göran

2013-01-01

Background Cognitive complaints involving problems with concentration, memory, decision-making and thinking are relatively common in the work force. The sensitivity of both subjective and objective cognitive functioning to common psychiatric conditions, stress levels and to cognitive load makes it plausible that psychosocial working conditions play a role in cognitive complaints. Thus, this study aimed to test the associations between psychosocial work factors and cognitive complaints in nationally representative samples of the Swedish work force. Cross-sectional (n = 9751) and prospective (n = 3644; two time points two years apart) sequential multiple regression analyses were run, adjusting for general confounders, depressive- and sleeping problems. Additional prospective analyses were run adjusting for baseline cognitive complaints. Cross-sectional results High quantitative demands, information and communication technology (ICT) demands, underqualification and conflicts were positively associated with cognitive complaints, while social support, good resources at work and overqualification were negatively associated with cognitive complaints in all models. Skill discretion and decision authority were weakly associated with cognitive complaints. Conflicts were more strongly associated with cognitive complaints in women than in men, after adjustment for general confounders. Prospective results Quantitative job demands, ICT demands and underqualification were positively associated with future cognitive complaints in all models, including when adjusted for baseline cognitive complaints. Decision authority was weakly positively associated with future cognitive complaints, only after adjustment for depressive- and sleeping problems respectively. Social support was negatively associated with future cognitive complaints after adjustment for general confounders and baseline cognitive complaints. Skill discretion and resources were negatively associated with future cognitive complaints after adjustment for general confounders. The associations between quantitative demands and future cognitive complaints were stronger in women. Discussion/Conclusions The findings indicate that psychosocial working conditions should be taken into account when considering cognitive complaints among employees. PMID:23560101

The Air Quality Model Evaluation International Initiative ...

EPA Pesticide Factsheets

This presentation provides an overview of the Air Quality Model Evaluation International Initiative (AQMEII). It contains a synopsis of the three phases of AQMEII, including objectives, logistics, and timelines. It also provides a number of examples of analyses conducted through AQMEII with a particular focus on past and future analyses of deposition. 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.

GeoLab 2011: New Instruments and Operations Tested at Desert RATS

NASA Technical Reports Server (NTRS)

Evans, Cindy A.; Calaway, M. J.; Bell, M. S.

2012-01-01

GeoLab is a geological laboratory and testbed designed for supporting geoscience activities during NASA's analog demonstrations. Scientists at NASA's Johnson Space Center built GeoLab as part of a technology project to aid the development of science operational concepts for future planetary surface missions [1, 2, 3]. It is integrated into NASA's Habitat Demonstration Unit, a first generation exploration habitat test article. As a prototype workstation, GeoLab provides a high fidelity working space for analog mission crewmembers to perform in-situ characterization of geologic samples and communicate their findings with supporting scientists. GeoLab analog operations can provide valuable data for assessing the operational and scientific considerations of surface-based geologic analyses such as preliminary examination of samples collected by astronaut crews [4, 5]. Our analog tests also feed into sample handling and advanced curation operational concepts and procedures that will, ultimately, help ensure that the most critical samples are collected during future exploration on a planetary surface, and aid decisions about sample prioritization, sample handling and return. Data from GeoLab operations also supports science planning during a mission by providing additional detailed geologic information to supporting scientists, helping them make informed decisions about strategies for subsequent sample collection opportunities.

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

GLIMPSE: a rapid decision framework for energy and environmental policy.

PubMed

Akhtar, Farhan H; Pinder, Robert W; Loughlin, Daniel H; Henze, Daven K

2013-01-01

Over the coming decades, new energy production technologies and the policies that oversee them will affect human health, the vitality of our ecosystems, and the stability of the global climate. The GLIMPSE decision model framework provides insights about the implications of technology and policy decisions on these outcomes. Using GLIMPSE, decision makers can identify alternative techno-policy futures, examining their air quality, health, and short- and long-term climate impacts. Ultimately, GLIMPSE will support the identification of cost-effective strategies for simultaneously achieving performance goals for these metrics. Here, we demonstrate the utility of GLIMPSE by analyzing several future energy scenarios under existing air quality regulations and potential CO2 emission reduction policies. We find opportunities for substantial cobenefits in setting both climate change mitigation and health-benefit based air quality improvement targets. Though current policies which prioritize public health protection increase near-term warming, establishing policies that also reduce greenhouse gas emissions may offset warming in the near-term and lead to significant reductions in long-term warming.

Perspectives of self-direction: a systematic review of key areas contributing to service users' engagement and choice-making in self-directed disability services and supports.

PubMed

Lakhani, Ali; McDonald, Donna; Zeeman, Heidi

2018-05-01

Self-directed disability support policies aim to encourage greater choice and control for service users in terms of the health and social care they receive. The proliferation of self-directed disability support policies throughout the developed world has resulted in a growing amount of research exploring the outcomes for service users, and their families and carers. Our understanding of the issues faced by people with disabilities, particularly how they make health and social care decisions and the key areas that determine their engagement with service providers within a self-directed environment is limited. A synthesis of research is timely and can provide knowledge for service users and health and social care support providers to ensure their successful participation. A systematic review guided by the PRISMA approach explored (i) the key areas determining service users' engagement with self-directed disability services and supports, and (ii) how service users make informed decisions about providers. In October 2014 and April 2016, three databases - MEDLINE, CINAHL and Web of Science - were searched for research and review articles. Eighteen sources met the search criteria. Findings were mapped into either: key areas determining service user engagement, or service users' informed decision-making. Findings concerning key areas determining engagement fell into three themes - personal responsibility for budgeting, personalised approaches, and a cultural shift in practice and delivery among service providers. Findings about decision-making yielded two themes - supporting informed decision-making and inhibiting informed decision-making. Literature suggests that self-directed models of care may provide service users with increased control over the services that they receive. Increased control for some service users and their families requires independent external decision-making support, particularly around the domains of budgeting, planning and hiring. Future research must continue to investigate the perspectives of service users pertaining to their engagement, as their participation is central to the effectiveness of the approach. © 2016 John Wiley & Sons Ltd.

Bridging groundwater models and decision support with a Bayesian network

USGS Publications Warehouse

Fienen, Michael N.; Masterson, John P.; Plant, Nathaniel G.; Gutierrez, Benjamin T.; Thieler, E. Robert

2013-01-01

Resource managers need to make decisions to plan for future environmental conditions, particularly sea level rise, in the face of substantial uncertainty. Many interacting processes factor in to the decisions they face. Advances in process models and the quantification of uncertainty have made models a valuable tool for this purpose. Long-simulation runtimes and, often, numerical instability make linking process models impractical in many cases. A method for emulating the important connections between model input and forecasts, while propagating uncertainty, has the potential to provide a bridge between complicated numerical process models and the efficiency and stability needed for decision making. We explore this using a Bayesian network (BN) to emulate a groundwater flow model. We expand on previous approaches to validating a BN by calculating forecasting skill using cross validation of a groundwater model of Assateague Island in Virginia and Maryland, USA. This BN emulation was shown to capture the important groundwater-flow characteristics and uncertainty of the groundwater system because of its connection to island morphology and sea level. Forecast power metrics associated with the validation of multiple alternative BN designs guided the selection of an optimal level of BN complexity. Assateague island is an ideal test case for exploring a forecasting tool based on current conditions because the unique hydrogeomorphological variability of the island includes a range of settings indicative of past, current, and future conditions. The resulting BN is a valuable tool for exploring the response of groundwater conditions to sea level rise in decision support.

Linking Science and Management in an Interactive Geospatial, Mutli-Criterion, Structured Decision Support Framework: Use Case Studies of the "Future Forests Geo-visualization and Decision Support Tool

NASA Astrophysics Data System (ADS)

Pontius, J.; Duncan, J.

2017-12-01

Land managers are often faced with balancing management activities to accomplish a diversity of management objectives, in systems faced with many stress agents. Advances in ecosystem modeling provide a rich source of information to inform management. Coupled with advances in decision support techniques and computing capabilities, interactive tools are now accessible for a broad audience of stakeholders. Here we present one such tool designed to capture information on how climate change may impact forested ecosystems, and how that impact varies spatially across the landscape. This tool integrates empirical models of current and future forest structure and function in a structured decision framework that allows users to customize weights for multiple management objectives and visualize suitability outcomes across the landscape. Combined with climate projections, the resulting products allow stakeholders to compare the relative success of various management objectives on a pixel by pixel basis and identify locations where management outcomes are most likely to be met. Here we demonstrate this approach with the integration of several of the preliminary models developed to map species distributions, sugar maple health, forest fragmentation risk and hemlock vulnerability to hemlock woolly adelgid under current and future climate scenarios. We compare three use case studies with objective weightings designed to: 1) Identify key parcels for sugarbush conservation and management, 2) Target state lands that may serve as hemlock refugia from hemlock woolly adelgid induced mortality, and 3) Examine how climate change may alter the success of managing for both sugarbush and hemlock across privately owned lands. This tool highlights the value of flexible models that can be easily run with customized weightings in a dynamic, integrated assessment that allows users to hone in on their potentially complex management objectives, and to visualize and prioritize locations across the landscape. It also demonstrates the importance of including climate considerations for long-term management. This merging of scientific knowledge with the diversity of stakeholder needs is an important step towards using science to inform management and policy decisions.

Evaluation of Nursing Documentation Completion of Stroke Patients in the Emergency Department: A Pre-Post Analysis Using Flowsheet Templates and Clinical Decision Support.

PubMed

Richardson, Karen J; Sengstack, Patricia; Doucette, Jeffrey N; Hammond, William E; Schertz, Matthew; Thompson, Julie; Johnson, Constance

2016-02-01

The primary aim of this performance improvement project was to determine whether the electronic health record implementation of stroke-specific nursing documentation flowsheet templates and clinical decision support alerts improved the nursing documentation of eligible stroke patients in seven stroke-certified emergency departments. Two system enhancements were introduced into the electronic record in an effort to improve nursing documentation: disease-specific documentation flowsheets and clinical decision support alerts. Using a pre-post design, project measures included six stroke management goals as defined by the National Institute of Neurological Disorders and Stroke and three clinical decision support measures based on entry of orders used to trigger documentation reminders for nursing: (1) the National Institutes of Health's Stroke Scale, (2) neurological checks, and (3) dysphagia screening. Data were reviewed 6 months prior (n = 2293) and 6 months following the intervention (n = 2588). Fisher exact test was used for statistical analysis. Statistical significance was found for documentation of five of the six stroke management goals, although effect sizes were small. Customizing flowsheets to meet the needs of nursing workflow showed improvement in the completion of documentation. The effects of the decision support alerts on the completeness of nursing documentation were not statistically significant (likely due to lack of order entry). For example, an order for the National Institutes of Health Stroke Scale was entered only 10.7% of the time, which meant no alert would fire for nursing in the postintervention group. Future work should focus on decision support alerts that trigger reminders for clinicians to place relevant orders for this population.

Healthcare provider education to support integration of pharmacogenomics in practice: the eMERGE Network experience

PubMed Central

Rohrer Vitek, Carolyn R; Abul-Husn, Noura S; Connolly, John J; Hartzler, Andrea L; Kitchner, Terrie; Peterson, Josh F; Rasmussen, Luke V; Smith, Maureen E; Stallings, Sarah; Williams, Marc S; Wolf, Wendy A; Prows, Cynthia A

2017-01-01

Ten organizations within the Electronic Medical Records and Genomics Network developed programs to implement pharmacogenomic sequencing and clinical decision support into clinical settings. Recognizing the importance of informed prescribers, a variety of strategies were used to incorporate provider education to support implementation. Education experiences with pharmacogenomics are described within the context of each organization's prior involvement, including the scope and scale of implementation specific to their Electronic Medical Records and Genomics projects. We describe common and distinct education strategies, provide exemplars and share challenges. Lessons learned inform future perspectives. Future pharmacogenomics clinical implementation initiatives need to include funding toward implementing provider education and evaluating outcomes. PMID:28639489

Shared decision making in endocrinology: present and future directions.

PubMed

Rodriguez-Gutierrez, Rene; Gionfriddo, Michael R; Ospina, Naykky Singh; Maraka, Spyridoula; Tamhane, Shrikant; Montori, Victor M; Brito, Juan P

2016-08-01

In medicine and endocrinology, there are few clinical circumstances in which clinicians can accurately predict what is best for their patients. As a result, patients and clinicians frequently have to make decisions about which there is uncertainty. Uncertainty results from limitations in the research evidence, unclear patient preferences, or an inability to predict how treatments will fit into patients' daily lives. The work that patients and clinicians do together to address the patient's situation and engage in a deliberative dialogue about reasonable treatment options is often called shared decision making. Decision aids are evidence-based tools that facilitate this process. Shared decision making is a patient-centred approach in which clinicians share information about the benefits, harms, and burden of different reasonable diagnostic and treatment options, and patients explain what matters to them in view of their particular values, preferences, and personal context. Beyond the ethical argument in support of this approach, decision aids have been shown to improve patients' knowledge about the available options, accuracy of risk estimates, and decisional comfort. Decision aids also promote patient participation in the decision-making process. Despite accumulating evidence from clinical trials, policy support, and expert recommendations in endocrinology practice guidelines, shared decision making is still not routinely implemented in endocrine practice. Additional work is needed to enrich the number of available tools and to implement them in practice workflows. Also, although the evidence from randomised controlled trials favours the use of this shared decision making in other settings, populations, and illnesses, the effect of this approach has been studied in a few endocrine disorders. Future pragmatic trials are needed to explore the effect and feasibility of shared decision making implementation into routine endocrinology and primary care practice. With the available evidence, however, endocrinologists can now start to practice shared decision making, partner with their patients, and use their expertise to formulate treatment plans that reflect patient preferences and are more likely to fit into the context of patients' lives. In this Personal View, we describe shared decision making, the evidence behind the approach, and why and how both endocrinologists and their patients could benefit from this approach. Copyright © 2016 Elsevier Ltd. All rights reserved.

Comparison of risk-based decision-support systems for brownfield site rehabilitation: DESYRE and SADA applied to a Romanian case study.

PubMed

Stezar, I C; Pizzol, L; Critto, A; Ozunu, A; Marcomini, A

2013-12-15

Brownfield rehabilitation is an essential step for sustainable land-use planning and management in the European Union. In brownfield regeneration processes, the legacy contamination plays a significant role, firstly because of the persistent contaminants in soil or groundwater which extends the existing hazards and risks well into the future; and secondly, problems from historical contamination are often more difficult to manage than contamination caused by new activities. Due to the complexity associated with the management of brownfield site rehabilitation, Decision Support Systems (DSSs) have been developed to support problem holders and stakeholders in the decision-making process encompassing all phases of the rehabilitation. This paper presents a comparative study between two DSSs, namely SADA (Spatial Analysis and Decision Assistance) and DESYRE (Decision Support System for the Requalification of Contaminated Sites), with the main objective of showing the benefits of using DSSs to introduce and process data and then to disseminate results to different stakeholders involved in the decision-making process. For this purpose, a former car manufacturing plant located in the Brasov area, Central Romania, contaminated chiefly by heavy metals and total petroleum hydrocarbons, has been selected as a case study to apply the two examined DSSs. Major results presented here concern the analysis of the functionalities of the two DSSs in order to identify similarities, differences and complementarities and, thus, to provide an indication of the most suitable integration options. Copyright © 2013 Elsevier Ltd. All rights reserved.

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.

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

PubMed

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

2014-12-12

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

Understanding complex clinical reasoning in infectious diseases for improving clinical decision support design.

PubMed

Islam, Roosan; Weir, Charlene R; Jones, Makoto; Del Fiol, Guilherme; Samore, Matthew H

2015-11-30

Clinical experts' cognitive mechanisms for managing complexity have implications for the design of future innovative healthcare systems. The purpose of the study is to examine the constituents of decision complexity and explore the cognitive strategies clinicians use to control and adapt to their information environment. We used Cognitive Task Analysis (CTA) methods to interview 10 Infectious Disease (ID) experts at the University of Utah and Salt Lake City Veterans Administration Medical Center. Participants were asked to recall a complex, critical and vivid antibiotic-prescribing incident using the Critical Decision Method (CDM), a type of Cognitive Task Analysis (CTA). Using the four iterations of the Critical Decision Method, questions were posed to fully explore the incident, focusing in depth on the clinical components underlying the complexity. Probes were included to assess cognitive and decision strategies used by participants. The following three themes emerged as the constituents of decision complexity experienced by the Infectious Diseases experts: 1) the overall clinical picture does not match the pattern, 2) a lack of comprehension of the situation and 3) dealing with social and emotional pressures such as fear and anxiety. All these factors contribute to decision complexity. These factors almost always occurred together, creating unexpected events and uncertainty in clinical reasoning. Five themes emerged in the analyses of how experts deal with the complexity. Expert clinicians frequently used 1) watchful waiting instead of over- prescribing antibiotics, engaged in 2) theory of mind to project and simulate other practitioners' perspectives, reduced very complex cases into simple 3) heuristics, employed 4) anticipatory thinking to plan and re-plan events and consulted with peers to share knowledge, solicit opinions and 5) seek help on patient cases. The cognitive strategies to deal with decision complexity found in this study have important implications for design future decision support systems for the management of complex patients.

Electricity generation and transmission planning in deregulated power markets

NASA Astrophysics Data System (ADS)

He, Yang

This dissertation addresses the long-term planning of power generation and transmission facilities in a deregulated power market. Three models with increasing complexities are developed, primarily for investment decisions in generation and transmission capacity. The models are presented in a two-stage decision context where generation and transmission capacity expansion decisions are made in the first stage, while power generation and transmission service fees are decided in the second stage. Uncertainties that exist in the second stage affect the capacity expansion decisions in the first stage. The first model assumes that the electric power market is not constrained by transmission capacity limit. The second model, which includes transmission constraints, considers the interactions between generation firms and the transmission network operator. The third model assumes that the generation and transmission sectors make capacity investment decisions separately. These models result in Nash-Cournot equilibrium among the unregulated generation firms, while the regulated transmission network operator supports the competition among generation firms. Several issues in the deregulated electric power market can be studied with these models such as market powers of generation firms and transmission network operator, uncertainties of the future market, and interactions between the generation and transmission sectors. Results deduced from the developed models include (a) regulated transmission network operator will not reserve transmission capacity to gain extra profits; instead, it will make capacity expansion decisions to support the competition in the generation sector; (b) generation firms will provide more power supplies when there is more demand; (c) in the presence of future uncertainties, the generation firms will add more generation capacity if the demand in the future power market is expected to be higher; and (d) the transmission capacity invested by the transmission network operator depends on the characteristic of the power market and the topology of the transmission network. Also, the second model, which considers interactions between generation and transmission sectors, yields higher social welfare in the electric power market, than the third model where generation firms and transmission network operator make investment decisions separately.

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.

Designing Smart Health Care Technology into the Home of the Future

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

Craft, R.L.; Warren, S.

1999-04-20

This editorial paper presents a vision for intelligent health care in the home of the future, focusing on technologies with the highest potential payoff given targeted government funding over the next ten years. A secure, plug-and-play information framework provides the starting point for identifying technologies that must be developed before home-based devices can know their context and assimilate information to support care decisions.

Warehouse location and freight attraction in the greater El Paso region.

DOT National Transportation Integrated Search

2013-12-01

This project analyzes the current and future warehouse and distribution center locations along the El Paso-Juarez regions in the U.S.-Mexico border. This research seeks has developed a comprehensive database to aid in decision support process for ide...

SMARTE 2007 TUTORIAL - JANUARY 2007 REVISION

EPA Science Inventory

SMARTe 2007 is a web-based decision support tool intended to help revitalization practitioners find information, perform data analysis, communicate, and evaluate future reuse options for a site or area. This tutorial CD was developed to help users navigate SMARTe 2007. It is appr...

SUSTAINABILITY AND WASTE MANAGEMENT

EPA Science Inventory

There is a need to move toward a more sustainable use of resources. Concern for the environment and future generations is leading us to shift the focus from waste management to resource management. This paper provides an overview of a decision support tool that provides a holis...

Free and open source enabling technologies for patient-centric, guideline-based clinical decision support: a survey.

PubMed

Leong, T Y; Kaiser, K; Miksch, S

2007-01-01

Guideline-based clinical decision support is an emerging paradigm to help reduce error, lower cost, and improve quality in evidence-based medicine. The free and open source (FOS) approach is a promising alternative for delivering cost-effective information technology (IT) solutions in health care. In this paper, we survey the current FOS enabling technologies for patient-centric, guideline-based care, and discuss the current trends and future directions of their role in clinical decision support. We searched PubMed, major biomedical informatics websites, and the web in general for papers and links related to FOS health care IT systems. We also relied on our background and knowledge for specific subtopics. We focused on the functionalities of guideline modeling tools, and briefly examined the supporting technologies for terminology, data exchange and electronic health record (EHR) standards. To effectively support patient-centric, guideline-based care, the computerized guidelines and protocols need to be integrated with existing clinical information systems or EHRs. Technologies that enable such integration should be accessible, interoperable, and scalable. A plethora of FOS tools and techniques for supporting different knowledge management and quality assurance tasks involved are available. Many challenges, however, remain in their implementation. There are active and growing trends of deploying FOS enabling technologies for integrating clinical guidelines, protocols, and pathways into the main care processes. The continuing development and maturation of such technologies are likely to make increasingly significant contributions to patient-centric, guideline-based clinical decision support.

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.

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.

SO-QT: Collaborative Tool to Project the Future Space Object Population

NASA Technical Reports Server (NTRS)

Stupl, Jan

2017-01-01

Earth orbit gets increasingly congested, a challenge to space operators, both in governments and industry. We present a web tool that provides: 1) data on todays and the historic space object environments, by aggregating object-specific tracking data; and 2) future trends through a collaboration platform to collect information on planed launches. The collaborative platform enables experts to pool and compare their data in order to generate future launch scenarios. The tool is intended to support decision makers and mission designers while they investigate future missions and scholars as they develop strategies for space traffic management.

TIUPAM: A Framework for Trustworthiness-Centric Information Sharing

NASA Astrophysics Data System (ADS)

Xu, Shouhuai; Sandhu, Ravi; Bertino, Elisa

Information is essential to decision making. Nowadays, decision makers are often overwhelmed with large volumes of information, some of which may be inaccurate, incorrect, inappropriate, misleading, or maliciously introduced. With the advocated shift of information sharing paradigm from “need to know” to “need to share” this problem will be further compounded. This poses the challenge of achieving assured information sharing so that decision makers can always get and utilize the up-to-date information for making the right decisions, despite the existence of malicious attacks and without breaching privacy of honest participants. As a first step towards answering this challenge this paper proposes a systematic framework we call TIUPAM, which stands for “Trustworthiness-centric Identity, Usage, Provenance, and Attack Management.” The framework is centered at the need of trustworthiness and risk management for decision makers, and supported by four key components: identity management, usage management, provenance management and attack management. We explore the characterization of both the core functions and the supporting components in the TIUPAM framework, which may guide the design and realization of concrete schemes in the future.

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.

Radiological emergency response for community agencies with cognitive task analysis, risk analysis, and decision support framework.

PubMed

Meyer, Travis S; Muething, Joseph Z; Lima, Gustavo Amoras Souza; Torres, Breno Raemy Rangel; del Rosario, Trystyn Keia; Gomes, José Orlando; Lambert, James H

2012-01-01

Radiological nuclear emergency responders must be able to coordinate evacuation and relief efforts following the release of radioactive material into populated areas. In order to respond quickly and effectively to a nuclear emergency, high-level coordination is needed between a number of large, independent organizations, including police, military, hazmat, and transportation authorities. Given the complexity, scale, time-pressure, and potential negative consequences inherent in radiological emergency responses, tracking and communicating information that will assist decision makers during a crisis is crucial. The emergency response team at the Angra dos Reis nuclear power facility, located outside of Rio de Janeiro, Brazil, presently conducts emergency response simulations once every two years to prepare organizational leaders for real-life emergency situations. However, current exercises are conducted without the aid of electronic or software tools, resulting in possible cognitive overload and delays in decision-making. This paper describes the development of a decision support system employing systems methodologies, including cognitive task analysis and human-machine interface design. The decision support system can aid the coordination team by automating cognitive functions and improving information sharing. A prototype of the design will be evaluated by plant officials in Brazil and incorporated to a future trial run of a response simulation.

Multi-objective optimization of riparian buffer networks; valuing present and future benefits

EPA Science Inventory

Multi-objective optimization has emerged as a popular approach to support water resources planning and management. This approach provides decision-makers with a suite of management options which are generated based on metrics that represent different social, economic, and environ...

75 FR 65385 - Agency Information Collection Activities: Proposed Collection; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2010-10-22

... Earthquake Engineering Simulation (NEES). SUMMARY: In compliance with the requirement of section 3506(c)(2)(A... of the Network for Earthquake Engineering Simulation. Type of Information Collection Request: New... inform decision making regarding the future of NSF support for earthquake engineering research...

De-Grading Developmental Studies.

ERIC Educational Resources Information Center

Erickson, Michael E.

If developmental studies programs are to successfully enhance affective and cognitive development in a non-competitive, supportive setting, they must abandon traditional A to F grading in favor of a descriptive, personalized feedback system that helps the student make intelligent decisions concerning his/her academic future. Indeed, research…

Biomarkers in prostate cancer - Current clinical utility and future perspectives.

PubMed

Kretschmer, Alexander; Tilki, Derya

2017-12-01

Current tendencies in the treatment course of prostate cancer patients increase the need for reliable biomarkers that help in decision-making in a challenging clinical setting. Within the last decade, several novel biomarkers have been introduced. In the following comprehensive review article, we focus on diagnostic (PHI ® , 4K score, SelectMDx ® , ConfirmMDx ® , PCA3, MiPS, ExoDX ® , mpMRI) and prognostic (OncotypeDX GPS ® , Prolaris ® , ProMark ® , DNA-ploidy, Decipher ® ) biomarkers that are in widespread clinical use and are supported by evidence. Hereby, we focus on multiple clinical situations in which innovative biomarkers may guide decision-making in prostate cancer therapy. In addition, we describe novel liquid biopsy approaches (circulating tumor cells, cell-free DNA) that have been described as predictive biomarkers in metastatic castration-resistant prostate cancer and might support an individual patient-centred oncological approach in the nearer future. Copyright © 2017 Elsevier B.V. All rights reserved.

Namibia Dashboard Enhancements

NASA Technical Reports Server (NTRS)

Mandl, Daniel; Handy, Matthew

2014-01-01

The purpose of this presentation is for a Technical Interchange Meeting with the Namibia Hydrological Services (NHS) in Namibia. The meeting serves as a capacity building exercise. This presentation goes over existing software functionality developed in collaboration with NHS over the past five years called the Namibia Flood Dashboard. Furthermore, it outlines new functionality developed over the past year and future functionality that will be developed. The main purpose of the Dashboard is to assist in decision support for flood warning. The Namibia Flood Dashboard already exists online in a cloud environment and has been used in prototype mode for the past few years.Functionality in the Dashboard includes river gauge hydrographs, TRMM estimate rainfall, EO-1 flood maps, infrastructure maps and other related functions. Future functionality includes attempting to integrate interoperability standards and crowd-sourcing capability. To this end, we are adding OpenStreetMap compatibility and an Applications Program Interface (API) called a GeoSocial API to enable discovery and sharing of data products useful for decision support via social media.

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.

Boosting Quality Registries with Clinical Decision Support Functionality*. User Acceptance of a Prototype Applied to HIV/TB Drug Therapy.

PubMed

Wannheden, Carolina; Hvitfeldt-Forsberg, Helena; Eftimovska, Elena; Westling, Katarina; Ellenius, Johan

2017-08-11

The care of HIV-related tuberculosis (HIV/TB) is complex and challenging. Clinical decision support (CDS) systems can contribute to improve quality of care, but more knowledge is needed on factors determining user acceptance of CDS. To analyze physicians' and nurses' acceptance of a CDS prototype for evidence-based drug therapy recommendations for HIV/TB treatment. Physicians and nurses were involved in designing a CDS prototype intended for future integration with the Swedish national HIV quality registry. Focus group evaluation was performed with ten nurses and four physicians, respectively. The Unified Theory of Acceptance and Use of Technology (UTAUT) was used to analyze acceptance. We identified several potential benefits with the CDS prototype as well as some concerns that could be addressed by redesign. There was also concern about dependence on physician attitudes, as well as technical, organizational, and legal issues. Acceptance evaluation at a prototype stage provided rich data to improve the future design of a CDS prototype. Apart from design and development efforts, substantial organizational efforts are needed to enable the implementation and maintenance of a future CDS system.

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.

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.

Blunt Cerebrovascular Injuries: Advances in Screening, Imaging, and Management Trends.

PubMed

Nagpal, P; Policeni, B A; Bathla, G; Khandelwal, A; Derdeyn, C; Skeete, D

2017-10-12

Blunt cerebrovascular injury is a relatively uncommon but sometimes life-threatening injury, particularly in patients presenting with ischemic symptoms in that vascular territory. The decision to pursue vascular imaging (generally CT angiography) is based on clinical and imaging findings. Several grading scales or screening criteria have been developed to guide the decision to pursue vascular imaging, as well as to recommend different treatment options for various injuries. The data supporting many of these guidelines and options are limited however. The purpose of this article is to review and compare these scales and criteria and the data supporting clinical efficacy and to make recommendations for future research in this area. © 2017 by American Journal of Neuroradiology.

Field Artillery and the Combined Arms Team: A Case for the Continued Relevance of American Fire Support

DTIC Science & Technology

2015-05-23

integrate with maneuver forces to meet future threats. Several former brigade combat team commanders mentioned the field artillery’s “identity crisis ” in...September 2008): 35. 5 Sean MacFarland, Michael Shields, and Jeffrey Snow, “White Paper: The King and I: The Impeding Crisis in Field Artillery’s Ability...Michael S. Coombes , “Agile Fires and Decisive Action: Achieving Pervasive Agility by Focusing On Fundamentals,” NTC Decisive Action Training

Performance indicators for the efficiency analysis of urban drainage systems.

PubMed

Artina, S; Becciu, G; Maglionico, M; Paoletti, A; Sanfilippo, U

2005-01-01

Performance indicators implemented in a decision support system (DSS) for the technical, managerial and economic evaluation of urban drainage systems (UDS), called MOMA FD, are presented. Several kinds of information are collected and processed by MOMA FD to evaluate both present situation and future scenarios of development and enhancement. Particular interest is focused on the evaluation of the environmental impact, which is considered a very relevant factor in the decision making process to identify the priorities for UDS improvements.

Valuating Privacy with Option Pricing Theory

NASA Astrophysics Data System (ADS)

Berthold, Stefan; Böhme, Rainer

One of the key challenges in the information society is responsible handling of personal data. An often-cited reason why people fail to make rational decisions regarding their own informational privacy is the high uncertainty about future consequences of information disclosures today. This chapter builds an analogy to financial options and draws on principles of option pricing to account for this uncertainty in the valuation of privacy. For this purpose, the development of a data subject's personal attributes over time and the development of the attribute distribution in the population are modeled as two stochastic processes, which fit into the Binomial Option Pricing Model (BOPM). Possible applications of such valuation methods to guide decision support in future privacy-enhancing technologies (PETs) are sketched.

Intraoperative Clinical Decision Support for Anesthesia: A Narrative Review of Available Systems.

PubMed

Nair, Bala G; Gabel, Eilon; Hofer, Ira; Schwid, Howard A; Cannesson, Maxime

2017-02-01

With increasing adoption of anesthesia information management systems (AIMS), there is growing interest in utilizing AIMS data for intraoperative clinical decision support (CDS). CDS for anesthesia has the potential for improving quality of care, patient safety, billing, and compliance. Intraoperative CDS can range from passive and post hoc systems to active real-time systems that can detect ongoing clinical issues and deviations from best practice care. Real-time CDS holds the most promise because real-time alerts and guidance can drive provider behavior toward evidence-based standardized care during the ongoing case. In this review, we describe the different types of intraoperative CDS systems with specific emphasis on real-time systems. The technical considerations in developing and implementing real-time CDS are systematically covered. This includes the functional modules of a CDS system, development and execution of decision rules, and modalities to alert anesthesia providers concerning clinical issues. We also describe the regulatory aspects that affect development, implementation, and use of intraoperative CDS. Methods and measures to assess the effectiveness of intraoperative CDS are discussed. Last, we outline areas of future development of intraoperative CDS, particularly the possibility of providing predictive and prescriptive decision support.

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

Integrated Modeling and Decision-Support System for Water Management in the Puget Sound Basin: Snow Caps to White Caps

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

Copping, Andrea E.; Yang, Zhaoqing; Voisin, Nathalie

2013-12-01

Final Report for the EPA-sponsored project Snow Caps to White Caps that provides data products and insight for water resource managers to support their predictions and management actions to address future changes in water resources (fresh and marine) in the Puget Sound basin. This report details the efforts of a team of scientists and engineers from Pacific Northwest National Laboratory (PNNL) and the University of Washington (UW) to examine the movement of water in the Snohomish Basin, within the watershed and the estuary, under present and future conditions, using a set of linked numerical models.

Nitrogen balance as an indicator of the environmental impact: towards sustainable agricultural production

USDA-ARS?s Scientific Manuscript database

Economics is a principle driver impacting management decisions in agricultural production systems. While increasing concern has focused on preserving the natural resource base to ensure continued support for future production, little emphasis has been placed on examining how drivers alter management...

Assessing Multi-scale Reptile and Amphibian Biodiversity: Mojave Ecoregion Case Study

EPA Science Inventory

The ability to assess, report, map, and forecast the life support functions of ecosystems is absolutely critical to our capacity to make informed decisions to maintain the sustainable nature of our environment now and into the future. Because of the variability among living orga...

Coordinating Aircraft During Field Campaigns: Real Time Mission Monitor Tool

NASA Technical Reports Server (NTRS)

Goodman, Michael

2012-01-01

RTMM has evolved into a powerful and easy to use application in support of planning, situational awareness and strategic decision-making during airborne field campaigns. NASA is very open to sharing these capabilities with any interested group through interagency collaborations in future field activities.

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

PubMed

Nibbelink, Christine W; Brewer, Barbara B

2018-03-01

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

Restoration of contaminated ecosystems: adaptive management in a changing climate

USGS Publications Warehouse

Farag, Aida; Larson, Diane L.; Stauber, Jenny; Stahl, Ralph; Isanhart, John; McAbee, Kevin T.; Walsh, Christopher J.

2017-01-01

Three case studies illustrate how adaptive management (AM) has been used in ecological restorations that involve contaminants. Contaminants addressed include mercury, selenium, and contaminants and physical disturbances delivered to streams by urban stormwater runoff. All three cases emphasize the importance of broad stakeholder input early and consistently throughout decision analysis for AM. Risk of contaminant exposure provided input to the decision analyses (e.g. selenium exposure to endangered razorback suckers, Stewart Lake; multiple contaminants in urban stormwater runoff, Melbourne) and was balanced with the protection of resources critical for a desired future state (e.g. preservation old growth trees, South River). Monitoring also played a critical role in the ability to conduct the decision analyses necessary for AM plans. For example, newer technologies in the Melbourne case provided a testable situation where contaminant concentrations and flow disturbance were reduced to support a return to good ecological condition. In at least one case (Stewart Lake), long-term monitoring data are being used to document the potential effects of climate change on a restoration trajectory. Decision analysis formalized the process by which stakeholders arrived at the priorities for the sites, which together constituted the desired future condition towards which each restoration is aimed. Alternative models were developed that described in mechanistic terms how restoration can influence the system towards the desired future condition. Including known and anticipated effects of future climate scenarios in these models will make them robust to the long-term exposure and effects of contaminants in restored ecosystems.

Individual versus Household Migration Decision Rules: Gender and Marital Status Differences in Intentions to Migrate in South Africa.

PubMed

Gubhaju, Bina; De Jong, Gordon F

2009-03-01

This research tests the thesis that the neoclassical micro-economic and the new household economic theoretical assumptions on migration decision-making rules are segmented by gender, marital status, and time frame of intention to migrate. Comparative tests of both theories within the same study design are relatively rare. Utilizing data from the Causes of Migration in South Africa national migration survey, we analyze how individually held "own-future" versus alternative "household well-being" migration decision rules effect the intentions to migrate of male and female adults in South Africa. Results from the gender and marital status specific logistic regressions models show consistent support for the different gender-marital status decision rule thesis. Specifically, the "maximizing one's own future" neoclassical microeconomic theory proposition is more applicable for never married men and women, the "maximizing household income" proposition for married men with short-term migration intentions, and the "reduce household risk" proposition for longer time horizon migration intentions of married men and women. Results provide new evidence on the way household strategies and individual goals jointly affect intentions to move or stay.

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

Design and evaluation of a web-based decision support tool for district-level disease surveillance in a low-resource setting

PubMed Central

Pore, Meenal; Sengeh, David M.; Mugambi, Purity; Purswani, Nuri V.; Sesay, Tom; Arnold, Anna Lena; Tran, Anh-Minh A.; Myers, Ralph

2017-01-01

During the 2014 West African Ebola Virus outbreak it became apparent that the initial response to the outbreak was hampered by limitations in the collection, aggregation, analysis and use of data for intervention planning. As part of the post-Ebola recovery phase, IBM Research Africa partnered with the Port Loko District Health Management Team (DHMT) in Sierra Leone and GOAL Global, to design, implement and deploy a web-based decision support tool for district-level disease surveillance. This paper discusses the design process and the functionality of the first version of the system. The paper presents evaluation results prior to a pilot deployment and identifies features for future iterations. A qualitative assessment of the tool prior to pilot deployment indicates that it improves the timeliness and ease of using data for making decisions at the DHMT level. PMID:29854209

Achieving Robustness to Uncertainty for Financial Decision-making

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

Barnum, George M.; Van Buren, Kendra L.; Hemez, Francois M.

2014-01-10

This report investigates the concept of robustness analysis to support financial decision-making. Financial models, that forecast future stock returns or market conditions, depend on assumptions that might be unwarranted and variables that might exhibit large fluctuations from their last-known values. The analysis of robustness explores these sources of uncertainty, and recommends model settings such that the forecasts used for decision-making are as insensitive as possible to the uncertainty. A proof-of-concept is presented with the Capital Asset Pricing Model. The robustness of model predictions is assessed using info-gap decision theory. Info-gaps are models of uncertainty that express the “distance,” or gapmore » of information, between what is known and what needs to be known in order to support the decision. The analysis yields a description of worst-case stock returns as a function of increasing gaps in our knowledge. The analyst can then decide on the best course of action by trading-off worst-case performance with “risk”, which is how much uncertainty they think needs to be accommodated in the future. The report also discusses the Graphical User Interface, developed using the MATLAB® programming environment, such that the user can control the analysis through an easy-to-navigate interface. Three directions of future work are identified to enhance the present software. First, the code should be re-written using the Python scientific programming software. This change will achieve greater cross-platform compatibility, better portability, allow for a more professional appearance, and render it independent from a commercial license, which MATLAB® requires. Second, a capability should be developed to allow users to quickly implement and analyze their own models. This will facilitate application of the software to the evaluation of proprietary financial models. The third enhancement proposed is to add the ability to evaluate multiple models simultaneously. When two models reflect past data with similar accuracy, the more robust of the two is preferable for decision-making because its predictions are, by definition, less sensitive to the uncertainty.« less

Ubiquitous computing in shared-care environments.

PubMed

Koch, S

2006-07-01

In light of future challenges, such as growing numbers of elderly, increase in chronic diseases, insufficient health care budgets and problems with staff recruitment for the health-care sector, information and communication technology (ICT) becomes a possible means to meet these challenges. Organizational changes such as the decentralization of the health-care system lead to a shift from in-hospital to both advanced and basic home health care. Advanced medical technologies provide solutions for distant home care in form of specialist consultations and home monitoring. Furthermore, the shift towards home health care will increase mobile work and the establishment of shared care teams which require ICT-based solutions that support ubiquitous information access and cooperative work. Clinical documentation and decision support systems are the main ICT-based solutions of interest in the context of ubiquitous computing for shared care environments. This paper therefore describes the prerequisites for clinical documentation and decision support at the point of care, the impact of mobility on the documentation process, and how the introduction of ICT-based solutions will influence organizations and people. Furthermore, the role of dentistry in shared-care environments is discussed and illustrated in the form of a future scenario.

Bibliometrics as a Tool for Supporting Prospective R&D Decision-Making in the Health Sciences

PubMed Central

Ismail, Sharif; Nason, Edward; Marjanovic, Sonja; Grant, Jonathan

2012-01-01

Abstract Bibliometric analysis is an increasingly important part of a broader “toolbox” of evaluation methods available to research and development (R&D) policymakers to support decision-making. In the US, UK and Australia, for example, there is evidence of gradual convergence over the past ten years towards a model of university research assessment and ranking incorporating the use of bibliometric measures. In Britain, the Department of Health (England) has shown growing interest in using bibliometric analysis to support prospective R&D decision-making, and has engaged RAND Europe's expertise in this area through a number of exercises since 2005. These range from the macro-level selection of potentially high impact institutions, to micro-level selection of high impact individuals for the National Institute for Health Research's faculty of researchers. The aim of this study is to create an accessible, “beginner's guide” to bibliometric theory and application in the area of health R&D decision-making. The study also aims to identify future directions and possible next steps in this area, based on RAND Europe's work with the Department of Health to date. It is targeted at a range of audiences, and will be of interest to health and biomedical researchers, as well as R&D decision-makers in the UK and elsewhere. The study was completed with funding support from RAND Europe's Health R&D Policy Research Unit with the Department of Health. PMID:28083218

Safety leadership and systems thinking: application and evaluation of a Risk Management Framework in the mining industry.

PubMed

Donovan, Sarah-Louise; Salmon, Paul M; Lenné, Michael G; Horberry, Tim

2017-10-01

Safety leadership is an important factor in supporting safety in high-risk industries. This article contends that applying systems-thinking methods to examine safety leadership can support improved learning from incidents. A case study analysis was undertaken of a large-scale mining landslide incident in which no injuries or fatalities were incurred. A multi-method approach was adopted, in which the Critical Decision Method, Rasmussen's Risk Management Framework and Accimap method were applied to examine the safety leadership decisions and actions which enabled the safe outcome. The approach enabled Rasmussen's predictions regarding safety and performance to be examined in the safety leadership context, with findings demonstrating the distribution of safety leadership across leader and system levels, and the presence of vertical integration as key to supporting the successful safety outcome. In doing so, the findings also demonstrate the usefulness of applying systems-thinking methods to examine and learn from incidents in terms of what 'went right'. The implications, including future research directions, are discussed. Practitioner Summary: This paper presents a case study analysis, in which systems-thinking methods are applied to the examination of safety leadership decisions and actions during a large-scale mining landslide incident. The findings establish safety leadership as a systems phenomenon, and furthermore, demonstrate the usefulness of applying systems-thinking methods to learn from incidents in terms of what 'went right'. Implications, including future research directions, are discussed.

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.

SU-E-T-23: A Developing Australian Network for Datamining and Modelling Routine Radiotherapy Clinical Data and Radiomics Information for Rapid Learning and Clinical Decision Support

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

Thwaites, D; Holloway, L; Bailey, M

2015-06-15

Purpose: Large amounts of routine radiotherapy (RT) data are available, which can potentially add clinical evidence to support better decisions. A developing collaborative Australian network, with a leading European partner, aims to validate, implement and extend European predictive models (PMs) for Australian practice and assess their impact on future patient decisions. Wider objectives include: developing multi-institutional rapid learning, using distributed learning approaches; and assessing and incorporating radiomics information into PMs. Methods: Two initial standalone pilots were conducted; one on NSCLC, the other on larynx, patient datasets in two different centres. Open-source rapid learning systems were installed, for data extraction andmore » mining to collect relevant clinical parameters from the centres’ databases. The European DSSs were learned (“training cohort”) and validated against local data sets (“clinical cohort”). Further NSCLC studies are underway in three more centres to pilot a wider distributed learning network. Initial radiomics work is underway. Results: For the NSCLC pilot, 159/419 patient datasets were identified meeting the PM criteria, and hence eligible for inclusion in the curative clinical cohort (for the larynx pilot, 109/125). Some missing data were imputed using Bayesian methods. For both, the European PMs successfully predicted prognosis groups, but with some differences in practice reflected. For example, the PM-predicted good prognosis NSCLC group was differentiated from a combined medium/poor prognosis group (2YOS 69% vs. 27%, p<0.001). Stage was less discriminatory in identifying prognostic groups. In the good prognosis group two-year overall survival was 65% in curatively and 18% in palliatively treated patients. Conclusion: The technical infrastructure and basic European PMs support prognosis prediction for these Australian patient groups, showing promise for supporting future personalized treatment decisions, improved treatment quality and potential practice changes. The early indications from the distributed learning and radiomics pilots strengthen this. Improved routine patient data quality should strengthen such rapid learning systems.« less

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.

Proxy decision making and dementia: Using Construal Level Theory to analyse the thoughts of decision makers.

PubMed

Convey, Helen; Holt, Janet; Summers, Barbara

2018-07-01

This study explored the feasibility of using Construal Level Theory to analyse proxy decision maker thinking about a hypothetical ethical dilemma, relating to a person who has dementia. Proxy decision makers make decisions on behalf of individuals who are living with dementia when dementia affects that individual's decision making ability. Ethical dilemmas arise because there is a need to balance the individual's past and contemporary values and views. Understanding of how proxy decision makers respond is incomplete. Construal Level Theory contends that individuals imagine reactions and make predications about the future by crossing psychological distance. This involves abstract thinking, giving meaning to decisions. There is no empirical evidence of Construal Level Theory being used to analyse proxy decision maker thinking. Exploring the feasibility of using Construal Level Theory to understand dementia carer thinking regarding proxy decisions may provide insights which inform the support given. Descriptive qualitative research with semi-structured interviews. Seven participants were interviewed using a hypothetical dementia care scenario in February 2016. Interview transcripts were analysed for themes. Construal Level Theory was applied to analyse participant responses within themes using the Linguistic Category Model. Participants travelled across psychological distance, using abstract thinking to clarify goals and provide a basis for decisions. When thinking concretely participants established boundaries regarding the ethical dilemma. Construal Level Theory gives insight into proxy decision maker thinking and the levels of abstraction used. Understanding what dementia carers think about when making proxy decisions may help nurses to understand their perspectives and to provide appropriate support. © 2018 John Wiley & Sons Ltd.

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.

An Exploration of Radiation Physics in Electromagnetics

NASA Technical Reports Server (NTRS)

Lee, Katherine K.

2005-01-01

Contents include the following: NASA's Missions and Aeronautics Research. Today's Air Traffic Control System. Development of Decision-Support Tools. The Center-TRACON Automation System (CTAS). The Traffic Management Advisor (TMA). The Multi-Center Traffic Management Advisor (McTMA). The Surface Management System (SMS). Future Directions: The Joint Planning and Development Office.

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...

Uncertainty considerations in calibration and validation of hydrologic and water quality models

USDA-ARS?s Scientific Manuscript database

Hydrologic and water quality models (HWQMs) are increasingly used to support decisions on the state of various environmental issues and policy directions on present and future scenarios, at scales varying from watershed to continental levels. Uncertainty associated with such models may impact the ca...

Teaching Students to Analyze Agency Actions via a NEPA Analysis Approach

ERIC Educational Resources Information Center

Whitworth, Paul M.

2008-01-01

Future recreation professionals need the ability to analyze the effects of proposed management actions and stakeholder concerns to make good decisions, maintain public support, and comply with state and federal laws. Importantly, when federal funds, lands, permits or licenses are involved, federal law requires consideration of environmental and…

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…

DECISION-SUPPORT SOFTWARE FOR SOIL VAPOR EXTRACTION TECHNOLOGY APPLICATION: HYPERVENTILATE

EPA Science Inventory

The U.S. Environmental Protection Agency (EPA) estimate* that 15% to 20% of the approximately 1.7 million underground storage tank (UST) systems containing petroleum products are either leaking or will leak In the near future. These UST systems could pose a serious threat to p...

Building a computer program to support children, parents, and distraction during healthcare procedures.

PubMed

Hanrahan, Kirsten; McCarthy, Ann Marie; Kleiber, Charmaine; Ataman, Kaan; Street, W Nick; Zimmerman, M Bridget; Ersig, Anne L

2012-10-01

This secondary data analysis used data mining methods to develop predictive models of child risk for distress during a healthcare procedure. Data used came from a study that predicted factors associated with children's responses to an intravenous catheter insertion while parents provided distraction coaching. From the 255 items used in the primary study, 44 predictive items were identified through automatic feature selection and used to build support vector machine regression models. Models were validated using multiple cross-validation tests and by comparing variables identified as explanatory in the traditional versus support vector machine regression. Rule-based approaches were applied to the model outputs to identify overall risk for distress. A decision tree was then applied to evidence-based instructions for tailoring distraction to characteristics and preferences of the parent and child. The resulting decision support computer application, titled Children, Parents and Distraction, is being used in research. Future use will support practitioners in deciding the level and type of distraction intervention needed by a child undergoing a healthcare procedure.

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

The case of the downsizing decision.

PubMed

Train, A S

1991-01-01

New CEO Charles Rampart's decision to make deep across-the-board cuts at Universal Products Company, Ltd. presents division manager Andrew Jordan with a thorny problem. Plagued by slow growth, a declining stock price, and an increasingly skeptical investment community, UPC needs to control costs and control them fast. But Jordan's division is the most profitable in the company, and the 11% cut proposed by Rampart could destroy already shaky morale and seriously threaten the division's ability to compete. "There comes a time in every manager's career when he has to fight a bad decision made by his boss," argues Sam Godwyn, Jordan's vice president for marketing and sales. "To cut across the board is to take a blunt axe to the company when a surgeon's scalpel is called for." He suggests it is better to line up support for an alternative plan that links cuts to a long-term strategy and that differentiates between successful and unsuccessful divisions. "It would be a terrible mistake for us to focus only on the narrow needs of the division when the future of the whole company is at stake," counters Mary Wyatt, Jordan's vice president for finance. Yes, the downsizing will hurt the division in the short term, but the real issue is getting behind the new CEO. Supporting the downsizing decision is a necessary investment in this future credibility and effectiveness--whatever the short-term costs. Four commentators debate Jordan's dilemma and how he should resolve it.

Neural signatures of experience-based improvements in deterministic decision-making.

PubMed

Tremel, Joshua J; Laurent, Patryk A; Wolk, David A; Wheeler, Mark E; Fiez, Julie A

2016-12-15

Feedback about our choices is a crucial part of how we gather information and learn from our environment. It provides key information about decision experiences that can be used to optimize future choices. However, our understanding of the processes through which feedback translates into improved decision-making is lacking. Using neuroimaging (fMRI) and cognitive models of decision-making and learning, we examined the influence of feedback on multiple aspects of decision processes across learning. Subjects learned correct choices to a set of 50 word pairs across eight repetitions of a concurrent discrimination task. Behavioral measures were then analyzed with both a drift-diffusion model and a reinforcement learning model. Parameter values from each were then used as fMRI regressors to identify regions whose activity fluctuates with specific cognitive processes described by the models. The patterns of intersecting neural effects across models support two main inferences about the influence of feedback on decision-making. First, frontal, anterior insular, fusiform, and caudate nucleus regions behave like performance monitors, reflecting errors in performance predictions that signal the need for changes in control over decision-making. Second, temporoparietal, supplementary motor, and putamen regions behave like mnemonic storage sites, reflecting differences in learned item values that inform optimal decision choices. As information about optimal choices is accrued, these neural systems dynamically adjust, likely shifting the burden of decision processing from controlled performance monitoring to bottom-up, stimulus-driven choice selection. Collectively, the results provide a detailed perspective on the fundamental ability to use past experiences to improve future decisions. Copyright © 2016 Elsevier B.V. All rights reserved.

Neural signatures of experience-based improvements in deterministic decision-making

PubMed Central

Tremel, Joshua J.; Laurent, Patryk A.; Wolk, David A.; Wheeler, Mark E.; Fiez, Julie A.

2016-01-01

Feedback about our choices is a crucial part of how we gather information and learn from our environment. It provides key information about decision experiences that can be used to optimize future choices. However, our understanding of the processes through which feedback translates into improved decision-making is lacking. Using neuroimaging (fMRI) and cognitive models of decision-making and learning, we examined the influence of feedback on multiple aspects of decision processes across learning. Subjects learned correct choices to a set of 50 word pairs across eight repetitions of a concurrent discrimination task. Behavioral measures were then analyzed with both a drift-diffusion model and a reinforcement learning model. Parameter values from each were then used as fMRI regressors to identify regions whose activity fluctuates with specific cognitive processes described by the models. The patterns of intersecting neural effects across models support two main inferences about the influence of feedback on decision-making. First, frontal, anterior insular, fusiform, and caudate nucleus regions behave like performance monitors, reflecting errors in performance predictions that signal the need for changes in control over decision-making. Second, temporoparietal, supplementary motor, and putamen regions behave like mnemonic storage sites, reflecting differences in learned item values that inform optimal decision choices. As information about optimal choices is accrued, these neural systems dynamically adjust, likely shifting the burden of decision processing from controlled performance monitoring to bottom-up, stimulus-driven choice selection. Collectively, the results provide a detailed perspective on the fundamental ability to use past experiences to improve future decisions. PMID:27523644

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

Coordinated Development and Deployment of Scenarios for Sustained Assessment

NASA Astrophysics Data System (ADS)

Lipschultz, F.; Weaver, C. P.; Leidner, A. K.; Delgado, A.; Grambsch, A.

2017-12-01

There has been a clear need for a more coordinated Federal government approach for authoritative, climate-relevant scenarios to support growing demands by decision-makers, to meet stakeholder needs for consistent approaches and guidance, and to better address the needs of the impacts, adaptation and vulnerability community. To begin to satisfy these decision-support needs, in early 2015 the U.S. Global Change Research Program (USGCRP) began coordinated production of scenario information for use across a suite of USGCRP activities. These have been implemented in the 4th National Climate Assessment (NCA4), the Climate Science Special Report and the Climate Resilience Toolkit (CRT), all of which are intended to help better organize, summarize, and communicate science to decision-makers as they think about our future. First, USGCRP introduced and implemented an explicit risk-framing approach across the entire scenario enterprise to encourage exploration of tail risks. A suite of scenario products was developed framed around three simplified storylines: `Lower', `Higher', and `Upper Bound' departures from current baselines. Second, USGCRP developed future climate information for the U.S. using Representative Concentration Pathway (RCP) 8.5 and RCP 4.5, including a weighted mean of Global Climate Models and adoption of an improved statistical downscaling approach across USGCRP products. Additional variables were derived from the downscaled parameters for use across USGCRP reports and in the CRT's Climate Explorer tool. Third, and given the need to address other tightly-coupled global changes in a more integrated way, a set of population, housing density, and impervious surface projections were developed based on global scenarios. In addition, USGCRP and the National Ocean Council developed scenarios of future sea-level rise and coastal-flood hazard for the U.S. and integrated them into existing Federal capabilities to support preparedness planning. To better convey these scenario components, next steps include capability for dynamic interaction between NCA4 products and CRT to permit users to explore and customize relevant information for their decision at spatial scales that matter to them, as well as links to more in-depth CRT content.

Evaluating the Utility of Web-Based Consumer Support Tools Using Rough Sets

NASA Astrophysics Data System (ADS)

Maciag, Timothy; Hepting, Daryl H.; Slezak, Dominik; Hilderman, Robert J.

On the Web, many popular e-commerce sites provide consumers with decision support tools to assist them in their commerce-related decision-making. Many consumers will rank the utility of these tools quite highly. Data obtained from web usage mining analyses, which may provide knowledge about a user's online experiences, could help indicate the utility of these tools. This type of analysis could provide insight into whether provided tools are adequately assisting consumers in conducting their online shopping activities or if new or additional enhancements need consideration. Although some research in this regard has been described in previous literature, there is still much that can be done. The authors of this paper hypothesize that a measurement of consumer decision accuracy, i.e. a measurement preferences, could help indicate the utility of these tools. This paper describes a procedure developed towards this goal using elements of rough set theory. The authors evaluated the procedure using two support tools, one based on a tool developed by the US-EPA and the other developed by one of the authors called cogito. Results from the evaluation did provide interesting insights on the utility of both support tools. Although it was shown that the cogito tool obtained slightly higher decision accuracy, both tools could be improved from additional enhancements. Details of the procedure developed and results obtained from the evaluation will be provided. Opportunities for future work are also discussed.

NASA Applied Sciences Program Rapid Prototyping Results and Conclusions

NASA Astrophysics Data System (ADS)

Cox, E. L.

2007-12-01

NASA's Applied Sciences Program seeks to expand the use of Earth science research results to benefit current and future operational systems tasked with making policy and management decisions. The Earth Science Division within the Science Mission Directorate sponsors over 1000 research projects annually to answer the fundamental research question: How is the Earth changing and what are the consequences for life on Earth? As research results become available, largely from satellite observations and Earth system model outputs, the Applied Sciences Program works diligently with scientists and researchers (internal and external to NASA) , and other government agency officials (USDA, EPA, CDC, DOE, US Forest Service, US Fish and Wildlife Service, DHS, USAID) to determine useful applications for these results in decision-making, ultimately benefiting society. The complexity of Earth science research results and the breadth of the Applied Sciences Program national priority areas dictate a broad scope and multiple approaches available to implement their use in decision-making. Over the past five years, the Applied Sciences Program has examined scientific and engineering practices and solicited the community for methods and steps that can lead to the enhancement of operational systems (Decision Support Systems - DSS) required for decision-making. In November 2006, the Applied Sciences Program launched an initiative aimed at demonstrating the applicability of NASA data (satellite observations, models, geophysical parameters from data archive centers) being incorporated into decision support systems and their related environments at a low cost and quick turnaround of results., i.e. designed rapid prototyping. Conceptually, an understanding of Earth science research (and results) coupled with decision-making requirements and needs leads to a demonstration (experiment) depicting enhancements or improvements to an operational decisions process through the use of NASA data. Five NASA centers (GSFC, LaRC, SSC, MSFC, ARC) participated and are currently conducting fifteen prototyping experiments covering eight of the twelve national priority applications - Energy, Coastal, Carbon, and Disaster Management; Agricultural Efficiency, Aviation, Air Quality, and Ecological Forecasting. Results from six experiments will be discussed highlighting purpose, expected results, enhancement to the decision-making process achieved, and the potential plans for future collaboration and sustainable projects.

Near-Term Actions to Address Long-Term Climate Risk

NASA Astrophysics Data System (ADS)

Lempert, R. J.

2014-12-01

Addressing climate change requires effective long-term policy making, which occurs when reflecting on potential events decades or more in the future causes policy makers to choose near-term actions different than those they would otherwise pursue. Contrary to some expectations, policy makers do sometimes make such long-term decisions, but not as commonly and successfully as climate change may require. In recent years however, the new capabilities of analytic decision support tools, combined with improved understanding of cognitive and organizational behaviors, has significantly improved the methods available for organizations to manage longer-term climate risks. In particular, these tools allow decision makers to understand what near-term actions consistently contribute to achieving both short- and long-term societal goals, even in the face of deep uncertainty regarding the long-term future. This talk will describe applications of these approaches for infrastructure, water, and flood risk management planning, as well as studies of how near-term choices about policy architectures can affect long-term greenhouse gas emission reduction pathways.

A formal framework for scenario development in support of environmental decision-making

USGS Publications Warehouse

Mahmoud, M.; Liu, Yajing; Hartmann, H.; Stewart, S.; Wagener, T.; Semmens, D.; Stewart, R.; Gupta, H.; Dominguez, D.; Dominguez, F.; Hulse, D.; Letcher, R.; Rashleigh, Brenda; Smith, C.; Street, R.; Ticehurst, J.; Twery, M.; van, Delden H.; Waldick, R.; White, D.; Winter, L.

2009-01-01

Scenarios are possible future states of the world that represent alternative plausible conditions under different assumptions. Often, scenarios are developed in a context relevant to stakeholders involved in their applications since the evaluation of scenario outcomes and implications can enhance decision-making activities. This paper reviews the state-of-the-art of scenario development and proposes a formal approach to scenario development in environmental decision-making. The discussion of current issues in scenario studies includes advantages and obstacles in utilizing a formal scenario development framework, and the different forms of uncertainty inherent in scenario development, as well as how they should be treated. An appendix for common scenario terminology has been attached for clarity. Major recommendations for future research in this area include proper consideration of uncertainty in scenario studies in particular in relation to stakeholder relevant information, construction of scenarios that are more diverse in nature, and sharing of information and resources among the scenario development research community. ?? 2008 Elsevier Ltd.

Patchy 'coherence': using normalization process theory to evaluate a multi-faceted shared decision making implementation program (MAGIC).

PubMed

Lloyd, Amy; Joseph-Williams, Natalie; Edwards, Adrian; Rix, Andrew; Elwyn, Glyn

2013-09-05

Implementing shared decision making into routine practice is proving difficult, despite considerable interest from policy-makers, and is far more complex than merely making decision support interventions available to patients. Few have reported successful implementation beyond research studies. MAking Good Decisions In Collaboration (MAGIC) is a multi-faceted implementation program, commissioned by The Health Foundation (UK), to examine how best to put shared decision making into routine practice. In this paper, we investigate healthcare professionals' perspectives on implementing shared decision making during the MAGIC program, to examine the work required to implement shared decision making and to inform future efforts. The MAGIC program approached implementation of shared decision making by initiating a range of interventions including: providing workshops; facilitating development of brief decision support tools (Option Grids); initiating a patient activation campaign ('Ask 3 Questions'); gathering feedback using Decision Quality Measures; providing clinical leads meetings, learning events, and feedback sessions; and obtaining executive board level support. At 9 and 15 months (May and November 2011), two rounds of semi-structured interviews were conducted with healthcare professionals in three secondary care teams to explore views on the impact of these interventions. Interview data were coded by two reviewers using a framework derived from the Normalization Process Theory. A total of 54 interviews were completed with 31 healthcare professionals. Partial implementation of shared decision making could be explained using the four components of the Normalization Process Theory: 'coherence,' 'cognitive participation,' 'collective action,' and 'reflexive monitoring.' Shared decision making was integrated into routine practice when clinical teams shared coherent views of role and purpose ('coherence'). Shared decision making was facilitated when teams engaged in developing and delivering interventions ('cognitive participation'), and when those interventions fit with existing skill sets and organizational priorities ('collective action') resulting in demonstrable improvements to practice ('reflexive monitoring'). The implementation process uncovered diverse and conflicting attitudes toward shared decision making; 'coherence' was often missing. The study showed that implementation of shared decision making is more complex than the delivery of patient decision support interventions to patients, a portrayal that often goes unquestioned. Normalizing shared decision making requires intensive work to ensure teams have a shared understanding of the purpose of involving patients in decisions, and undergo the attitudinal shifts that many health professionals feel are required when comprehension goes beyond initial interpretations. Divergent views on the value of engaging patients in decisions remain a significant barrier to implementation.

Patchy ‘coherence’: using normalization process theory to evaluate a multi-faceted shared decision making implementation program (MAGIC)

PubMed Central

2013-01-01

Background Implementing shared decision making into routine practice is proving difficult, despite considerable interest from policy-makers, and is far more complex than merely making decision support interventions available to patients. Few have reported successful implementation beyond research studies. MAking Good Decisions In Collaboration (MAGIC) is a multi-faceted implementation program, commissioned by The Health Foundation (UK), to examine how best to put shared decision making into routine practice. In this paper, we investigate healthcare professionals’ perspectives on implementing shared decision making during the MAGIC program, to examine the work required to implement shared decision making and to inform future efforts. Methods The MAGIC program approached implementation of shared decision making by initiating a range of interventions including: providing workshops; facilitating development of brief decision support tools (Option Grids); initiating a patient activation campaign (‘Ask 3 Questions’); gathering feedback using Decision Quality Measures; providing clinical leads meetings, learning events, and feedback sessions; and obtaining executive board level support. At 9 and 15 months (May and November 2011), two rounds of semi-structured interviews were conducted with healthcare professionals in three secondary care teams to explore views on the impact of these interventions. Interview data were coded by two reviewers using a framework derived from the Normalization Process Theory. Results A total of 54 interviews were completed with 31 healthcare professionals. Partial implementation of shared decision making could be explained using the four components of the Normalization Process Theory: ‘coherence,’ ‘cognitive participation,’ ‘collective action,’ and ‘reflexive monitoring.’ Shared decision making was integrated into routine practice when clinical teams shared coherent views of role and purpose (‘coherence’). Shared decision making was facilitated when teams engaged in developing and delivering interventions (‘cognitive participation’), and when those interventions fit with existing skill sets and organizational priorities (‘collective action’) resulting in demonstrable improvements to practice (‘reflexive monitoring’). The implementation process uncovered diverse and conflicting attitudes toward shared decision making; ‘coherence’ was often missing. Conclusions The study showed that implementation of shared decision making is more complex than the delivery of patient decision support interventions to patients, a portrayal that often goes unquestioned. Normalizing shared decision making requires intensive work to ensure teams have a shared understanding of the purpose of involving patients in decisions, and undergo the attitudinal shifts that many health professionals feel are required when comprehension goes beyond initial interpretations. Divergent views on the value of engaging patients in decisions remain a significant barrier to implementation. PMID:24006959

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.

Automated Modular Magnetic Resonance Imaging Clinical Decision Support System (MIROR): An Application in Pediatric Cancer Diagnosis

PubMed Central

Zarinabad, Niloufar; Meeus, Emma M; Manias, Karen; Foster, Katharine

2018-01-01

Background Advances in magnetic resonance imaging and the introduction of clinical decision support systems has underlined the need for an analysis tool to extract and analyze relevant information from magnetic resonance imaging data to aid decision making, prevent errors, and enhance health care. Objective The aim of this study was to design and develop a modular medical image region of interest analysis tool and repository (MIROR) for automatic processing, classification, evaluation, and representation of advanced magnetic resonance imaging data. Methods The clinical decision support system was developed and evaluated for diffusion-weighted imaging of body tumors in children (cohort of 48 children, with 37 malignant and 11 benign tumors). Mevislab software and Python have been used for the development of MIROR. Regions of interests were drawn around benign and malignant body tumors on different diffusion parametric maps, and extracted information was used to discriminate the malignant tumors from benign tumors. Results Using MIROR, the various histogram parameters derived for each tumor case when compared with the information in the repository provided additional information for tumor characterization and facilitated the discrimination between benign and malignant tumors. Clinical decision support system cross-validation showed high sensitivity and specificity in discriminating between these tumor groups using histogram parameters. Conclusions MIROR, as a diagnostic tool and repository, allowed the interpretation and analysis of magnetic resonance imaging images to be more accessible and comprehensive for clinicians. It aims to increase clinicians’ skillset by introducing newer techniques and up-to-date findings to their repertoire and make information from previous cases available to aid decision making. The modular-based format of the tool allows integration of analyses that are not readily available clinically and streamlines the future developments. PMID:29720361

Testing the hierarchy of effects model: ParticipACTION's serial mass communication campaigns on physical activity in Canada.

PubMed

Craig, C L; Bauman, A; Reger-Nash, B

2010-03-01

The hierarchy of effects (HOE) model is often used in planning mass-reach communication campaigns to promote health, but has rarely been empirically tested. This paper examines Canada's 30 year ParticipACTION campaign to promote physical activity (PA). A cohort from the nationally representative 1981 Canada Fitness Survey was followed up in 1988 and 2002-2004. Modelling of these data tested whether the mechanisms of campaign effects followed the theoretical framework proposed in the HOE. Campaign awareness was measured in 1981. Outcome expectancy, attitudes, decision balance and future intention were asked in 1988. PA was assessed at all time points. Logistic regression was used to sequentially test mediating and moderating variables adjusting for age, sex and education. No selection bias was observed; however, relatively fewer respondents than non-respondents smoked or were underweight at baseline. Among those inactive at baseline, campaign awareness predicted outcome expectancy which in turn predicted positive attitude to PA. Positive attitudes predicted high decision balance, which predicted future intention. Future intention mediated the relationship between decision balance and sufficient activity. Among those sufficiently active at baseline, awareness was unrelated to outcome expectancy and inversely related to positive attitude. These results lend support to the HOE model, in that the effects of ParticipACTION's serial mass media campaigns were consistent with the sequential rollout of its messages, which in turn was associated with achieving an active lifestyle among those initially insufficiently active. This provides support to an often-used theoretical framework for designing health promotion media campaigns.

A review of fuzzy cognitive maps in medicine: Taxonomy, methods, and applications.

PubMed

Amirkhani, Abdollah; Papageorgiou, Elpiniki I; Mohseni, Akram; Mosavi, Mohammad R

2017-04-01

A high percentage of medical errors, committed because of physician's lack of experience, huge volume of data to be analyzed, and inaccessibility to medical records of previous patients, can be reduced using computer-aided techniques. Therefore, designing more efficient medical decision-support systems (MDSSs) to assist physicians in decision-making is crucially important. Through combining the properties of fuzzy logic and neural networks, fuzzy cognitive maps (FCMs) are among the latest, most efficient, and strongest artificial intelligence techniques for modeling complex systems. This review study is conducted to identify different FCM structures used in MDSS designs. The best structure for each medical application can be introduced by studying the properties of FCM structures. This paper surveys the most important decision- making methods and applications of FCMs in the medical field in recent years. To investigate the efficiency and capability of different FCM models in designing MDSSs, medical applications are categorized into four key areas: decision-making, diagnosis, prediction, and classification. Also, various diagnosis and decision support problems addressed by FCMs in recent years are reviewed with the goal of introducing different types of FCMs and determining their contribution to the improvements made in the fields of medical diagnosis and treatment. In this survey, a general trend for future studies in this field is provided by analyzing various FCM structures used for medical purposes, and the results from each category. Due to the unique specifications of FCMs in integrating human knowledge and experience with computer-aided techniques, they are among practical instruments for MDSS design. In the not too distant future, they will have a significant role in medical sciences. Copyright © 2017 Elsevier B.V. All rights reserved.

Factors influencing men undertaking active surveillance for the management of low-risk prostate cancer.

PubMed

Davison, B Joyce; Oliffe, John L; Pickles, Tom; Mroz, Lawrence

2009-01-01

To identify and describe decision-making influences on men who decide to manage their low-risk prostate cancer with active surveillance. Qualitative, semistructured interview. The Prostate Centre at Vancouver General Hospital in Canada. 25 patients diagnosed with low-risk prostate cancer and on active surveillance. An interpretative, descriptive, qualitative design. Factors that influenced men's decisions to take up active surveillance. The specialists' description of the prostate cancer was the most influential factor on men choosing active surveillance. Patients did not consider their prostate cancer to be life threatening and, in general, were relieved that no treatment was required. Avoiding treatment-related suffering and physical dysfunction and side effects such as impotence and incontinence was cited as the major reason to delay treatment. Few men actively sought treatment or health-promotion information following their treatment decision. Female partners played a supportive role in the decision. The need for active treatment if the cancer progressed was acknowledged. Patients were hopeful that new treatments would be available when and if they needed them. Being older and having comorbidities did not preclude the desire for future active treatment. Patients carried on with their lives as usual and did not report having any major distress related to being on active surveillance. The study findings indicate that men are strongly influenced by the treating specialist in taking up active surveillance and planning future active treatments. As such, most men relied on their specialists' recommendation and did not perceive the need for any adjunct therapy or support until the cancer required active treatment. Oncology nurses should work collaborative-ly with specialists to ensure that men receive the information they need to make informed treatment decisions.

Space station systems analysis study. Part 1, volume 1: Executive study

NASA Technical Reports Server (NTRS)

1976-01-01

Potential space station system options were examined for a permanent, manned, orbital space facility and to provide data to NASA program planners and decision makers for their use in future program planning. There were ten space station system objectives identified. These were categorized into five major objectives and five supporting objectives. The major objectives were to support the development of: (1) satellite power systems, (2) nuclear energy plants in space, (3) space processing, (4) earth services, and (5) space cosmological research and development. The five supporting objectives, to define space facilities which would be basic building blocks for future systems, were: (1) a multidiscipline science laboratory, (2) an orbital depot to maintain, fuel, and service orbital transfer vehicles, (3) cluster support systems to provide power and data processing for multiple orbital elements, (4) a sensor development facility, and (5) the facilities necessary to enhance man's living and working in space.

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

Moral disengagement in ethical decision making: a study of antecedents and outcomes.

PubMed

Detert, James R; Treviño, Linda Klebe; Sweitzer, Vicki L

2008-03-01

This article advances understanding of the antecedents and outcomes of moral disengagement by testing hypotheses with 3 waves of survey data from 307 business and education undergraduate students. The authors theorize that 6 individual differences will either increase or decrease moral disengagement, defined as a set of cognitive mechanisms that deactivate moral self-regulatory processes and thereby help to explain why individuals often make unethical decisions without apparent guilt or self-censure (Bandura, 1986). Results support 4 individual difference hypotheses, specifically, that empathy and moral identity are negatively related to moral disengagement, while trait cynicism and chance locus of control orientation are positively related to moral disengagement. Two additional locus of control orientations are not significantly related to moral disengagement. The authors also hypothesize and find that moral disengagement is positively related to unethical decision making. Finally, the authors hypothesize that moral disengagement plays a mediating role between the individual differences they studied and unethical decisions. Their results offer partial support for these mediating hypotheses. The authors discuss the implications of these findings for future research and for practice. Copyright 2008 APA

Future perspectives toward the early definition of a multivariate decision-support scheme employed in clinical decision making for senior citizens.

PubMed

Frantzidis, Christos A; Gilou, Sotiria; Billis, Antonis; Karagianni, Maria; Bratsas, Charalampos D; Bamidis, Panagiotis

2016-03-01

Recent neuroscientific studies focused on the identification of pathological neurophysiological patterns (emotions, geriatric depression, memory impairment and sleep disturbances) through computerised clinical decision-support systems. Almost all these research attempts employed either resting-state condition (e.g. eyes-closed) or event-related potentials extracted during a cognitive task known to be affected by the disease under consideration. This Letter reviews existing data mining techniques and aims to enhance their robustness by proposing a holistic decision framework dealing with comorbidities and early symptoms' identification, while it could be applied in realistic occasions. Multivariate features are elicited and fused in order to be compared with average activities characteristic of each neuropathology group. A proposed model of the specific cognitive function which may be based on previous findings (a priori information) and/or validated by current experimental data should be then formed. So, the proposed scheme facilitates the early identification and prevention of neurodegenerative phenomena. Neurophysiological semantic annotation is hypothesised to enhance the importance of the proposed framework in facilitating the personalised healthcare of the information society and medical informatics research community.

[Treatment Decision-Making Process of Cancer Patients].

PubMed

Lee, Shiu-Yu C Katie

2016-10-01

The decision-making process that is used by cancer patients to determine their treatment has become more multi-foci, difficult and complicated in recent years. This has in part been attributed to the increasing incidence rate of cancer in Taiwan and the rapid development of medical technologies and treatment modalities. Oncology nurses must assist patients and family to make informed and value-based treatment decisions. Decision-making is an information process that involves appraising one's own expectation and values based on his/her knowledge on cancer and treatment options. Because cancer treatment involves risks and uncertainties, and impacts quality of life, the treatment decision-making for cancer is often stressful, or even conflicting. This paper discusses the decision-making behaviors of cancer patients and the decisional conflict, participation, and informational needs that are involved in cancer treatment. The trend toward shared decision-making and decisional support will be also explored in order to facilitate the future development of appropriate clinical interventions and research.

Managing cancer and employment: Decisions and strategies used by breast cancer survivors employed in low-wage jobs

PubMed Central

Swanberg, Jennifer E.; Nichols, Helen M.; Ko, Jungyai; Tracy, J. Kathleen; Vanderpool, Robin C.

2017-01-01

Advances in breast cancer screening and treatment have led to an overall 5-year survival rate of 90%. Many of these cancer cases are diagnosed in working women. Few studies have explicitly examined the cancer–work interface, as experienced by low-wage earning women with breast cancer. This study uses in-depth, semistructured interviews with 24 low-wage breast cancer survivors to identify employment decisions and factors that influenced or enabled these decisions, and examine the individual strategies and workplace supports used to manage the cancer–work interface among a subset of women (n = 13) who continued to work. Future research areas and clinical implications are discussed. PMID:28045595

Managing cancer and employment: Decisions and strategies used by breast cancer survivors employed in low-wage jobs.

PubMed

Swanberg, Jennifer E; Nichols, Helen M; Ko, Jungyai; Tracy, J Kathleen; Vanderpool, Robin C

2017-01-01

Advances in breast cancer screening and treatment have led to an overall 5-year survival rate of 90%. Many of these cancer cases are diagnosed in working women. Few studies have explicitly examined the cancer-work interface, as experienced by low-wage earning women with breast cancer. This study uses in-depth, semistructured interviews with 24 low-wage breast cancer survivors to identify employment decisions and factors that influenced or enabled these decisions, and examine the individual strategies and workplace supports used to manage the cancer-work interface among a subset of women (n = 13) who continued to work. Future research areas and clinical implications are discussed.

SUSTAINABLE MANAGEMENT APPROACHES AND REVITALIZATION TOOLS - ELECTRONIC (SMARTE), A DECISION SUPPORT TOOL TO EVALUATE FUTURE REUSE SCENARIOS

EPA Science Inventory

In 2000, the United States Environmental Protection Agency (EPA) and the German Federal Ministry of Education and Research (BMBF) began Phase 3 of the U.S.-German Bilateral Working Group. EPA and BMBF have an ongoing partnership designed to gain an understanding of each country's...

EPA leadership on Science, Innovation, and Decision Support Tools for Addressing Current and Future Challenges

EPA Science Inventory

When the U.S. Environmental Protection Agency (EPA) was established nearly 50 years ago, the nation faced serious threats to its air, land, and water, which in turn impacted human health. These threats were effectively addressed by the creation of EPA (in 1970) and many subsequen...

Supporting and Preparing Future First-Generation College Students in the High School Environment: Implications for School Counselors

ERIC Educational Resources Information Center

Bryant, Jill K.; Nicolas, Joanna

2011-01-01

This study surveyed college freshmen from two different institutions in order to examine differences between First-Generation College Students and Continuing-Generation College Students. Differences between groups emerged for high school academic preparation, college exploration behaviors, college application behaviors, and college decision-making…

Group Action Planning: An Innovative Manual for Building a Self-Determined Future.

ERIC Educational Resources Information Center

Anderson, Emma Longan; And Others

This manual is designed to provide adolescents and young adults who have disabilities with a blueprint for setting and achieving goals, making decisions, acquiring needed supports, and achieving a self-determined and sustainable lifestyle. A planning process called Group Action Planning is used as a foundation for self-determination, with…

Using decision analysis to support proactive management of emerging infectious wildlife diseases

Treesearch

Evan H Campbell Grant; Erin Muths; Rachel A Katz; Stefano Canessa; Michael J Adams; Jennifer R Ballard; Lee Berger; Cheryl J Briggs; Jeremy TH Coleman; Matthew J Gray; M Camille Harris; Reid N Harris; Blake Hossack; Kathryn P Huyvaert; Jonathan Kolby; Karen R Lips; Robert E Lovich; Hamish I McCallum; Joseph R Mendelson; Priya Nanjappa; Deanna H Olson; Jenny G Powers; Katherine LD Richgels; Robin E Russell; Benedikt R Schmidt; Annemarieke Spitzen-van der Sluijs; Mary Kay Watry; Douglas C Woodhams; C LeAnn White

2017-01-01

Despite calls for improved responses to emerging infectious diseases in wildlife, management is seldom considered until a disease has been detected in affected populations. Reactive approaches may limit the potential for control and increase total response costs. An alternative, proactive management framework can identify immediate actions that reduce future impacts...

NED-2 User's Guide

Treesearch

Mark J. Twery; Peter D. Knopp; Scott A. Thomasma; Donald E. Nute

2011-01-01

This is the user's guide for NED-2, which is the latest version of NED, a forest ecosystem management decision support system. This software is part of a family of software products intended to help resource managers develop goals, assess current and future conditions, and produce sustainable management plans for forest properties. Designed for stand-alone Windows...

NED-2 reference guide

Treesearch

Mark J. Twery; Peter D. Knopp; Scott A. Thomasma; Donald E. Nute

2012-01-01

This is the reference guide for NED-2, which is the latest version of NED, a forest ecosystem management decision support system. This software is part of a family of software products intended to help resource managers develop goals, assess current and future conditions, and produce sustainable management plans for forest properties. Designed for stand-alone Windows-...

Strategic Human Resource Planning in Academia

ERIC Educational Resources Information Center

Ulferts, Gregory; Wirtz, Patrick; Peterson, Evan

2009-01-01

A strategic plan guides a college in successfully meeting its mission. Based on the strategic plan, a college can develop a human resource plan that will allow it to make management decisions in the present to support the future direction of the college. The overall purpose of human resource management is to: (1) ensure the organization has…

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.

Climate Modeling and Analysis with Decision Makers in Mind

NASA Astrophysics Data System (ADS)

Jones, A. D.; Jagannathan, K.; Calvin, K. V.; Lamarque, J. F.; Ullrich, P. A.

2016-12-01

There is a growing need for information about future climate conditions to support adaptation planning across a wide range of sectors and stakeholder communities. However, our principal tools for understanding future climate - global Earth system models - were not developed with these user needs in mind, nor have we developed transparent methods for evaluating and communicating the credibility of various climate information products with respect to the climate characteristics that matter most to decision-makers. Several recent community engagements have identified a need for "co-production" of knowledge among stakeholders and scientists. Here we highlight some of the barriers to communication and collaboration that must be overcome to improve the dialogue among researchers and climate adaptation practitioners in a meaningful way. Solutions to this challenge are two-fold: 1) new institutional arrangements and collaborative mechanisms designed to improve coordination and understanding among communities, and 2) a research agenda that explicitly incorporates stakeholder needs into model evaluation, development, and experimental design. We contrast the information content in global-scale model evaluation exercises with that required for in specific decision contexts, such as long-term agricultural management decisions. Finally, we present a vision for advancing the science of model evaluation in the context of predicting decision-relevant hydroclimate regime shifts in North America.

Optimizing farm landscape by two decision-support tools for present and future: A case study in a mountainous farm of Taiwan

NASA Astrophysics Data System (ADS)

Chou, S.; Lin, Y.

2013-12-01

Rapid expansion of agricultural land-use has been identified as the main factor degrading biodiversity. Many studies have indicated that habitat quality and connectivity for multiple species can be preserved by applying the systematic conservation planning and software programs for spatial conservation prioritizations are usually used by planners to solve conservation problems for present and future. However, each conservation software program uses different algorithms and may not be suitable or efficient for all case studies. Therefore, in this study we compared the performance of two commonly used decision-support tools, Marxan and Zonation, on identifying priority areas as reserve region for 16 bird species in the mountain area of Taiwan. The priority areas are considered as the results of the tradeoff between bird presence (biological factor) and agricultural products (economic factor). Marxan uses the minimum set approach to identify priority areas for meeting specific targets while Zonation uses the maximum coverage approach to identify priority areas given a fixed budget. Therefore, we design the scenario with the most comparable setting, which selects target-based planning as the removal rule and boundary length penalty option in zonation. The landscape composition and configuration of the simulated priority areas were further evaluated by using landscape metrics and their similarity were examined by using Spearman's rank tests. The results showed that Marxan performed more efficiently while Zonation generated the priority areas in better connectivity. As the selection of conservation programs depends on users objectives and needs for present and future, this study provides useful information on determining suitable and efficient decision-support tools for future bird conservation. Conservation maps for Zonation based on different BLP parameter. The conservation value for Zonation is based on the hierarchical solution output. (a)BLP =1000 (b)BLP =3000 (c)BLP =5000 (d)BLP =7000 Conservation maps for Marxan based on different BMP parameter. The conservation value for Marxan is based on the selection frequency. (a)BMP =2500 (b)BMP =5000 (c)BMP =7500 (d)BMP =10000

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.

Future Secretariat: an innovation research coordination and governance structure

NASA Astrophysics Data System (ADS)

Ojima, D. S.; Johan, R.; Cramer, W.; Fukushi, K.; Allard, S.

2014-12-01

Future Earth, an emerging global sustainability research program, will be managed by a novel, internationally distributed secretariat spanning the globe and providing a platform for co-design, co-production, and co-delivery of knowledge to support research on the earth system, global development and transformation toward sustainability. The Future Earth secretariat has an innovative structure consisting of five global hubs functioning as a single entity; these hubs are located in Canada, Japan, France, Sweden, and the United States. The secretariat's reach is extended through a set of regional hubs covering Latin America, the Middle East, Africa, Europe, and Asia, with the potential to expand to additional areas. This secretariat will operate under the auspices of the Future Earth Governing Council The Future Earth Secretariat will support and enable the implementation of knowledge-sharing between research and stakeholder communities to enable society to cope with and to alter global environmental trends, and to transition society toward sustainability. The secretariat will provide coordination support to over 25 global environmental core projects and committees; coordinate scientific work across the whole Future Earth agenda; develop and implement innovative mechanisms for bottom-up inputs, synthesis and integration. Future Earth, as a research program, aims to support global transformations toward sustainability through partnerships among scientific and stakeholder communities worldwide. It brings together existing international environmental research core projects associated with DIVERSITAS, the International Geosphere-Biosphere Programme, the International Human Dimensions Programme, and the World Climate Research Programme—to support coordinated, interdisciplinary research that can be used by decision makers seeking to reduce their impact and provide more sustainable products and services. USGCRP partners with Future Earth through scientific participation in and annual funding for its constituent programs.

From science to action: Principles for undertaking environmental research that enables knowledge exchange and evidence-based decision-making.

PubMed

Cvitanovic, C; McDonald, J; Hobday, A J

2016-12-01

Effective conservation requires knowledge exchange among scientists and decision-makers to enable learning and support evidence-based decision-making. Efforts to improve knowledge exchange have been hindered by a paucity of empirically-grounded guidance to help scientists and practitioners design and implement research programs that actively facilitate knowledge exchange. To address this, we evaluated the Ningaloo Research Program (NRP), which was designed to generate new scientific knowledge to support evidence-based decisions about the management of the Ningaloo Marine Park in north-western Australia. Specifically, we evaluated (1) outcomes of the NRP, including the extent to which new knowledge informed management decisions; (2) the barriers that prevented knowledge exchange among scientists and managers; (3) the key requirements for improving knowledge exchange processes in the future; and (4) the core capacities that are required to support knowledge exchange processes. While the NRP generated expansive and multidisciplinary science outputs directly relevant to the management of the Ningaloo Marine Park, decision-makers are largely unaware of this knowledge and little has been integrated into decision-making processes. A range of barriers prevented efficient and effective knowledge exchange among scientists and decision-makers including cultural differences among the groups, institutional barriers within decision-making agencies, scientific outputs that were not translated for decision-makers and poor alignment between research design and actual knowledge needs. We identify a set of principles to be implemented routinely as part of any applied research program, including; (i) stakeholder mapping prior to the commencement of research programs to identify all stakeholders, (ii) research questions to be co-developed with stakeholders, (iii) implementation of participatory research approaches, (iv) use of a knowledge broker, and (v) tailored knowledge management systems. Finally, we articulate the individual, institutional and financial capacities that must be developed to underpin successful knowledge exchange strategies. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

The impact of DECISION+2 on patient intention to engage in shared decision making: secondary analysis of a multicentre clustered randomized trial.

PubMed

Couët, Nicolas; Labrecque, Michel; Robitaille, Hubert; Turcotte, Stéphane; Légaré, France

2015-12-01

Training health professionals in shared decision making (SDM) may influence their patients' intention to engage in SDM. To assess the impact of DECISION+2, a SDM training programme for family physicians about the use of antibiotics to treat acute respiratory infections (ARIs), on their patients' intention to engage in SDM in future consultations. Secondary analysis of a multicentre clustered randomized trial. Three hundred and fifty-nine patients consulting family physicians about an ARI in nine family practice teaching units (FPTUs). DECISION+2 (two-hour online tutorial, two-hour workshop, and decision support tools) was offered in the experimental group (five FPTUs, 162 physicians, 181 patients). Usual care was provided in the control group (four FPTUs, 108 physicians, 178 patients). Change in patients' intention scores (range -3 to +3) between pre- and post-consultation. The mean ± SD [median] scores of intention to engage in SDM were high in both study groups before consultation (DECISION+2 group: 1.4 ± 1.0 [1.7]; control group: 1.5 ± 1.1 [1.7]) and increased in both groups after consultation (DECISION+2 group: 2.1 ± 1.1 [2.7]; control group: 1.9 ± 1.2 [2.3]). Change of intention, classified as either increased, stable or decreased, was not statistically associated with the exposure to the DECISION+2 programme after adjusting for the cluster design (proportional odds ratio = 1.5; 95% confidence interval = 0.8-3.0). DECISION+2 had no significant impact on patients' intention to engage in SDM for choosing to use antibiotics or not to treat an ARI in future consultations. Patient-targeted interventions may be necessary to achieve this purpose. © 2014 John Wiley & Sons Ltd.

Forward view: advancing health library and knowledge services in England.

PubMed

Lacey Bryant, Sue; Bingham, Helen; Carlyle, Ruth; Day, Alison; Ferguson, Linda; Stewart, David

2018-03-01

This article is the fourth in a series on New Directions. The National Health Service is under pressure, challenged to meet the needs of an ageing population, whilst striving to improve standards and ensure decision making is underpinned by evidence. Health Education England is steering a new course for NHS library and knowledge services in England to ensure access to knowledge and evidence for all decision makers. Knowledge for Healthcare calls for service transformation, role redesign, greater coordination and collaboration. To meet user expectations, health libraries must achieve sustainable, affordable access to digital content. Traditional tasks will progressively become mechanised. Alongside supporting learners, NHS librarians and knowledge specialists will take a greater role as knowledge brokers, delivering business critical services. They will support the NHS workforce to signpost patients and the public to high-quality information. There is a need for greater efficiency and effectiveness through greater co-operation and service mergers. Evaluation of service quality will focus more on outcomes, less on counting. These changes require an agile workforce, fit for the future. There is a bright future in which librarians' expertise is used to mobilise evidence, manage and share knowledge, support patients, carers and families, optimise technology and social media and provide a keystone for improved patient care and safety. © 2018 Health Libraries Group.

Which medical and social decision topics are important after early diagnosis of Alzheimer's Disease from the perspectives of people with Alzheimer's Disease, spouses and professionals?

PubMed

Bronner, Katharina; Perneczky, Robert; McCabe, Rose; Kurz, Alexander; Hamann, Johannes

2016-03-08

The relevance of early decision making will rise with increasing availability of early detection of Alzheimer's disease (AD) using brain imaging or biomarkers. Five people with mild AD, six relatives and 13 healthcare professionals with experience in the management of AD were interviewed in a qualitative study regarding medical and social decision topics that emerge after early diagnosis of Alzheimer's disease. Medical treatment, assistance in everyday life and legal issues emerged as the main decision topics after an early diagnosis of AD. People with AD mostly got in contact with the health and social care system through the initiative of their spouses. They were usually aware of their illness and most received antidementia drugs and/or behavioural interventions. Following diagnosis people with AD received support by their spouses. Healthcare professionals were aware of the risk of excessive demand on relatives due to supporting their family member with AD. In the opinion of healthcare professionals legal issues should be arranged in time before patients lose their decisional capacity. In addition, people with AD and spouses reported various coping strategies, in particular "carry on as normal" after diagnosis but mostly are reluctant to actively plan for future stages of the disease. Due to the common desire to "carry on as usual" after a diagnosis of AD, many people with AD and spouses may miss the opportunity to discuss and decide on important medical and social topics. A structured approach e.g. a decision aid might support people with AD and spouses in their decision making process and thereby preserve persons' with AD autonomy before they lose the capacity in decision-making.

Fertility preservation and cancer: Challenges for adolescent and young adult patients

PubMed Central

Benedict, Catherine; Thom, Bridgette; Kelvin, Joanne

2016-01-01

Purpose of review With increasing survival rates, fertility is an important quality of life concern for many young cancer patients. There is a critical need for improvements in clinical care to ensure patients are well informed about infertility risks and fertility preservation (FP) options and to support them in their reproductive decision-making prior to treatment. Recent findings A number of barriers prevent fertility from being adequately addressed in the clinical context. Providers’ and patients’ incomplete or inaccurate understanding of infertility risks exacerbate patients’ reproductive concerns. For female patients in particular, making decisions about FP before treatment often leads to decision conflict, reducing the likelihood of making informed, values-based decisions, and post-treatment regret and distress. Recent empirically-based interventions to improve provider training around fertility issues and to support patient decision-making about FP show promise. Summary Providers should be knowledgeable about the infertility risks associated with cancer therapies and proactively address fertility with all patients who might one day wish to have a child. Comprehensive counseling should also include related issues such as contraceptive use and health implications of early menopause, regardless of desire for future children. Although the negative psychosocial impact of cancer-related infertility is now well accepted, limited work has been done to explore how to improve clinical management of fertility issues in the context of cancer care. Evidence-based interventions should be developed to address barriers and provide psychosocial and decision-making support to patients who are concerned about their fertility and interested in FP options. PMID:26730794

A pathway to personalization of integrated treatment: informatics and decision science in psychiatric rehabilitation.

PubMed

Spaulding, William; Deogun, Jitender

2011-09-01

Personalization of treatment is a current strategic goal for improving health care. Integrated treatment approaches such as psychiatric rehabilitation benefit from personalization because they involve matching diverse arrays of treatment options to individually unique profiles of need. The need for personalization is evident in the heterogeneity of people with severe mental illness and in the findings of experimental psychopathology. One pathway to personalization lies in analysis of the judgments and decision making of human experts and other participants as they respond to complex circumstances in pursuit of treatment and rehabilitation goals. Such analysis is aided by computer simulation of human decision making, which in turn informs development of computerized clinical decision support systems. This inspires a research program involving concurrent development of databases, domain ontology, and problem-solving algorithms, toward the goal of personalizing psychiatric rehabilitation through human collaboration with intelligent cyber systems. The immediate hurdle is to demonstrate that clinical decisions beyond diagnosis really do affect outcome. This can be done by supporting the hypothesis that a human treatment team with access to a reasonably comprehensive clinical database that tracks patient status and treatment response over time achieves better outcome than a treatment team without such access, in a controlled experimental trial. Provided the hypothesis can be supported, the near future will see prototype systems that can construct an integrated assessment, formulation, and rehabilitation plan from clinical assessment data and contextual information. This will lead to advanced systems that collaborate with human decision makers to personalize psychiatric rehabilitation and optimize outcome.

The Conservation Effects Assessment Project (CEAP): a national scale natural resources and conservation needs assessment and decision support tool

NASA Astrophysics Data System (ADS)

Johnson, M.-V. V.; Norfleet, M. L.; Atwood, J. D.; Behrman, K. D.; Kiniry, J. R.; Arnold, J. G.; White, M. J.; Williams, J.

2015-07-01

The Conservation Effects Assessment Project (CEAP) was initiated to quantify the impacts of agricultural conservation practices at the watershed, regional, and national scales across the United States. Representative cropland acres in all major U.S. watersheds were surveyed in 2003-2006 as part of the seminal CEAP Cropland National Assessment. Two process-based models, the Agricultural Policy Environmental eXtender(APEX) and the Soil Water Assessment Tool (SWAT), were applied to the survey data to provide a quantitative assessment of current conservation practice impacts, establish a benchmark against which future conservation trends and efforts could be measured, and identify outstanding conservation concerns. The flexibility of these models and the unprecedented amount of data on current conservation practices across the country enabled Cropland CEAP to meet its Congressional mandate of quantifying the value of current conservation practices. It also enabled scientifically grounded exploration of a variety of conservation scenarios, empowering CEAP to not only inform on past successes and additional needs, but to also provide a decision support tool to help guide future policy development and conservation practice decision making. The CEAP effort will repeat the national survey in 2015-2016, enabling CEAP to provide analyses of emergent conservation trends, outstanding needs, and potential costs and benefits of pursuing various treatment scenarios for all agricultural watersheds across the United States.

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.

Using the Reliability Theory for Assessing the Decision Confidence Probability for Comparative Life Cycle Assessments.

PubMed

Wei, Wei; Larrey-Lassalle, Pyrène; Faure, Thierry; Dumoulin, Nicolas; Roux, Philippe; Mathias, Jean-Denis

2016-03-01

Comparative decision making process is widely used to identify which option (system, product, service, etc.) has smaller environmental footprints and for providing recommendations that help stakeholders take future decisions. However, the uncertainty problem complicates the comparison and the decision making. Probability-based decision support in LCA is a way to help stakeholders in their decision-making process. It calculates the decision confidence probability which expresses the probability of a option to have a smaller environmental impact than the one of another option. Here we apply the reliability theory to approximate the decision confidence probability. We compare the traditional Monte Carlo method with a reliability method called FORM method. The Monte Carlo method needs high computational time to calculate the decision confidence probability. The FORM method enables us to approximate the decision confidence probability with fewer simulations than the Monte Carlo method by approximating the response surface. Moreover, the FORM method calculates the associated importance factors that correspond to a sensitivity analysis in relation to the probability. The importance factors allow stakeholders to determine which factors influence their decision. Our results clearly show that the reliability method provides additional useful information to stakeholders as well as it reduces the computational time.

Enabling Real-time Water Decision Support Services Using Model as a Service

NASA Astrophysics Data System (ADS)

Zhao, T.; Minsker, B. S.; Lee, J. S.; Salas, F. R.; Maidment, D. R.; David, C. H.

2014-12-01

Through application of computational methods and an integrated information system, data and river modeling services can help researchers and decision makers more rapidly understand river conditions under alternative scenarios. To enable this capability, workflows (i.e., analysis and model steps) are created and published as Web services delivered through an internet browser, including model inputs, a published workflow service, and visualized outputs. The RAPID model, which is a river routing model developed at University of Texas Austin for parallel computation of river discharge, has been implemented as a workflow and published as a Web application. This allows non-technical users to remotely execute the model and visualize results as a service through a simple Web interface. The model service and Web application has been prototyped in the San Antonio and Guadalupe River Basin in Texas, with input from university and agency partners. In the future, optimization model workflows will be developed to link with the RAPID model workflow to provide real-time water allocation decision support services.

The Implications of Meno’s Paradox for the Mental Capacity Act 2005

PubMed Central

2016-01-01

Meno’s paradox—which asks ‘how will you know it is the thing you didn’t know?’—appears in Plato’s dialogue of the same name. This article suggests that a similar question arises in some supportive relationships. Attention to this question clarifies one condition necessary to justify making a best interests decisions against someone’s will: the decided-for person must be unable to recognise that they have failed to recognise a need. From this condition, two duties are derived: a duty to ensure that someone cannot recognise that they have failed to recognise a need before making a decision against their will; and a duty to provide consensual support to those who have had decisions made against their will, in order to help them to avoid such second-order failures of recognition in the future. The article assesses the Mental Capacity Act 2005 against each of these duties. For each duty, it finds that the Act allows compliance, but does not robustly require it. PMID:28007809

Stochastic Modeling of Past Volcanic Crises

NASA Astrophysics Data System (ADS)

Woo, Gordon

2018-01-01

The statistical foundation of disaster risk analysis is past experience. From a scientific perspective, history is just one realization of what might have happened, given the randomness and chaotic dynamics of Nature. Stochastic analysis of the past is an exploratory exercise in counterfactual history, considering alternative possible scenarios. In particular, the dynamic perturbations that might have transitioned a volcano from an unrest to an eruptive state need to be considered. The stochastic modeling of past volcanic crises leads to estimates of eruption probability that can illuminate historical volcanic crisis decisions. It can also inform future economic risk management decisions in regions where there has been some volcanic unrest, but no actual eruption for at least hundreds of years. Furthermore, the availability of a library of past eruption probabilities would provide benchmark support for estimates of eruption probability in future volcanic crises.

Use of Mobile Apps Among Medical and Nursing Students in Iran.

PubMed

Sheikhtaheri, Abbas; Kermani, Farzaneh

2018-01-01

Mobile technologies have a positive impact on patient care and cause to improved decision making, reduced medical errors and improved communication in care team. The purpose of this study was to investigate the use of mobile technologies by medical and nursing students and their tendency in future. This study was conducted among 372 medical and nursing students of Tehran University of Medical Science. Respectively, 60.8% and 62.4% of medical and nursing students use smartphone. The most commonly used apps among medical students were medical dictionary, drug apps, medical calculators and anatomical atlases and among nursing students were medical dictionary, anatomical atlases and nursing care guides. Also, the use of decision support systems, remote monitoring, patient imagery and remote diagnosis, patient records documentation, diagnostic guidelines and laboratory tests will be increased in the future.

Modelling Coral Reef Futures to Inform Management: Can Reducing Local-Scale Stressors Conserve Reefs under Climate Change?

PubMed Central

Gurney, Georgina G.; Melbourne-Thomas, Jessica; Geronimo, Rollan C.; Aliño, Perry M.; Johnson, Craig R.

2013-01-01

Climate change has emerged as a principal threat to coral reefs, and is expected to exacerbate coral reef degradation caused by more localised stressors. Management of local stressors is widely advocated to bolster coral reef resilience, but the extent to which management of local stressors might affect future trajectories of reef state remains unclear. This is in part because of limited understanding of the cumulative impact of multiple stressors. Models are ideal tools to aid understanding of future reef state under alternative management and climatic scenarios, but to date few have been sufficiently developed to be useful as decision support tools for local management of coral reefs subject to multiple stressors. We used a simulation model of coral reefs to investigate the extent to which the management of local stressors (namely poor water quality and fishing) might influence future reef state under varying climatic scenarios relating to coral bleaching. We parameterised the model for Bolinao, the Philippines, and explored how simulation modelling can be used to provide decision support for local management. We found that management of water quality, and to a lesser extent fishing, can have a significant impact on future reef state, including coral recovery following bleaching-induced mortality. The stressors we examined interacted antagonistically to affect reef state, highlighting the importance of considering the combined impact of multiple stressors rather than considering them individually. Further, by providing explicit guidance for management of Bolinao's reef system, such as which course of management action will most likely to be effective over what time scales and at which sites, we demonstrated the utility of simulation models for supporting management. Aside from providing explicit guidance for management of Bolinao's reef system, our study offers insights which could inform reef management more broadly, as well as general understanding of reef systems. PMID:24260347

Modelling coral reef futures to inform management: can reducing local-scale stressors conserve reefs under climate change?

PubMed

Gurney, Georgina G; Melbourne-Thomas, Jessica; Geronimo, Rollan C; Aliño, Perry M; Johnson, Craig R

2013-01-01

Climate change has emerged as a principal threat to coral reefs, and is expected to exacerbate coral reef degradation caused by more localised stressors. Management of local stressors is widely advocated to bolster coral reef resilience, but the extent to which management of local stressors might affect future trajectories of reef state remains unclear. This is in part because of limited understanding of the cumulative impact of multiple stressors. Models are ideal tools to aid understanding of future reef state under alternative management and climatic scenarios, but to date few have been sufficiently developed to be useful as decision support tools for local management of coral reefs subject to multiple stressors. We used a simulation model of coral reefs to investigate the extent to which the management of local stressors (namely poor water quality and fishing) might influence future reef state under varying climatic scenarios relating to coral bleaching. We parameterised the model for Bolinao, the Philippines, and explored how simulation modelling can be used to provide decision support for local management. We found that management of water quality, and to a lesser extent fishing, can have a significant impact on future reef state, including coral recovery following bleaching-induced mortality. The stressors we examined interacted antagonistically to affect reef state, highlighting the importance of considering the combined impact of multiple stressors rather than considering them individually. Further, by providing explicit guidance for management of Bolinao's reef system, such as which course of management action will most likely to be effective over what time scales and at which sites, we demonstrated the utility of simulation models for supporting management. Aside from providing explicit guidance for management of Bolinao's reef system, our study offers insights which could inform reef management more broadly, as well as general understanding of reef systems.

The Library of the Future

DTIC Science & Technology

2009-05-01

Information Literacy – Oral Communication – Written Communication – Critical Thinking – Decision Making – Stamina – Courage – Discipline...Emory     8  I n t e g r i t y - S e r v i c e - E x c e l l e n c e Supporting “ information literacy ” - Provide right type of help near “point of...plays central role in supporting “ information literacy ” Columbia University •Computer Lab •Center for New Media in Teaching and Learning

Air Force Reusable Booster System A Quick-look, Design Focused Modeling and Cost Analysis Study

NASA Technical Reports Server (NTRS)

Zapata, Edgar

2011-01-01

Presents work supporting the Air force Reusable Booster System (RBS) - A Cost Study with Goals as follows: Support US launch systems decision makers, esp. in regards to the research, technology and demonstration investments required for reusable systems to succeed. Encourage operable directions in Reusable Booster / Launch Vehicle Systems technology choices, system design and product and process developments. Perform a quick-look cost study, while developing a cost model for more refined future analysis.

Application of stakeholder-based and modelling approaches for supporting robust adaptation decision making under future climatic uncertainty and changing urban-agricultural water demand

NASA Astrophysics Data System (ADS)

Bhave, Ajay; Dessai, Suraje; Conway, Declan; Stainforth, David

2016-04-01

Deep uncertainty in future climate change and socio-economic conditions necessitates the use of assess-risk-of-policy approaches over predict-then-act approaches for adaptation decision making. Robust Decision Making (RDM) approaches embody this principle and help evaluate the ability of adaptation options to satisfy stakeholder preferences under wide-ranging future conditions. This study involves the simultaneous application of two RDM approaches; qualitative and quantitative, in the Cauvery River Basin in Karnataka (population ~23 million), India. The study aims to (a) determine robust water resources adaptation options for the 2030s and 2050s and (b) compare the usefulness of a qualitative stakeholder-driven approach with a quantitative modelling approach. For developing a large set of future scenarios a combination of climate narratives and socio-economic narratives was used. Using structured expert elicitation with a group of climate experts in the Indian Summer Monsoon, climatic narratives were developed. Socio-economic narratives were developed to reflect potential future urban and agricultural water demand. In the qualitative RDM approach, a stakeholder workshop helped elicit key vulnerabilities, water resources adaptation options and performance criteria for evaluating options. During a second workshop, stakeholders discussed and evaluated adaptation options against the performance criteria for a large number of scenarios of climatic and socio-economic change in the basin. In the quantitative RDM approach, a Water Evaluation And Planning (WEAP) model was forced by precipitation and evapotranspiration data, coherent with the climatic narratives, together with water demand data based on socio-economic narratives. We find that compared to business-as-usual conditions options addressing urban water demand satisfy performance criteria across scenarios and provide co-benefits like energy savings and reduction in groundwater depletion, while options reducing agricultural water demand significantly affect downstream water availability. Water demand options demonstrate potential to improve environmental flow conditions and satisfy legal water supply requirements for downstream riparian states. On the other hand, currently planned large scale infrastructural projects demonstrate reduced value in certain scenarios, illustrating the impacts of lock-in effects of large scale infrastructure. From a methodological perspective, we find that while the stakeholder-driven approach revealed robust options in a resource-light manner and helped initiate much needed interaction amongst stakeholders, the modelling approach provides complementary quantitative information. The study reveals robust adaptation options for this important basin and provides a strong methodological basis for carrying out future studies that support adaptation decision making.

Building a Computer Program to Support Children, Parents, and Distraction during Healthcare Procedures

PubMed Central

McCarthy, Ann Marie; Kleiber, Charmaine; Ataman, Kaan; Street, W. Nick; Zimmerman, M. Bridget; Ersig, Anne L.

2012-01-01

This secondary data analysis used data mining methods to develop predictive models of child risk for distress during a healthcare procedure. Data used came from a study that predicted factors associated with children’s responses to an intravenous catheter insertion while parents provided distraction coaching. From the 255 items used in the primary study, 44 predictive items were identified through automatic feature selection and used to build support vector machine regression models. Models were validated using multiple cross-validation tests and by comparing variables identified as explanatory in the traditional versus support vector machine regression. Rule-based approaches were applied to the model outputs to identify overall risk for distress. A decision tree was then applied to evidence-based instructions for tailoring distraction to characteristics and preferences of the parent and child. The resulting decision support computer application, the Children, Parents and Distraction (CPaD), is being used in research. Future use will support practitioners in deciding the level and type of distraction intervention needed by a child undergoing a healthcare procedure. PMID:22805121

High Resolution Visualization Applied to Future Heavy Airlift Concept Development and Evaluation

NASA Technical Reports Server (NTRS)

FordCook, A. B.; King, T.

2012-01-01

This paper explores the use of high resolution 3D visualization tools for exploring the feasibility and advantages of future military cargo airlift concepts and evaluating compatibility with existing and future payload requirements. Realistic 3D graphic representations of future airlifters are immersed in rich, supporting environments to demonstrate concepts of operations to key personnel for evaluation, feedback, and development of critical joint support. Accurate concept visualizations are reviewed by commanders, platform developers, loadmasters, soldiers, scientists, engineers, and key principal decision makers at various stages of development. The insight gained through the review of these physically and operationally realistic visualizations is essential to refining design concepts to meet competing requirements in a fiscally conservative defense finance environment. In addition, highly accurate 3D geometric models of existing and evolving large military vehicles are loaded into existing and proposed aircraft cargo bays. In this virtual aircraft test-loading environment, materiel developers, engineers, managers, and soldiers can realistically evaluate the compatibility of current and next-generation airlifters with proposed cargo.

Decision Making and Reward in Frontal Cortex

PubMed Central

Kennerley, Steven W.; Walton, Mark E.

2011-01-01

Patients with damage to the prefrontal cortex (PFC)—especially the ventral and medial parts of PFC—often show a marked inability to make choices that meet their needs and goals. These decision-making impairments often reflect both a deficit in learning concerning the consequences of a choice, as well as deficits in the ability to adapt future choices based on experienced value of the current choice. Thus, areas of PFC must support some value computations that are necessary for optimal choice. However, recent frameworks of decision making have highlighted that optimal and adaptive decision making does not simply rest on a single computation, but a number of different value computations may be necessary. Using this framework as a guide, we summarize evidence from both lesion studies and single-neuron physiology for the representation of different value computations across PFC areas. PMID:21534649

Designing for the Future: How the Learning Sciences Can Inform the Trajectories of Preservice Teachers

ERIC Educational Resources Information Center

Jurow, A. Susan; Tracy, Rita; Hotchkiss, Jacqueline S.; Kirshner, Ben

2012-01-01

In this article, the authors discuss how they redesigned an educational psychology course for preservice teachers using insights from the burgeoning, interdisciplinary field of the Learning Sciences. Research on the situated nature of learning and the value of out-of-school contexts for supporting children s development informed their decisions to…

Computer-based tools for decision support in agroforestry: Current state and future needs

Treesearch

E.A. Ellis; G. Bentrup; Michelle M. Schoeneberger

2004-01-01

Successful design of agroforestry practices hinges on the ability to pull together very diverse and sometimes large sets of information (i.e., biophysical, economic and social factors), and then implementing the synthesis of this information across several spatial scales from site to landscape. Agroforestry, by its very nature, creates complex systems with impacts...

SMARTe Framework: Present Structure And Ideas For The Future, 25 June 2009

EPA Science Inventory

SMARTe (Sustainable Management Approaches and Revitalization Tools-electronic) is a web-based decision support tool being developed by the Office of Research and Development (ORD) in partnership with the Office of Brownfields and Land Rev...

75 FR 38093 - ConocoPhillips Alaska Natural Gas Corporation and Marathon Oil Company; Application for Blanket...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-01

... regasification terminal; and use of the existing terminal for exports to support the economic viability of a... LNG shipping at economic rates; and (3) strategic decisions regarding the future role of the Kenai LNG... Facility provides local economic benefits, including as an employer and as a source of royalties and taxes...

[Decisions on limiting treatment in critically-ill neonates: a multicenter study].

PubMed

2002-12-01

Backgrounds Some patients with a poor prognosis cause serious doubts about the real benefit of life-sustaining treatment. In some cases the possibility of limiting those treatments is raised. Such end-of-life decisions provoke ethical dilemmas and questions about procedure.ObjectivesTwo determine the frequency of end-of-life decisions in neonates, patient characteristics, and the criteria used by those taking decisions.Patients and methodsWe performed a multicenter, descriptive, prospective study. Neonates from 15 neonatal intensive care units who died during their stay in the hospital between 1999 and 2000, as well as those in whom end-of-life decisions were taken, were included. End-of-life decisions were defined as clinical decisions to withhold or withdraw life-sustaining treatment.ResultsA total of 330 patients were included. End-of-life decisions were taken in 171 (52 %); of these, 169 (98.8 %) died. The remaining 159 patients (48.2 %) died without treatment limitation. The main disorders involving end-of-life decisions were congenital malformation (47 %), neurologic disorders secondary to perinatal asphyxia and intracranial hemorrhage-periventricular leukomalacia (37 %). Of the 171 neonates, treatment was withheld in 80 and vital support was withdrawn in 91. The most frequently withdrawn life-sustaining treatment was mechanical ventilation (68 %). The criteria most commonly used in end-of-life decisions were poor vital prognosis (79.5 %), and current and future quality of life (37 % and 48 % respectively). The patient's external factors such as unfavorable family environment or possible negative consequences for familial equilibrium were a factor in 5 % of decisions.ConclusionsThe present study, the first of this type performed in Spain, reveals little-known aspects about the clinical practice of withholding and/or withdrawing life-sustaining treatment in critically ill neonates. End-of-life decisions were frequent (52 %) and were followed by death in most of the patients (98,8 %). The main criteria in decision-making were poor vital prognosis and the patient's current and future quality of life.

Supporting global health goals with information and communications technology

PubMed Central

Boman, Magnus; Kruse, Erik

2017-01-01

ABSTRACT The objective of this study is to critically assess the possible roles of information and communications technology (ICT) in supporting global health goals. This is done by considering privilege and connectibility. In short, ICT can contribute by providing health information via four different kinds of access, each with its own history and prospective future. All four are analyzed here, in two perspectives: business-as-usual and disruptive. Health data analytics is difficult since the digital representation of past, current, and future health information is lacking. The flow of analytics that may prove beneficial to the individual and not just meet abstract population-level goals or ambitions is analyzed in detail. Sensemaking is also needed, to meet the minimum requirement of making prospective future services understandable to policymakers. Drivers as well as barriers for areas in which policy decisions have the potential to drive positive developments for meeting the Sustainable Development Goals are identified. PMID:28838300

Supporting global health goals with information and communications technology.

PubMed

Boman, Magnus; Kruse, Erik

2017-06-01

The objective of this study is to critically assess the possible roles of information and communications technology (ICT) in supporting global health goals. This is done by considering privilege and connectibility. In short, ICT can contribute by providing health information via four different kinds of access, each with its own history and prospective future. All four are analyzed here, in two perspectives: business-as-usual and disruptive. Health data analytics is difficult since the digital representation of past, current, and future health information is lacking. The flow of analytics that may prove beneficial to the individual and not just meet abstract population-level goals or ambitions is analyzed in detail. Sensemaking is also needed, to meet the minimum requirement of making prospective future services understandable to policymakers. Drivers as well as barriers for areas in which policy decisions have the potential to drive positive developments for meeting the Sustainable Development Goals are identified.

Exploring the future with anticipatory networks

NASA Astrophysics Data System (ADS)

Skulimowski, A. M. J.

2013-01-01

This paper presents a theory of anticipatory networks that originates from anticipatory models of consequences in multicriteria decision problems. When making a decision, the decision maker takes into account the anticipated outcomes of each future decision problem linked by the causal relations with the present one. In a network of linked decision problems, the causal relations are defined between time-ordered nodes. The scenarios of future consequences of each decision are modeled by multiple vertices starting from an appropriate node. The network is supplemented by one or more relations of anticipation, or future feedback, which describe a situation where decision makers take into account the anticipated results of some future optimization problems while making their choice. So arises a multigraph of decision problems linked causally and by one or more anticipation relation, termed here the anticipatory network. We will present the properties of anticipatory networks and propose a method of reducing, transforming and using them to solve current decision problems. Furthermore, it will be shown that most anticipatory networks can be regarded as superanticipatory systems, i.e. systems that are anticipatory in the Rosen sense and contain a future model of at least one other anticipatory system. The anticipatory networks can also be applied to filter the set of future scenarios in a foresight exercise.

Pathways to Late-Life Suicidal Behavior: Cluster Analysis and Predictive Validation of Suicidal Behavior in a Sample of Older Adults With Major Depression.

PubMed

Szanto, Katalin; Galfalvy, Hanga; Vanyukov, Polina M; Keilp, John G; Dombrovski, Alexandre Y

Clinical heterogeneity is a key challenge to understanding suicidal risk, as different pathways to suicidal behavior are likely to exist. We aimed to identify such pathways by uncovering latent classes of late-life depression cases and relating them to prior and future suicidal behavior. Data were collected from June 2010 to September 2015. In this longitudinal study we examined distinct associations of clinical and cognitive/decision-making factors with suicidal behavior in 194 older (50+ years) nondemented, depressed patients; 57 nonpsychiatric healthy controls provided benchmark data. The DSM-IV was used to establish diagnostic criteria. We identified multivariate patterns of risk factors, defining clusters based on personality traits, perceived social support, cognitive performance, and decision-making in an analysis blinded to participants' history of suicidal behavior. We validated these clusters using past and prospective suicidal ideation and behavior. Of 5 clusters identified, 3 were associated with high risk for suicidal behavior: (1) cognitive deficits, dysfunctional personality, low social support, high willingness to delay future rewards, and overrepresentation of high-lethality attempters; (2) high-personality pathology (ie, low self-esteem), minimal or no cognitive deficits, and overrepresentation of low-lethality attempters and ideators; (3) cognitive deficits, inability to delay future rewards, and similar distribution of high- and low-lethality attempters. There were significant between-cluster differences in number (P < .001) and lethality (P = .002) of past suicide attempts and in the likelihood of future suicide attempts (P = .010, 30 attempts by 22 patients, 2 fatal) and emergency psychiatric hospitalizations to prevent suicide (P = .005, 31 participants). Three pathways to suicidal behavior in older patients were found, marked by (1) very high levels of cognitive and dispositional risk factors suggesting a dementia prodrome, (2) dysfunctional personality traits, and (3) impulsive decision-making and cognitive deficits. © Copyright 2018 Physicians Postgraduate Press, Inc.

What is lacking in current decision aids on cancer screening?

PubMed Central

Jimbo, Masahito; Rana, Gurpreet K.; Hawley, Sarah; Holmes-Rovner, Margaret; Kelly-Blake, Karen; Nease, Donald E.; Ruffin, Mack T.

2013-01-01

Recent guidelines on cancer screening have given not only more screening options but also conflicting recommendations. Thus, patients, with their clinicians’ support, must decide whether to get screened or not, which modality to use, and how often to get screened. Decision aids could potentially lead to better shared decision making regarding screening between the patient and the clinician. We reviewed 73 decision aids on screening for breast, cervical, colorectal, and prostate cancers. The goal of this review was to assess the effectiveness of such decision aids, examine areas in need for more research, and determine how the decision aids can be currently applied in the real world setting. Most studies used sound study design. Significant variation existed in setting, theoretical framework, and measured outcomes. Just over a third of the decision aids included an explicit values clarification. Other than knowledge, little consistency was noted in which patient attributes were measured as outcomes. Few studies actually measured shared decision making. Little information was available on the feasibility and outcomes of integrating decision aids into practice. We discuss the implications for future research, as well as what the clinicians can do now to incorporate decision aids into their practice. PMID:23504675

Qualitative study of patients’ decision-making when accepting second-line treatment after failure of first-line chemotherapy

PubMed Central

Roch, Benoît; Roth, Caroline; Mérel, Jean-Pierre

2018-01-01

Objective Treatment failures in advanced lung cancer are frequent events affecting patients during or after first-line chemotherapy. International guidelines recommend second-line chemotherapy. However, around one half of patients who experience disease progression enter a systemic second-line therapy. In the herein qualitative study, we investigated patients' thoughts and attitudes determining the decision to undergo a second-line chemotherapy. Methods Thirty-three purposively selected patients who recently accepted second-line or palliative chemotherapy were invited to participate in this survey consisting of semi-structured in-depth interviews. Grounded theory was applied to investigate participants’ perceptions of the context that have surrounded their decision to undergo palliative chemotherapy. Results For most patients, tumor burden and reduced quality of life in relation with lung cancer itself were major drivers of the decision-making process. There was a balance between two different attitudes: making a decision to undergo a new line of chemotherapy or starting a psychological process in order to accept end of life. Choosing between these two attitudes allowed the patient to keep the matter of palliative care at a distance. Even in case of low chance of success, many patients who worried about their life partner's future would accept a new chemotherapy line. Some patients experienced ambivalent thoughts regarding social network, particularly about their family as daily function impairment required an increased need for relative's support. The initial "Worrying about others" thoughts left place to in an increasing self-need of care as those provided by relatives; this phenomenon might increase patients' self- perception of being a burden for others. Confidence previously established with formal caregiver support was another major decision driver: some patients with sustained confidence in their medical staff may have privileged this formal support rather than family support when the latter was perceived as weak, insufficient or intrusive. Conclusion This study identified three domains involved into a complex interplay for lung cancer patients’ decision regarding second-line palliative chemotherapy: (i) perception of the definitive loss of health, (ii) interactions between idiosyncrasy (hope, disease burden) and environment (healthcare and social network support), and (iii) patient's subjective evaluation of chemotherapy benefit–risk. PMID:29799879

Emotional and cognitive experiences during the time of diagnosis and decision-making following a prenatal diagnosis: a qualitative study of males presented with congenital heart defect in the fetus carried by their pregnant partner.

PubMed

Carlsson, Tommy; Mattsson, Elisabet

2018-01-12

Expectant fathers consider the second-trimester obstetric ultrasound examination as an important step towards parenthood, but are ill prepared for a detection of a fetal anomaly. Inductive research is scarce concerning their experiences and needs for support. Consequently, the aim of this study was to explore the emotional and cognitive experiences, during the time of diagnosis and decision-making, among males presented with congenital heart defect in the fetus carried by their pregnant partner. Twelve expectant fathers were consecutively recruited through two tertiary referral centers for fetal cardiology in Sweden, after they had been presented with a prenatal diagnosis of congenital heart defect in the fetus carried by their pregnant partner. The respondents were interviewed via telephone, and the interviews were analyzed using inductive qualitative content analysis. The respondents experienced an intense emotional shock in connection with detection. However, they set their own needs aside to attend to the supportive needs of their pregnant partner, and stressed the importance of an informed joint decision regarding whether to continue or terminate the pregnancy. When terminating the pregnancy, they experienced a loss of a wanted child, an emotionally intense termination procedure, needs of support neglected by professionals, and worries about the risk of recurrence in future pregnancies. When continuing the pregnancy, they tried to keep a positive attitude about the coming birth, but were simultaneously worried about the postnatal situation. The findings illustrate the importance of inclusive care and adequate follow-up routines for both expectant parents following a prenatal diagnosis. This includes the initial emotional shock, the decisional process, and depending on decision reached, the termination or continuation of the pregnancy. Expectant fathers presented with a fetal anomaly need adequate follow-up routines to address worries about risk of recurrence in future pregnancies and worries about the postnatal situation.

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.

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.

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.

Evaluating hydrological response to forecasted land-use change—scenario testing with the automated geospatial watershed assessment (AGWA) tool

USGS Publications Warehouse

Kepner, William G.; Semmens, Darius J.; Hernandez, Mariano; Goodrich, David C.

2009-01-01

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 to maintain the sustainable nature of our ecosystem services now and into the future. During the past two decades, important advances in the integration of remote imagery, computer processing, and spatial-analysis technologies have been used to develop landscape information that can be integrated with hydrologic models to determine long-term change and make predictive inferences about the future. Two diverse case studies in northwest Oregon (Willamette River basin) and southeastern Arizona (San Pedro River) were examined in regard to future land use scenarios relative to their impact on surface water conditions (e.g., sediment yield and surface runoff) using hydrologic models associated with the Automated Geospatial Watershed Assessment (AGWA) tool. The base reference grid for land cover was modified in both study locations to reflect stakeholder preferences 20 to 60 yrs into the future, and the consequences of landscape change were evaluated relative to the selected future scenarios. The two studies provide examples of integrating hydrologic modeling with a scenario analysis framework to evaluate plausible future forecasts and to understand the potential impact of landscape change on ecosystem services.

Windsor and Perry: reactions of siblings in same-sex and heterosexual couples.

PubMed

Clark, Jennifer B; Riggle, Ellen D B; Rostosky, Sharon S; Rothblum, Esther D; Balsam, Kimberly F

2015-01-01

The U.S. Supreme Court decisions in U.S. v. Windsor (570 U.S. 307) and Hollingsworth v. Perry (570 U.S. 399) created a focal point for public discussion of marriage equality for same-sex couples. This article reports the results of an exploratory study of the reactions of individuals currently or previously in same-sex couple relationships and a heterosexual sibling who is currently or previously married (N = 371) to the Supreme Court decisions. Thematic content analysis was used to explore participants' responses to an open-ended question on a survey. Reactions of individuals from same-sex couples revealed the following themes: (1) longitudinal perspectives on the advancement of rights for same-sex couples; (2) emotional responses celebrating the decisions or expressing relief; (3) affirmation of their relationship or rights; (4) practical consequences of the extension of rights; and (5) minority stress related to anticipation of future prejudice or discrimination. Themes in the heterosexual siblings' responses were (1) ally support; (2) flat support without emotion or elaboration; (3) indifference to or ignorance about the decisions; and (4) disapproval of the decisions. These themes are compared and discussed in light of prior research on reactions to marriage restriction debates and marriage (in)equality and family relationships.

A Markovian state-space framework for integrating flexibility into space system design decisions

NASA Astrophysics Data System (ADS)

Lafleur, Jarret M.

The past decades have seen the state of the art in aerospace system design progress from a scope of simple optimization to one including robustness, with the objective of permitting a single system to perform well even in off-nominal future environments. Integrating flexibility, or the capability to easily modify a system after it has been fielded in response to changing environments, into system design represents a further step forward. One challenge in accomplishing this rests in that the decision-maker must consider not only the present system design decision, but also sequential future design and operation decisions. Despite extensive interest in the topic, the state of the art in designing flexibility into aerospace systems, and particularly space systems, tends to be limited to analyses that are qualitative, deterministic, single-objective, and/or limited to consider a single future time period. To address these gaps, this thesis develops a stochastic, multi-objective, and multi-period framework for integrating flexibility into space system design decisions. Central to the framework are five steps. First, system configuration options are identified and costs of switching from one configuration to another are compiled into a cost transition matrix. Second, probabilities that demand on the system will transition from one mission to another are compiled into a mission demand Markov chain. Third, one performance matrix for each design objective is populated to describe how well the identified system configurations perform in each of the identified mission demand environments. The fourth step employs multi-period decision analysis techniques, including Markov decision processes from the field of operations research, to find efficient paths and policies a decision-maker may follow. The final step examines the implications of these paths and policies for the primary goal of informing initial system selection. Overall, this thesis unifies state-centric concepts of flexibility from economics and engineering literature with sequential decision-making techniques from operations research. The end objective of this thesis’ framework and its supporting tools is to enable selection of the next-generation space systems today, tailored to decision-maker budget and performance preferences, that will be best able to adapt and perform in a future of changing environments and requirements. Following extensive theoretical development, the framework and its steps are applied to space system planning problems of (1) DARPA-motivated multiple- or distributed-payload satellite selection and (2) NASA human space exploration architecture selection.

Contribution to solving the energy crisis - Simulating the prospects for low cost energy through silicon solar cells

NASA Technical Reports Server (NTRS)

Kran, A.

1978-01-01

PECAN (Photovoltaic Energy Conversion Analysis) is a highly interactive decision analysis and support system. It simulates the prospects for widespread use of solar cells for the generation of electrical power. PECAN consists of a set of integrated APL functions for evaluating the potential of terrestrial photovoltaics. Specifically, the system is a deterministic simulator, which translates present and future manufacturing technology into economic and financial terms, using the production unit concept. It guides solar cell development in three areas: tactical decision making, strategic planning, and the formulation of alternative options.

Deciding for Future Selves Reduces Loss Aversion

PubMed Central

Cheng, Qiqi; He, Guibing

2017-01-01

In this paper, we present an incentivized experiment to investigate the degree of loss aversion when people make decisions for their current selves and future selves under risk. We find that when participants make decisions for their future selves, they are less loss averse compared to when they make decisions for their current selves. This finding is consistent with the interpretation of loss aversion as a bias in decision-making driven by emotions, which are reduced when making decisions for future selves. Our findings endorsed the external validity of previous studies on the impact of emotion on loss aversion in a real world decision-making environment. PMID:28979234

Deciding for Future Selves Reduces Loss Aversion.

PubMed

Cheng, Qiqi; He, Guibing

2017-01-01

In this paper, we present an incentivized experiment to investigate the degree of loss aversion when people make decisions for their current selves and future selves under risk. We find that when participants make decisions for their future selves, they are less loss averse compared to when they make decisions for their current selves. This finding is consistent with the interpretation of loss aversion as a bias in decision-making driven by emotions, which are reduced when making decisions for future selves. Our findings endorsed the external validity of previous studies on the impact of emotion on loss aversion in a real world decision-making environment.

Payload accommodations. Avionics payload support architecture

NASA Technical Reports Server (NTRS)

Creasy, Susan L.; Levy, C. D.

1990-01-01

Concepts for vehicle and payload avionics architectures for future NASA programs, including the Assured Shuttle Access program, Space Station Freedom (SSF), Shuttle-C, Advanced Manned Launch System (AMLS), and the Lunar/Mars programs are discussed. Emphasis is on the potential available to increase payload services which will be required in the future, while decreasing the operational cost/complexity by utilizing state of the art advanced avionics systems and a distributed processing architecture. Also addressed are the trade studies required to determine the optimal degree of vehicle (NASA) to payload (customer) separation and the ramifications of these decisions.

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

MacMartin, Douglas G.; Kravitz, Ben; Long, Jane C. S.

Any well-informed future decision on whether and how to deploy solar geoengineering requires balancing the impacts (both intended and unintended) of intervening in the climate against the impacts of not doing so. In spite of the tremendous progress in the last decade, the current state of knowledge remains insufficient to support an assessment of this balance, even for stratospheric aerosol geoengineering (SAG), arguably the best understood (practical) geoengineering method. We then articulate key unknowns associated with SAG, including both climate-science and design questions, as an essential step toward developing a future strategic research program that could address outstanding uncertainties.

Automatic Scheduling and Planning (ASAP) in future ground control systems

NASA Technical Reports Server (NTRS)

Matlin, Sam

1988-01-01

This report describes two complementary approaches to the problem of space mission planning and scheduling. The first is an Expert System or Knowledge-Based System for automatically resolving most of the activity conflicts in a candidate plan. The second is an Interactive Graphics Decision Aid to assist the operator in manually resolving the residual conflicts which are beyond the scope of the Expert System. The two system designs are consistent with future ground control station activity requirements, support activity timing constraints, resource limits and activity priority guidelines.

The Watershed and River Systems Management Program: Decision Support for Water- and Environmental-Resource Management

NASA Astrophysics Data System (ADS)

Leavesley, G.; Markstrom, S.; Frevert, D.; Fulp, T.; Zagona, E.; Viger, R.

2004-12-01

Increasing demands for limited fresh-water supplies, and increasing complexity of water-management issues, present the water-resource manager with the difficult task of achieving an equitable balance of water allocation among a diverse group of water users. The Watershed and River System Management Program (WARSMP) is a cooperative effort between the U.S. Geological Survey (USGS) and the Bureau of Reclamation (BOR) to develop and deploy a database-centered, decision-support system (DSS) to address these multi-objective, resource-management problems. The decision-support system couples the USGS Modular Modeling System (MMS) with the BOR RiverWare tools using a shared relational database. MMS is an integrated system of computer software that provides a research and operational framework to support the development and integration of a wide variety of hydrologic and ecosystem models, and their application to water- and ecosystem-resource management. RiverWare is an object-oriented reservoir and river-system modeling framework developed to provide tools for evaluating and applying water-allocation and management strategies. The modeling capabilities of MMS and Riverware include simulating watershed runoff, reservoir inflows, and the impacts of resource-management decisions on municipal, agricultural, and industrial water users, environmental concerns, power generation, and recreational interests. Forecasts of future climatic conditions are a key component in the application of MMS models to resource-management decisions. Forecast methods applied in MMS include a modified version of the National Weather Service's Extended Streamflow Prediction Program (ESP) and statistical downscaling from atmospheric models. The WARSMP DSS is currently operational in the Gunnison River Basin, Colorado; Yakima River Basin, Washington; Rio Grande Basin in Colorado and New Mexico; and Truckee River Basin in California and Nevada.

Decaying relevance of clinical data towards future decisions in data-driven inpatient clinical order sets.

PubMed

Chen, Jonathan H; Alagappan, Muthuraman; Goldstein, Mary K; Asch, Steven M; Altman, Russ B

2017-06-01

Determine how varying longitudinal historical training data can impact prediction of future clinical decisions. Estimate the "decay rate" of clinical data source relevance. We trained a clinical order recommender system, analogous to Netflix or Amazon's "Customers who bought A also bought B..." product recommenders, based on a tertiary academic hospital's structured electronic health record data. We used this system to predict future (2013) admission orders based on different subsets of historical training data (2009 through 2012), relative to existing human-authored order sets. Predicting future (2013) inpatient orders is more accurate with models trained on just one month of recent (2012) data than with 12 months of older (2009) data (ROC AUC 0.91 vs. 0.88, precision 27% vs. 22%, recall 52% vs. 43%, all P<10 -10 ). Algorithmically learned models from even the older (2009) data was still more effective than existing human-authored order sets (ROC AUC 0.81, precision 16% recall 35%). Training with more longitudinal data (2009-2012) was no better than using only the most recent (2012) data, unless applying a decaying weighting scheme with a "half-life" of data relevance about 4 months. Clinical practice patterns (automatically) learned from electronic health record data can vary substantially across years. Gold standards for clinical decision support are elusive moving targets, reinforcing the need for automated methods that can adapt to evolving information. Prioritizing small amounts of recent data is more effective than using larger amounts of older data towards future clinical predictions. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

How long can global ecological overshoot last?

NASA Astrophysics Data System (ADS)

McBain, Bonnie; Lenzen, Manfred; Wackernagel, Mathis; Albrecht, Glenn

2017-08-01

The ability of the Ecological Footprint to communicate complex environmental information in a clear and accessible way is well known; however, with growing environmental complexity, we will require increasingly sophisticated environmental indicators to inform our decisions. We have developed an integrated and dynamic global model to investigate future trajectories of the Ecological Footprint. Under a range of futures and without the mitigation of human resource demand, we find that the discrepancy between global demand and renewable supply of resources is likely to increase. Continued overshoot, although possible in the short term, means the global community is increasingly exposed to risks of environmental collapse due to the approach of at least two planetary boundaries relating to land use expansion and climate change. We show that, the Ecological Footprint trajectory and the time between the commencement of ecological overshoot and ecological collapse is sensitive to global technological, economic and population policy decisions. Importantly, this work presents a tool which can be used to support transdisciplinary decision-maker collaborations examining the risk associated with alternative policy options in the face of uncertainty at multiple scales.

Evidence Based Medicine and Shared Decision Making: the challenge of getting both evidence and preferences into health care.

PubMed

Barratt, Alexandra

2008-12-01

Evidence Based Medicine (EBM) and Shared Medical Decision Making (SDM) are changing the nature of health care decisions. It is broadly accepted that health care decisions require the integration of research evidence and individual preferences. These approaches are justified on both efficacy grounds (that evidence based practice and Shared Decision Making should lead to better health outcomes and may lead to a more cost-effective use of health care resources) and ethical grounds (patients' autonomy should be respected in health care). However, despite endorsement by physicians and consumers of these approaches, implementation remains limited in practice, particularly outside academic and tertiary health care centres. There are practical problems of implementation, which include training, access to research, and development of and access to tools to display evidence and support decision making. There may also be philosophical difficulties, and some have even suggested that the two approaches (evidence based practice and Shared Decision Making) are fundamentally incompatible. This paper look at the achievements of EBM and SDM so far, the potential tensions between them, and how things might progress in the future.

Aid decision algorithms to estimate the risk in congenital heart surgery.

PubMed

Ruiz-Fernández, Daniel; Monsalve Torra, Ana; Soriano-Payá, Antonio; Marín-Alonso, Oscar; Triana Palencia, Eddy

2016-04-01

In this paper, we have tested the suitability of using different artificial intelligence-based algorithms for decision support when classifying the risk of congenital heart surgery. In this sense, classification of those surgical risks provides enormous benefits as the a priori estimation of surgical outcomes depending on either the type of disease or the type of repair, and other elements that influence the final result. This preventive estimation may help to avoid future complications, or even death. We have evaluated four machine learning algorithms to achieve our objective: multilayer perceptron, self-organizing map, radial basis function networks and decision trees. The architectures implemented have the aim of classifying among three types of surgical risk: low complexity, medium complexity and high complexity. Accuracy outcomes achieved range between 80% and 99%, being the multilayer perceptron method the one that offered a higher hit ratio. According to the results, it is feasible to develop a clinical decision support system using the evaluated algorithms. Such system would help cardiology specialists, paediatricians and surgeons to forecast the level of risk related to a congenital heart disease surgery. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

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

Implications of the Bangor Hydro decision on FERC relicensings

USGS Publications Warehouse

Pizzi, L.

1997-01-01

In the next 15 years, over 400 existing nonfederal dams will require new licenses by the Federal Energy Regulatory Commission (FERC) in order to continue operations. In many cases, state or federal agencies have a unique opportunity to condition the hydropower licenses to protect environmental values. In 1996, the Court of Appeals for the District of Columbia Circuit issued an opinion striking down a mandatory license condition imposed by the U.S. Department of the Interior in a FERC relicensing. The case, Bangor Hydro-Electric Company v.Federal Energy Regulatory Commission, is instructive for agencies regarding the procedures to be followed in imposing mandatory FERC licensing conditions in the future. After Bangor Hydro, agencies should: (1) support their decisions by substantial evidence in the FERC record, (2) request applicant studies to support agency decisions and allow public comment on the decisions as a means to test the facts and analysis, and (3) consider intervening in a case to defend the condition on appeal. Bangor Hydro also raises, but does not decide, the issue of whether the agency imposing the mandatory condition should engage in balancing the economics of the hydropower project with the public resources affected by the project.

Decision analysis framing study; in-valley drainage management strategies for the western San Joaquin Valley, California

USGS Publications Warehouse

Presser, Theresa S.; Jenni, Karen E.; Nieman, Timothy; Coleman, James

2010-01-01

Constraints on drainage management in the western San Joaquin Valley and implications of proposed approaches to management were recently evaluated by the U.S. Geological Survey (USGS). The USGS found that a significant amount of data for relevant technical issues was available and that a structured, analytical decision support tool could help optimize combinations of specific in-valley drainage management strategies, address uncertainties, and document underlying data analysis for future use. To follow-up on USGS's technical analysis and to help define a scientific basis for decisionmaking in implementing in-valley drainage management strategies, this report describes the first step (that is, a framing study) in a Decision Analysis process. In general, a Decision Analysis process includes four steps: (1) problem framing to establish the scope of the decision problem(s) and a set of fundamental objectives to evaluate potential solutions, (2) generation of strategies to address identified decision problem(s), (3) identification of uncertainties and their relationships, and (4) construction of a decision support model. Participation in such a systematic approach can help to promote consensus and to build a record of qualified supporting data for planning and implementation. In December 2008, a Decision Analysis framing study was initiated with a series of meetings designed to obtain preliminary input from key stakeholder groups on the scope of decisions relevant to drainage management that were of interest to them, and on the fundamental objectives each group considered relevant to those decisions. Two key findings of this framing study are: (1) participating stakeholders have many drainage management objectives in common; and (2) understanding the links between drainage management and water management is necessary both for sound science-based decisionmaking and for resolving stakeholder differences about the value of proposed drainage management solutions. Citing ongoing legal processes associated with drainage management in the western San Joaquin Valley, the U.S. Bureau of Reclamation (USBR) withdrew from the Decision Analysis process early in the proceedings. Without the involvement of the USBR, the USGS discontinued further development of this study.

Predictive Technologies: Can Smart Tools Augment the Brain's Predictive Abilities?

PubMed Central

Pezzulo, Giovanni; D'Ausilio, Alessandro; Gaggioli, Andrea

2016-01-01

The ability of “looking into the future”—namely, the capacity of anticipating future states of the environment or of the body—represents a fundamental function of human (and animal) brains. A goalkeeper who tries to guess the ball's direction; a chess player who attempts to anticipate the opponent's next move; or a man-in-love who tries to calculate what are the chances of her saying yes—in all these cases, people are simulating possible future states of the world, in order to maximize the success of their decisions or actions. Research in neuroscience is showing that our ability to predict the behavior of physical or social phenomena is largely dependent on the brain's ability to integrate current and past information to generate (probabilistic) simulations of the future. But could predictive processing be augmented using advanced technologies? In this contribution, we discuss how computational technologies may be used to support, facilitate or enhance the prediction of future events, by considering exemplificative scenarios across different domains, from simpler sensorimotor decisions to more complex cognitive tasks. We also examine the key scientific and technical challenges that must be faced to turn this vision into reality. PMID:27199648

Event-Driven Technology to Generate Relevant Collections of Near-Realtime Data

NASA Astrophysics Data System (ADS)

Graves, S. J.; Keiser, K.; Nair, U. S.; Beck, J. M.; Ebersole, S.

2017-12-01

Getting the right data when it is needed continues to be a challenge for researchers and decision makers. Event-Driven Data Delivery (ED3), funded by the NASA Applied Science program, is a technology that allows researchers and decision makers to pre-plan what data, information and processes they need to have collected or executed in response to future events. The Information Technology and Systems Center at the University of Alabama in Huntsville (UAH) has developed the ED3 framework in collaboration with atmospheric scientists at UAH, scientists at the Geological Survey of Alabama, and other federal, state and local stakeholders to meet the data preparedness needs for research, decisions and situational awareness. The ED3 framework supports an API that supports the addition of loosely-coupled, distributed event handlers and data processes. This approach allows the easy addition of new events and data processes so the system can scale to support virtually any type of event or data process. Using ED3's underlying services, applications have been developed that monitor for alerts of registered event types and automatically triggers subscriptions that match new events, providing users with a living "album" of results that can continued to be curated as more information for an event becomes available. This capability can allow users to improve capacity for the collection, creation and use of data and real-time processes (data access, model execution, product generation, sensor tasking, social media filtering, etc), in response to disaster (and other) events by preparing in advance for data and information needs for future events. This presentation will provide an update on the ED3 developments and deployments, and further explain the applicability for utilizing near-realtime data in hazards research, response and situational awareness.

Highlights from the Future Earth Water-Energy-Food (W-E-F) Nexus Cluster Project Consultations

NASA Astrophysics Data System (ADS)

Lawford, R. G.

2017-12-01

Future Earth launched its W-E-F Nexus project in 2015. The focus of the project was to explore how improved governance and integrated information systems could support sustainability in the W-E-F Nexus. Workshops were held in four regions of the world (North America, Europe, Eastern Asia, and Southern Africa) which facilitated a better understanding of the current role of information in decision-making within the W-E-F Nexus. In each of these workshops, needs and options for improving the provision of relevant integrated data and information to support decision-making were discussed. The workshops provided distinct perspectives on W-E-F issues for each region and each sector. Regional differences arise from climate, geomorphology, natural resources and existing infrastructure as well as the economic and social policies within each country. While the needs associated with this diversity are large, it is still possible to identify unifying themes and requirements for data and information which appeared very similar in all the regions. Important themes involve developing a common rigorous definition of the Nexus, ensuring the availability of data of all types are available in the scales, frequencies, and accuracies needed to support better decision making; and promoting the gathering, analysis and use of information to break down the silos associated with the three sectors are made. Information is also needed to monitor the effects of land ownership and land management on W-E-F issues, to maximize the efficiencies that can be realized from joint planning and increased coherence in the sectoral policy approaches to address climate and environmental issues. After commenting on these opportunities the presentation will outline possible elements of a research agenda for moving the W-E-F Nexus approach forward.

An overview of future EU health systems. An insight into governance, primary care, data collection and citizens' participation.

PubMed

Quaglio, Gianluca; Figueras, Josep; Mantoan, Domenico; Dawood, Amr; Karapiperis, Theodoros; Costongs, Caroline; Bernal-Delgado, Enrique

2018-03-26

Health systems in the European Union (EU) are being questioned over their effectiveness and sustainability. In pursuing both goals, they have to conciliate coexisting, not always aligned, realities. This paper originated from a workshop entitled 'Health systems for the future' held at the European Parliament. Experts and decision makers were asked to discuss measures that may increase the effectiveness and sustainability of health systems, namely: (i) increasing citizens' participation; (ii) the importance of primary care in providing integrated services; (iii) improving the governance and (iv) fostering better data collection and information channels to support the decision making process. In the parliamentary debate, was discussed the concept that, in the near future, health systems' effectiveness and sustainability will very much depend on effective access to integrated services where primary care is pivotal, a clearer shift from care-oriented systems to health promotion and prevention, a profound commitment to good governance, particularly to stakeholders participation, and a systematic reuse of data meant to build health data-driven learning systems. Many health issues, such as future health systems in the EU, are potentially transformative and hence an intense political issue. It is policy-making leadership that will mostly determine how well EU health systems are prepared to face future challenges.

Data mining for health executive decision support: an imperative with a daunting future!

PubMed Central

Glover, Saundra; Rivers, Patrick A; Asoh, Derek A; Piper, Crystal N; Murph, Keva

2010-01-01

Summary Data mining is highly profiled. It has the potential to enhance executive information systems. Such enhancement would mean better decision-making by management, which in turn would mean better services for customers. While the future of data mining as technology should be exciting, some are worried about privacy concerns, which make the future of data mining daunting. This paper examines why data mining is highly profiled – the imperative toward data mining, data mining models and processes. Additionally, the paper examines some of the benefits and challenges of using data mining processes within the health-care arena. We cast the future of data mining by highlighting two of the many data mining tools available – one commercial and one freely available. Subsequently, we discuss a number of social and technical factors that may thwart the extensive deployment of data mining, especially when the intent is to know more about the people that organizations have to serve and cast a view of what the future holds for data mining. This component is especially important when attempting to determine the longevity of data mining within health-care organizations. It is hoped that our discussions would be useful to organizations as they engage data mining, strategies for executive information systems and information policy issues. PMID:20150610

Evaluation of a Decision-Making Curriculum for Teaching Adolescents with Disabilities to Resist Negative Peer Pressure.

PubMed

Khemka, Ishita; Hickson, Linda; Mallory, Sarah B

2016-07-01

This study was designed to assess the impact of a decision-making curriculum (PEER-DM) on the social peer relationship knowledge and self-protective decision-making skills of adolescents with disabilities in hypothetical situations involving negative peer pressure. A randomized design was used to assign students with disabilities from self-contained special education classes to an intervention group (n = 22) or a wait-list control group (n = 20). ANCOVA analyses, using pretest scores as covariates, indicated that students who were trained on PEER-DM had significantly higher effective decision-making action and correct risk perception scores, relative to participants in the control group. This study provides supporting evidence that PEER-DM is a promising intervention for students with disabilities, including those with identified autism spectrum disorders, during transition years to help them develop a better understanding of positive and negative peer relationships and learn systematic decision-making skills for improved handling of social situations in the school and community, especially situations involving negative peer pressure. The study adds credence to using systematic, strategy-based decision making interventions designed to address the cognitive, emotional and motivational processes underlying adolescent decision making in sensitive interpersonal situations involving peer pressure. The study points to the lack of preparedness to handle situations of negative peer pressure as a serious social and health risk for adolescents with disabilities that deserves urgent and concerted attention in transition services programming. Implications for future curriculum-development efforts and replication of treatment findings are discussed. Future research examining disability-specific patterns of decision-making in peer situations and comparisons with typically developing populations is recommended.

Analysis of space systems for the space disposal of nuclear waste follow-on study. Volume 1: Executive summary

NASA Technical Reports Server (NTRS)

1982-01-01

The impact on space systems of three alternative waste mixes was evaluated as part of an effort to investigate the disposal of certain high-level nuclear wastes in space as a complement to mined geologic repositories. A brief overview of the study background, objectives, scope, approach and guidelines, and limitations is presented. The effects of variations in waste mixes on space system concepts were studied in order to provide data for determining relative total system risk benefits resulting from space disposal of the alternative waste mixes. Overall objectives of the NASA-DOE sustaining-level study program are to investigate space disposal concepts which can provide information to support future nuclear waste terminal storage programmatic decisions and to maintain a low level of research activity in this area to provide a baseline for future development should a decision be made to increase the emphasis on this option.

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.

Back to the Bedside: Developing a Bedside Aid for Concussion and Brain Injury Decisions in the Emergency Department

PubMed Central

Melnick, Edward R.; Lopez, Kevin; Hess, Erik P.; Abujarad, Fuad; Brandt, Cynthia A.; Shiffman, Richard N.; Post, Lori A.

2015-01-01

Context: Current information-rich electronic health record (EHR) interfaces require large, high-resolution screens running on desktop computers. This interface compromises the provider’s already limited time at the bedside by physically separating the patient from the doctor. The case study presented here describes a patient-centered clinical decision support (CDS) design process that aims to bring the physician back to the bedside by integrating a patient decision aid with CDS for shared use by the patient and provider on a touchscreen tablet computer for deciding whether or not to obtain a CT scan for minor head injury in the emergency department, a clinical scenario that could benefit from CDS but has failed previous implementation attempts. Case Description: This case study follows the user-centered design (UCD) approach to build a bedside aid that is useful and usable, and that promotes shared decision-making between patients and their providers using a tablet computer at the bedside. The patient-centered decision support design process focuses on the prototype build using agile software development, but also describes the following: (1) the requirement gathering phase including triangulated qualitative research (focus groups and cognitive task analysis) to understand current challenges, (2) features for patient education, the physician, and shared decision-making, (3) system architecture and technical requirements, and (4) future plans for formative usability testing and field testing. Lessons Learned: We share specific lessons learned and general recommendations from critical insights gained in the patient-centered decision support design process about early stakeholder engagement, EHR integration, external expert feedback, challenges to two users on a single device, project management, and accessibility. Conclusions: Successful implementation of this tool will require seamless integration into the provider’s workflow. This protocol can create an effective interface for shared decision-making and safe resource reduction at the bedside in the austere and dynamic clinical environment of the ED and is generalizable for these purposes in other clinical environments as well. PMID:26290885

Back to the Bedside: Developing a Bedside Aid for Concussion and Brain Injury Decisions in the Emergency Department.

PubMed

Melnick, Edward R; Lopez, Kevin; Hess, Erik P; Abujarad, Fuad; Brandt, Cynthia A; Shiffman, Richard N; Post, Lori A

2015-01-01

Current information-rich electronic health record (EHR) interfaces require large, high-resolution screens running on desktop computers. This interface compromises the provider's already limited time at the bedside by physically separating the patient from the doctor. The case study presented here describes a patient-centered clinical decision support (CDS) design process that aims to bring the physician back to the bedside by integrating a patient decision aid with CDS for shared use by the patient and provider on a touchscreen tablet computer for deciding whether or not to obtain a CT scan for minor head injury in the emergency department, a clinical scenario that could benefit from CDS but has failed previous implementation attempts. This case study follows the user-centered design (UCD) approach to build a bedside aid that is useful and usable, and that promotes shared decision-making between patients and their providers using a tablet computer at the bedside. The patient-centered decision support design process focuses on the prototype build using agile software development, but also describes the following: (1) the requirement gathering phase including triangulated qualitative research (focus groups and cognitive task analysis) to understand current challenges, (2) features for patient education, the physician, and shared decision-making, (3) system architecture and technical requirements, and (4) future plans for formative usability testing and field testing. We share specific lessons learned and general recommendations from critical insights gained in the patient-centered decision support design process about early stakeholder engagement, EHR integration, external expert feedback, challenges to two users on a single device, project management, and accessibility. Successful implementation of this tool will require seamless integration into the provider's workflow. This protocol can create an effective interface for shared decision-making and safe resource reduction at the bedside in the austere and dynamic clinical environment of the ED and is generalizable for these purposes in other clinical environments as well.

Clinical decision support: effectiveness in improving quality processes and clinical outcomes and factors that may influence success.

PubMed

Murphy, Elizabeth V

2014-06-01

The use of electronic health records has skyrocketed following the 2009 HITECH Act, which provides financial incentives to health care providers for the "meaningful use" of electronic medical record systems. An important component of the "Meaningful Use" legislation is the integration of Clinical Decision Support Systems (CDSS) into the computerized record, providing up-to-date medical knowledge and evidence-based guidance to the physician at the point of care. As reimbursement is increasingly tied to process and clinical outcomes, CDSS will be integral to future medical practice. Studies of CDSS indicate improvement in preventive services, appropriate care, and clinical and cost outcomes with strong evidence for CDSS effectiveness in process measures. Increasing provider adherence to CDSS recommendations is essential in improving CDSS effectiveness, and factors that influence adherence are currently under study.

Human Factors Report: TMA Operational Evaluations 1996 and 1998

NASA Technical Reports Server (NTRS)

Lee, Katharine K.; Quinn, Cheryl M.; Hoang, Ty; Sanford, Beverly D.

2000-01-01

The Traffic Management Advisor (TMA) is a component of the Center-TRACON Automation System (CTAS), a suite of decision-support tools for the air traffic control (ATC) environment which is being developed at NASA Ames Research Center. TMA has been operational at the ATC facilities in Dallas/Fort Worth, Texas, since an operational field evaluation in 1996. The Operational Evaluation demonstrated significant benefits, including an approximately 5 percent increase in airport capacity. This report describes the human factors results from the 1996 Operational Evaluation and an investigation of TMA usage performed two years later, during the 1998 TMA Daily Use Field Survey. The results described are instructive for CTAS focused development, and provide valuable lessons for future research in ATC decision-support tools where it is critical to merge a well-defined, complex work environment with advanced automation.

Service oriented architecture for clinical decision support: a systematic review and future directions.

PubMed

Loya, Salvador Rodriguez; Kawamoto, Kensaku; Chatwin, Chris; Huser, Vojtech

2014-12-01

The use of a service-oriented architecture (SOA) has been identified as a promising approach for improving health care by facilitating reliable clinical decision support (CDS). A review of the literature through October 2013 identified 44 articles on this topic. The review suggests that SOA related technologies such as Business Process Model and Notation (BPMN) and Service Component Architecture (SCA) have not been generally adopted to impact health IT systems' performance for better care solutions. Additionally, technologies such as Enterprise Service Bus (ESB) and architectural approaches like Service Choreography have not been generally exploited among researchers and developers. Based on the experience of other industries and our observation of the evolution of SOA, we found that the greater use of these approaches have the potential to significantly impact SOA implementations for CDS.

Service Oriented Architecture for Clinical Decision Support: A Systematic Review and Future Directions

PubMed Central

Loya, Salvador Rodriguez; Kawamoto, Kensaku; Chatwin, Chris; Huser, Vojtech

2017-01-01

The use of a service-oriented architecture (SOA) has been identified as a promising approach for improving health care by facilitating reliable clinical decision support (CDS). A review of the literature through October 2013 identified 44 articles on this topic. The review suggests that SOA related technologies such as Business Process Model and Notation (BPMN) and Service Component Architecture (SCA) have not been generally adopted to impact health IT systems’ performance for better care solutions. Additionally, technologies such as Enterprise Service Bus (ESB) and architectural approaches like Service Choreography have not been generally exploited among researchers and developers. Based on the experience of other industries and our observation of the evolution of SOA, we found that the greater use of these approaches have the potential to significantly impact SOA implementations for CDS PMID:25325996

Features of Computer-Based Decision Aids: Systematic Review, Thematic Synthesis, and Meta-Analyses.

PubMed

Syrowatka, Ania; Krömker, Dörthe; Meguerditchian, Ari N; Tamblyn, Robyn

2016-01-26

Patient information and education, such as decision aids, are gradually moving toward online, computer-based environments. Considerable research has been conducted to guide content and presentation of decision aids. However, given the relatively new shift to computer-based support, little attention has been given to how multimedia and interactivity can improve upon paper-based decision aids. The first objective of this review was to summarize published literature into a proposed classification of features that have been integrated into computer-based decision aids. Building on this classification, the second objective was to assess whether integration of specific features was associated with higher-quality decision making. Relevant studies were located by searching MEDLINE, Embase, CINAHL, and CENTRAL databases. The review identified studies that evaluated computer-based decision aids for adults faced with preference-sensitive medical decisions and reported quality of decision-making outcomes. A thematic synthesis was conducted to develop the classification of features. Subsequently, meta-analyses were conducted based on standardized mean differences (SMD) from randomized controlled trials (RCTs) that reported knowledge or decisional conflict. Further subgroup analyses compared pooled SMDs for decision aids that incorporated a specific feature to other computer-based decision aids that did not incorporate the feature, to assess whether specific features improved quality of decision making. Of 3541 unique publications, 58 studies met the target criteria and were included in the thematic synthesis. The synthesis identified six features: content control, tailoring, patient narratives, explicit values clarification, feedback, and social support. A subset of 26 RCTs from the thematic synthesis was used to conduct the meta-analyses. As expected, computer-based decision aids performed better than usual care or alternative aids; however, some features performed better than others. Integration of content control improved quality of decision making (SMD 0.59 vs 0.23 for knowledge; SMD 0.39 vs 0.29 for decisional conflict). In contrast, tailoring reduced quality of decision making (SMD 0.40 vs 0.71 for knowledge; SMD 0.25 vs 0.52 for decisional conflict). Similarly, patient narratives also reduced quality of decision making (SMD 0.43 vs 0.65 for knowledge; SMD 0.17 vs 0.46 for decisional conflict). Results were varied for different types of explicit values clarification, feedback, and social support. Integration of media rich or interactive features into computer-based decision aids can improve quality of preference-sensitive decision making. However, this is an emerging field with limited evidence to guide use. The systematic review and thematic synthesis identified features that have been integrated into available computer-based decision aids, in an effort to facilitate reporting of these features and to promote integration of such features into decision aids. The meta-analyses and associated subgroup analyses provide preliminary evidence to support integration of specific features into future decision aids. Further research can focus on clarifying independent contributions of specific features through experimental designs and refining the designs of features to improve effectiveness.

The use of syndromic surveillance for decision-making during the H1N1 pandemic: a qualitative study.

PubMed

Chu, Anna; Savage, Rachel; Willison, Don; Crowcroft, Natasha S; Rosella, Laura C; Sider, Doug; Garay, Jason; Gemmill, Ian; Winter, Anne-Luise; Davies, Richard F; Johnson, Ian

2012-10-30

Although an increasing number of studies are documenting uses of syndromic surveillance by front line public health, few detail the value added from linking syndromic data to public health decision-making. This study seeks to understand how syndromic data informed specific public health actions during the 2009 H1N1 pandemic. Semi-structured telephone interviews were conducted with participants from Ontario's public health departments, the provincial ministry of health and federal public health agency to gather information about syndromic surveillance systems used and the role of syndromic data in informing specific public health actions taken during the pandemic. Responses were compared with how the same decisions were made by non-syndromic surveillance users. Findings from 56 interviews (82% response) show that syndromic data were most used for monitoring virus activity, measuring impact on the health care system and informing the opening of influenza assessment centres in several jurisdictions, and supporting communications and messaging, rather than its intended purpose of early outbreak detection. Syndromic data had limited impact on decisions that involved the operation of immunization clinics, school closures, sending information letters home with school children or providing recommendations to health care providers. Both syndromic surveillance users and non-users reported that guidance from the provincial ministry of health, communications with stakeholders and vaccine availability were driving factors in these public health decisions. Syndromic surveillance had limited use in decision-making during the 2009 H1N1 pandemic in Ontario. This study provides insights into the reasons why this occurred. Despite this, syndromic data were valued for providing situational awareness and confidence to support public communications and recommendations. Developing an understanding of how syndromic data are utilized during public health events provides valuable evidence to support future investments in public health surveillance.

Future Needs and Recommendations in the Development of Species Sensitivity Distributions: Estimating Toxicity Thresholds for Aquatic Ecological Communities and Assessing Impacts of Chemical Exposures

EPA Science Inventory

A species sensitivity distribution (SSD) is a probability model of the variation of species sensitivities to a stressor, in particular chemical exposure. The SSD approach has been used as a decision support tool in environmental protection and management since the 1980s, and the ...

Institutional Transformation Model

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

2015-10-19

Reducing the energy consumption of large institutions with dozens to hundreds of existing buildings while maintaining and improving existing infrastructure is a critical economic and environmental challenge. SNL's Institutional Transformation (IX) work integrates facilities and infrastructure sustainability technology capabilities and collaborative decision support modeling approaches to help facilities managers at Sandia National Laboratories (SNL) simulate different future energy reduction strategies and meet long term energy conservation goals.

"What with Your Grades?" Students' Motivation for and Experiences of Vocational Courses in Further Education

ERIC Educational Resources Information Center

Fuller, C.; Macfadyen, T.

2012-01-01

In this article we seek to explore the motivations for studying a vocational qualification of 40 students currently in further education. We consider student decision making, in terms of the support and guidance received, and examine the value these students place on their training, particularly with respect to their future employment. Drawing on…

17 CFR 171.42 - Notice of a final decision of the National Futures Association in a member responsibility action.

Code of Federal Regulations, 2012 CFR

2012-04-01

... ACTIONS Commission Review of Decisions by the National Futures Association In Member Responsibility Actions § 171.42 Notice of a final decision of the National Futures Association in a member responsibility... the Proceeding Clerk and Secretary of the Commission, with a written notice of any final decision in a...

17 CFR 171.42 - Notice of a final decision of the National Futures Association in a member responsibility action.

Code of Federal Regulations, 2013 CFR

2013-04-01

... ACTIONS Commission Review of Decisions by the National Futures Association In Member Responsibility Actions § 171.42 Notice of a final decision of the National Futures Association in a member responsibility... the Proceeding Clerk and Secretary of the Commission, with a written notice of any final decision in a...

17 CFR 171.42 - Notice of a final decision of the National Futures Association in a member responsibility action.

Code of Federal Regulations, 2010 CFR

2010-04-01

... ACTIONS Commission Review of Decisions by the National Futures Association In Member Responsibility Actions § 171.42 Notice of a final decision of the National Futures Association in a member responsibility... the Proceeding Clerk and Secretary of the Commission, with a written notice of any final decision in a...

17 CFR 171.42 - Notice of a final decision of the National Futures Association in a member responsibility action.

Code of Federal Regulations, 2011 CFR

2011-04-01

... ACTIONS Commission Review of Decisions by the National Futures Association In Member Responsibility Actions § 171.42 Notice of a final decision of the National Futures Association in a member responsibility... the Proceeding Clerk and Secretary of the Commission, with a written notice of any final decision in a...

Competing neurobehavioral decision systems theory of cocaine addiction: From mechanisms to therapeutic opportunities.

PubMed

Bickel, Warren K; Snider, Sarah E; Quisenberry, Amanda J; Stein, Jeffrey S; Hanlon, Colleen A

2016-01-01

Cocaine dependence is a difficult-to-treat, chronically relapsing disorder. Multiple scientific disciplines provide distinct perspectives on this disorder; however, connections between disciplines are rare. The competing neurobehavioral decision systems (CNDS) theory posits that choice results from the interaction between two decision systems (impulsive and executive) and that regulatory imbalance between systems can induce pathology, including addiction. Using this view, we integrate a diverse set of observations on cocaine dependence, including bias for immediacy, neural activity and structure, developmental time course, behavioral comorbidities, and the relationship between cocaine dependence and socioeconomic status. From the CNDS perspective, we discuss established and emerging behavioral, pharmacological, and neurological treatments and identify possible targets for future treatments. The ability of the CNDS theory to integrate diverse findings highlights its utility for understanding cocaine dependence and supports that dysregulation between the decision systems contributes to addiction. © 2016 Elsevier B.V. All rights reserved.

Narrative dynamics in social groups: A discrete choice model

NASA Astrophysics Data System (ADS)

Antoci, A.; Bellanca, N.; Galdi, G.; Sodini, M.

2018-05-01

Individuals follow different rules for action: they react swiftly, grasping the short-term advantages in sight, or they waste cognitive resources to complete otherwise easy tasks, but they are able to plan ahead future complex decisions. Scholars from different disciplines studied the conditions under which either decision rule may enhance the fitness of its adopters, with a focus on the environmental features. However, we here propose that a crucial feature of the evolution of populations and their decision rules is rather inter-group interactions. Indeed, we study what happens when two groups support different decision rules, encapsulated in narratives, and their populations interact with each other. In particular, we assume that the payoff of each rule depends on the share of both social groups which adopt such rules. We then describe the most salient dynamics scenarios and identify the conditions which lead to chaotic dynamics and multistability regimes.

Modeling the customer in electronic commerce.

PubMed

Helander, M G; Khalid, H M

2000-12-01

This paper reviews interface design of web pages for e-commerce. Different tasks in e-commerce are contrasted. A systems model is used to illustrate the information flow between three subsystems in e-commerce: store environment, customer, and web technology. A customer makes several decisions: to enter the store, to navigate, to purchase, to pay, and to keep the merchandize. This artificial environment must be designed so that it can support customer decision-making. To retain customers it must be pleasing and fun, and create a task with natural flow. Customers have different needs, competence and motivation, which affect decision-making. It may therefore be important to customize the design of the e-store environment. Future ergonomics research will have to investigate perceptual aspects, such as presentation of merchandize, and cognitive issues, such as product search and navigation, as well as decision making while considering various economic parameters. Five theories on e-commerce research are presented.

Using decision analysis to support proactive management of emerging infectious wildlife diseases

USGS Publications Warehouse

Grant, Evan H. Campbell; Muths, Erin L.; Katz, Rachel A.; Canessa, Stefano; Adams, Michael J.; Ballard, Jennifer R.; Berger, Lee; Briggs, Cheryl J.; Coleman, Jeremy; Gray, Matthew J.; Harris, M. Camille; Harris, Reid N.; Hossack, Blake R.; Huyvaert, Kathryn P.; Kolby, Jonathan E.; Lips, Karen R.; Lovich, Robert E.; McCallum, Hamish I.; Mendelson, Joseph R.; Nanjappa, Priya; Olson, Deanna H.; Powers, Jenny G.; Richgels, Katherine L. D.; Russell, Robin E.; Schmidt, Benedikt R.; Spitzen-van der Sluijs, Annemarieke; Watry, Mary Kay; Woodhams, Douglas C.; White, C. LeAnn

2017-01-01

Despite calls for improved responses to emerging infectious diseases in wildlife, management is seldom considered until a disease has been detected in affected populations. Reactive approaches may limit the potential for control and increase total response costs. An alternative, proactive management framework can identify immediate actions that reduce future impacts even before a disease is detected, and plan subsequent actions that are conditional on disease emergence. We identify four main obstacles to developing proactive management strategies for the newly discovered salamander pathogen Batrachochytrium salamandrivorans (Bsal). Given that uncertainty is a hallmark of wildlife disease management and that associated decisions are often complicated by multiple competing objectives, we advocate using decision analysis to create and evaluate trade-offs between proactive (pre-emergence) and reactive (post-emergence) management options. Policy makers and natural resource agency personnel can apply principles from decision analysis to improve strategies for countering emerging infectious diseases.

Competing neurobehavioral decision systems theory of cocaine addiction: From mechanisms to therapeutic opportunities

PubMed Central

Bickel, Warren K.; Snider, Sarah E.; Quisenberry, Amanda J.; Stein, Jeffrey S.; Hanlon, Colleen A.

2017-01-01

Cocaine dependence is a difficult-to-treat, chronically relapsing disorder. Multiple scientific disciplines provide distinct perspectives on this disorder; however, connections between disciplines are rare. The competing neurobehavioral decision systems (CNDS) theory posits that choice results from the interaction between two decision systems (impulsive and executive) and that regulatory imbalance between systems can induce pathology, including addiction. Using this view, we integrate a diverse set of observations on cocaine dependence, including bias for immediacy, neural activity and structure, developmental time course, behavioral comorbidities, and the relationship between cocaine dependence and socioeconomic status. From the CNDS perspective, we discuss established and emerging behavioral, pharmacological, and neurological treatments and identify possible targets for future treatments. The ability of the CNDS theory to integrate diverse findings highlights its utility for understanding cocaine dependence and supports that dysregulation between the decision systems contributes to addiction. PMID:26806781

An overview and discussion of the Patient-Centered Outcomes Research Institute's decision aid portfolio.

PubMed

Gayer, Christopher C; Crowley, Matthew J; Lawrence, William F; Gierisch, Jennifer M; Gaglio, Bridget; Williams, John W; Myers, Evan R; Kendrick, Amy; Slutsky, Jean; Sanders, Gillian D

2016-07-01

Decision aids (DAs) help patients make informed healthcare decisions in a manner consistent with their values and preferences. Despite their promise, DAs developed with public research dollars are not being implemented and adopted in real-world patient care settings at a rate consistent with which they are being developed. To appraise the sum of the parts of the portfolio and create a strategic imperative surrounding future funding, the Patient-Centered Outcomes Research Institute (PCORI) tasked the Duke Evidence Synthesis Group with evaluating its DA portfolio. This paper describes PCORI's portfolio of DAs according to the Duke Evidence Synthesis Group's analysis in the context of PCORI's mission and the field of decision science. The results revealed a diversity within PCORI's portfolio of funded DA projects. Findings support the movement toward more rigorous DA development, assessment and maintenance. PCORI's funding priorities related to DAs are clarified and comparative questions of interest are posed.

Building Capacity to Use Earth Observations in Decision Making: A Case Study of NASA's DEVELOP National Program Methods and Best Practices

NASA Astrophysics Data System (ADS)

Childs-Gleason, L. M.; Ross, K. W.; Crepps, G.; Miller, T. N.; Favors, J. E.; Rogers, L.; Allsbrook, K. N.; Bender, M. R.; Ruiz, M. L.

2015-12-01

NASA's DEVELOP National Program fosters an immersive research environment for dual capacity building. Through rapid feasibility Earth science projects, the future workforce and current decision makers are engaged in research projects to build skills and capabilities to use Earth observation in environmental management and policy making. DEVELOP conducts over 80 projects annually, successfully building skills through partnerships with over 150 organizations and providing over 350 opportunities for project participants each year. Filling a void between short-term training courses and long-term research projects, the DEVELOP model has been successful in supporting state, local, federal and international government organizations to adopt methodologies and enhance decision making processes. This presentation will highlight programmatic best practices, feedback from participants and partner organizations, and three sample case studies of successful adoption of methods in the decision making process.

Patient, surgeon, and healthcare purchaser views on the use of decision and communication aids in orthopaedic surgery: a mixed methods study.

PubMed

Bozic, Kevin J; Chenok, Kate Eresian; Schindel, Jennifer; Chan, Vanessa; Huddleston, James I; Braddock, Clarence; Belkora, Jeffrey

2014-08-31

Despite evidence that decision and communication aids are effective for enhancing the quality of preference-sensitive decisions, their adoption in the field of orthopaedic surgery has been limited. The purpose of this mixed-methods study was to evaluate the perceived value of decision and communication aids among different healthcare stakeholders. Patients with hip or knee arthritis, orthopaedic surgeons who perform hip and knee replacement procedures, and a group of large, self-insured employers (healthcare purchasers) were surveyed regarding their views on the value of decision and communication aids in orthopaedics. Patients with hip or knee arthritis who participated in a randomized controlled trial involving decision and communication aids were asked to complete an online survey about what was most and least beneficial about each of the tools they used, the ideal mode of administration of these tools and services, and their interest in receiving comparable materials and services in the future. A subset of these patients were invited to participate in a telephone interview, where there were asked to rank and attribute a monetary value to the interventions. These interviews were analyzed using a qualitative and mixed methods analysis software. Members of the American Hip and Knee Surgeons (AAHKS) were surveyed on their perceptions and usage of decision and communication aids in orthopaedic practice. Healthcare purchasers were interviewed about their perspectives on patient-oriented decision support. All stakeholders saw value in decision and communication aids, with the major barrier to implementation being cost. Both patients and surgeons would be willing to bear at least part of the cost of implementing these tools, while employers felt health plans should be responsible for shouldering the costs. Decision and communication aids can be effective tools for incorporating patients preferences and values into preference-sensitive decisions in orthopaedics. Future efforts should be aimed at assessing strategies for efficient implementation of these tools into widespread orthopaedic practice.

Automated Modular Magnetic Resonance Imaging Clinical Decision Support System (MIROR): An Application in Pediatric Cancer Diagnosis.

PubMed

Zarinabad, Niloufar; Meeus, Emma M; Manias, Karen; Foster, Katharine; Peet, Andrew

2018-05-02

Advances in magnetic resonance imaging and the introduction of clinical decision support systems has underlined the need for an analysis tool to extract and analyze relevant information from magnetic resonance imaging data to aid decision making, prevent errors, and enhance health care. The aim of this study was to design and develop a modular medical image region of interest analysis tool and repository (MIROR) for automatic processing, classification, evaluation, and representation of advanced magnetic resonance imaging data. The clinical decision support system was developed and evaluated for diffusion-weighted imaging of body tumors in children (cohort of 48 children, with 37 malignant and 11 benign tumors). Mevislab software and Python have been used for the development of MIROR. Regions of interests were drawn around benign and malignant body tumors on different diffusion parametric maps, and extracted information was used to discriminate the malignant tumors from benign tumors. Using MIROR, the various histogram parameters derived for each tumor case when compared with the information in the repository provided additional information for tumor characterization and facilitated the discrimination between benign and malignant tumors. Clinical decision support system cross-validation showed high sensitivity and specificity in discriminating between these tumor groups using histogram parameters. MIROR, as a diagnostic tool and repository, allowed the interpretation and analysis of magnetic resonance imaging images to be more accessible and comprehensive for clinicians. It aims to increase clinicians' skillset by introducing newer techniques and up-to-date findings to their repertoire and make information from previous cases available to aid decision making. The modular-based format of the tool allows integration of analyses that are not readily available clinically and streamlines the future developments. ©Niloufar Zarinabad, Emma M Meeus, Karen Manias, Katharine Foster, Andrew Peet. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 02.05.2018.

Exploration-Related Research on ISS: Connecting Science Results to Future Missions

NASA Technical Reports Server (NTRS)

Rhatigan, Jennifer L.; Robinson, Julie A.; Sawin, Charles F.

2005-01-01

In January, 2004, the U.S. President announced The Vision for Space Exploration, and charged the National Aeronautics and Space Administration (NASA) with using the International Space Station (ISS) for research and technology targeted at supporting U.S. space exploration goals. This paper describes: What we have learned from the first four years of research on ISS relative to the exploration mission; The on-going research being conducted in this regard; and Our current understanding of the major exploration mission risks that the ISS can be used to address. Specifically, we discuss research carried out on the ISS to determine the mechanisms by which human health is affected on long-duration missions, and to develop countermeasures to protect humans from the space environment. These bioastronautics experiments are key enablers of future long duration human exploration missions. We also discuss how targeted technological developments can enable mission design trade studies. We discuss the relationship between the ultimate number of human test subjects available on the ISS to the quality and quantity of scientific insight that can be used to reduce health risks to future explorers. We discuss the results of NASA's efforts over the past year to realign the ISS research programs to support a product-driven portfolio that is directed towards reducing the major risks of exploration missions. The fundamental challenge to science on ISS is completing experiments that answer key questions in time to shape design decisions for future exploration. In this context, exploration relevant research must do more than be conceptually connected to design decisions - it must become a part of the mission design process.

Transportation Energy Futures Series: Vehicle Technology Deployment Pathways: An Examination of Timing and Investment Constraints

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

Plotkin, S.; Stephens, T.; McManus, W.

2013-03-01

Scenarios of new vehicle technology deployment serve various purposes; some will seek to establish plausibility. This report proposes two reality checks for scenarios: (1) implications of manufacturing constraints on timing of vehicle deployment and (2) investment decisions required to bring new vehicle technologies to market. An estimated timeline of 12 to more than 22 years from initial market introduction to saturation is supported by historical examples and based on the product development process. Researchers also consider the series of investment decisions to develop and build the vehicles and their associated fueling infrastructure. A proposed decision tree analysis structure could bemore » used to systematically examine investors' decisions and the potential outcomes, including consideration of cash flow and return on investment. This method requires data or assumptions about capital cost, variable cost, revenue, timing, and probability of success/failure, and would result in a detailed consideration of the value proposition of large investments and long lead times. This is one of a series of reports produced as a result of the Transportation Energy Futures (TEF) project, a Department of Energy-sponsored multi-agency effort to pinpoint underexplored strategies for abating GHGs and reducing petroleum dependence related to transportation.« less

Transportation Energy Futures Series. Vehicle Technology Deployment Pathways. An Examination of Timing and Investment Constraints

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

Plotkin, Steve; Stephens, Thomas; McManus, Walter

2013-03-01

Scenarios of new vehicle technology deployment serve various purposes; some will seek to establish plausibility. This report proposes two reality checks for scenarios: (1) implications of manufacturing constraints on timing of vehicle deployment and (2) investment decisions required to bring new vehicle technologies to market. An estimated timeline of 12 to more than 22 years from initial market introduction to saturation is supported by historical examples and based on the product development process. Researchers also consider the series of investment decisions to develop and build the vehicles and their associated fueling infrastructure. A proposed decision tree analysis structure could bemore » used to systematically examine investors' decisions and the potential outcomes, including consideration of cash flow and return on investment. This method requires data or assumptions about capital cost, variable cost, revenue, timing, and probability of success/failure, and would result in a detailed consideration of the value proposition of large investments and long lead times. This is one of a series of reports produced as a result of the Transportation Energy Futures (TEF) project, a Department of Energy-sponsored multi-agency effort to pinpoint underexplored strategies for abating GHGs and reducing petroleum dependence related to transportation.« less

'The family is only one part …': understanding the role of family in young Thai women's sexual decision making.

PubMed

Bangpan, Mukdarut; Operario, Don

2014-01-01

This study aims to understand young Thai women's perspectives about family influences on their sexual decisions with the goal of informing the future development of HIV programmes and interventions for young Thai women in urban areas. Eight focus groups were conducted with 40 young single women aged 18-25 years, recruited through a peer network of key informants from four sites across Bangkok: universities, government offices, slums and garment factories. Predetermined topics relating to family, sexual decisions and HIV were discussed with 4-5 participants in each group. Qualitative thematic and framework-analysis techniques were used to explore participants' narratives. Findings suggest that young Thai women's sexual decisions are complex and take place under a wide range of personal, familial and social influences. Parents were perceived as a barrier to parent-child communication about sex and HIV. Young women regarded mothers as more supportive and receptive than fathers when discussing sensitive topics. Young Thai women described a tension between having a strong sense of self and modern sexual norms versus traditionally conservative relational orientations. Future HIV interventions could benefit by developing strategies to consider barriers to parent-child communication, strengthening family relationships and addressing the coexistence of conflicting sexual norms in the Thai context.

Treatment limitation decisions under uncertainty: the value of subsequent euthanasia.

PubMed

Savulescu, Julian

1994-01-01

This paper examines how decisions to limit treatment to critically ill patients under uncertainty can be made rationally. Expected utility theory offers one way of making rational decisions under uncertainty. One problem with using this approach is that we may not know the value of each option. One rational course open is to treat until further information becomes available. However, treatment can limit the range of options open. With treatment, a patient may recover such that he no longer requires life-supporting treatment. However, his life may be not worth living. If active euthanasia of 'non-terminal' conditions is prohibited, the option of dying will no longer be available. Taking a rational 'wait and see' course may result in being trapped within an unbearable life. On the other hand, sometimes present practice 'lets nature take its course'. Critically ill patients are allowed to die because it is believed that their lives will be not worth living. It is likely that some patients are allowed to die when there is some objective chance of worthwhile future life. This paper argues that a policy of treating critically ill patients until the nature of future options can be better evaluated, in company with an offer of subsequent euthanasia where appropriate, allows a more rational and humane approach to treatment limitation decisions under uncertainty.

Integrative sensing and prediction of urban water for sustainable cities (iSPUW)

NASA Astrophysics Data System (ADS)

Seo, D. J.; Fang, N. Z.; Yu, X.; Zink, M.; Gao, J.; Kerkez, B.

2014-12-01

We describe a newly launched project in the Dallas-Fort Worth Metroplex (DFW) area to develop a cyber-physical prototype system that integrates advanced sensing, modeling and prediction of urban water, to support its early adoption by a spectrum of users and stakeholders, and to educate a new generation of future sustainability scientists and engineers. The project utilizes the very high-resolution precipitation and other sensing capabilities uniquely available in DFW as well as crowdsourcing and cloud computing to advance understanding of the urban water cycle and to improve urban sustainability from transient shocks of heavy-to-extreme precipitation under climate change and urbanization. All available water information from observations and models will be fused objectively via advanced data assimilation to produce the best estimate of the state of the uncertain system. Modeling, prediction and decision support tools will be developed in the ensemble framework to increase the information content of the analysis and prediction and to support risk-based decision making.

mHealth for Clinical Decision-Making in Sub-Saharan Africa: A Scoping Review

PubMed Central

Albersen, Bregje Joanna Antonia; De Brouwere, Vincent; van Roosmalen, Jos; Zweekhorst, Marjolein

2017-01-01

Background In a bid to deliver quality health services in resource-poor settings, mobile health (mHealth) is increasingly being adopted. The role of mHealth in facilitating evidence-based clinical decision-making through data collection, decision algorithms, and evidence-based guidelines, for example, is established in resource-rich settings. However, the extent to which mobile clinical decision support systems (mCDSS) have been adopted specifically in resource-poor settings such as Africa and the lessons learned about their use in such settings are yet to be established. Objective The aim of this study was to synthesize evidence on the use of mHealth for point-of-care decision support and improved quality of care by health care workers in Africa. Methods A scoping review of 4 peer-reviewed and 1 grey literature databases was conducted. No date limits were applied, but only articles in English language were selected. Using pre-established criteria, 2 reviewers screened articles and extracted data. Articles were analyzed using Microsoft Excel and MAXQDA. Results We retained 22 articles representing 11 different studies in 7 sub-Saharan African countries. Interventions were mainly in the domain of maternal health and ranged from simple text messaging (short message service, SMS) to complex multicomponent interventions. Although health workers are generally supportive of mCDSS and perceive them as useful, concerns about increased workload and altered workflow hinder sustainability. Facilitators and barriers to use of mCDSS include technical and infrastructural support, ownership, health system challenges, and training. Conclusions The use of mCDSS in sub-Saharan Africa is an indication of progress in mHealth, although their effect on quality of service delivery is yet to be fully explored. Lessons learned are useful for informing future research, policy, and practice for technologically supported health care delivery, especially in resource-poor settings. PMID:28336504

Impact of disability on families: grandparents' perspectives.

PubMed

Miller, E; Buys, L; Woodbridge, S

2012-01-01

Caring for a child with a disability can be a unique and challenging experience, with families often relying on informal networks for support. Often, grandparents are key support resources, yet little is known about their roles and experiences. Reporting on data collected in a larger Australian study, this article explores grandparents' experiences of caring for a child with a disability and the impact on their family relationships and quality of life. A qualitative purposive sampling design was utilised; semi-structured interviews were conducted with 22 grandparents (17 women, 5 men) of children with a disability. Grandparents ranged in age from 55 to 75 years old and lived within a 90-min drive of Brisbane, Australia. Interviews were transcribed and responses analysed using a thematic approach, identifying categories, themes and patterns. Four key themes characterised grandparents' views about their role in the family: holding own emotions (decision to be positive), self-sacrifice (decision to put family needs first), maintaining family relationships (being the 'go-between') and quality of life for family in the future (concerns about the future). Grandparents are central to family functioning and quality of life, but this contribution comes with a significant cost to their own personal well-being. Implications for policy, practice and research are discussed, particularly grandparents' fear that their family could not cope without their support. © 2011 The Authors. Journal of Intellectual Disability Research © 2011 Blackwell Publishing Ltd.

Model-based choices involve prospective neural activity

PubMed Central

Doll, Bradley B.; Duncan, Katherine D.; Simon, Dylan A.; Shohamy, Daphna; Daw, Nathaniel D.

2015-01-01

Decisions may arise via “model-free” repetition of previously reinforced actions, or by “model-based” evaluation, which is widely thought to follow from prospective anticipation of action consequences using a learned map or model. While choices and neural correlates of decision variables sometimes reflect knowledge of their consequences, it remains unclear whether this actually arises from prospective evaluation. Using functional MRI and a sequential reward-learning task in which paths contained decodable object categories, we found that humans’ model-based choices were associated with neural signatures of future paths observed at decision time, suggesting a prospective mechanism for choice. Prospection also covaried with the degree of model-based influences on neural correlates of decision variables, and was inversely related to prediction error signals thought to underlie model-free learning. These results dissociate separate mechanisms underlying model-based and model-free evaluation and support the hypothesis that model-based influences on choices and neural decision variables result from prospection. PMID:25799041

[Suspension of Respiratory Support in Patients with Amyotrophic Lateral Sclerosis].

PubMed

Silberberg, Agustín A; Robetto, Josefina; Achával, Mora

2018-01-01

Decision making in advanced Amyotrophic Lateral Sclerosis (ALS) patients keeps on being a controversial issue. The aim of this work is to discuss ethical implications of withdrawing respiratory support treatment in patients with ALS. Through a bibliographic search on Pubmed database (2010-2016) we investigated whether or not the use of Non-Invasive Ventilation (NIV) and Mechanical Ventilation (MV) would increase survival and quality of life. We included 38 review articles. From these papers, results and ethical implications of initiating and mainly withdrawing respiratory support were analyzed. Survival time increased with NIV and with MV. Quality of life, above all according to physiological criteria, improved with NIV but regarding MV it remained controversial. Implementation and future withdrawal of MV seemed open to medical and ethical discussion. From a perspective of the intrinsic dignity of every human being, whatever its quality of life was, and knowing that no effective therapies for the underlying disease are available, the decision to remove MV in a patient with advanced ALS requires: knowledge of the will of the patient and, above all, evaluating whether this respiratory support measure is becoming objectively disproportionate.

Parametric Analysis of Life Support Systems for Future Space Exploration Missions

NASA Technical Reports Server (NTRS)

Swickrath, Michael J.; Anderson, Molly S.; Bagdigian, Bob M.

2011-01-01

The National Aeronautics and Space Administration is in a process of evaluating future targets for space exploration. In order to maintain the welfare of a crew during future missions, a suite of life support technology is responsible for oxygen and water generation, carbon dioxide control, the removal of trace concentrations of organic contaminants, processing and recovery of water, and the storage and reclamation of solid waste. For each particular life support subsystem, a variety competing technologies either exist or are under aggressive development efforts. Each individual technology has strengths and weaknesses with regard to launch mass, power and cooling requirements, volume of hardware and consumables, and crew time requirements for operation. However, from a system level perspective, the favorability of each life support architecture is better assessed when the sub-system technologies are analyzed in aggregate. In order to evaluate each specific life support system architecture, the measure of equivalent system mass (ESM) was employed to benchmark system favorability. Moreover, the results discussed herein will be from the context of loop-closure with respect to the air, water, and waste sub-systems. Specifically, closure relates to the amount of consumables mass that crosses the boundary of the vehicle over the lifetime of a mission. As will be demonstrated in this manuscript, the optimal level of loop closure is heavily dependent upon mission requirements such as duration and the level of extra-vehicular activity (EVA) performed. Sub-system level trades were also considered as a function of mission duration to assess when increased loop closure is practical. Although many additional factors will likely merit consideration in designing life support systems for future missions, the ESM results described herein provide a context for future architecture design decisions toward a flexible path program.

CAEP 2016 Academic Symposium on Education Scholarship: Training our Future Clinician Educators in Emergency Medicine.

PubMed

Woods, Robert A; Artz, Jennifer D; Carrière, Benoit; Field, Simon; Huffman, James; Dong, Sandy L; Bhanji, Farhan; Yiu, Stella; Smith, Sheila; Mengual, Rose; Hicks, Chris; Frank, Jason

2017-05-01

To develop consensus recommendations for training future clinician educators (CEs) in emergency medicine (EM). A panel of EM education leaders was assembled from across Canada and met regularly by teleconference over the course of 1 year. Recommendations for CE training were drafted based on the panel's experience, a literature review, and a survey of current and past EM education leaders in Canada. Feedback was sought from attendees at the Canadian Association of Emergency Physicians (CAEP) annual academic symposium. Recommendations were distributed to the society's Academic Section for further feedback and updated by a consensus of the expert panel. Recommendations were categorized for one of three audiences: 1) Future CEs; 2) Academic departments and divisions (AD&D) that support training to fulfill their education leadership goals; and 3) The CAEP Academic Section. Advanced medical education training is recommended for any emergency physician or resident who pursues an education leadership role. Individuals should seek out mentorship in making decisions about career opportunities and training options. AD&D should regularly perform a needs assessment of their future CE needs and identify and encourage potential individuals who fulfill education leadership roles. AD&D should develop training opportunities at their institution, provide support to complete this training, and advocate for the recognition of education scholarship in their institutional promotions process. The CAEP Academic Section should support mentorship of future CEs on a national scale. These recommendations serve as a framework for training and supporting the next generation of Canadian EM medical educators.

Development of a decision aid for energy resource management for the Navajo Nation incorporating environmental cultural values

NASA Astrophysics Data System (ADS)

Necefer, Len Edward

Decision-making surrounding pathways of future energy resource management are complexity and requires balancing tradeoffs of multiple environmental, social, economic, and technical outcomes. Technical decision aid can provide a framework for informed decision making, allowing individuals to better understand the tradeoff between resources, technology, energy services, and prices. While technical decision aid have made significant advances in evaluating these quantitative aspects of energy planning and performance, they have not been designed to incorporate human factors, such as preferences and behavior that are informed by cultural values. Incorporating cultural values into decision tools can provide not only an improved decision framework for the Navajo Nation, but also generate new insights on how these perspective can improve decision making on energy resources. Ensuring these aids are a cultural fit for each context has the potential to increase trust and promote understanding of the tradeoffs involved in energy resource management. In this dissertation I present the development of a technical tool that explicitly addresses cultural and spiritual values and experimentally assesses their influence on the preferences and decision making of Navajo citizens. Chapter 2 describes the results of a public elicitation effort to gather information about stakeholder views and concerns related to energy development in the Navajo Nation in order to develop a larger sample survey and a decision-support tool that links techno-economic energy models with sociocultural attributes. Chapter 3 details the methods of developing the energy decision aid and its underlying assumptions for alternative energy projects and their impacts. This tool also provides an alternative to economic valuation of cultural impacts based upon an ordinal index tied to environmental impacts. Chapter 4 details the the influence of various cultural, environmental, and economic outcome information provided through the developed decision aid on beliefs and preferences related to the type and scale of energy development, trust of decision makers, and larger concern for environmental protection. Finally, chapter 5 presents concluding thoughts future research and on how technical-social decision tools can provide a means ensuring effective decision making on the Navajo Nation and other American Indian communities.

Evidence and Options for Informed Decision-Making to Achive Arctic Sustainability

NASA Astrophysics Data System (ADS)

Berkman, P. A.

2017-12-01

This presentation will consider the development of evidence and options for informed decision-making that will need to operate across generations to achieve Arctic sustainability (Figure). Context of these Arctic decisions is global, recognizing that we live in an interconnected civilization on a planetary scale, as revealed unambiguously with evidence from the `world' wars in the first half of the 20thcentury. First, for clarification, data and evidence are not the same. Data is generated from information and observations to answer specific questions, posed with methods from the natural and social sciences as well as indigenous knowledge. These data reveal patterns and trends in our societies and natural world, underscoring the evidence for decisions to address impacts, issues and resources within, across and beyond the boundaries of nations - recognizing that nations still are the principal jurisdictional unit. However, for this decision-support process to be effective, options (without advocacy) - which can be used or ignored explicitly - must be generated from the evidence, taking into consideration stakeholder perspectives and governance records in a manner that will contribute to informed decision-making. The resulting decisions will involve built elements that require capitalization and technology as well as governance mechanisms coming from diverse jurisdictional authorities. The innovation required is to balance economic prosperity, environmental protection and societal well-being. These three pillars of sustainability further involve stability, balancing urgencies of the moment and of future generations, recognizing that children born today will be alive in the 22nd century. Consequently, options for informed decisions must operate across a continuum of urgencies from security time scales to sustainability time scales. This decision-support process is holistic (international, interdisciplinary and inclusive), reflecting the applications of science diplomacy to balance national interests and common interests for the benefit of all on Earth.

Treatment decision-making processes in the systemic treatment of ovarian cancer: review of the scientific evidence.

PubMed

Luketina, Hrvoje; Fotopoulou, Christina; Luketina, Ruzica-Rosalia; Pilger, Adak; Sehouli, Jalid

2012-09-01

The systemic treatment of epithelial ovarian cancer (OC) is one of the cornerstones in the multimodal management of advanced OC in both primary and recurrent stages of this disease. In most situations various treatment options are available but only few data exists about the treatment decision-making process. Therefore, we conducted a review of the current literature regarding the decision-making process concerning the systemic therapy in patients with advanced ovarian cancer. The electronic database MEDLINE (PubMed) was systematically reviewed for studies that evaluate the treatment decision-making processes in patients with advanced OC. The PubMed database was searched in detail for all titles and abstracts of potentially relevant studies published between 1995 and 2011. An initial search identified 15 potentially relevant studies, but only seven met all inclusion criteria. Factors that influence treatment decisions in patients with OC include not only rational arguments and medical reasons, but also individual attitudes, fears, existential questions, various projections resulting from the physician patient relationship and the social environment. The physician's personal experience with OC treatment seems to be an important factor, followed by previous personal experience with medical issues, and the fear of side-effects and future metastases. Family and self-support organisations also seem to play a significant role in the treatment decision-making process. This review underlines the need for more research activities to explore the treatment decision-making process to enable the best individual support for patients in treatment decision-making. It is a challenge for clinicians to determine the individual information needs of women with OC and to involve them during the decision-making process to the extent they wish.

Advance care planning and proxy decision making for patients with advanced Parkinson disease.

PubMed

Kwak, Jung; Wallendal, Maggie S; Fritsch, Thomas; Leo, Gary; Hyde, Trevor

2014-03-01

To examine advance care planning practices and proxy decision making by family healthcare proxies for patients with advanced Parkinson disease (PD). Sixty-four spouses and adult children, self-designated as a/the healthcare proxy for advanced patients with PD, participated in a cross-sectional survey study. Sixty patients with PD (95%) had completed a living will, but only 38% had shared the document with a physician. Among three life-support treatments--cardiopulmonary resuscitation (CPR), ventilator, and feeding tube--47% of patients opted for CPR, 16% for ventilator, and 20% for feeding tube. Forty-two percent of proxies did not know patients' preferences for one or more of the three life-support treatments. Only 28% of proxies reported that patients wanted hospice. Patients who shared advance directives with a physician were significantly less likely to choose CPR and a feeding tube and they were more likely to choose hospice. In a hypothetical end-of-life (EOL) scenario, the majority of proxies chose comfort care as the EOL goal of care (53%) and pain and symptom management only as the course of treatment option (72%); these proxy choices for patients, however, were not associated with patients' preferences for life support. Patients' proxies preferred a form of shared decision making with other family members and physicians. Advance care planning is effective when patients, families, and healthcare professionals together consider future needs for EOL care decisions. Further efforts are needed by healthcare professionals to provide evidence-based education about care options and facilitate advanced discussion and shared decision making by the patient and families.

Strategies to support drug discovery through integration of systems and data.

PubMed

Waller, Chris L; Shah, Ajay; Nolte, Matthias

2007-08-01

Much progress has been made over the past several years to provide technologies for the integration of drug discovery software applications and the underlying data bits. Integration at the application layer has focused primarily on developing and delivering applications that support specific workflows within the drug discovery arena. A fine balance between creating behemoth applications and providing business value must be maintained. Heterogeneous data sources have typically been integrated at the data level in an effort to provide a more holistic view of the data packages supporting key decision points. This review will highlight past attempts, current status, and potential future directions for systems and data integration strategies in support of drug discovery efforts.

Automatic Decision Support for Clinical Diagnostic Literature Using Link Analysis in a Weighted Keyword Network.

PubMed

Li, Shuqing; Sun, Ying; Soergel, Dagobert

2017-12-23

We present a novel approach to recommending articles from the medical literature that support clinical diagnostic decision-making, giving detailed descriptions of the associated ideas and principles. The specific goal is to retrieve biomedical articles that help answer questions of a specified type about a particular case. Based on the filtered keywords, MeSH(Medical Subject Headings) lexicon and the automatically extracted acronyms, the relationship between keywords and articles was built. The paper gives a detailed description of the process of by which keywords were measured and relevant articles identified based on link analysis in a weighted keywords network. Some important challenges identified in this study include the extraction of diagnosis-related keywords and a collection of valid sentences based on the keyword co-occurrence analysis and existing descriptions of symptoms. All data were taken from medical articles provided in the TREC (Text Retrieval Conference) clinical decision support track 2015. Ten standard topics and one demonstration topic were tested. In each case, a maximum of five articles with the highest relevance were returned. The total user satisfaction of 3.98 was 33% higher than average. The results also suggested that the smaller the number of results, the higher the average satisfaction. However, a few shortcomings were also revealed since medical literature recommendation for clinical diagnostic decision support is so complex a topic that it cannot be fully addressed through the semantic information carried solely by keywords in existing descriptions of symptoms. Nevertheless, the fact that these articles are actually relevant will no doubt inspire future research.

Practitioner perspectives on extended clinical placement programs in optometry.

PubMed

Bentley, Sharon A; Cartledge, Amy; Guest, Daryl J; Cappuccio, Skye; Woods, Craig A

2016-05-01

Some universities are looking to provide a more diverse range of clinical learning experiences through extended clinical placement programs. This approach will potentially have a significant impact on practitioners. The aim of this study was to conduct a national survey of optometrists to ascertain their perspectives on participating in extended clinical placement programs. Members of Optometry Australia were invited to participate in a survey conducted during June and July 2014. A total of 268 practitioners participated (six per cent of registered Australian optometrists): 159 were predominantly employees or locums and 109 were owners or managers who identified as the key representative of a practice or organisation for the purpose of this survey. Almost two-thirds (65 per cent) of participants, who were employees or locums were supportive of extended clinical placement programs. Among this group, females were more likely to be supportive than males (p = 0.033). In comparison, just over one-third (34 per cent) of participants who were key decision-makers were supportive, with 30 per cent possibly supportive and 36 per cent not supportive. Among key decision-makers, males were more likely to be supportive (p = 0.009). The top three perceived advantages of supervising a student were: opportunity to mentor early career development, opportunity to give back to the profession and future recruitment. The top three perceived disadvantages were: burden on time, decrease in number of patients examined and burden on support staff. Suggested incentives for supervising students were credit for continuing professional development and financial remuneration. There appears to be moderate support for extended clinical placement programs; however, there are incentives that might engage a larger proportion of the profession in the future. These findings can inform the development of effective and sustainable clinical training programs for optometry students. Additionally, the findings might be used as evidence to seek Government support for clinical placement training in optometry. © 2016 Optometry Australia.

The role of emotion in decision-making: evidence from neurological patients with orbitofrontal damage.

PubMed

Bechara, Antoine

2004-06-01

Most theories of choice assume that decisions derive from an assessment of the future outcomes of various options and alternatives through some type of cost-benefit analyses. The influence of emotions on decision-making is largely ignored. The studies of decision-making in neurological patients who can no longer process emotional information normally suggest that people make judgments not only by evaluating the consequences and their probability of occurring, but also and even sometimes primarily at a gut or emotional level. Lesions of the ventromedial (which includes the orbitofrontal) sector of the prefrontal cortex interfere with the normal processing of "somatic" or emotional signals, while sparing most basic cognitive functions. Such damage leads to impairments in the decision-making process, which seriously compromise the quality of decisions in daily life. The aim of this paper is to review evidence in support of "The Somatic Marker Hypothesis," which provides a systems-level neuroanatomical and cognitive framework for decision-making and suggests that the process of decision-making depends in many important ways on neural substrates that regulate homeostasis, emotion, and feeling. The implications of this theoretical framework for the normal and abnormal development of the orbitofrontal cortex are also discussed.

The reciprocal dynamic model of career decision ambiguity tolerance with career indecision: A longitudinal three-wave investigation.

PubMed

Xu, Hui; Tracey, Terence J G

2017-10-01

The current study investigated the dynamic interplay of career decision ambiguity tolerance and career indecision over 3 assessment times in a sample of college students (n = 583). While the previous research has repeatedly shown an association of career decision ambiguity tolerance with career indecision, the direction of this association has not been adequately assessed with longitudinal investigation. It was hypothesized in this study that there is a reciprocal pattern of career decision ambiguity tolerance leading to subsequent career indecision and career indecision leading to subsequent career decision ambiguity tolerance. Using a cross-lagged panel design, this study found support for the reciprocal pattern that aversion to ambiguity led to increased negative affect and choice anxiety in career decision making, while negative affect and choice anxiety led to increased aversion to ambiguity. Additionally, this study revealed that aversion led to decreased readiness for career decision making and readiness for career decision making led to increased interests in new information. The key findings were discussed with respect to the theoretical and clinical implications for career counseling along with limitations and suggestions for future research. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Mass balances for a biological life support system simulation model

NASA Technical Reports Server (NTRS)

Volk, Tyler; Rumel, John D.

1987-01-01

Design decisions to aid the development of future space-based biological life support systems (BLSS) can be made with simulation models. Here the biochemical stoichiometry is developed for: (1) protein, carbohydrate, fat, fiber, and lignin production in the edible and inedible parts of plants; (2) food consumption and production of organic solids in urine, feces, and wash water by the humans; and (3) operation of the waste processor. Flux values for all components are derived for a steady-state system with wheat as the sole food source.

Human factors in spacecraft design

NASA Technical Reports Server (NTRS)

Harrison, Albert A.; Connors, Mary M.

1990-01-01

This paper describes some of the salient implications of evolving mission parameters for spacecraft design. Among the requirements for future spacecraft are new, higher standards of living, increased support of human productivity, and greater accommodation of physical and cultural variability. Design issues include volumetric allowances, architecture and layouts, closed life support systems, health maintenance systems, recreational facilities, automation, privacy, and decor. An understanding of behavioral responses to design elements is a precondition for critical design decisions. Human factors research results must be taken into account early in the course of the design process.

A Web-Based Decision Support System for Assessing Regional Water-Quality Conditions and Management Actions

USGS Publications Warehouse

Booth, N.L.; Everman, E.J.; Kuo, I.-L.; Sprague, L.; Murphy, L.

2011-01-01

The U.S. Geological Survey National Water Quality Assessment Program has completed a number of water-quality prediction models for nitrogen and phosphorus for the conterminous United States as well as for regional areas of the nation. In addition to estimating water-quality conditions at unmonitored streams, the calibrated SPAtially Referenced Regressions On Watershed attributes (SPARROW) models can be used to produce estimates of yield, flow-weighted concentration, or load of constituents in water under various land-use condition, change, or resource management scenarios. A web-based decision support infrastructure has been developed to provide access to SPARROW simulation results on stream water-quality conditions and to offer sophisticated scenario testing capabilities for research and water-quality planning via a graphical user interface with familiar controls. The SPARROW decision support system (DSS) is delivered through a web browser over an Internet connection, making it widely accessible to the public in a format that allows users to easily display water-quality conditions and to describe, test, and share modeled scenarios of future conditions. SPARROW models currently supported by the DSS are based on the modified digital versions of the 1:500,000-scale River Reach File (RF1) and 1:100,000-scale National Hydrography Dataset (medium-resolution, NHDPlus) stream networks. ?? 2011 American Water Resources Association. This article is a U.S. Government work and is in the public domain in the USA.

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.

Decision-making for delivery location and quality of care among slum-dwellers: a qualitative study in Uttar Pradesh, India.

PubMed

Sudhinaraset, May; Beyeler, Naomi; Barge, Sandhya; Diamond-Smith, Nadia

2016-07-07

In 2013, the Government of India launched the National Urban Health Mission (NUHM) in order to better address the health needs of urban populations, including the nearly 100 million living in slums. Maternal and neonatal health indicators remain poor in India. The objective of this study is to highlight the experiences of women, their husbands, and mothers-in-law related to maternal health services and delivery experiences. In total, we conducted 80 in-depth interviews, including 40 with recent mothers, 20 with their husbands, and 20 with their mothers-in-law. Purposeful sampling was conducted in order to obtain differences across delivery experiences (facility vs. home), followed by their family members. Major factors that influence decision-making about where to seek care included household dynamics and joint-decision-making with families, financial barriers, and perceived quality of care. Women perceived that private facilities were higher quality compared to public facilities, but also more expensive. Disrespectful care, bribes in the facility, and payment challenges were common in this population. A number of programmatic and policy recommendations are highlighted from this study. Future endeavors should include a greater focus on health education and public programs, including educating women on how to access programs, who is eligible, and how to obtain public funds. Families need to be educated on their rights and expectations in facilities. Future programs should consider the role of husbands and mothers-in-law in reproductive decision-making and support during deliveries. Triangulating information from multiple sources is important for future research efforts.

Exploring views on current and future cochlear implant service delivery: the perspectives of users, parents and professionals at cochlear implant centres and in the community.

PubMed

Athalye, Sheetal; Archbold, Sue; Mulla, Imran; Lutman, Mark; Nikolopoulous, Thomas

2015-09-01

The objective of this survey was to explore the perceptions of implant users/carers and professionals across the UK about current and future cochlear implant service delivery and the challenges. Data were collected via an online questionnaire consisting of totally 22 questions. The questionnaire contained both open- and close-ended questions. Totally, seven hundred and forty-eight responses were received. In spite of the wide range of respondents, there was a broad consensus of opinion across groups. The majority of participants were satisfied with the service they currently receive, but wanted some changes. They reported their current experience of implant services to be mainly driven by decisions made by the implant team. For the future, they preferred the service to be mainly driven by decisions made jointly by the team and the user and/or parent/carer. The majority of participants wanted the cochlear implant services to be integrated into local audiology and other services such as education. Restrictions on number of candidates funded and political decisions and issues were seen as major challenges. Qualitative analysis of the open-ended responses supported the questionnaire responses. This research highlighted the benefits and limitations of the current cochlear implant service delivery as well as the potential implications for the long term. While respondents were generally happy with the current cochlear implant service provision, they expressed some concerns about the long-term sustainability and management, wanting integration into the local services, and more involvement of parents and users in decisions.

Towards the next generation of climate change assessment: learning from past experiences to inform a sustainable future

NASA Astrophysics Data System (ADS)

Mach, K. J.; Field, C. B.

2017-12-01

Over decades, assessment by the Intergovernmental Panel on Climate Change and many others has bolstered understanding of the climate problem: unequivocal warming, pervasive impacts, and serious risks from continued high emissions of heat-trapping gases. Societies are increasingly responding with early actions to decarbonize energy systems and prepare for impacts. This emerging era of climate solutions creates a need for new approaches to assessment that emphasize learning from ongoing real-world experiences and that help close the gap between aspirations and the pace of progress. Against this backdrop, the presentation will take stock of recent advances and challenges in assessment, especially drawing from analysis of climate change assessment. Four assessment priorities will be considered: (1) integrating diverse evidence including quantitative and qualitative results, (2) applying rigorous expert judgment in evaluating knowledge and uncertainties, (3) exploring widely ranging futures and their connections to ongoing choices and actions, and (4) incorporating interactions among experts and decision-makers in assessment processes. Across these assessment priorities, the presentation will critique both opportunities and pitfalls, outlining possibilities for future experimentation, innovation, and learning. It will evaluate, in particular, lessons from risk-based approaches; strategies for transparently acknowledging persistent uncertainties and contested priorities; ways to minimize biases and foster creativity in expert judgments; scenario-based assessment of surprises, deep uncertainties, and decision-making implications; and opportunities for broadening the conception of expertise and engaging different decision-makers and stakeholders. Overall, these approaches can advance assessment products and processes as a basis for sustained dialogue supporting decision-making.

Overcoming barriers to cancer-helpline professionals providing decision support for callers: an implementation study.

PubMed

Stacey, Dawn; Chambers, Suzanne K; Jacobsen, Mary Jane; Dunn, Jeff

2008-11-01

To evaluate the effect of an intervention on healthcare professionals' perceptions of barriers influencing their provision of decision support for callers facing cancer-related decisions. A pre- and post-test study guided by the Ottawa Model of Research Use. Australian statewide cancer call center that provides public access to information and supportive cancer services. 34 nurses, psychologists, and other allied healthcare professionals at the cancer call center. Participants completed baseline measures and, subsequently, were exposed to an intervention that included a decision support tutorial, coaching protocol, and skill-building workshop. Strategies were implemented to address organizational barriers. Perceived barriers and facilitators influencing provision of decision support, decision support knowledge, quality of decision support provided to standardized callers, and call length. Postintervention participants felt more prepared, confident in providing decision support, and aware of decision support resources. They had a stronger belief that providing decision support was within their role. Participants significantly improved their knowledge and provided higher-quality decision support to standardized callers without changing call length. The implementation intervention overcame several identified barriers that influenced call center professionals when providing decision support. Nurses and other helpline professionals have the potential to provide decision support designed to help callers understand cancer information, clarify their values associated with their options, and reduce decisional conflict. However, they require targeted education and organizational interventions to reduce their perceived barriers to providing decision support.

Future decision-making without episodic mental time travel.

PubMed

Kwan, Donna; Craver, Carl F; Green, Leonard; Myerson, Joel; Boyer, Pascal; Rosenbaum, R Shayna

2012-06-01

Deficits in episodic memory are associated with deficits in the ability to imagine future experiences (i.e., mental time travel). We show that K.C., a person with episodic amnesia and an inability to imagine future experiences, nonetheless systematically discounts the value of future rewards, and his discounting is within the range of controls in terms of both rate and consistency. Because K.C. is neither able to imagine personal uses for the rewards nor provide a rationale for selecting larger future rewards over smaller current rewards, this study demonstrates a dissociation between imagining and making decisions involving the future. Thus, although those capable of mental time travel may use it in making decisions about future rewards, these results demonstrate that it is not required for such decisions. Copyright © 2011 Wiley Periodicals, Inc.

A climate game based on a Multi-Actor Dynamic Integrated Assessment Model (MADIAM)

NASA Astrophysics Data System (ADS)

Weber, M.; Hasselmann, K.

2003-04-01

In November 2002 a special exhibition on climate issues opened in the German Museum for Science and Techniques ('Deutsches Museum') in Munich. Within this exposition we present an interactive game in which visitors control future climate policy by adopting the role of either the government, a CEO (Chief Executive Officer) of a global company or a typical private household of an industrialized country. The players endeavor to maintain a sustainable climate in the future (global goal) while pursuing their own individual welfare goals. Task of the exhibition visitor is to combine the personal interests of the actor he is adopting with the global goal. The individual goal of government is maintain economic growth while avoiding conflicts due to inter-regional or societal inequalities. The CEO seeks to maximize total profits (business earnings). The goal of households is to maximize wages and interest earnings. The evolution of the economic system and climate is governed by the decisions of the actors. Government sets economic side conditions in terms of carbon taxes, subsidies for R&D or market infusion support for climate-friendly technologies, and transfers development aid to less advanced regions. The CEOs decide how much to invest in a number of alternative investment options and in which region. Households influences the economy by their purchasing and savings decisions. The model considers four regions, three real actors (mentioned above) and two different goods (climate-adverse and a climate-friendly). We introduce four different kinds of energy (coal, oil/gas, nuclear, renewable). A World Bank handles money flows. At different points in time the actors can cooperate with other actors in order to reach the global goal Stochastic elements regarding future technology and future climate are included. A touch-screen monitor with user friendly interface is used to present animations and videos. An animated climate scientist uses a climate simulator to compute future climate scenarios in response to the actors decisions. The goal of the project is t o to give them a feeling for the problem and demonstrate that that a sustainable future climate can be combined with individual welfare goals if the right decisions are made at the right time.

Developing an Environmental Decision Support System for Stream Management: the STREAMES Experience

NASA Astrophysics Data System (ADS)

Riera, J.; Argerich, A.; Comas, J.; Llorens, E.; Martí, E.; Godé, L.; Pargament, D.; Puig, M.; Sabater, F.

2005-05-01

Transferring research knowledge to stream managers is crucial for scientifically sound management. Environmental decision support systems are advocated as an effective means to accomplish this. STREAMES (STream REAach Management: an Expert System) is a decision tree based EDSS prototype developed within the context of an European project as a tool to assist water managers in the diagnosis of problems, detection of causes, and selection of management strategies for coping with stream degradation issues related mostly to excess nutrient availability. STREAMES was developed by a team of scientists, water managers, and experts in knowledge engineering. Although the tool focuses on management at the stream reach scale, it also incorporates a mass-balance catchment nutrient emission model and a simple GIS module. We will briefly present the prototype and share our experience in its development. Emphasis will be placed on the process of knowledge acquisition, the design process, the pitfalls and benefits of the communication between scientists and managers, and the potential for future development of STREAMES, particularly in the context of the EU Water Framework Directive.

Decision Making Under Uncertainty and Complexity: A Model-Based Scenario Approach to Supporting Integrated Water Resources Management

NASA Astrophysics Data System (ADS)

Liu, Y.; Gupta, H.; Wagener, T.; Stewart, S.; Mahmoud, M.; Hartmann, H.; Springer, E.

2007-12-01

Some of the most challenging issues facing contemporary water resources management are those typified by complex coupled human-environmental systems with poorly characterized uncertainties. In other words, major decisions regarding water resources have to be made in the face of substantial uncertainty and complexity. It has been suggested that integrated models can be used to coherently assemble information from a broad set of domains, and can therefore serve as an effective means for tackling the complexity of environmental systems. Further, well-conceived scenarios can effectively inform decision making, particularly when high complexity and poorly characterized uncertainties make the problem intractable via traditional uncertainty analysis methods. This presentation discusses the integrated modeling framework adopted by SAHRA, an NSF Science & Technology Center, to investigate stakeholder-driven water sustainability issues within the semi-arid southwestern US. The multi-disciplinary, multi-resolution modeling framework incorporates a formal scenario approach to analyze the impacts of plausible (albeit uncertain) alternative futures to support adaptive management of water resources systems. Some of the major challenges involved in, and lessons learned from, this effort will be discussed.

17 CFR 171.21 - Notice of final decision.

Code of Federal Regulations, 2013 CFR

2013-04-01

... Futures Association shall promptly serve all parties, as well as the Proceedings Clerk and the Secretary... decision issued by the National Futures Association. (b) Content of the notice. At a minimum, the notice... notice. (1) If the National Futures Association issues a notice of a final decision subject to these...

17 CFR 171.21 - Notice of final decision.

Code of Federal Regulations, 2014 CFR

2014-04-01

... Futures Association shall promptly serve all parties, as well as the Proceedings Clerk and the Secretary... decision issued by the National Futures Association. (b) Content of the notice. At a minimum, the notice... notice. (1) If the National Futures Association issues a notice of a final decision subject to these...

17 CFR 171.21 - Notice of final decision.

Code of Federal Regulations, 2011 CFR

2011-04-01

... Futures Association shall promptly serve all parties, as well as the Proceedings Clerk and the Secretary... decision issued by the National Futures Association. (b) Content of the notice. At a minimum, the notice... notice. (1) If the National Futures Association issues a notice of a final decision subject to these...

17 CFR 171.21 - Notice of final decision.

Code of Federal Regulations, 2012 CFR

2012-04-01

... Futures Association shall promptly serve all parties, as well as the Proceedings Clerk and the Secretary... decision issued by the National Futures Association. (b) Content of the notice. At a minimum, the notice... notice. (1) If the National Futures Association issues a notice of a final decision subject to these...

17 CFR 171.21 - Notice of final decision.

Code of Federal Regulations, 2010 CFR

2010-04-01

... Futures Association shall promptly serve all parties, as well as the Proceedings Clerk and the Secretary... decision issued by the National Futures Association. (b) Content of the notice. At a minimum, the notice... notice. (1) If the National Futures Association issues a notice of a final decision subject to these...

Combining ecosystem services assessment with structured decision making to support ecological restoration planning.

PubMed

Martin, David M; Mazzotta, Marisa; Bousquin, Justin

2018-04-10

Accounting for ecosystem services in environmental decision making is an emerging research topic. Modern frameworks for ecosystem services assessment emphasize evaluating the social benefits of ecosystems, in terms of who benefits and by how much, to aid in comparing multiple courses of action. Structured methods that use decision analytic-approaches are emerging for the practice of ecological restoration. In this article, we combine ecosystem services assessment with structured decision making to estimate and evaluate measures of the potential benefits of ecological restoration with a case study in the Woonasquatucket River watershed, Rhode Island, USA. We partnered with a local watershed management organization to analyze dozens of candidate wetland restoration sites for their abilities to supply five ecosystem services-flood water retention, scenic landscapes, learning opportunities, recreational opportunities, and birds. We developed 22 benefit indicators related to the ecosystem services as well as indicators for social equity and reliability that benefits will sustain in the future. We applied conceptual modeling and spatial analysis to estimate indicator values for each candidate restoration site. Lastly, we developed a decision support tool to score and aggregate the values for the organization to screen the restoration sites. Results show that restoration sites in urban areas can provide greater social benefits than sites in less urban areas. Our research approach is general and can be used to investigate other restoration planning studies that perform ecosystem services assessment and fit into a decision-making process.

Planning for successful outcomes in the new millennium.

PubMed

Matthews, P

2000-02-01

The complexity of the health care environment will increase in the next millennium. Organizations must adopt an approach of selecting outcomes management solutions that are focused on data capture, analysis, and comparative reviews and reporting. They must decisively and creatively implement, in a phased approach, integrated solutions from existing robust systems, while considering future systems targeted for implementation. Outcomes management solutions must be integrated with the organization's information systems strategic plan. The successful organization must be able to turn business-critical data into information that supports both business and clinical decision-making activities. In short, health care organizations will have to become information-driven.

Decaying Relevance of Clinical Data Towards Future Decisions in Data-Driven Inpatient Clinical Order Sets

PubMed Central

Chen, Jonathan H; Alagappan, Muthuraman; Goldstein, Mary K; Asch, Steven M; Altman, Russ B

2017-01-01

Objective Determine how varying longitudinal historical training data can impact prediction of future clinical decisions. Estimate the “decay rate” of clinical data source relevance. Materials and Methods We trained a clinical order recommender system, analogous to Netflix or Amazon’s “Customers who bought A also bought B…” product recommenders, based on a tertiary academic hospital’s structured electronic health record data. We used this system to predict future (2013) admission orders based on different subsets of historical training data (2009 through 2012), relative to existing human-authored order sets. Results Predicting future (2013) inpatient orders is more accurate with models trained on just one month of recent (2012) data than with 12 months of older (2009) data (ROC AUC 0.91 vs. 0.88, precision 27% vs. 22%, recall 52% vs. 43%, all P<10−10). Algorithmically learned models from even the older (2009) data was still more effective than existing human-authored order sets (ROC AUC 0.81, precision 16% recall 35%). Training with more longitudinal data (2009–2012) was no better than using only the most recent (2012) data, unless applying a decaying weighting scheme with a “half-life” of data relevance about 4 months. Discussion Clinical practice patterns (automatically) learned from electronic health record data can vary substantially across years. Gold standards for clinical decision support are elusive moving targets, reinforcing the need for automated methods that can adapt to evolving information. Conclusions and Relevance Prioritizing small amounts of recent data is more effective than using larger amounts of older data towards future clinical predictions. PMID:28495350

Implications of sperm banking for health-related quality of life up to 1 year after cancer diagnosis

PubMed Central

Pacey, A; Merrick, H; Arden-Close, E; Morris, K; Rowe, R; Stark, D; Eiser, C

2013-01-01

Background: Sperm banking is recommended for all men diagnosed with cancer where treatment is associated with risk of long-term gonadatoxicity, to offer the opportunity of fatherhood and improved quality of life. However, uptake of sperm banking is lower than expected and little is known about why men refuse. Our aims were to determine: (i) demographic and medical variables associated with decisions about banking and (ii) differences in quality of life between bankers and non-bankers at diagnosis (Time 1 (T1)) and 1 year later (Time 2 (T2)). Methods: Questionnaires were completed by 91 men (response rate=86.67%) at T1 and 78 (85.71% response rate) at T2. Results: In all, 44 (56.41%) banked sperm. They were younger and less likely to have children than non-bankers. In a subset of men who were not sure if they wanted children in the future (n=36), 24 banked sperm. Among this group, those who banked were younger, more satisfied with clinic appointments and less worried about the health of future children. At T2, there were no differences in quality of life between bankers and non-bankers. Conclusion: For those who are uncertain about future reproductive plans, decisions depend on their health on diagnosis and satisfaction with clinic care. We conclude that extra care should be taken in counselling younger men who may have given little consideration to future parenting. Results support previous findings that the role of the doctor is vital in facilitating decisions, especially for those who are undecided about whether they wanted children in the future or not. PMID:23470465

EPA Leadership on Science, Innovation, and Decision Support Tools for Addressing Current and Future Challenges.

PubMed

Hecht, Alan D; Ferster, Aaron; Summers, Kevin

2017-10-16

When the U.S. Environmental Protection Agency (EPA) was established nearly 50 years ago, the nation faced serious threats to its air, land, and water, which in turn impacted human health. These threats were effectively addressed by the creation of EPA (in 1970) and many subsequent landmark environmental legislations which in turn significantly reduced threats to the Nation's environment and public health. A key element of historic legislation is research aimed at dealing with current and future problems. Today we face national and global challenges that go beyond classic media-specific (air, land, water) environmental legislation and require an integrated paradigm of action and engagement based on (1) innovation based on science and technology, (2) stakeholder engagement and collaboration, and (3) public education and support. This three-pronged approach recognizes that current environmental problems, include social as well as physical and environmental factors, are best addressed through collaborative problem solving, the application of innovation in science and technology, and multiple stakeholder engagement. To achieve that goal, EPA's Office of Research and Development (ORD) is working directly with states and local communities to develop and apply a suite of accessible decision support tools (DST) that aim to improve environmental conditions, protect human health, enhance economic opportunity, and advance a resilient and sustainability society. This paper showcases joint EPA and state actions to develop tools and approaches that not only meet current environmental and public health challenges, but do so in a way that advances sustainable, healthy, and resilient communities well into the future. EPA's future plans should build on current work but aim to effectively respond to growing external pressures. Growing pressures from megatrends are a major challenge for the new Administration and for cities and states across the country. The recent hurricanes hitting Texas and the Gulf Coast, part of the increase in extreme weather events, make it clear that building resilient infrastructure is a crucial step to sustainability.

Review of Family Financial Decision Making: Suggestions for Future Research and Implications for Financial Education

ERIC Educational Resources Information Center

Kim, Jinhee; Gutter, Michael S.; Spangler, Taylor

2017-01-01

This article reviews the theories and literature in intrahousehold financial decisions, spousal partners and financial decision making, family system and financial decision process, children, and financial decisions. The article draws conclusions from the literature review and discusses directions for future research and educational programs. Most…

Thinking outside the box: prenatal care and the call for a prenatal advance directive.

PubMed

Catlin, Anita

2005-01-01

The concept of advance directives is well-known in the care of adults as a mechanism for choosing in advance the extent of medical interventions desired in clinical situations, particularly life-extending interventions such as ventilation support and drugs to maintain cardiopulmonary status. Infants born extremely prematurely often require life-supporting measures for which their parents or guardians report feeling unprepared to make decisions about. Current prenatal care does not include an educational component that teaches women about the length of gestation needed for a healthy viability, survivorship, and outcome without major impairment. Women who go into preterm labor are asked to make immediate decisions during times of crisis without any formal education base for this decision making. Feminist ethics (the philosophical stance that articulates that women's moral experience is worthy of respect and disallows women's subordination) (Becker LB, Becker CB, eds. Feminist ethics. In: Encyclopedia of Ethics. New York: Routledge Press; 2001) requires that healthcare decisions be based on education, context, and particular situations. The purpose of this article is to examine the current content of typical prenatal care and education and to suggest an additional educational component to prenatal care-education of women about infant viability and the planning of future decisions if a nonviable or critically ill newborn is delivered. A prenatal discussion and parental/family directive is suggested.

Conclusion: challenges for the future.

PubMed

North, D W

1993-12-01

The title "Challenges for the Future" implies the challenge to summarize a very complex meeting. Of necessity, I will present a personal impression. My interest is in risk assessment, which I define as a process for summarizing science in support of decision making. Risk assessment is sometimes regarded as arcane numerology, a rigid process of computing risk numbers in which much available science is unused. I am a strong advocate for the broader definition of risk assessment. It is encouraging to learn how much science is becoming available for use in risk assessment for gasoline, its components, and alternative fuels.

Beyond Control Centers

NASA Technical Reports Server (NTRS)

Trimble, Jay

2017-01-01

For NASA's Resource Prospector (RP) Lunar Rover Mission, we are moving away from a control center concept, to a fully distributed operation utilizing control nodes, with decision support from anywhere via mobile devices. This operations concept will utilize distributed information systems, notifications, mobile data access, and optimized mobile data display for off-console decision support. We see this concept of operations as a step in the evolution of mission operations from a central control center concept to a mission operations anywhere concept. The RP example is part of a trend, in which mission expertise for design, development and operations is distributed across countries and across the globe. Future spacecraft operations will be most cost efficient and flexible by following this distributed expertise, enabling operations from anywhere. For the RP mission we arrived at the decision to utilize a fully distributed operations team, where everyone operates from their home institution, based on evaluating the following factors: the requirement for physical proximity for near-real time command and control decisions; the cost of distributed control nodes vs. a centralized control center; the impact on training and mission preparation of flying the team to a central location. Physical proximity for operational decisions is seldom required, though certain categories of decisions, such as launch abort, or close coordination for mission or safety-critical near-real-time command and control decisions may benefit from co-location. The cost of facilities and operational infrastructure has not been found to be a driving factor for location in our studies. Mission training and preparation benefit from having all operators train and operate from home institutions.

Managing controversy through consultation: a qualitative study of communication and trust around MMR vaccination decisions

PubMed Central

McMurray, Robert; Cheater, Francine M; Weighall, Anna; Nelson, Carolyn; Schweiger, Martin; Mukherjee, Suzanne

2004-01-01

Background: Controversy over the measles, mumps, and rubella (MMR) vaccine has reduced uptake, raising concerns of a future disease epidemic. Aims: To explore parents' accounts of decision making relating to the MMR vaccine controversy, identifying uptake determinants and education needs. Design of study: Qualitative interviews analysed using the ‘framework’ approach. Setting: Five general practices in the Leeds area, 2002–2003. Method: Sixty-nine interviews conducted with parents of children aged between 4 and 5 years, and 12 interviews with primary care practitioners, managers and immunisation coordinators serving participating sites. Participants were interviewed one-to-one in a place of their choice. Results: The vaccination decision is primarily a function of parental assessments of the relative acceptability and likelihood of possible outcomes. For most parents the evidence of science and medicine plays little role in the decision. Although local general practitioners and health visitors are trusted information sources, the influence of primary care providers on the vaccination decision is limited by concerns over consultation legitimacy, discussion opportunity, and perceptions of financial and political partiality. Parents and practitioners identify a need for new approaches to support decisions and learning when faced with this and similar healthcare controversies. These include new collaborative approaches to information exchange designed to transform rather than supplant existing parent knowledge as part of an ongoing learning process. Conclusion: The study identified new ways in which parents and practitioners need to be supported in order to increase understanding of medical science and secure more informed decisions in the face of health controversy. PMID:15239914

A Lunar Surface System Supportability Technology Development Roadmap

NASA Technical Reports Server (NTRS)

Oeftering, Richard C.; Struk, Peter M.; Taleghani, Barmac K.

2009-01-01

This paper discusses the establishment of a Supportability Technology Development Roadmap as a guide for developing capabilities intended to allow NASA's Constellation program to enable a supportable, sustainable and affordable exploration of the Moon and Mars. Presented is a discussion of "supportability", in terms of space facility maintenance, repair and related logistics and a comparison of how lunar outpost supportability differs from the International Space Station. Supportability lessons learned from NASA and Department of Defense experience and their impact on a future lunar outpost is discussed. A supportability concept for future missions to the Moon and Mars that involves a transition from a highly logistics dependent to a logistically independent operation is discussed. Lunar outpost supportability capability needs are summarized and a supportability technology development strategy is established. The resulting Lunar Surface Systems Supportability Strategy defines general criteria that will be used to select technologies that will enable future flight crews to act effectively to respond to problems and exploit opportunities in a environment of extreme resource scarcity and isolation. This strategy also introduces the concept of exploiting flight hardware as a supportability resource. The technology roadmap involves development of three mutually supporting technology categories, Diagnostics Test & Verification, Maintenance & Repair, and Scavenging & Recycling. The technology roadmap establishes two distinct technology types, "Embedded" and "Process" technologies, with different implementation and thus different criteria and development approaches. The supportability technology roadmap addresses the technology readiness level, and estimated development schedule for technology groups that includes down-selection decision gates that correlate with the lunar program milestones. The resulting supportability technology roadmap is intended to develop a set of technologies with widest possible capability and utility with a minimum impact on crew time and training and remain within the time and cost constraints of the Constellation program

A Lunar Surface System Supportability Technology Development Roadmap

NASA Technical Reports Server (NTRS)

Oeftering, Richard C.; Struk, Peter M.; Taleghani, barmac K.

2011-01-01

This paper discusses the establishment of a Supportability Technology Development Roadmap as a guide for developing capabilities intended to allow NASA s Constellation program to enable a supportable, sustainable and affordable exploration of the Moon and Mars. Presented is a discussion of supportability, in terms of space facility maintenance, repair and related logistics and a comparison of how lunar outpost supportability differs from the International Space Station. Supportability lessons learned from NASA and Department of Defense experience and their impact on a future lunar outpost is discussed. A supportability concept for future missions to the Moon and Mars that involves a transition from a highly logistics dependent to a logistically independent operation is discussed. Lunar outpost supportability capability needs are summarized and a supportability technology development strategy is established. The resulting Lunar Surface Systems Supportability Strategy defines general criteria that will be used to select technologies that will enable future flight crews to act effectively to respond to problems and exploit opportunities in an environment of extreme resource scarcity and isolation. This strategy also introduces the concept of exploiting flight hardware as a supportability resource. The technology roadmap involves development of three mutually supporting technology categories, Diagnostics Test and Verification, Maintenance and Repair, and Scavenging and Recycling. The technology roadmap establishes two distinct technology types, "Embedded" and "Process" technologies, with different implementation and thus different criteria and development approaches. The supportability technology roadmap addresses the technology readiness level, and estimated development schedule for technology groups that includes down-selection decision gates that correlate with the lunar program milestones. The resulting supportability technology roadmap is intended to develop a set of technologies with widest possible capability and utility with a minimum impact on crew time and training and remain within the time and cost constraints of the Constellation program.

Biogas Potential in the United States (Fact Sheet)

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

Not Available

2013-10-01

Biogas has received increased attention as an alternative energy source in the United States. The factsheet provides information about the biogas (methane) potential from various sources in the country (by county and state) and estimates the power generation and transportation fuels production (renewable natural gas) potential from these biogas sources. It provides valuable information to the industry, academia and policy makers in support of their future decisions.

The U.S. Army Functional Concept for Intelligence 2020-2040

DTIC Science & Technology

2017-02-01

Soldiers to mitigate many complex problems of the future OE. Improved or new analytic processes will use very large data sets to address emerging...increasing. Army collection against publically available data sources may offer insights to social interconnectedness, political dynamics and complex... data used to support situational understanding. (5) Uncertainty and rapid change elevate the analytic risk associated with decision making and

Flood risk assessment and robust management under deep uncertainty: Application to Dhaka City

NASA Astrophysics Data System (ADS)

Mojtahed, Vahid; Gain, Animesh Kumar; Giupponi, Carlo

2014-05-01

The socio-economic changes as well as climatic changes have been the main drivers of uncertainty in environmental risk assessment and in particular flood. The level of future uncertainty that researchers face when dealing with problems in a future perspective with focus on climate change is known as Deep Uncertainty (also known as Knightian uncertainty), since nobody has already experienced and undergone those changes before and our knowledge is limited to the extent that we have no notion of probabilities, and therefore consolidated risk management approaches have limited potential.. Deep uncertainty is referred to circumstances that analysts and experts do not know or parties to decision making cannot agree on: i) the appropriate models describing the interaction among system variables, ii) probability distributions to represent uncertainty about key parameters in the model 3) how to value the desirability of alternative outcomes. The need thus emerges to assist policy-makers by providing them with not a single and optimal solution to the problem at hand, such as crisp estimates for the costs of damages of natural hazards considered, but instead ranges of possible future costs, based on the outcomes of ensembles of assessment models and sets of plausible scenarios. Accordingly, we need to substitute optimality as a decision criterion with robustness. Under conditions of deep uncertainty, the decision-makers do not have statistical and mathematical bases to identify optimal solutions, while instead they should prefer to implement "robust" decisions that perform relatively well over all conceivable outcomes out of all future unknown scenarios. Under deep uncertainty, analysts cannot employ probability theory or other statistics that usually can be derived from observed historical data and therefore, we turn to non-statistical measures such as scenario analysis. We construct several plausible scenarios with each scenario being a full description of what may happen in future and based on a meaningful synthesis of parameters' values with control of their correlations for maintaining internal consistencies. This paper aims at incorporating a set of data mining and sampling tools to assess uncertainty of model outputs under future climatic and socio-economic changes for Dhaka city and providing a decision support system for robust flood management and mitigation policies. After constructing an uncertainty matrix to identify the main sources of uncertainty for Dhaka City, we identify several hazard and vulnerability maps based on future climatic and socio-economic scenarios. The vulnerability of each flood management alternative under different set of scenarios is determined and finally the robustness of each plausible solution considered is defined based on the above assessment.

Deferred Personal Life Decisions of Women Physicians.

PubMed

Bering, Jamie; Pflibsen, Lacey; Eno, Cassie; Radhakrishnan, Priya

2018-05-01

Inadequate work-life balance can have significant implications regarding individual performance, retention, and on the future of the workforce in medicine. The purpose of this study was to determine whether women physicians defer personal life decisions in pursuit of their medical career. We conducted a survey study of women physicians ages 20-80 from various medical specialties using a combination of social media platforms and women physicians' professional listservs with 801 survey responses collected from May through November 2015. The primary endpoint was whether women physicians deferred personal life decisions in pursuit of their medical career. Secondary outcomes include types of decisions deferred and correlations with age, hours worked per week, specialty, number of children, and career satisfaction. Respondents were categorized into deferred and nondeferred groups. Personal decision deferments were reported by 64% of respondents. Of these, 86% reported waiting to have children and 22% reported waiting to get married. Finally, while 85% of women in the nondeferment group would choose medicine again as a career, only 71% of women in the deferment group would do so (p < 0.0001). Physicians who would choose medicine again cited reasons such as career satisfaction, positive patient interactions, and intellectual stimulation, whereas those who would not choose medicine again reported poor work-life balance, decreasing job satisfaction, and insurance/administrative burden. The results of this survey have significant implications on the future of the workforce in medicine. Overall, our analysis shows that 64% of women physicians defer important life decisions in pursuit of their medical career. With an increase in the number of women physicians entering the workforce, lack of support and deferred personal decisions have a potential negative impact on individual performance and retention. Employers must consider the economic impact and potential workforce shortages that may develop if these issues are not addressed.

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.

Ethics support for GPs: what should it look like?

PubMed

Clark-Grill, Monika

2016-03-01

INTRODUCTION Ethics support services for hospital clinicians have become increasingly common globally but not as yet in New Zealand. However, an initiative to change this is gathering momentum. Its slogan 'Clinical ethics is everyone's business' indicates that the aim is to encompass all of health care, not just the hospital sector. General Practitioners (GPs) deal with ethical issues on a daily basis. These issues are often quite different from ethical issues in hospitals. To make future ethics support relevant for primary care, local GPs were interviewed to find out how they might envisage ethics support services that could be useful to them. METHODS A focus group interview with six GPs and semi-structured individual interviews with three GPs were conducted. Questions included how they made decisions on ethical issues at present, what they perceived as obstacles to ethical reflection and decision-making, and what support might be helpful. FINDINGS Three areas of ethics support were considered potentially useful: Formal ethics education during GP training, access to an ethicist for assistance with analysing an ethical issue, and professional guidance with structured ethics conversations in peer groups. CONCLUSION The complex nature of general practice requires GPs to be well educated and supported for handling ethical issues. The findings from this study could serve as input to the development of ethics support services. KEYWORDS General practice; primary care; ethics; support; education.

Basolateral Amygdala to Orbitofrontal Cortex Projections Enable Cue-Triggered Reward Expectations.

PubMed

Lichtenberg, Nina T; Pennington, Zachary T; Holley, Sandra M; Greenfield, Venuz Y; Cepeda, Carlos; Levine, Michael S; Wassum, Kate M

2017-08-30

To make an appropriate decision, one must anticipate potential future rewarding events, even when they are not readily observable. These expectations are generated by using observable information (e.g., stimuli or available actions) to retrieve often quite detailed memories of available rewards. The basolateral amygdala (BLA) and orbitofrontal cortex (OFC) are two reciprocally connected key nodes in the circuitry supporting such outcome-guided behaviors. But there is much unknown about the contribution of this circuit to decision making, and almost nothing known about the whether any contribution is via direct, monosynaptic projections, or the direction of information transfer. Therefore, here we used designer receptor-mediated inactivation of OFC→BLA or BLA→OFC projections to evaluate their respective contributions to outcome-guided behaviors in rats. Inactivation of BLA terminals in the OFC, but not OFC terminals in the BLA, disrupted the selective motivating influence of cue-triggered reward representations over reward-seeking decisions as assayed by Pavlovian-to-instrumental transfer. BLA→OFC projections were also required when a cued reward representation was used to modify Pavlovian conditional goal-approach responses according to the reward's current value. These projections were not necessary when actions were guided by reward expectations generated based on learned action-reward contingencies, or when rewards themselves, rather than stored memories, directed action. These data demonstrate that BLA→OFC projections enable the cue-triggered reward expectations that can motivate the execution of specific action plans and allow adaptive conditional responding. SIGNIFICANCE STATEMENT Deficits anticipating potential future rewarding events are associated with many psychiatric diseases. Presently, we know little about the neural circuits supporting such reward expectation. Here we show that basolateral amygdala to orbitofrontal cortex projections are required for expectations of specific available rewards to influence reward seeking and decision making. The necessity of these projections was limited to situations in which expectations were elicited by reward-predictive cues. These projections therefore facilitate adaptive behavior by enabling the orbitofrontal cortex to use environmental stimuli to generate expectations of potential future rewarding events. Copyright © 2017 the authors 0270-6474/17/378374-11$15.00/0.

Basolateral Amygdala to Orbitofrontal Cortex Projections Enable Cue-Triggered Reward Expectations

PubMed Central

Lichtenberg, Nina T.; Pennington, Zachary T.; Holley, Sandra M.; Greenfield, Venuz Y.; Levine, Michael S.

2017-01-01

To make an appropriate decision, one must anticipate potential future rewarding events, even when they are not readily observable. These expectations are generated by using observable information (e.g., stimuli or available actions) to retrieve often quite detailed memories of available rewards. The basolateral amygdala (BLA) and orbitofrontal cortex (OFC) are two reciprocally connected key nodes in the circuitry supporting such outcome-guided behaviors. But there is much unknown about the contribution of this circuit to decision making, and almost nothing known about the whether any contribution is via direct, monosynaptic projections, or the direction of information transfer. Therefore, here we used designer receptor-mediated inactivation of OFC→BLA or BLA→OFC projections to evaluate their respective contributions to outcome-guided behaviors in rats. Inactivation of BLA terminals in the OFC, but not OFC terminals in the BLA, disrupted the selective motivating influence of cue-triggered reward representations over reward-seeking decisions as assayed by Pavlovian-to-instrumental transfer. BLA→OFC projections were also required when a cued reward representation was used to modify Pavlovian conditional goal-approach responses according to the reward's current value. These projections were not necessary when actions were guided by reward expectations generated based on learned action-reward contingencies, or when rewards themselves, rather than stored memories, directed action. These data demonstrate that BLA→OFC projections enable the cue-triggered reward expectations that can motivate the execution of specific action plans and allow adaptive conditional responding. SIGNIFICANCE STATEMENT Deficits anticipating potential future rewarding events are associated with many psychiatric diseases. Presently, we know little about the neural circuits supporting such reward expectation. Here we show that basolateral amygdala to orbitofrontal cortex projections are required for expectations of specific available rewards to influence reward seeking and decision making. The necessity of these projections was limited to situations in which expectations were elicited by reward-predictive cues. These projections therefore facilitate adaptive behavior by enabling the orbitofrontal cortex to use environmental stimuli to generate expectations of potential future rewarding events. PMID:28743727

A "building block" approach to application development for education and decision support in radiology: implications for integrated clinical information systems environments.

PubMed

Greenes, R A

1991-11-01

Education and decision-support resources useful to radiologists are proliferating for the personal computer/workstation user or are potentially accessible via high-speed networks. These resources are typically made available through a set of application programs that tend to be developed in isolation and operate independently. Nonetheless, there is a growing need for an integrated environment for access to these resources in the context of professional work, during clinical problem-solving and decision-making activities, and for use in conjunction with other information resources. New application development environments are required to provide these capabilities. One such architecture for applications, which we have implemented in a prototype environment called DeSyGNER, is based on separately delineating the component information resources required for an application, termed entities, and the user interface and organizational paradigms, or composition methods, by which the entities are used to provide particular kinds of capability. Examples include composition methods to support query, book browsing, hyperlinking, tutorials, simulations, or question/answer testing. Future steps must address true integration of such applications with existing clinical information systems. We believe that the most viable approach for evolving this capability is based on the use of new software engineering methodologies, open systems, client-server communication, and delineation of standard message protocols.

Knowledge as a Service at the Point of Care.

PubMed

Shellum, Jane L; Freimuth, Robert R; Peters, Steve G; Nishimura, Rick A; Chaudhry, Rajeev; Demuth, Steve J; Knopp, Amy L; Miksch, Timothy A; Milliner, Dawn S

2016-01-01

An electronic health record (EHR) can assist the delivery of high-quality patient care, in part by providing the capability for a broad range of clinical decision support, including contextual references (e.g., Infobuttons), alerts and reminders, order sets, and dashboards. All of these decision support tools are based on clinical knowledge; unfortunately, the mechanisms for managing rules, order sets, Infobuttons, and dashboards are often unrelated, making it difficult to coordinate the application of clinical knowledge to various components of the clinical workflow. Additional complexity is encountered when updating enterprise-wide knowledge bases and delivering the content through multiple modalities to different consumers. We present the experience of Mayo Clinic as a case study to examine the requirements and implementation challenges related to knowledge management across a large, multi-site medical center. The lessons learned through the development of our knowledge management and delivery platform will help inform the future development of interoperable knowledge resources.

Knowledge as a Service at the Point of Care

PubMed Central

Shellum, Jane L.; Freimuth, Robert R.; Peters, Steve G.; Nishimura, Rick A.; Chaudhry, Rajeev; Demuth, Steve J.; Knopp, Amy L.; Miksch, Timothy A.; Milliner, Dawn S.

2016-01-01

An electronic health record (EHR) can assist the delivery of high-quality patient care, in part by providing the capability for a broad range of clinical decision support, including contextual references (e.g., Infobuttons), alerts and reminders, order sets, and dashboards. All of these decision support tools are based on clinical knowledge; unfortunately, the mechanisms for managing rules, order sets, Infobuttons, and dashboards are often unrelated, making it difficult to coordinate the application of clinical knowledge to various components of the clinical workflow. Additional complexity is encountered when updating enterprise-wide knowledge bases and delivering the content through multiple modalities to different consumers. We present the experience of Mayo Clinic as a case study to examine the requirements and implementation challenges related to knowledge management across a large, multi-site medical center. The lessons learned through the development of our knowledge management and delivery platform will help inform the future development of interoperable knowledge resources. PMID:28269911

Feasibility of Extracting Key Elements from ClinicalTrials.gov to Support Clinicians' Patient Care Decisions.

PubMed

Kim, Heejun; Bian, Jiantao; Mostafa, Javed; Jonnalagadda, Siddhartha; Del Fiol, Guilherme

2016-01-01

Motivation: Clinicians need up-to-date evidence from high quality clinical trials to support clinical decisions. However, applying evidence from the primary literature requires significant effort. Objective: To examine the feasibility of automatically extracting key clinical trial information from ClinicalTrials.gov. Methods: We assessed the coverage of ClinicalTrials.gov for high quality clinical studies that are indexed in PubMed. Using 140 random ClinicalTrials.gov records, we developed and tested rules for the automatic extraction of key information. Results: The rate of high quality clinical trial registration in ClinicalTrials.gov increased from 0.2% in 2005 to 17% in 2015. Trials reporting results increased from 3% in 2005 to 19% in 2015. The accuracy of the automatic extraction algorithm for 10 trial attributes was 90% on average. Future research is needed to improve the algorithm accuracy and to design information displays to optimally present trial information to clinicians.

Clinical Decision Support: Effectiveness in Improving Quality Processes and Clinical Outcomes and Factors That May Influence Success

PubMed Central

Murphy, Elizabeth V.

2014-01-01

The use of electronic health records has skyrocketed following the 2009 HITECH Act, which provides financial incentives to health care providers for the “meaningful use” of electronic medical record systems. An important component of the “Meaningful Use” legislation is the integration of Clinical Decision Support Systems (CDSS) into the computerized record, providing up-to-date medical knowledge and evidence-based guidance to the physician at the point of care. As reimbursement is increasingly tied to process and clinical outcomes, CDSS will be integral to future medical practice. Studies of CDSS indicate improvement in preventive services, appropriate care, and clinical and cost outcomes with strong evidence for CDSS effectiveness in process measures. Increasing provider adherence to CDSS recommendations is essential in improving CDSS effectiveness, and factors that influence adherence are currently under study. PMID:24910564

Design of a Multi-mode Flight Deck Decision Support System for Airborne Conflict Management

NASA Technical Reports Server (NTRS)

Barhydt, Richard; Krishnamurthy, Karthik

2004-01-01

NASA Langley has developed a multi-mode decision support system for pilots operating in a Distributed Air-Ground Traffic Management (DAG-TM) environment. An Autonomous Operations Planner (AOP) assists pilots in performing separation assurance functions, including conflict detection, prevention, and resolution. Ongoing AOP design has been based on a comprehensive human factors analysis and evaluation results from previous human-in-the-loop experiments with airline pilot test subjects. AOP considers complex flight mode interactions and provides flight guidance to pilots consistent with the current aircraft control state. Pilots communicate goals to AOP by setting system preferences and actively probing potential trajectories for conflicts. To minimize training requirements and improve operational use, AOP design leverages existing alerting philosophies, displays, and crew interfaces common on commercial aircraft. Future work will consider trajectory prediction uncertainties, integration with the TCAS collision avoidance system, and will incorporate enhancements based on an upcoming air-ground coordination experiment.

Southern California Disasters II

NASA Technical Reports Server (NTRS)

Nicholson, Heather; Todoroff, Amber L.; LeBoeuf, Madeline A.

2015-01-01

The USDA Forest Service (USFS) has multiple programs in place which primarily utilize Landsat imagery to produce burn severity indices for aiding wildfire damage assessment and mitigation. These indices provide widely-used wildfire damage assessment tools to decision makers. When the Hyperspectral Infrared Imager (HyspIRI) is launched in 2022, the sensor's hyperspectral resolution will support new methods for assessing natural disaster impacts on ecosystems, including wildfire damage to forests. This project used simulated HyspIRI data to study three southern California fires: Aspen, French, and King. Burn severity indices were calculated from the data and the results were quantitatively compared to the comparable USFS products currently in use. The final results from this project illustrate how HyspIRI data may be used in the future to enhance assessment of fire-damaged areas and provide additional monitoring tools for decision support to the USFS and other land management agencies.

Cognitive Systems Modeling and Analysis of Command and Control Systems

NASA Technical Reports Server (NTRS)

Norlander, Arne

2012-01-01

Military operations, counter-terrorism operations and emergency response often oblige operators and commanders to operate within distributed organizations and systems for safe and effective mission accomplishment. Tactical commanders and operators frequently encounter violent threats and critical demands on cognitive capacity and reaction time. In the future they will make decisions in situations where operational and system characteristics are highly dynamic and non-linear, i.e. minor events, decisions or actions may have serious and irreversible consequences for the entire mission. Commanders and other decision makers must manage true real time properties at all levels; individual operators, stand-alone technical systems, higher-order integrated human-machine systems and joint operations forces alike. Coping with these conditions in performance assessment, system development and operational testing is a challenge for both practitioners and researchers. This paper reports on research from which the results led to a breakthrough: An integrated approach to information-centered systems analysis to support future command and control systems research development. This approach integrates several areas of research into a coherent framework, Action Control Theory (ACT). It comprises measurement techniques and methodological advances that facilitate a more accurate and deeper understanding of the operational environment, its agents, actors and effectors, generating new and updated models. This in turn generates theoretical advances. Some good examples of successful approaches are found in the research areas of cognitive systems engineering, systems theory, and psychophysiology, and in the fields of dynamic, distributed decision making and naturalistic decision making.

Ongoing child welfare services: Understanding the relationship of worker and organizational characteristics to service provision.

PubMed

Lwin, Kristen; Fluke, John; Trocmé, Nico; Fallon, Barbara; Mishna, Faye

2018-06-01

Ongoing child welfare services are put in place after completion of the initial maltreatment investigation when there is a perceived need to mitigate the risk of future harm. The knowledge of how clinical, worker, and organizational characteristics interact with this decision to provide ongoing child welfare services is not well integrated in the research literature. Using secondary data from the Canadian Incidence Study of Reported Child Abuse and Neglect-2008, this study's primary objective is to understand the relationship of clinical, worker, and organizational characteristics to the decision to transfer a case to ongoing child welfare services and their relative contribution to the transfer decision in Canada. Findings indicate that several clinical level variables are associated with families receiving ongoing services. Additionally, organizational factors, such as type of services offered by the organization and the number of employee support programs available to workers, significantly predicted the decision to transfer a case to ongoing services. While no worker factors, such as education, amount of training, experience, or caseload, were associated with ongoing service receipt, the intraclass correlation coefficient of the final three-level parsimonious model indicated substantial clustering at the worker level. Results indicate that Canadian child welfare workers make decisions differently based on factors not available in the current study and that what would be deemed as important worker characteristics do not necessarily predict this outcome. Findings and implications for future research are discussed. Copyright © 2018 Elsevier Ltd. All rights reserved.

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.

Use of handheld computers in clinical practice: a systematic review.

PubMed

Mickan, Sharon; Atherton, Helen; Roberts, Nia Wyn; Heneghan, Carl; Tilson, Julie K

2014-07-06

Many healthcare professionals use smartphones and tablets to inform patient care. Contemporary research suggests that handheld computers may support aspects of clinical diagnosis and management. This systematic review was designed to synthesise high quality evidence to answer the question; Does healthcare professionals' use of handheld computers improve their access to information and support clinical decision making at the point of care? A detailed search was conducted using Cochrane, MEDLINE, EMBASE, PsycINFO, Science and Social Science Citation Indices since 2001. Interventions promoting healthcare professionals seeking information or making clinical decisions using handheld computers were included. Classroom learning and the use of laptop computers were excluded. Two authors independently selected studies, assessed quality using the Cochrane Risk of Bias tool and extracted data. High levels of data heterogeneity negated statistical synthesis. Instead, evidence for effectiveness was summarised narratively, according to each study's aim for assessing the impact of handheld computer use. We included seven randomised trials investigating medical or nursing staffs' use of Personal Digital Assistants. Effectiveness was demonstrated across three distinct functions that emerged from the data: accessing information for clinical knowledge, adherence to guidelines and diagnostic decision making. When healthcare professionals used handheld computers to access clinical information, their knowledge improved significantly more than peers who used paper resources. When clinical guideline recommendations were presented on handheld computers, clinicians made significantly safer prescribing decisions and adhered more closely to recommendations than peers using paper resources. Finally, healthcare professionals made significantly more appropriate diagnostic decisions using clinical decision making tools on handheld computers compared to colleagues who did not have access to these tools. For these clinical decisions, the numbers need to test/screen were all less than 11. Healthcare professionals' use of handheld computers may improve their information seeking, adherence to guidelines and clinical decision making. Handheld computers can provide real time access to and analysis of clinical information. The integration of clinical decision support systems within handheld computers offers clinicians the highest level of synthesised evidence at the point of care. Future research is needed to replicate these early results and to identify beneficial clinical outcomes.

Use of handheld computers in clinical practice: a systematic review

PubMed Central

2014-01-01

Background Many healthcare professionals use smartphones and tablets to inform patient care. Contemporary research suggests that handheld computers may support aspects of clinical diagnosis and management. This systematic review was designed to synthesise high quality evidence to answer the question; Does healthcare professionals’ use of handheld computers improve their access to information and support clinical decision making at the point of care? Methods A detailed search was conducted using Cochrane, MEDLINE, EMBASE, PsycINFO, Science and Social Science Citation Indices since 2001. Interventions promoting healthcare professionals seeking information or making clinical decisions using handheld computers were included. Classroom learning and the use of laptop computers were excluded. Two authors independently selected studies, assessed quality using the Cochrane Risk of Bias tool and extracted data. High levels of data heterogeneity negated statistical synthesis. Instead, evidence for effectiveness was summarised narratively, according to each study’s aim for assessing the impact of handheld computer use. Results We included seven randomised trials investigating medical or nursing staffs’ use of Personal Digital Assistants. Effectiveness was demonstrated across three distinct functions that emerged from the data: accessing information for clinical knowledge, adherence to guidelines and diagnostic decision making. When healthcare professionals used handheld computers to access clinical information, their knowledge improved significantly more than peers who used paper resources. When clinical guideline recommendations were presented on handheld computers, clinicians made significantly safer prescribing decisions and adhered more closely to recommendations than peers using paper resources. Finally, healthcare professionals made significantly more appropriate diagnostic decisions using clinical decision making tools on handheld computers compared to colleagues who did not have access to these tools. For these clinical decisions, the numbers need to test/screen were all less than 11. Conclusion Healthcare professionals’ use of handheld computers may improve their information seeking, adherence to guidelines and clinical decision making. Handheld computers can provide real time access to and analysis of clinical information. The integration of clinical decision support systems within handheld computers offers clinicians the highest level of synthesised evidence at the point of care. Future research is needed to replicate these early results and to identify beneficial clinical outcomes. PMID:24998515

Future tendencies of climate indicators important for adaptation and mitigation strategies in forestry

NASA Astrophysics Data System (ADS)

Galos, Borbala; Hänsler, Andreas; Gulyas, Krisztina; Bidlo, Andras; Czimber, Kornel

2014-05-01

Climate change is expected to have severe impacts in the forestry sector, especially in low-elevation regions in Southeast Europe, where forests are vulnerable and sensitive to the increasing probability and severity of climatic extremes, especially to droughts. For providing information about the most important regional and local risks and mitigation options for the Carpathian basin, a GIS-supported Decision Support System is under development. This study focuses on the future tendencies of climate indicators that determine the distribution, growth, health status and production of forests as well as the potential pests and diseases. For the analyses the climate database of the Decision Support System has been applied, which contains daily time series for precipitation and temperature means and extremes as well as derived climate indices for 1961-2100. For the future time period, simulation results of 12 regional climate models are included (www.ensembles-eu.org) based on the A1B emission scenario. The main results can be summarized as follows: · The projected change of the climate indices (e.g. total number of hot days, frost days, dry days, consecutive dry periods) and forestry indices (e.g. Ellenberg climate quotient, Forestry aridity index; Tolerance index for beech) indicates the warming and drying of the growing season towards the end of the 21st century. These can have severe consequences on the ecosystem services of forests. · The climatic suitable area of the native tree species is projected to move northwards and upwards in the mountains, respectively. For beech (Fagus sylvatica L.) this shift would mean the drastic shrink of the distribution area in the analyzed region. · The characteristic climate conditions that are expected in the Carpathian basin in the second half of the century, are now located southeastern from the case study region. In this way, the potential future provenance regions can be determined. Results provide input for the climate impact analyses and build an important basis of the future adaptation strategies in forestry, agriculture and water management. Funding: The research is supported by the TÁMOP-4.2.2.A-11/1/KONV-2012-0013 and TÁMOP-4.1.1.C-12/1/KONV-2012-0012 (ZENFE) joint EU-national research projects. Keywords: climate indices, climate change impacts, forestry, regional climate modelling

RiskChanges Spatial Decision Support system for the analysis of changing multi-hazard risk

NASA Astrophysics Data System (ADS)

van Westen, Cees; Zhang, Kaixi; Bakker, Wim; Andrejchenko, Vera; Berlin, Julian; Olyazadeh, Roya; Cristal, Irina

2015-04-01

Within the framework of the EU FP7 Marie Curie Project CHANGES and the EU FP7 Copernicus project INCREO a spatial decision support system was developed 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. Central to the SDSS are the stakeholders. The envisaged users of the system are organizations involved in planning of risk reduction measures, and that have staff capable of visualizing and analyzing spatial data at a municipal scale. The SDSS should be able to function in different countries with different legal frameworks and with organizations with different mandates. These could be subdivided into Civil protection organization with the mandate to design disaster response plans, Expert organizations with the mandate to design structural risk reduction measures (e.g. dams, dikes, check-dams etc), and planning organizations with the mandate to make land development plans. The SDSS can be used in different ways: analyzing the current level of risk, analyzing the best alternatives for risk reduction, the evaluation of the consequences of possible future scenarios to the risk levels, and the evaluation how different risk reduction alternatives will lead to risk reduction under different future scenarios. The SDSS is developed based on open source software and following open standards, for code as well as for data formats and service interfaces. Code development was based upon open source software as well. The architecture of the system is modular. The various parts of the system are loosely coupled, extensible, using standards for interoperability, flexible and web-based. The Spatial Decision Support System is 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)

Features of Computer-Based Decision Aids: Systematic Review, Thematic Synthesis, and Meta-Analyses

PubMed Central

Krömker, Dörthe; Meguerditchian, Ari N; Tamblyn, Robyn

2016-01-01

Background Patient information and education, such as decision aids, are gradually moving toward online, computer-based environments. Considerable research has been conducted to guide content and presentation of decision aids. However, given the relatively new shift to computer-based support, little attention has been given to how multimedia and interactivity can improve upon paper-based decision aids. Objective The first objective of this review was to summarize published literature into a proposed classification of features that have been integrated into computer-based decision aids. Building on this classification, the second objective was to assess whether integration of specific features was associated with higher-quality decision making. Methods Relevant studies were located by searching MEDLINE, Embase, CINAHL, and CENTRAL databases. The review identified studies that evaluated computer-based decision aids for adults faced with preference-sensitive medical decisions and reported quality of decision-making outcomes. A thematic synthesis was conducted to develop the classification of features. Subsequently, meta-analyses were conducted based on standardized mean differences (SMD) from randomized controlled trials (RCTs) that reported knowledge or decisional conflict. Further subgroup analyses compared pooled SMDs for decision aids that incorporated a specific feature to other computer-based decision aids that did not incorporate the feature, to assess whether specific features improved quality of decision making. Results Of 3541 unique publications, 58 studies met the target criteria and were included in the thematic synthesis. The synthesis identified six features: content control, tailoring, patient narratives, explicit values clarification, feedback, and social support. A subset of 26 RCTs from the thematic synthesis was used to conduct the meta-analyses. As expected, computer-based decision aids performed better than usual care or alternative aids; however, some features performed better than others. Integration of content control improved quality of decision making (SMD 0.59 vs 0.23 for knowledge; SMD 0.39 vs 0.29 for decisional conflict). In contrast, tailoring reduced quality of decision making (SMD 0.40 vs 0.71 for knowledge; SMD 0.25 vs 0.52 for decisional conflict). Similarly, patient narratives also reduced quality of decision making (SMD 0.43 vs 0.65 for knowledge; SMD 0.17 vs 0.46 for decisional conflict). Results were varied for different types of explicit values clarification, feedback, and social support. Conclusions Integration of media rich or interactive features into computer-based decision aids can improve quality of preference-sensitive decision making. However, this is an emerging field with limited evidence to guide use. The systematic review and thematic synthesis identified features that have been integrated into available computer-based decision aids, in an effort to facilitate reporting of these features and to promote integration of such features into decision aids. The meta-analyses and associated subgroup analyses provide preliminary evidence to support integration of specific features into future decision aids. Further research can focus on clarifying independent contributions of specific features through experimental designs and refining the designs of features to improve effectiveness. PMID:26813512

How Decision Support Systems Can Benefit from a Theory of Change Approach.

PubMed

Allen, Will; Cruz, Jennyffer; Warburton, Bruce

2017-06-01

Decision support systems are now mostly computer and internet-based information systems designed to support land managers with complex decision-making. However, there is concern that many environmental and agricultural decision support systems remain underutilized and ineffective. Recent efforts to improve decision support systems use have focused on enhancing stakeholder participation in their development, but a mismatch between stakeholders' expectations and the reality of decision support systems outputs continues to limit uptake. Additional challenges remain in problem-framing and evaluation. We propose using an outcomes-based approach called theory of change in conjunction with decision support systems development to support both wider problem-framing and outcomes-based monitoring and evaluation. The theory of change helps framing by placing the decision support systems within a wider context. It highlights how decision support systems use can "contribute" to long-term outcomes, and helps align decision support systems outputs with these larger goals. We illustrate the benefits of linking decision support systems development and application with a theory of change approach using an example of pest rabbit management in Australia. We develop a theory of change that outlines the activities required to achieve the outcomes desired from an effective rabbit management program, and two decision support systems that contribute to specific aspects of decision making in this wider problem context. Using a theory of change in this way should increase acceptance of the role of decision support systems by end-users, clarify their limitations and, importantly, increase effectiveness of rabbit management. The use of a theory of change should benefit those seeking to improve decision support systems design, use and, evaluation.

How Decision Support Systems Can Benefit from a Theory of Change Approach

NASA Astrophysics Data System (ADS)

Allen, Will; Cruz, Jennyffer; Warburton, Bruce

2017-06-01

Decision support systems are now mostly computer and internet-based information systems designed to support land managers with complex decision-making. However, there is concern that many environmental and agricultural decision support systems remain underutilized and ineffective. Recent efforts to improve decision support systems use have focused on enhancing stakeholder participation in their development, but a mismatch between stakeholders' expectations and the reality of decision support systems outputs continues to limit uptake. Additional challenges remain in problem-framing and evaluation. We propose using an outcomes-based approach called theory of change in conjunction with decision support systems development to support both wider problem-framing and outcomes-based monitoring and evaluation. The theory of change helps framing by placing the decision support systems within a wider context. It highlights how decision support systems use can "contribute" to long-term outcomes, and helps align decision support systems outputs with these larger goals. We illustrate the benefits of linking decision support systems development and application with a theory of change approach using an example of pest rabbit management in Australia. We develop a theory of change that outlines the activities required to achieve the outcomes desired from an effective rabbit management program, and two decision support systems that contribute to specific aspects of decision making in this wider problem context. Using a theory of change in this way should increase acceptance of the role of decision support systems by end-users, clarify their limitations and, importantly, increase effectiveness of rabbit management. The use of a theory of change should benefit those seeking to improve decision support systems design, use and, evaluation.

The decision-making process of workers in using sick time.

PubMed

Sandal, Candace L; Click, Elizabeth R; Dowling, Donna A; Guzik, Arlene

2014-08-01

The cost of employee absenteeism in the United States is significant in terms of sick pay, overtime costs, replacement personnel compensation, and lost productivity. Little is known about what workers consider when deciding to use sick time. Previous studies have examined work absence from an array of perspectives, including resulting work strain, job satisfaction, and job security, but absenteeism in the workplace has not been examined in terms of decision making. To scrutinize workers' decisions about using sick time, a descriptive pilot study was undertaken with a convenience sample (n = 94) of working college students. The responses to the survey revealed that the majority of the workers (73.4%) used sick time because they were too ill to work. These results are in direct opposition to previous research and suggest that workers may need education about preventing and managing minor illnesses before an absence is needed. Supporting and engaging employees and their significant others in healthy worker programs, regular surveillance examinations, and illness prevention strategies are wise investments in companies' financial futures. Future research should include a comparative study of worker absenteeism between worksites with occupational health nurses and those without nurses. Copyright 2014, SLACK Incorporated.

Developing Mobile Clinical Decision Support for Nursing Home Staff Assessment of Urinary Tract Infection using Goal-Directed Design.

PubMed

Jones, Wallace; Drake, Cynthia; Mack, David; Reeder, Blaine; Trautner, Barbara; Wald, Heidi

2017-06-20

Unique characteristics of nursing homes (NHs) contribute to high rates of inappropriate antibiotic use for asymptomatic bacteriuria (ASB), a benign condition. A mobile clinical decision support system (CDSS) may support NH staff in differentiating urinary tract infections (UTI) from ASB and reducing antibiotic days. We used Goal-Directed Design to: 1) Characterize information needs for UTI identification and management in NHs; 2) Develop UTI Decide, a mobile CDSS prototype informed by personas and scenarios of use constructed from Aim 1 findings; 3) Evaluate the UTI Decide prototype with NH staff. Focus groups were conducted with providers and nurses in NHs in Denver, Colorado (n= 24). Qualitative descriptive analysis was applied to focus group transcripts to identify information needs and themes related to mobile clinical decision support for UTI identification and management. Personas representing typical end users were developed; typical clinical context scenarios were constructed using information needs as goals. Usability testing was performed using cognitive walk-throughs and a think-aloud protocol. Four information needs were identified including guidance regarding resident assessment; communication with providers; care planning; and urine culture interpretation. Design of a web-based application incorporating a published decision support algorithm for evidence-based UTI diagnoses proceeded with a focus on nursing information needs during resident assessment and communication with providers. Certified nursing assistant (CNA) and registered nurse (RN) personas were constructed in 4 context scenarios with associated key path scenarios. After field testing, a high fidelity prototype of UTI Decide was completed and evaluated by potential end users. Design recommendations and content recommendations were elicited. Goal-Directed Design informed the development of a mobile CDSS supporting participant-identified information needs for UTI assessment and communication in NHs. Future work will include iterative deployment and evaluation of UTI Decide in NHs to decrease inappropriate use of antibiotics for suspected UTI.

ProVac Global Initiative: a vision shaped by ten years of supporting evidence-based policy decisions.

PubMed

Jauregui, Barbara; Janusz, Cara Bess; Clark, Andrew D; Sinha, Anushua; Garcia, Ana Gabriela Felix; Resch, Stephen; Toscano, Cristiana M; Sanderson, Colin; Andrus, Jon Kim

2015-05-07

The Pan American Health Organization (PAHO) created the ProVac Initiative in 2004 with the goal of strengthening national technical capacity to make evidence-based decisions on new vaccine introduction, focusing on economic evaluations. In view of the 10th anniversary of the ProVac Initiative, this article describes its progress and reflects on lessons learned to guide the next phase. We quantified the output of the Initiative's capacity-building efforts and critically assess its progress toward achieving the milestones originally proposed in 2004. Additionally, we reviewed how country studies supported by ProVac have directly informed and strengthened the deliberations around new vaccine introduction. Since 2004, ProVac has conducted four regional workshops and supported 24 health economic analyses in 15 Latin American and Caribbean countries. Five Regional Centers of Excellence were funded, resulting in six operational research projects and nine publications. Twenty four decisions on new vaccine introductions were supported with ProVac studies. Enduring products include the TRIVAC and CERVIVAC cost-effectiveness models, the COSTVAC program costing model, methodological guides, workshop training materials and the OLIVES on-line data repository. Ten NITAGs were strengthened through ProVac activities. The evidence accumulated suggests that initiatives with emphasis on sustainable training and direct support for countries to generate evidence themselves, can help accelerate the introduction of the most valuable new vaccines. International and Regional Networks of Collaborators are necessary to provide technical support and tools to national teams conducting analyses. Timeliness, integration, quality and country ownership of the process are four necessary guiding principles for national economic evaluations to have an impact on policymaking. It would be an asset to have a model that offers different levels of complexity to choose from depending on the vaccine being evaluated, the availability of data, and the time frame of the decision. Decision support for new vaccine introduction in low- and middle-income countries is critical to maximizing the efficiency and impact of vaccination programs. Global technical cooperation will be required. In the future, PAHO and WHO have an opportunity to expand the reach of the ProVac philosophy, models, and methods to additional regions and countries requiring real-time support. The ProVac Global Initiative is proposed as an effective mechanism to do so. Copyright © 2015. Published by Elsevier Ltd.

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.

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

PubMed

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

2015-01-01

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

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

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.

ALTERNATIVE FUTURES ANALYSIS: A FRAMEWORK FOR COMMUNITY DECISION-MAKING

EPA Science Inventory

Alternative futures analysis is an assessment approach designed to inform community decisions about land and water use. We conducted an alternative futures analysis in Oregon's Willamette River Basin. Three alternative future landscapes for the year 2050 were depicted and compare...

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.

17 CFR 171.42 - Notice of a final decision of the National Futures Association in a member responsibility action.

Code of Federal Regulations, 2014 CFR

2014-04-01

... RESPONSIBILITY ACTIONS Commission Review of Decisions by the National Futures Association In Member Responsibility Actions § 171.42 Notice of a final decision of the National Futures Association in a member... well as the Proceeding Clerk and Secretary of the Commission, with a written notice of any final...

Emerging Adulthood among Palestinian Minority in Israel: The Relation between Perceived Career Barriers, Future Orientation and Career Decisions

ERIC Educational Resources Information Center

Mahajna, Sami

2017-01-01

This study examines the relation between perceived career barriers, future orientation and career decisions among young Palestinian-Israeli youth. The study employs a theoretical model that links perceived career barriers and career decisions via variables of future orientation. Three hundred eighty-eight young Palestinian-Israeli women (73.20%)…

Factors that influence career decisions in Canada's nurses.

PubMed

Price, Sheri; Hall, Linda McGillis; Lalonde, Michelle; Andrews, Gavin; Harris, Alexandra; MacDonald-Rencz, Sandra

2013-01-01

Understanding the experiences of nurses who have moved between the provinces and territories (P/T) in Canada for work provides insight into the role of professional socialization in career decision-making. This paper analyzes some of the qualitative data arising from a survey of nurses from across Canada. The findings provide insight into nurses' professional socialization and demonstrate that early perceptions and expectations of nursing practice can influence future career decisions such as mobility and intent to remain. Participants described how "caring" and direct patient contact were central to their choice of nursing and career satisfaction. As the data reveal, nursing is also regarded as a career that enables mobility to accommodate both family considerations and professional development opportunities. The findings highlight the need for professional socialization strategies and supports that motivate Canadian nurses to continue practising within the profession and the country.

Shared decision making in Australia in 2017.

PubMed

Trevena, Lyndal; Shepherd, Heather L; Bonner, Carissa; Jansen, Jesse; Cust, Anne E; Leask, Julie; Shadbolt, Narelle; Del Mar, Chris; McCaffery, Kirsten; Hoffmann, Tammy

2017-06-01

Shared decision making (SDM) is now firmly established within national clinical standards for accrediting hospitals, day procedure services, public dental services and medical education in Australia, with plans to align general practice, aged care and disability service. Implementation of these standards and training of health professionals is a key challenge for the Australian health sector at this time. Consumer involvement in health research, policy and clinical service governance has also increased, with a major focus on encouraging patients to ask questions during their clinical care. Tools to support shared decision making are increasingly used but there is a need for more systemic approaches to their development, cultural adaptation and implementation. Sustainable solutions to ensure tools are kept up-to-date with the best available evidence will be important for the future. Copyright © 2017. Published by Elsevier GmbH.

Smart Devices for Older Adults Managing Chronic Disease: A Scoping Review

PubMed Central

Kim, Ben YB

2017-01-01

Background The emergence of smartphones and tablets featuring vastly advancing functionalities (eg, sensors, computing power, interactivity) has transformed the way mHealth interventions support chronic disease management for older adults. Baby boomers have begun to widely adopt smart devices and have expressed their desire to incorporate technologies into their chronic care. Although smart devices are actively used in research, little is known about the extent, characteristics, and range of smart device-based interventions. Objective We conducted a scoping review to (1) understand the nature, extent, and range of smart device-based research activities, (2) identify the limitations of the current research and knowledge gap, and (3) recommend future research directions. Methods We used the Arksey and O’Malley framework to conduct a scoping review. We identified relevant studies from MEDLINE, Embase, CINAHL, and Web of Science databases using search terms related to mobile health, chronic disease, and older adults. Selected studies used smart devices, sampled older adults, and were published in 2010 or after. The exclusion criteria were sole reliance on text messaging (short message service, SMS) or interactive voice response, validation of an electronic version of a questionnaire, postoperative monitoring, and evaluation of usability. We reviewed references. We charted quantitative data and analyzed qualitative studies using thematic synthesis. To collate and summarize the data, we used the chronic care model. Results A total of 51 articles met the eligibility criteria. Research activity increased steeply in 2014 (17/51, 33%) and preexperimental design predominated (16/50, 32%). Diabetes (16/46, 35%) and heart failure management (9/46, 20%) were most frequently studied. We identified diversity and heterogeneity in the collection of biometrics and patient-reported outcome measures within and between chronic diseases. Across studies, we found 8 self-management supporting strategies and 4 distinct communication channels for supporting the decision-making process. In particular, self-monitoring (38/40, 95%), automated feedback (15/40, 38%), and patient education (13/40, 38%) were commonly used as self-management support strategies. Of the 23 studies that implemented decision support strategies, clinical decision making was delegated to patients in 10 studies (43%). The impact on patient outcomes was consistent with studies that used cellular phones. Patients with heart failure and asthma reported improved quality of life. Qualitative analysis yielded 2 themes of facilitating technology adoption for older adults and 3 themes of barriers. Conclusions Limitations of current research included a lack of gerontological focus, dominance of preexperimental design, narrow research scope, inadequate support for participants, and insufficient evidence for clinical outcome. Recommendations for future research include generating evidence for smart device-based programs, using patient-generated data for advanced data mining techniques, validating patient decision support systems, and expanding mHealth practice through innovative technologies. PMID:28536089

A DICOM-RT radiation oncology ePR with decision support utilizing a quantified knowledge base from historical data

NASA Astrophysics Data System (ADS)

Documet, Jorge R.; Liu, Brent; Le, Anh; Law, Maria

2008-03-01

During the last 2 years we have been working on developing a DICOM-RT (Radiation Therapy) ePR (Electronic Patient Record) with decision support that will allow physicists and radiation oncologists during their decision-making process. This ePR allows offline treatment dose calculations and plan evaluation, while at the same time it compares and quantifies treatment planning algorithms using DICOM-RT objects. The ePR framework permits the addition of visualization, processing, and analysis tools, which combined with the core functionality of reporting, importing and exporting of medical studies, creates a very powerful application that can improve the efficiency while planning cancer treatments. Usually a Radiation Oncology department will have disparate and complex data generated by the RT modalities as well as data scattered in RT Information/Management systems, Record & Verify systems, and Treatment Planning Systems (TPS) which can compromise the efficiency of the clinical workflow since the data crucial for a clinical decision may be time-consuming to retrieve, temporarily missing, or even lost. To address these shortcomings, the ACR-NEMA Standards Committee extended its DICOM (Digital Imaging & Communications in Medicine) standard from Radiology to RT by ratifying seven DICOM RT objects starting in 1997 [1,2]. However, they are not broadly used yet by the RT community in daily clinical operations. In the past, the research focus of an RT department has primarily been developing new protocols and devices to improve treatment process and outcomes of cancer patients with minimal effort dedicated to integration of imaging and information systems. Our attempt is to show a proof-of-concept that a DICOM-RT ePR system can be developed as a foundation to perform medical imaging informatics research in developing decision-support tools and knowledge base for future data mining applications.

A systematic review of clinical decision support systems for antimicrobial management: are we failing to investigate these interventions appropriately?

PubMed

Rawson, T M; Moore, L S P; Hernandez, B; Charani, E; Castro-Sanchez, E; Herrero, P; Hayhoe, B; Hope, W; Georgiou, P; Holmes, A H

2017-08-01

Clinical decision support systems (CDSS) for antimicrobial management can support clinicians to optimize antimicrobial therapy. We reviewed all original literature (qualitative and quantitative) to understand the current scope of CDSS for antimicrobial management and analyse existing methods used to evaluate and report such systems. PRISMA guidelines were followed. Medline, EMBASE, HMIC Health and Management and Global Health databases were searched from 1 January 1980 to 31 October 2015. All primary research studies describing CDSS for antimicrobial management in adults in primary or secondary care were included. For qualitative studies, thematic synthesis was performed. Quality was assessed using Integrated quality Criteria for the Review Of Multiple Study designs (ICROMS) criteria. CDSS reporting was assessed against a reporting framework for behaviour change intervention implementation. Fifty-eight original articles were included describing 38 independent CDSS. The majority of systems target antimicrobial prescribing (29/38;76%), are platforms integrated with electronic medical records (28/38;74%), and have a rules-based infrastructure providing decision support (29/38;76%). On evaluation against the intervention reporting framework, CDSS studies fail to report consideration of the non-expert, end-user workflow. They have narrow focus, such as antimicrobial selection, and use proxy outcome measures. Engagement with CDSS by clinicians was poor. Greater consideration of the factors that drive non-expert decision making must be considered when designing CDSS interventions. Future work must aim to expand CDSS beyond simply selecting appropriate antimicrobials with clear and systematic reporting frameworks for CDSS interventions developed to address current gaps identified in the reporting of evidence. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

An integrated decision support system for wastewater nutrient recovery and recycling to agriculture

NASA Astrophysics Data System (ADS)

Roy, E. D.; Bomeisl, L.; Cornbrooks, P.; Mo, W.

2017-12-01

Nutrient recovery and recycling has become a key research topic within the wastewater engineering and nutrient management communities. Several technologies now exist that can effectively capture nutrients from wastewater, and innovation in this area continues to be an important research pursuit. However, practical nutrient recycling solutions require more than capable nutrient capture technologies. We also need to understand the role that wastewater nutrient recovery and recycling can play within broader nutrient management schemes at the landscape level, including important interactions at the nexus of food, energy, and water. We are developing an integrated decision support system that combines wastewater treatment data, agricultural data, spatial nutrient balance modeling, life cycle assessment, stakeholder knowledge, and multi-criteria decision making. Our goals are to: (1) help guide design decisions related to the implementation of sustainable nutrient recovery technology, (2) support innovations in watershed nutrient management that operate at the interface of the built environment and agriculture, and (3) aid efforts to protect aquatic ecosystems while supporting human welfare in a circular nutrient economy. These goals will be realized partly through the assessment of plausible alternative scenarios for the future. In this presentation, we will describe the tool and focus on nutrient balance results for the New England region. These results illustrate that both centralized and decentralized wastewater nutrient recovery schemes have potential to transform nutrient flows in many New England watersheds, diverting wastewater N and P away from aquatic ecosystems and toward local or regional agricultural soils where they can offset a substantial percentage of imported fertilizer. We will also highlight feasibility criteria and next steps to integrate stakeholder knowledge, economics, and life cycle assessment into the tool.

Imaging informatics-based multimedia ePR system for data management and decision support in rehabilitation research

NASA Astrophysics Data System (ADS)

Wang, Ximing; Verma, Sneha; Qin, Yi; Sterling, Josh; Zhou, Alyssa; Zhang, Jeffrey; Martinez, Clarisa; Casebeer, Narissa; Koh, Hyunwook; Winstein, Carolee; Liu, Brent

2013-03-01

With the rapid development of science and technology, large-scale rehabilitation centers and clinical rehabilitation trials usually involve significant volumes of multimedia data. Due to the global aging crisis, millions of new patients with age-related chronic diseases will produce huge amounts of data and contribute to soaring costs of medical care. Hence, a solution for effective data management and decision support will significantly reduce the expenditure and finally improve the patient life quality. Inspired from the concept of the electronic patient record (ePR), we developed a prototype system for the field of rehabilitation engineering. The system is subject or patient-oriented and customized for specific projects. The system components include data entry modules, multimedia data presentation and data retrieval. To process the multimedia data, the system includes a DICOM viewer with annotation tools and video/audio player. The system also serves as a platform for integrating decision-support tools and data mining tools. Based on the prototype system design, we developed two specific applications: 1) DOSE (a phase 1 randomized clinical trial to determine the optimal dose of therapy for rehabilitation of the arm and hand after stroke.); and 2) NEXUS project from the Rehabilitation Engineering Research Center(RERC, a NIDRR funded Rehabilitation Engineering Research Center). Currently, the system is being evaluated in the context of the DOSE trial with a projected enrollment of 60 participants over 5 years, and will be evaluated by the NEXUS project with 30 subjects. By applying the ePR concept, we developed a system in order to improve the current research workflow, reduce the cost of managing data, and provide a platform for the rapid development of future decision-support tools.

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.

Working memory involved in predicting future outcomes based on past experiences.

PubMed

Dretsch, Michael N; Tipples, Jason

2008-02-01

Deficits in working memory have been shown to contribute to poor performance on the Iowa Gambling Task [IGT: Bechara, A., & Martin, E.M. (2004). Impaired decision making related to working memory deficits in individuals with substance addictions. Neuropsychology, 18, 152-162]. Similarly, a secondary memory load task has been shown to impair task performance [Hinson, J., Jameson, T. & Whitney, P. (2002). Somatic markers, working memory, and decision making. Cognitive, Affective, & Behavioural Neuroscience, 2, 341-353]. In the present study, we investigate whether the latter findings were due to increased random responding [Franco-Watkins, A. M., Pashler, H., & Rickard, T. C. (2006). Does working memory load lead to greater impulsivity? Commentary on Hinson, Jameson, and Whitney's (2003). Journal of Experimental Psychology: Learning, Memory & Cognition, 32, 443-447]. Participants were tested under Low Working Memory (LWM; n=18) or High Working Memory (HWM; n=17) conditions while performing the Reversed IGT in which punishment was immediate and reward delayed [Bechara, A., Dolan, S., & Hindes, A. (2002). Decision making and addiction (part II): Myopia for the future or hypersensitivity to reward? Neuropsychologia, 40, 1690-1705]. In support of a role for working memory in emotional decision making, compared to the LWM condition, participants in the HWM condition made significantly greater number of disadvantageous selections than that predicted by chance. Performance by the HWM group could not be fully explained by random responding.

Developing a Corrective Action Simulator to Support Decision Making Research and Training

DTIC Science & Technology

2008-05-01

positions, and any time-based simulation injects (e.g., JSTARS reporting tracks, the Engineer reporting a new aircraft bingo time, a threat being active...future instantiations would benefit from migrating to the IMPRINT Pro version. During the course of this development effort the Army Research...initiating corrective action when a subordinate is observed to make an error (of omission or commission) 58 • Benefits of a Corrective

A decision support tool for setting population objectives for priority landbirds in the Central Hardwoods and West Gulf Coastal Plain/Quachitas Bird Conservation Regions

Treesearch

D. Todd Jones-Farrand; John M. Tirpak; Frank R. Thompson; Daniel J. Twedt; Charles K. Baxter; Jane A. Fitzgerald; William B. Uihlein

2009-01-01

Setting and achieving population objectives for priority landbirds must be informed by, 1) the quantity, quality, and spatial confi guration of available habitat, 2) an explicit linkage between habitat condition and population response, and 3) expected future habitat conditions. Based on this philosophy, the Central Hardwoods and Lower Mississippi Valley Joint Ventures...

Loglines. May - June 2010

DTIC Science & Technology

2010-06-01

able to get construction materials, food and spare parts into a land-locked country . More than 80 percent of the containers shipped through this...procurement management at DLA Oklahoma City, has developed a strategic roadmap for DLR decision-makers. “Trying to get our arms around all the contracts...currently in place and develop - ing a comprehensive approach to future support has been challenging,” Yort said. Transferring procurement of DLRs to

The Development of a Remote Sensor System and Decision Support Systems Architecture to Monitor Resistance Development in Transgenic Crops

NASA Technical Reports Server (NTRS)

Cacas, Joseph; Glaser, John; Copenhaver, Kenneth; May, George; Stephens, Karen

2008-01-01

The United States Environmental Protection Agency (EPA) has declared that "significant benefits accrue to growers, the public, and the environment" from the use of transgenic pesticidal crops due to reductions in pesticide usage for crop pest management. Large increases in the global use of transgenic pesticidal crops has reduced the amounts of broad spectrum pesticides used to manage pest populations, improved yield and reduced the environmental impact of crop management. A significant threat to the continued use of this technology is the evolution of resistance in insect pest populations to the insecticidal Bt toxins expressed by the plants. Management of transgenic pesticidal crops with an emphasis on conservation of Bt toxicity in field populations of insect pests is important to the future of sustainable agriculture. A vital component of this transgenic pesticidal crop management is establishing the proof of concept basic understanding, situational awareness, and monitoring and decision support system tools for more than 133650 square kilometers (33 million acres) of bio-engineered corn and cotton for development of insect resistance . Early and recent joint NASA, US EPA and ITD remote imagery flights and ground based field experiments have provided very promising research results that will potentially address future requirements for crop management capabilities.

Evaluating the Effectiveness of Web-based Climate Resilience Decision Support Tools: Insights from Coastal New Jersey

NASA Astrophysics Data System (ADS)

Brady, M.; Lathrop, R.; Auermuller, L. M.; Leichenko, R.

2016-12-01

Despite the recent surge of Web-based decision support tools designed to promote resiliency in U.S. coastal communities, to-date there has been no systematic study of their effectiveness. This study demonstrates a method to evaluate important aspects of effectiveness of four Web map tools designed to promote consideration of climate risk information in local decision-making and planning used in coastal New Jersey. In summer 2015, the research team conducted in-depth phone interviews with users of one regulatory and three non-regulatory Web map tools using a semi-structured questionnaire. The interview and analysis design drew from a combination of effectiveness evaluation approaches developed in software and information usability, program evaluation, and management information system (MIS) research. Effectiveness assessment results were further analyzed and discussed in terms of conceptual hierarchy of system objectives defined by respective tool developer and user organizations represented in the study. Insights from the interviews suggest that users rely on Web tools as a supplement to desktop and analog map sources because they provide relevant and up-to-date information in a highly accessible and mobile format. The users also reported relying on multiple information sources and comparison between digital and analog sources for decision support. However, with respect to this decision support benefit, users were constrained by accessibility factors such as lack of awareness and training with some tools, lack of salient information such as planning time horizons associated with future flood scenarios, and environmental factors such as mandates restricting some users to regulatory tools. Perceptions of Web tool credibility seem favorable overall, but factors including system design imperfections and inconsistencies in data and information across platforms limited trust, highlighting a need for better coordination between tools. Contributions of the study include user feedback on web-tool system designs consistent with collaborative methods for enhancing usability and a systematic look at effectiveness that includes both user perspectives and consideration of developer and organizational objectives.

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.

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

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).

The emotional context facing nursing home residents' families: a call for role reinforcement strategies from nursing homes and the community.

PubMed

Bern-Klug, Mercedes

2008-01-01

Identify useful concepts related to the emotional context facing family members of nursing home residents. These concepts can be used in future studies to design and test interventions that benefit family caregivers. Secondary data analyses of qualitative ethnographic data. Two nursing homes in a large Midwestern city; 8 months of data collection in each. 44 family members of nursing home residents whose health was considered, "declining." Role theory was used to design and help interpret the findings. Data included transcripts of conversations between family members and researchers and were analyzed using a coding scheme developed for the secondary analysis. Comments about emotions related to the social role of family member were grouped into three categories: relief related to admission, stress, and decision making support/stress. Subcategories of stress include the role strain associated with "competing concerns" and the psychological pressures of 1) witnessing the decline of a loved one in a nursing home, and 2) guilt about placement. Decision-making was discussed as a challenge which family members did not want to face alone; support from the resident, health care professionals, and other family members was appreciated. Family members may benefit from role reinforcement activities provided by nursing home staff and community members. All nursing home staff members (in particular social workers) and physicians are called upon to provide educationa and support regarding nursing home admissions, during the decline of the resident, and especially regarding medical decision-making. Community groups are asked to support the family member by offering assistance with concrete tasks (driving, visiting, etc.) and social support.

Resolving future fire management conflicts using multicriteria decision making.

PubMed

Driscoll, Don A; Bode, Michael; Bradstock, Ross A; Keith, David A; Penman, Trent D; Price, Owen F

2016-02-01

Management strategies to reduce the risks to human life and property from wildfire commonly involve burning native vegetation. However, planned burning can conflict with other societal objectives such as human health and biodiversity conservation. These conflicts are likely to intensify as fire regimes change under future climates and as growing human populations encroach farther into fire-prone ecosystems. Decisions about managing fire risks are therefore complex and warrant more sophisticated approaches than are typically used. We applied a multicriteria decision making approach (MCDA) with the potential to improve fire management outcomes to the case of a highly populated, biodiverse, and flammable wildland-urban interface. We considered the effects of 22 planned burning options on 8 objectives: house protection, maximizing water quality, minimizing carbon emissions and impacts on human health, and minimizing declines of 5 distinct species types. The MCDA identified a small number of management options (burning forest adjacent to houses) that performed well for most objectives, but not for one species type (arboreal mammal) or for water quality. Although MCDA made the conflict between objectives explicit, resolution of the problem depended on the weighting assigned to each objective. Additive weighting of criteria traded off the arboreal mammal and water quality objectives for other objectives. Multiplicative weighting identified scenarios that avoided poor outcomes for any objective, which is important for avoiding potentially irreversible biodiversity losses. To distinguish reliably among management options, future work should focus on reducing uncertainty in outcomes across a range of objectives. Considering management actions that have more predictable outcomes than landscape fuel management will be important. We found that, where data were adequate, an MCDA can support decision making in the complex and often conflicted area of fire management. © 2015 Society for Conservation Biology.

Decision making for breast cancer prevention among women at elevated risk.

PubMed

Padamsee, Tasleem J; Wills, Celia E; Yee, Lisa D; Paskett, Electra D

2017-03-24

Several medical management approaches have been shown to be effective in preventing breast cancer and detecting it early among women at elevated risk: 1) prophylactic mastectomy; 2) prophylactic oophorectomy; 3) chemoprevention; and 4) enhanced screening routines. To varying extents, however, these approaches are substantially underused relative to clinical practice recommendations. This article reviews the existing research on the uptake of these prevention approaches, the characteristics of women who are likely to use various methods, and the decision-making processes that underlie the differing choices of women. It also highlights important areas for future research, detailing the types of studies that are particularly needed in four key areas: documenting women's perspectives on their own perceptions of risk and prevention decisions; explicit comparisons of available prevention pathways and their likely health effects; the psychological, interpersonal, and social processes of prevention decision making; and the dynamics of subgroup variation. Ultimately, this research could support the development of interventions that more fully empower women to make informed and values-consistent decisions, and to move towards favorable health outcomes.

Authors' response: the primacy of conscious decision making.

PubMed

Shanks, David R; Newell, Ben R

2014-02-01

The target article sought to question the common belief that our decisions are often biased by unconscious influences. While many commentators offer additional support for this perspective, others question our theoretical assumptions, empirical evaluations, and methodological criteria. We rebut in particular the starting assumption that all decision making is unconscious, and that the onus should be on researchers to prove conscious influences. Further evidence is evaluated in relation to the core topics we reviewed (multiple-cue judgment, deliberation without attention, and decisions under uncertainty), as well as priming effects. We reiterate a key conclusion from the target article, namely, that it now seems to be generally accepted that awareness should be operationally defined as reportable knowledge, and that such knowledge can only be evaluated by careful and thorough probing. We call for future research to pay heed to the different ways in which awareness can intervene in decision making (as identified in our lens model analysis) and to employ suitable methodology in the assessment of awareness, including the requirements that awareness assessment must be reliable, relevant, immediate, and sensitive.

Cognitive Task Analysis of Business Jet Pilots' Weather Flying Behaviors: Preliminary Results

NASA Technical Reports Server (NTRS)

Latorella, Kara; Pliske, Rebecca; Hutton, Robert; Chrenka, Jason

2001-01-01

This report presents preliminary findings from a cognitive task analysis (CTA) of business aviation piloting. Results describe challenging weather-related aviation decisions and the information and cues used to support these decisions. Further, these results demonstrate the role of expertise in business aviation decision-making in weather flying, and how weather information is acquired and assessed for reliability. The challenging weather scenarios and novice errors identified in the results provide the basis for experimental scenarios and dependent measures to be used in future flight simulation evaluations of candidate aviation weather information systems. Finally, we analyzed these preliminary results to recommend design and training interventions to improve business aviation decision-making with weather information. The primary objective of this report is to present these preliminary findings and to document the extended CTA methodology used to elicit and represent expert business aviator decision-making with weather information. These preliminary findings will be augmented with results from additional subjects using this methodology. A summary of the complete results, absent the detailed treatment of methodology provided in this report, will be documented in a separate publication.

A multi-university study of which factors medical students consider when deciding to attend a rural clinical school in Australia.

PubMed

Krahe, Lee M; McColl, Alexander R; Pallant, Julie F; Cunningham, Chris E; Dewitt, Dawn E

2010-01-01

As in many developed nations, there is a shortage in the rural medical workforce in Australia. Research indicates that a strong relationship exists between rural educational exposure and an increased interest in pursuing a rural career or selecting a rural internship. Accordingly, in 2000 the Australian Commonwealth Government established the Rural Clinical Schools (RCS) program. Under this program, 25% of parent medical schools' Commonwealth Supported Place (CSP) medical students must spend at least 1 year of their clinical medical education in a rural setting. Research indicates that positive experiences are of vital importance in determining future rural practice. Arguably, if students are conscripted to a RCS, they may view their overall experience negatively. Thus, the development and sustainability of an adequate future rural medical workforce depends on medical schools understanding and fostering the factors that encourage voluntary student recruitment to the RCSs. The aim of the present study was to determine which factors Australian medical students consider in their decision to attend RCSs. This study employed survey research. The questionnaire, which used a 6 point Likert scale, addressed factors influencing students' decision to attend an RCS, including whether these factors were viewed as positive or negative. Open-ended questions provided students with an opportunity to make comments about their decision-making. The setting was the RCSs of six participating Australian universities. The participants were medical students enrolled at one of six Australian universities in 2006 (n=166) who had completed their RCS term; 125 students responded (75% response rate). At least three-quarters of the respondents considered the following when deciding whether to attend an RCS: patient access, academic reputation, their friends, the availability of subsidized accommodation provided by the clinical school, extra-curricular activities, social opportunities and transport costs. The majority of students considered the following as positive considerations: 'patient access', 'academic reputation', and 'subsidized accommodation'. However, for other students these same factors were negative considerations. Students consider both clinical and non-clinical factors in their decision to attend an RCS. The primary positive factor in the present study was patient access with 97% students (n=119) considering this to be important, and 84% students (n=81) stating that this was a positive factor in their decision-making. The other major factors, friends and academic reputation, appear equally considered. However, they differed in the degree to which they were regarded as a positive or negative consideration. Identifying and promoting positive factors is essential if the future rural medical workforce is to be enhanced. This study supports the importance of RCSs not being over-crowded and, thus, maintaining patient access, and also the importance of institutions having sufficient resources to support an excellent academic reputation. Interestingly, and perhaps somewhat contrary to expectations, students of metropolitan origin appear to be increasingly attracted to RCSs. Although numerous studies show that rural origin is a strong predictor of rural medical workforce membership, urban students who attend an RCS and have a positive experience may also be open to future rural practice.

Chronic Motivational State Interacts with Task Reward Structure in Dynamic Decision-Making

PubMed Central

Cooper, Jessica A.; Worthy, Darrell A.; Maddox, W. Todd

2015-01-01

Research distinguishes between a habitual, model-free system motivated toward immediately rewarding actions, and a goal-directed, model-based system motivated toward actions that improve future state. We examined the balance of processing in these two systems during state-based decision-making. We tested a regulatory fit hypothesis (Maddox & Markman, 2010) that predicts that global trait motivation affects the balance of habitual- vs. goal-directed processing but only through its interaction with the task framing as gain-maximization or loss-minimization. We found support for the hypothesis that a match between an individual’s chronic motivational state and the task framing enhances goal-directed processing, and thus state-based decision-making. Specifically, chronic promotion-focused individuals under gain-maximization and chronic prevention-focused individuals under loss-minimization both showed enhanced state-based decision-making. Computational modeling indicates that individuals in a match between global chronic motivational state and local task reward structure engaged more goal-directed processing, whereas those in a mismatch engaged more habitual processing. PMID:26520256

Developmental telomere attrition predicts impulsive decision-making in adult starlings

PubMed Central

Bateson, Melissa; Brilot, Ben O.; Gillespie, Robert; Monaghan, Pat; Nettle, Daniel

2015-01-01

Animals in a poor biological state face reduced life expectancy, and as a consequence should make decisions that prioritize immediate survival and reproduction over long-term benefits. We tested the prediction that if, as has been suggested, developmental telomere attrition is a biomarker of state and future life expectancy, then individuals who have undergone greater developmental telomere attrition should display greater choice impulsivity as adults. We measured impulsive decision-making in a cohort of European starlings (Sturnus vulgaris) in which we had previously manipulated developmental telomere attrition by cross-fostering sibling chicks into broods of different sizes. We show that as predicted by state-dependent optimality models, individuals who had sustained greater developmental telomere attrition and who had shorter current telomeres made more impulsive foraging decisions as adults, valuing smaller, sooner food rewards more highly than birds with less attrition and longer telomeres. Our findings shed light on the biological embedding of early adversity and support a functional explanation for its consequences that could be applicable to other species, including humans. PMID:25473012

Aviation Weather Information Communications Study (AWIN). Phase 1 and 2

NASA Technical Reports Server (NTRS)

Ball, J. W.; Herron, R. G.; Nozawa, E. T.; Thomas, E. A.; Witchey, R. D.

2000-01-01

This two part study examines the communication requirements to provide weather information in the cockpit as well as public and private communication systems available to address the requirements. Ongoing research projects combined with user needs for weather related information are used to identify and describe potential weather products that address decision support in three time frames: Far-Term Strategic, Near-Term Strategic and Tactical. Data requirements of these future products are identified and quantified. Communications systems and technologies available in the public as well as private sector are analyzed to identify potential solutions. Recommendations for further research identify cost, performance, and safety benefits to justify the investment. The study concludes that not all weather information has the same level of urgency to safety-of-flight and some information is more critical to one category of flight than another. Specific weather products need to be matched with communication systems with appropriate levels of reliability to support the criticality of the information. Available bandwidth for highly critical information should be preserved and dedicated to safety. Meanwhile, systems designed for in-flight-entertainment and other passenger/crew services could be used to support less critical information that is used only for planning and economic decision support.

Northern Eurasia Future Initiative (NEFI): Presentation and Justification of the NEFI Science Plan

NASA Astrophysics Data System (ADS)

Groisman, P. Y.; Gutman, G.; Gulev, S.; Maksyutov, S. S.; Qi, J.; Shugart, H. H., Jr.

2016-12-01

Since 2004, 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. At the Synthesis NEESPI Workshop in Prague, Czechia (April 9-12, 2015) 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. The NEESPI Research Team has reorganized itself into "Northern Eurasia Future Initiative" (NEFI) and began development of the NEFI Programmatic White Paper released at http://neespi.org in June 2016. Presentation will provide justification of the new NEFI research 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), Russian Federation (in particular, the Ministry of Education and Science, e.g., mega-grant 14.B25.31.0026), European Union, Japan, and China. We anticipate a similar kind of support for NEFI.

Mesolimbic Dopamine Signals the Value of Work

PubMed Central

Hamid, Arif A.; Pettibone, Jeffrey R.; Mabrouk, Omar S.; Hetrick, Vaughn L.; Schmidt, Robert; Vander Weele, Caitlin M.; Kennedy, Robert T.; Aragona, Brandon J.; Berke, Joshua D.

2015-01-01

Dopamine cell firing can encode errors in reward prediction, providing a learning signal to guide future behavior. Yet dopamine is also a key modulator of motivation, invigorating current behavior. Existing theories propose that fast (“phasic”) dopamine fluctuations support learning, while much slower (“tonic”) dopamine changes are involved in motivation. We examined dopamine release in the nucleus accumbens across multiple time scales, using complementary microdialysis and voltammetric methods during adaptive decision-making. We first show that minute-by-minute dopamine levels covary with reward rate and motivational vigor. We then show that second-by-second dopamine release encodes an estimate of temporally-discounted future reward (a value function). We demonstrate that changing dopamine immediately alters willingness to work, and reinforces preceding action choices by encoding temporal-difference reward prediction errors. Our results indicate that dopamine conveys a single, rapidly-evolving decision variable, the available reward for investment of effort, that is employed for both learning and motivational functions. PMID:26595651

Bringing ecosystem services into integrated water resources management.

PubMed

Liu, Shuang; Crossman, Neville D; Nolan, Martin; Ghirmay, Hiyoba

2013-11-15

In this paper we propose an ecosystem service framework to support integrated water resource management and apply it to the Murray-Darling Basin in Australia. Water resources in the Murray-Darling Basin have been over-allocated for irrigation use with the consequent degradation of freshwater ecosystems. In line with integrated water resource management principles, Australian Government reforms are reducing the amount of water diverted for irrigation to improve ecosystem health. However, limited understanding of the broader benefits and trade-offs associated with reducing irrigation diversions has hampered the planning process supporting this reform. Ecosystem services offer an integrative framework to identify the broader benefits associated with integrated water resource management in the Murray-Darling Basin, thereby providing support for the Government to reform decision-making. We conducted a multi-criteria decision analysis for ranking regional potentials to provide ecosystem services at river basin scale. We surveyed the wider public about their understanding of, and priorities for, managing ecosystem services and then integrated the results with spatially explicit indicators of ecosystem service provision. The preliminary results of this work identified the sub-catchments with the greatest potential synergies and trade-offs of ecosystem service provision under the integrated water resources management reform process. With future development, our framework could be used as a decision support tool by those grappling with the challenge of the sustainable allocation of water between irrigation and the environment. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

The motivation of massage therapy students to enter professional education.

PubMed

Finch, Paul

2004-12-01

In Ontario massage therapy is a regulated health profession, and it has been speculated that massage therapy students are motivated primarily by altruistic values, as has been documented in medicine. Students at Sutherland-Chan School and Teaching Clinic in Ontario were surveyed regarding their motivation to enter massage therapy education, with the intention of assessing the influence of certain value complexes on their decision. The results indicate that their decision was influenced more strongly by intrinsic values related to helping and working with people than by the prospect of extrinsic rewards (p < 0.0005). This supports a belief commonly held within the professional community, and bodies well for the future of massage therapy as a caring profession.

Redefining risk research priorities for nanomaterials

NASA Astrophysics Data System (ADS)

Grieger, Khara D.; Baun, Anders; Owen, Richard

2010-02-01

Chemical-based risk assessment underpins the current approach to responsible development of nanomaterials (NM). It is now recognised, however, that this process may take decades, leaving decision makers with little support in the near term. Despite this, current and near future research efforts are largely directed at establishing (eco)toxicological and exposure data for NM, and comparatively little research has been undertaken on tools or approaches that may facilitate near-term decisions, some of which we briefly outline in this analysis. We propose a reprioritisation of NM risk research efforts to redress this imbalance, including the development of more adaptive risk governance frameworks, alternative/complementary tools to risk assessment, and health and environment surveillance.

The information value of early career productivity in mathematics: a ROC analysis of prediction errors in bibliometricly informed decision making.

PubMed

Lindahl, Jonas; Danell, Rickard

The aim of this study was to provide a framework to evaluate bibliometric indicators as decision support tools from a decision making perspective and to examine the information value of early career publication rate as a predictor of future productivity. We used ROC analysis to evaluate a bibliometric indicator as a tool for binary decision making. The dataset consisted of 451 early career researchers in the mathematical sub-field of number theory. We investigated the effect of three different definitions of top performance groups-top 10, top 25, and top 50 %; the consequences of using different thresholds in the prediction models; and the added prediction value of information on early career research collaboration and publications in prestige journals. We conclude that early career performance productivity has an information value in all tested decision scenarios, but future performance is more predictable if the definition of a high performance group is more exclusive. Estimated optimal decision thresholds using the Youden index indicated that the top 10 % decision scenario should use 7 articles, the top 25 % scenario should use 7 articles, and the top 50 % should use 5 articles to minimize prediction errors. A comparative analysis between the decision thresholds provided by the Youden index which take consequences into consideration and a method commonly used in evaluative bibliometrics which do not take consequences into consideration when determining decision thresholds, indicated that differences are trivial for the top 25 and the 50 % groups. However, a statistically significant difference between the methods was found for the top 10 % group. Information on early career collaboration and publication strategies did not add any prediction value to the bibliometric indicator publication rate in any of the models. The key contributions of this research is the focus on consequences in terms of prediction errors and the notion of transforming uncertainty into risk when we are choosing decision thresholds in bibliometricly informed decision making. The significance of our results are discussed from the point of view of a science policy and management.

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.

Development of an instrument to understand the child protective services decision-making process, with a focus on placement decisions.

PubMed

Dettlaff, Alan J; Christopher Graham, J; Holzman, Jesse; Baumann, Donald J; Fluke, John D

2015-11-01

When children come to the attention of the child welfare system, they become involved in a decision-making process in which decisions are made that have a significant effect on their future and well-being. The decision to remove children from their families is particularly complex; yet surprisingly little is understood about this decision-making process. This paper presents the results of a study to develop an instrument to explore, at the caseworker level, the context of the removal decision, with the objective of understanding the influence of the individual and organizational factors on this decision, drawing from the Decision Making Ecology as the underlying rationale for obtaining the measures. The instrument was based on the development of decision-making scales used in prior decision-making studies and administered to child protection caseworkers in several states. Analyses included reliability analyses, principal components analyses, and inter-correlations among the resulting scales. For one scale regarding removal decisions, a principal components analysis resulted in the extraction of two components, jointly identified as caseworkers' decision-making orientation, described as (1) an internal reference to decision-making and (2) an external reference to decision-making. Reliability analyses demonstrated acceptable to high internal consistency for 9 of the 11 scales. Full details of the reliability analyses, principal components analyses, and inter-correlations among the seven scales are discussed, along with implications for practice and the utility of this instrument to support the understanding of decision-making in child welfare. Copyright © 2015 Elsevier Ltd. All rights reserved.

Machine Learning Techniques for Prediction of Early Childhood Obesity.

PubMed

Dugan, T M; Mukhopadhyay, S; Carroll, A; Downs, S

2015-01-01

This paper aims to predict childhood obesity after age two, using only data collected prior to the second birthday by a clinical decision support system called CHICA. Analyses of six different machine learning methods: RandomTree, RandomForest, J48, ID3, Naïve Bayes, and Bayes trained on CHICA data show that an accurate, sensitive model can be created. Of the methods analyzed, the ID3 model trained on the CHICA dataset proved the best overall performance with accuracy of 85% and sensitivity of 89%. Additionally, the ID3 model had a positive predictive value of 84% and a negative predictive value of 88%. The structure of the tree also gives insight into the strongest predictors of future obesity in children. Many of the strongest predictors seen in the ID3 modeling of the CHICA dataset have been independently validated in the literature as correlated with obesity, thereby supporting the validity of the model. This study demonstrated that data from a production clinical decision support system can be used to build an accurate machine learning model to predict obesity in children after age two.

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.

A Data-Driven Framework for Incorporating New Tools for ...

EPA Pesticide Factsheets

This talk was given during the “Exposure-Based Toxicity Testing” session at the annual meeting of the International Society for Exposure Science. It provided an update on the state of the science and tools that may be employed in risk-based prioritization efforts. It outlined knowledge gained from the data provided using these high-throughput tools to assess chemical bioactivity and to predict chemical exposures and also identified future needs. It provided an opportunity to showcase ongoing research efforts within the National Exposure Research Laboratory and the National Center for Computational Toxicology within the Office of Research and Development to an international audience. 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.

Electronic decision support for diagnostic imaging in a primary care setting

PubMed Central

Reed, Martin H

2011-01-01

Methods Clinical guideline adherence for diagnostic imaging (DI) and acceptance of electronic decision support in a rural community family practice clinic was assessed over 36 weeks. Physicians wrote 904 DI orders, 58% of which were addressed by the Canadian Association of Radiologists guidelines. Results Of those orders with guidelines, 76% were ordered correctly; 24% were inappropriate or unnecessary resulting in a prompt from clinical decision support. Physicians followed suggestions from decision support to improve their DI order on 25% of the initially inappropriate orders. The use of decision support was not mandatory, and there were significant variations in use rate. Initially, 40% reported decision support disruptive in their work flow, which dropped to 16% as physicians gained experience with the software. Conclusions Physicians supported the concept of clinical decision support but were reluctant to change clinical habits to incorporate decision support into routine work flow. PMID:21486884

Of possible cheminformatics futures.

PubMed

Oprea, Tudor I; Taboureau, Olivier; Bologa, Cristian G

2012-01-01

For over a decade, cheminformatics has contributed to a wide array of scientific tasks from analytical chemistry and biochemistry to pharmacology and drug discovery; and although its contributions to decision making are recognized, the challenge is how it would contribute to faster development of novel, better products. Here we address the future of cheminformatics with primary focus on innovation. Cheminformatics developers often need to choose between "mainstream" (i.e., accepted, expected) and novel, leading-edge tools, with an increasing trend for open science. Possible futures for cheminformatics include the worst case scenario (lack of funding, no creative usage), as well as the best case scenario (complete integration, from systems biology to virtual physiology). As "-omics" technologies advance, and computer hardware improves, compounds will no longer be profiled at the molecular level, but also in terms of genetic and clinical effects. Among potentially novel tools, we anticipate machine learning models based on free text processing, an increased performance in environmental cheminformatics, significant decision-making support, as well as the emergence of robot scientists conducting automated drug discovery research. Furthermore, cheminformatics is anticipated to expand the frontiers of knowledge and evolve in an open-ended, extensible manner, allowing us to explore multiple research scenarios in order to avoid epistemological "local information minimum trap".

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.

Owning the program technical baseline for future space systems acquisition: program technical baseline tracking tool

NASA Astrophysics Data System (ADS)

Nguyen, Tien M.; Guillen, Andy T.; Hant, James J.; Kizer, Justin R.; Min, Inki A.; Siedlak, Dennis J. L.; Yoh, James

2017-05-01

The U.S. Air Force (USAF) has recognized the needs for owning the program and technical knowledge within the Air Force concerning the systems being acquired to ensure success. This paper extends the previous work done by the authors [1-2] on the "Resilient Program Technical Baseline Framework for Future Space Systems" and "Portfolio Decision Support Tool (PDST)" to the development and implementation of the Program and Technical Baseline (PTB) Tracking Tool (PTBTL) for the DOD acquisition life cycle. The paper describes the "simplified" PTB tracking model with a focus on the preaward phases and discusses how to implement this model in PDST.

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.

Integrative evaluation for sustainable decisions of urban wastewater system management under uncertainty

NASA Astrophysics Data System (ADS)

Hadjimichael, A.; Corominas, L.; Comas, J.

2017-12-01

With sustainable development as their overarching goal, urban wastewater system (UWS) managers need to take into account multiple social, economic, technical and environmental facets related to their decisions. In this complex decision-making environment, uncertainty can be formidable. It is present both in the ways the system is interpreted stochastically, but also in its natural ever-shifting behavior. This inherent uncertainty suggests that wiser decisions would be made under an adaptive and iterative decision-making regime. No decision-support framework has been presented in the literature to effectively addresses all these needs. The objective of this work is to describe such a conceptual framework to evaluate and compare alternative solutions for various UWS challenges within an adaptive management structure. Socio-economic aspects such as externalities are taken into account, along with other traditional criteria as necessary. Robustness, reliability and resilience analyses test the performance of the system against present and future variability. A valuation uncertainty analysis incorporates uncertain valuation assumptions in the decision-making process. The framework is demonstrated with an application to a case study presenting a typical problem often faced by managers: poor river water quality, increasing population, and more stringent water quality legislation. The application of the framework made use of: i) a cost-benefit analysis including monetized environmental benefits and damages; ii) a robustness analysis of system performance against future conditions; iii) reliability and resilience analyses of the system given contextual variability; and iv) a valuation uncertainty analysis of model parameters. The results suggest that the installation of bigger volumes would give rise to increased benefits despite larger capital costs, as well as increased robustness and resilience. Population numbers appear to affect the estimated benefits most, followed by electricity prices and climate change projections. The presented framework is expected to be a valuable tool for the next generation of UWS decision-making and the application demonstrates a novel and valuable integration of metrics and methods for UWS analysis.

Impact of a decision-support tool on decision making at the district level in Kenya

PubMed Central

2013-01-01

Background In many countries, the responsibility for planning and delivery of health services is devolved to the subnational level. Health programs, however, often fall short of efficient use of data to inform decisions. As a result, programs are not as effective as they can be at meeting the health needs of the populations they serve. In Kenya, a decision-support tool, the District Health Profile (DHP) tool was developed to integrate data from health programs, primarily HIV, at the district level and to enable district health management teams to review and monitor program progress for specific health issues to make informed service delivery decisions. Methods Thirteen in-depth interviews were conducted with ten tool users and three non-users in six districts to qualitatively assess the process of implementing the tool and its effect on data-informed decision making at the district level. The factors that affected use or non-use of the tool were also investigated. Respondents were selected via convenience sample from among those that had been trained to use the DHP tool except for one user who was self-taught to use the tool. Selection criteria also included respondents from urban districts with significant resources as well as respondents from more remote, under-resourced districts. Results Findings from the in-depth interviews suggest that among those who used it, the DHP tool had a positive effect on data analysis, review, interpretation, and sharing at the district level. The automated function of the tool allowed for faster data sharing and immediate observation of trends that facilitated data-informed decision making. All respondents stated that the DHP tool assisted them to better target existing services in need of improvement and to plan future services, thus positively influencing program improvement. Conclusions This paper stresses the central role that a targeted decision-support tool can play in making data aggregation, analysis, and presentation easier and faster. The visual synthesis of data facilitates the use of information in health decision making at the district level of a health system and promotes program improvement. The experience in Kenya can be applied to other countries that face challenges making district-level, data-informed decisions with data from fragmented information systems. PMID:24011028

Examining the Relationships Between Education, Social Networks and Democratic Support With ABM

NASA Technical Reports Server (NTRS)

Drucker, Nick; Campbell, Kenyth

2011-01-01

This paper introduces an agent-based model that explores the relationships between education, social networks, and support for democratic ideals. This study examines two factors thai affect democratic support, education, and social networks. Current theory concerning these two variables suggests that positive relationships exist between education and democratic support and between social networks and the spread of ideas. The model contains multiple variables of democratic support, two of which are evaluated through experimentation. The model allows individual entities within the system to make "decisions" about their democratic support independent of one another. The agent based approach also allows entities to utilize their social networks to spread ideas. Current theory supports experimentation results. In addion , these results show the model is capable of reproducing real world outcomes. This paper addresses the model creation process and the experimentation procedure, as well as future research avenues and potential shortcomings of the model

Computerised Decision Support Systems for the management of freshwater radioecological emergencies: assessment of the state-of-the-art with respect to the experiences and needs of end-users.

PubMed

Hofman, D; Monte, L; Boyer, P; Brittain, J; Donchyts, G; Gallego, E; Gheorghiu, D; Håkanson, L; Heling, R; Kerekes, A; Kocsy, G; Lepicard, S; Slavik, O; Slavnicu, D; Smith, J; Zheleznyak, M

2011-02-01

Assessment of the environmental and radiological consequences of a nuclear accident requires the management of a great deal of data and information as well as the use of predictive models. Computerised Decision Support Systems (CDSS) are essential tools for this kind of complex assessment and for assisting experts with a rational decision process. The present work focuses on the assessment of the main features of selected state-of-the-art CDSS for off-site management of freshwater ecosystems contaminated by radionuclides. This study involved both developers and end-users of the assessed CDSS and was based on practical customisation exercises, installation and application of the decision systems. Potential end-users can benefit from the availability of several ready-to-use CDSS that allow one to run different kinds of models aimed at predicting the behaviour of radionuclides in aquatic ecosystems, evaluating doses to humans, assessing the effectiveness of different kinds of environmental management interventions and ranking these interventions, accounting for their social, economic and environmental impacts. As a result of the present assessment, the importance of CDSS "integration" became apparent: in many circumstances, different CDSS can be used as complementary tools for the decision-making process. The results of this assessment can also be useful for the future development and improvement of the CDSS. Copyright © 2010 Elsevier Ltd. All rights reserved.