75 FR 5338 - Announcement of Funding Awards for the Section 4 Capacity Building for Community Development and...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-02-02

... decisions made by the Department in a competition for funding under the 2009 Notice of Funding Availability... low-income families and persons. Capacity Building funds support activities such as training, education, support, loans, grants, and development assistance. The Fiscal Year 2009 competition was...

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.

The Politics of Information: Building a Relational Database To Support Decision-Making at a Public University.

ERIC Educational Resources Information Center

Friedman, Debra; Hoffman, Phillip

2001-01-01

Describes creation of a relational database at the University of Washington supporting ongoing academic planning at several levels and affecting the culture of decision making. Addresses getting started; sharing the database; questions, worries, and issues; improving access to high-demand courses; the advising function; management of instructional…

Building an Evidence-Driven Child Welfare Workforce: A University–Agency Partnership

PubMed Central

Lery, Bridgette; Wiegmann, Wendy; Berrick, Jill Duerr

2016-01-01

The federal government increasingly expects child welfare systems to be more responsive to the needs of their local populations, connect strategies to results, and use continuous quality improvement (CQI) to accomplish these goals. A method for improving decision making, CQI relies on an inflow of high-quality data, up-to-date research evidence, and a robust organizational structure and climate that supports the deliberate use of evidence for decision making. This article describes an effort to build and support these essential system components through one public-private child welfare agency–university partnership. PMID:27429534

Development of a digital clinical pathway for emergency medicine: Lessons from usability testing and implementation failure.

PubMed

Gutenstein, Marc; Pickering, John W; Than, Martin

2018-06-01

Clinical pathways are used to support the management of patients in emergency departments. An existing document-based clinical pathway was used as the foundation on which to design and build a digital clinical pathway for acute chest pain, with the aim of improving clinical calculations, clinician decision-making, documentation, and data collection. Established principles of decision support system design were used to build an application within the existing electronic health record, before testing with a multidisciplinary team of doctors using a think-aloud protocol. Technical authoring was successful, however, usability testing revealed that the user experience and the flexibility of workflow within the application were critical barriers to implementation. Emergency medicine and acute care decision support systems face particular challenges to existing models of linear workflow that should be deliberately addressed in digital pathway design. We make key recommendations regarding digital pathway design in emergency medicine.

Multi-Sector Sustainability Browser (MSSB) User Manual: A Decision Support Tool (DST) for Supporting Sustainability Efforts in Four Areas - Land Use, Transportation, Buildings and Infrastructure, and Materials Management

EPA Science Inventory

EPA’s Sustainable and Healthy Communities (SHC) Research Program is developing methodologies, resources, and tools to assist community members and local decision makers in implementing policy choices that facilitate sustainable approaches in managing their resources affecti...

Scalable Clinical Decision Support for Individualized Cancer Risk Management | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

We will build a scalable clinical decision support (CDS) platform that helps clinicians and patients select cancer screening strategies that are best suited to each individual. This kind of CDS is important because increased evidence supports personalizing cancer screening decisions according to each individual's unique cancer risks. While a highly desired goal, individualizing screening at a population scale requires the implementation of patient-specific risk assessments for several types of cancer. This is quite challenging in today's overwhelmed primary care environment.

Using Best Practices to Extract, Organize, and Reuse Embedded Decision Support Content Knowledge Rules from Mature Clinical Systems

PubMed Central

DesAutels, Spencer J.; Fox, Zachary E.; Giuse, Dario A.; Williams, Annette M.; Kou, Qing-hua; Weitkamp, Asli; Neal R, Patel; Bettinsoli Giuse, Nunzia

2016-01-01

Clinical decision support (CDS) knowledge, embedded over time in mature medical systems, presents an interesting and complex opportunity for information organization, maintenance, and reuse. To have a holistic view of all decision support requires an in-depth understanding of each clinical system as well as expert knowledge of the latest evidence. This approach to clinical decision support presents an opportunity to unify and externalize the knowledge within rules-based decision support. Driven by an institutional need to prioritize decision support content for migration to new clinical systems, the Center for Knowledge Management and Health Information Technology teams applied their unique expertise to extract content from individual systems, organize it through a single extensible schema, and present it for discovery and reuse through a newly created Clinical Support Knowledge Acquisition and Archival Tool (CS-KAAT). CS-KAAT can build and maintain the underlying knowledge infrastructure needed by clinical systems. PMID:28269846

An Intelligent Polar Cyberinfrastrucuture to Support Spatiotemporal Decision Making

NASA Astrophysics Data System (ADS)

Song, M.; Li, W.; Zhou, X.

2014-12-01

In the era of big data, polar sciences have already faced an urgent demand of utilizing intelligent approaches to support precise and effective spatiotemporal decision-making. Service-oriented cyberinfrastructure has advantages of seamlessly integrating distributed computing resources, and aggregating a variety of geospatial data derived from Earth observation network. This paper focuses on building a smart service-oriented cyberinfrastructure to support intelligent question answering related to polar datasets. The innovation of this polar cyberinfrastructure includes: (1) a problem-solving environment that parses geospatial question in natural language, builds geoprocessing rules, composites atomic processing services and executes the entire workflow; (2) a self-adaptive spatiotemporal filter that is capable of refining query constraints through semantic analysis; (3) a dynamic visualization strategy to support results animation and statistics in multiple spatial reference systems; and (4) a user-friendly online portal to support collaborative decision-making. By means of this polar cyberinfrastructure, we intend to facilitate integration of distributed and heterogeneous Arctic datasets and comprehensive analysis of multiple environmental elements (e.g. snow, ice, permafrost) to provide a better understanding of the environmental variation in circumpolar regions.

A Decision Support Tool for Sustainable Land Use, Transportation, Buildings/Infrastructure, and Materials Management

EPA Science Inventory

One issue for community groups, local and regional planners, and politicians, is that they require relevant information to develop programs and initiatives for incorporating sustainability principles into their physical infrastructure, operations, and decision-making processes. T...

A framework for ecological decision support systems: Building the right systems and building the systems right

USGS Publications Warehouse

D'Erchia, Frank; Korschgen, Carl E.; Nyquist, M.; Root, Ralph; Sojda, Richard S.; Stine, Peter

2001-01-01

Workshops in the late 1990's launched the commitment of the U.S. Geological Survey's Biological Resources Division (BRD) to develop and implement decision support systems (DSS) applications. One of the primary goals of this framework document is to provide sufficient background and information for Department of the Interior (DOI) bureau stakeholders and other clients to determine the potential for DSS development. Such an understanding can assist them in carrying out effective land planning and management practices. This document provides a definition of DSS and its characteristics and capabilities. It proceeds to describe issues related to meeting resource managers needs, such as the needs for specific applications, customer requirements, information and technology transfer, user support, and institutionalization. Using the decision process as a means to guide DSS development and determine users needs is also discussed. We conclude with information on method to evaluate DSS development efforts and recommended procedures for verification and validation. 

Study protocol: a mixed methods study to assess mental health recovery, shared decision-making and quality of life (Plan4Recovery).

PubMed

Coffey, Michael; Hannigan, Ben; Meudell, Alan; Hunt, Julian; Fitzsimmons, Deb

2016-08-17

Recovery in mental health care is complex, highly individual and can be facilitated by a range of professional and non-professional support. In this study we will examine how recovery from mental health problems is promoted in non-medical settings. We hypothesise a relationship between involvement in decisions about care, social support and recovery and quality of life outcomes. We will use standardised validated instruments of involvement in decision-making, social contacts, recovery and quality of life with a random sample of people accessing non-statutory mental health social care services in Wales. We will add to this important information with detailed one to one case study interviews with people, their family members and their support workers. We will use a series of these interviews to examine how people build recovery over time to help us understand more about their involvement in decisions and the social links they build. We want to see how being involved in decisions about care and the social links people have are related to recovery and quality of life for people with experience of using mental health support services. We want to understand the different perspectives of the people involved in making recovery possible. We will use this information to guide further studies of particular types of social interventions and their use in helping recovery from mental health problems.

Refurbishment and school buildings management in a smart building environment

NASA Astrophysics Data System (ADS)

Di Giuda, Giuseppe Martino; Villa, Valentina; Tagliabue, Lavinia Chiara; Giana, Paolo Ettore; Rinaldi, Stefano; Ciribini, Angelo Luigi Camillo

2018-05-01

Building Information Modelling is a methodology, which is able to take into account many data, both geometrical and non-geometrical, in order to evaluate at the actual condition of the asset. The project has the scope of evaluating the conditions of different school buildings, in order to develop a way to choose the best-tailored management solution to the owner. A further step is the management and planning of design solutions during the life cycle customized on monitored buildings' conditions. The research work focuses on providing a support decisions concerning the gap between the present building state laws and the current state of the existing buildings. The process will be developed in an expanded BIM environment, using sensors, which will give back the state of the consistency of the actual conditions to enable the buildings to adapt themselves in the best way into their specific constraints and boundaries. The results of the study are (i) a complete workflow to make decision and the possibility to shape the decision process on an objective through a scientific approach, (ii) evaluate the current state of the asset and (iii) manage maintenance in the lifespan. Further development will take in consideration all the aspects related to management of big data environment generated by a smart buildings system.

COMMUNITY CAPACITY BUILDING FOR REVITALIZATION AND SUSTAINABLE REDEVELOPMENT

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

Downing, Melinda; Rosenthall, John; Hudson, Michelle

2003-02-27

Capacity building programs help poor and disadvantaged communities to improve their ability to participate in the environmental decision-making processes. They encourage citizen involvement, and provide the tools that enable them to do so. Capacity building enables communities that would otherwise be excluded to participate in the process, leading to better, and more just decisions. The Department of Energy (DOE) continues to be committed to promoting environmental justice and involving its stakeholders more directly in the planning and decision-making process for environmental cleanup. DOE's Environmental Management Program (EM) is in full support of this commitment. Through its environmental justice project, EMmore » provides communities with the capacity to effectively contribute to a complex technical decision-making process by furnishing access to computers, the Internet, training and technical assistance. DOE's Dr. Samuel P. Massie Chairs of Excellence Program (Massie Chairs) function as technical advisors to many of these community projects. The Massie Chairs consist of nationally and internationally recognized engineers and scientists from nine Historically Black Colleges and Universities (HBCUs) and one Hispanic Serving Institution (HIS). This paper will discuss capacity building initiatives in various jurisdictions.« less

Intelligent ship traffic monitoring for oil spill prevention: risk based decision support building on AIS.

PubMed

Eide, Magnus S; Endresen, Oyvind; Brett, Per Olaf; Ervik, Jon Leon; Røang, Kjell

2007-02-01

The paper describes a model, which estimates the risk levels of individual crude oil tankers. The intended use of the model, which is ready for trial implementation at The Norwegian Coastal Administrations new Vardø VTS (Vessel Traffic Service) centre, is to facilitate the comparison of ships and to support a risk based decision on which ships to focus attention on. For a VTS operator, tasked with monitoring hundreds of ships, this is a valuable decision support tool. The model answers the question, "Which ships are likely to produce an oil spill accident, and how much is it likely to spill?".

Prioritization of engineering support requests and advanced technology projects using decision support and industrial engineering models

NASA Technical Reports Server (NTRS)

Tavana, Madjid

1995-01-01

The evaluation and prioritization of Engineering Support Requests (ESR's) is a particularly difficult task at the Kennedy Space Center (KSC) -- Shuttle Project Engineering Office. This difficulty is due to the complexities inherent in the evaluation process and the lack of structured information. The evaluation process must consider a multitude of relevant pieces of information concerning Safety, Supportability, O&M Cost Savings, Process Enhancement, Reliability, and Implementation. Various analytical and normative models developed over the past have helped decision makers at KSC utilize large volumes of information in the evaluation of ESR's. The purpose of this project is to build on the existing methodologies and develop a multiple criteria decision support system that captures the decision maker's beliefs through a series of sequential, rational, and analytical processes. The model utilizes the Analytic Hierarchy Process (AHP), subjective probabilities, the entropy concept, and Maximize Agreement Heuristic (MAH) to enhance the decision maker's intuition in evaluating a set of ESR's.

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)

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.

Decisive management in selecting locations for development of construction projects

NASA Astrophysics Data System (ADS)

Szafranko, E.; Pawłowicz, J. A.

2017-08-01

The location of an investment project is one of the most important decisions in the construction and land development business. The shape of a new building and aspects of its future use depend on making a good choice of a land plot where it will be constructed. There are many characteristics involved descriptions of land available for development. On the one hand, different buildings (with different envisaged use) fit differently to a given location. Residential homes, for example, require a location which will ensure a peaceful lifestyle, with places for walks and recreation, situated in a relatively quite setting. On the other hand, close proximity to schools, shops or a health clinic is another important consideration. Industrial buildings should be localized so as not to be a nuisance to others, and their location should facilitate efficient transport of raw materials and ready products. Yet other requirements are defined for public buildings. It is therefore evident that the characteristics included in an evaluation of the location of a planned building can be highly diverse and their diversity makes the evaluation difficult. Selection of a location can be supported by a variety of methods. For instance, an evaluation can rely on assigning points which indicate the fulfillment of certain criteria. This approach generates a complex evaluation in the form of tables and maps of usefulness. Another possibility is to make an assessment of the criteria that a given land parcels should satisfy in order to develop a specific type of a building. Having combined these two sets of information, we can create a system or a model for the management of land resources, which will easily help to support decision making processes pertaining to the choice of a location. This article shows a model approach for a specific building.

Building Capacity for Earth Observations in Support of the United Nations Sustainable Development Goals

NASA Astrophysics Data System (ADS)

Blevins, B.; Prados, A. I.; Hook, E.

2017-12-01

The Group on Earth Observations (GEO) looks to build a future where the international community uses Earth observations to make better, informed decisions. This includes application in international agreements such as the UN Sustainable Development Goals (SDGs), the Sendai Framework for Disaster Risk Reduction, and the Convention on Biological Diversity. To do this, decision makers first need to build the necessary skills. NASA's Applied Remote Sensing Training program (ARSET) seeks to build capacity through remote sensing training. In-person and online trainings raise awareness, enable data access, and demonstrate applications of Earth observations. Starting in 2017, ARSET began offering training focused on applying Earth data to the UN SDGs. These trainings offer insight into applications of satellite data in support of implementing, monitoring, and evaluating the SDGs. This presentation will provide an overview of the use of NASA satellite data to track progress towards increased food security, disaster risk reduction, and conservation of natural resources for societal benefit. It will also include a discussion on capacity building best practices and lessons learned for using Earth observations to meet SDG targets, based on feedback from engaging over 800 participants from 89 nations and 580 organizations in ARSET SDG trainings.

Building and Strengthening Policy Research Capacity: Key Issues in Canadian Higher Education

ERIC Educational Resources Information Center

Jones, Glen A.

2014-01-01

Given the importance of higher education in social and economic development, governments need to build a strong higher education data and policy research infrastructure to support informed decision-making, provide policy advice, and offer a critical assessment of key trends and issues. The author discusses the decline of higher education policy…

Development of a Knowledge-Based System Approach for Decision Making in Construction Projects

DTIC Science & Technology

1992-05-01

a generic model for an administrative facility and medical facility with predefined fixed building systems based on Air Force criteria and past...MAINTENANCE HANGAR (MEDIUM BAY) CORROSION CONTROL HANGAR (HIGH BAY) FUEL SYSTEM MAINTENANCE HANGAR (MEDIUM BAY) MEDICAL MODEL 82 Table 5-1--continued...BUILDING SUPPORT MEDICAL LOGISTICS MEDICAL TOTAL 85 Table 5-2--continued MISSILE ASSEMBLY AND MAINTENANCE BUILDING TOTAL MISSILE LOADING AND UNLOADING

Beyond access: a case study on the intersection between accessibility, sustainability, and universal design.

PubMed

Gossett, Andrea; Mirza, Mansha; Barnds, Ann Kathleen; Feidt, Daisy

2009-11-01

A growing emphasis has been placed on providing equal opportunities for all people, particularly people with disabilities, to support participation. Barriers to participation are represented in part by physical space restrictions. This article explores the decision-making process during the construction of a new office building housing a disability-rights organization. The building project featured in this study was developed on the principles of universal design, maximal accessibility, and sustainability to support access and participation. A qualitative case study approach was used involving collection of data through in-depth interviews with key decision-makers; non-participant observations at design meetings; and on-site tours. Qualitative thematic analysis along with the development of a classification system was used to understand specific building elements and the relevant decision processes from which they resulted. Recording and analyzing the design process revealed several key issues including grassroots involvement of stakeholders; interaction between universal design and sustainable design; addressing diversity through flexibility and universality; and segregationist accessibility versus universal design. This case study revealed complex interactions between accessibility, universal design, and sustainability. Two visual models were proposed to understand and analyze these complexities.

Pink Is for Girls: Sugar and Spice and Everything Nice--A Case of Single-Sex Education

ERIC Educational Resources Information Center

Martin, Jennifer; Beese, Jane A.

2016-01-01

Leaders must know how to use evidence to inform district decisions, particularly as decisions related to learning become standard practice, and provide professional development that builds the organizational capacity needed to support continuous and sustainable district improvement. Collaboration and implementation of a shared vision and mission…

Building an Evidence Base for Speech-Language Services in the Schools: Challenges and Recommendations

ERIC Educational Resources Information Center

Whitmire, Kathleen A.; Rivers, Kenyatta O.; Mele-McCarthy, Joan A.; Staskowski, Maureen

2014-01-01

Speech-language pathologists are faced with demands for evidence to support practice. Federal legislation requires high-quality evidence for decisions regarding school-based services as part of evidence-based practice. The purpose of this article is to discuss the limited scientific evidence for making appropriate decisions about speech-language…

Grand Challenges in Clinical Decision Support v10

PubMed Central

Sittig, Dean F.; Wright, Adam; Osheroff, Jerome A.; Middleton, Blackford; Teich, Jonathan M.; Ash, Joan S.; Campbell, Emily; Bates, David W.

2008-01-01

There is a pressing need for high-quality, effective means of designing, developing, presenting, implementing, evaluating, and maintaining all types of clinical decision support capabilities for clinicians, patients and consumers. Using an iterative, consensus-building process we identified a rank-ordered list of the top 10 grand challenges in clinical decision support. This list was created to educate and inspire researchers, developers, funders, and policy-makers. The list of challenges in order of importance that they be solved if patients and organizations are to begin realizing the fullest benefits possible of these systems consists of: Improve the human-computer interface; Disseminate best practices in CDS design, development, and implementation; Summarize patient-level information; Prioritize and filter recommendations to the user; Create an architecture for sharing executable CDS modules and services; Combine recommendations for patients with co-morbidities; Prioritize CDS content development and implementation; Create internet-accessible clinical decision support repositories; Use freetext information to drive clinical decision support; Mine large clinical databases to create new CDS. Identification of solutions to these challenges is critical if clinical decision support is to achieve its potential and improve the quality, safety and efficiency of healthcare. PMID:18029232

New FEDS Software Helps You Design for Maximum Energy Efficiency, Minimum Cost

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

Gilbride, Theresa L.

2003-01-30

This article was written for the Partner Update a newsletter put out by Potomac Communications for DOE's Rebuild America program. The article describes the FEDS (Federal Energy Decision System) software, the official analytical tool of the Rebuild America program. This software, developed by PNNL with support from DOE, FEMP and Rebuild, helps government entities and contractors make informed decisions about which energy efficiency improvements are the most cost effective for their facilities. FEDS churns thru literally thousands of calculations accounting for energy uses, costs, and interactions from different types of HVAC systems, lighting types, insulation levels, building types, occupancy levelsmore » and times. FEDS crunchs the numbers so decision makers can get fast reliable answers on which alternatives are the best for their particular building. In this article, we're touting the improvements in the latest upgrade of FEDS, which is available free to Rebuild America partners. We tell partners what FEDS does, how to order it, and even where to get tech support and training.« less

Using an ecosystem service decision support tool to support ridge to reef management: An example of sediment reduction in west Maui, Hawaii

NASA Astrophysics Data System (ADS)

Falinski, K. A.; Oleson, K.; Htun, H.; Kappel, C.; Lecky, J.; Rowe, C.; Selkoe, K.; White, C.

2016-12-01

Faced with anthropogenic stressors and declining coral reef states, managers concerned with restoration and resilience of coral reefs are increasingly recognizing the need to take a ridge-to-reef, ecosystem-based approach. An ecosystem services framing can help managers move towards these goals, helping to illustrate trade-offs and opportunities of management actions in terms of their impacts on society. We describe a research program building a spatial ecosystem services-based decision-support tool, and being applied to guide ridge-to-reef management in a NOAA priority site in West Maui. We use multiple modeling methods to link biophysical processes to ecosystem services and their spatial flows and social values in an integrating platform. Modeled services include water availability, sediment retention, nutrient retention and carbon sequestration on land. A coral reef ecosystem service model is under development to capture the linkages between terrestrial and coastal ecosystem services. Valuation studies are underway to quantify the implications for human well-being. The tool integrates techniques from decision science to facilitate decision making. We use the sediment retention model to illustrate the types of analyses the tool can support. The case study explores the tradeoffs between road rehabilitation costs and sediment export avoided. We couple the sediment and cost models with trade-off analysis to identify optimal distributed solutions that are most cost-effective in reducing erosion, and then use those models to estimate sediment exposure to coral reefs. We find that cooperation between land owners reveals opportunities for maximizing the benefits of fixing roads and minimizes costs. This research forms the building blocks of an ecosystem service decision support tool that we intend to continue to test and apply in other Pacific Island settings.

Decision problems in management of construction projects

NASA Astrophysics Data System (ADS)

Szafranko, E.

2017-10-01

In a construction business, one must oftentimes make decisions during all stages of a building process, from planning a new construction project through its execution to the stage of using a ready structure. As a rule, the decision making process is made more complicated due to certain conditions specific for civil engineering. With such diverse decision situations, it is recommended to apply various decision making support methods. Both, literature and hands-on experience suggest several methods based on analytical and computational procedures, some less and some more complex. This article presents the methods which can be helpful in supporting decision making processes in the management of civil engineering projects. These are multi-criteria methods, such as MCE, AHP or indicator methods. Because the methods have different advantages and disadvantages, whereas decision situations have their own specific nature, a brief summary of the methods alongside some recommendations regarding their practical applications has been given at the end of the paper. The main aim of this article is to review the methods of decision support and their analysis for possible use in the construction industry.

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

NASA Astrophysics Data System (ADS)

Fatkhutdinov, Aybulat; Stefan, Catalin; Junghanns, Ralf

2016-04-01

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

Innovative Strategies for Building Community Resilience: Lessons from the Frontlines of Climate Change Capacity-Building

NASA Astrophysics Data System (ADS)

Abrash Walton, A.

2017-12-01

There is broad scientific consensus that climate change is occurring; however, there is limited implementation of measures to create resilient local communities (Abrash Walton, Simpson, Rhoades, & Daniels, 2016; Adger, Arnell, & Tompkins, 2005; Glavovic & Smith, 2014; Moser & Ekstrom, 2010; Picketts, Déry, & Curry, 2014). Communities that are considered climate leaders in the United States may have adopted climate change plans, yet few have actually implemented the policies, projects and recommendations in those plans. A range of innovative, education strategies have proven effective in building the capacity of local decision makers to strengthen community resilience. This presentation draws on the results of two years of original research regarding the information and support local decision makers require for effective action. Findings are based on information from four datasets, with more than 600 respondents from 48 U.S. states and 19 other countries working on local adaptation in a range of capacities. These research results can inform priority setting for public policy, budget setting, and action as well as private sector funding and investment. The presentation will focus, in particular, on methods and results of a pioneering Facilitated Community of Practice model (FCoP) for building climate preparedness and community resilience capacity, among local-level decision makers. The FCoP process includes group formation and shared capacity building experience. The process can also support collective objective setting and creation of structures and processes for ongoing sustainable collaboration. Results from two FCoPs - one fully online and the other hybrid - suggest that participants viewed the interpersonal and technical assistance elements of the FCoP as highly valuable. These findings suggest that there is an important need for facilitated networking and other relational aspects of building capacity among those advancing resilience at the local level.

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

A new security model for collaborative environments

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

Agarwal, Deborah; Lorch, Markus; Thompson, Mary

Prevalent authentication and authorization models for distributed systems provide for the protection of computer systems and resources from unauthorized use. The rules and policies that drive the access decisions in such systems are typically configured up front and require trust establishment before the systems can be used. This approach does not work well for computer software that moderates human-to-human interaction. This work proposes a new model for trust establishment and management in computer systems supporting collaborative work. The model supports the dynamic addition of new users to a collaboration with very little initial trust placed into their identity and supportsmore » the incremental building of trust relationships through endorsements from established collaborators. It also recognizes the strength of a users authentication when making trust decisions. By mimicking the way humans build trust naturally the model can support a wide variety of usage scenarios. Its particular strength lies in the support for ad-hoc and dynamic collaborations and the ubiquitous access to a Computer Supported Collaboration Workspace (CSCW) system from locations with varying levels of trust and security.« less

Shared decision making

MedlinePlus

... and your provider communicate openly and build a relationship of trust. Alternative Names Patient-centered care References ... ADAM Health Solutions. About MedlinePlus Site Map FAQs Customer Support Get email updates Subscribe to RSS Follow ...

Prioritization of information using decision support systems for seismic risk in Bucharest city

NASA Astrophysics Data System (ADS)

Armas, Iuliana; Gheorghe, Diana

2014-05-01

Nowadays, because of the ever increasing volume of information, policymakers are faced with decision making problems. Achieving an objective and suitable decision making may become a challenge. In such situations decision support systems (DSS) have been developed. DSS can assist in the decision making process, offering support on how a decision should be made, rather than what decision should be made (Simon, 1979). This in turn potentially involves a huge number of stakeholders and criteria. Regarding seismic risk, Bucharest City is highly vulnerable (Mandrescu et al., 2007). The aim of this study is to implement a spatial decision support system in order to secure a suitable shelter in case of an earthquake occurrence in the historical centre of Bucharest City. In case of a seismic risk, a shelter is essential for sheltering people who lost their homes or whose homes are in danger of collapsing while people at risk receive first aid in the post-disaster phase. For the present study, the SMCE Module for ILWIS 3.4 was used. The methodology included structuring the problem by creating a decision tree, standardizing and weighting of the criteria. The results showed that the most suitable buildings are Tania Hotel, Hanul lui Manuc, The National Bank of Romania, The Romanian Commercial Bank and The National History Museum.

From complex questionnaire and interviewing data to intelligent Bayesian Network models for medical decision support

PubMed Central

Constantinou, Anthony Costa; Fenton, Norman; Marsh, William; Radlinski, Lukasz

2016-01-01

Objectives 1) To develop a rigorous and repeatable method for building effective Bayesian network (BN) models for medical decision support from complex, unstructured and incomplete patient questionnaires and interviews that inevitably contain examples of repetitive, redundant and contradictory responses; 2) To exploit expert knowledge in the BN development since further data acquisition is usually not possible; 3) To ensure the BN model can be used for interventional analysis; 4) To demonstrate why using data alone to learn the model structure and parameters is often unsatisfactory even when extensive data is available. Method The method is based on applying a range of recent BN developments targeted at helping experts build BNs given limited data. While most of the components of the method are based on established work, its novelty is that it provides a rigorous consolidated and generalised framework that addresses the whole life-cycle of BN model development. The method is based on two original and recent validated BN models in forensic psychiatry, known as DSVM-MSS and DSVM-P. Results When employed with the same datasets, the DSVM-MSS demonstrated competitive to superior predictive performance (AUC scores 0.708 and 0.797) against the state-of-the-art (AUC scores ranging from 0.527 to 0.705), and the DSVM-P demonstrated superior predictive performance (cross-validated AUC score of 0.78) against the state-of-the-art (AUC scores ranging from 0.665 to 0.717). More importantly, the resulting models go beyond improving predictive accuracy and into usefulness for risk management purposes through intervention, and enhanced decision support in terms of answering complex clinical questions that are based on unobserved evidence. Conclusions This development process is applicable to any application domain which involves large-scale decision analysis based on such complex information, rather than based on data with hard facts, and in conjunction with the incorporation of expert knowledge for decision support via intervention. The novelty extends to challenging the decision scientists to reason about building models based on what information is really required for inference, rather than based on what data is available and hence, forces decision scientists to use available data in a much smarter way. PMID:26830286

From complex questionnaire and interviewing data to intelligent Bayesian network models for medical decision support.

PubMed

Constantinou, Anthony Costa; Fenton, Norman; Marsh, William; Radlinski, Lukasz

2016-02-01

(1) To develop a rigorous and repeatable method for building effective Bayesian network (BN) models for medical decision support from complex, unstructured and incomplete patient questionnaires and interviews that inevitably contain examples of repetitive, redundant and contradictory responses; (2) To exploit expert knowledge in the BN development since further data acquisition is usually not possible; (3) To ensure the BN model can be used for interventional analysis; (4) To demonstrate why using data alone to learn the model structure and parameters is often unsatisfactory even when extensive data is available. The method is based on applying a range of recent BN developments targeted at helping experts build BNs given limited data. While most of the components of the method are based on established work, its novelty is that it provides a rigorous consolidated and generalised framework that addresses the whole life-cycle of BN model development. The method is based on two original and recent validated BN models in forensic psychiatry, known as DSVM-MSS and DSVM-P. When employed with the same datasets, the DSVM-MSS demonstrated competitive to superior predictive performance (AUC scores 0.708 and 0.797) against the state-of-the-art (AUC scores ranging from 0.527 to 0.705), and the DSVM-P demonstrated superior predictive performance (cross-validated AUC score of 0.78) against the state-of-the-art (AUC scores ranging from 0.665 to 0.717). More importantly, the resulting models go beyond improving predictive accuracy and into usefulness for risk management purposes through intervention, and enhanced decision support in terms of answering complex clinical questions that are based on unobserved evidence. This development process is applicable to any application domain which involves large-scale decision analysis based on such complex information, rather than based on data with hard facts, and in conjunction with the incorporation of expert knowledge for decision support via intervention. The novelty extends to challenging the decision scientists to reason about building models based on what information is really required for inference, rather than based on what data is available and hence, forces decision scientists to use available data in a much smarter way. Copyright © 2016 Elsevier B.V. All rights reserved.

Automatically updating predictive modeling workflows support decision-making in drug design.

PubMed

Muegge, Ingo; Bentzien, Jörg; Mukherjee, Prasenjit; Hughes, Robert O

2016-09-01

Using predictive models for early decision-making in drug discovery has become standard practice. We suggest that model building needs to be automated with minimum input and low technical maintenance requirements. Models perform best when tailored to answering specific compound optimization related questions. If qualitative answers are required, 2-bin classification models are preferred. Integrating predictive modeling results with structural information stimulates better decision making. For in silico models supporting rapid structure-activity relationship cycles the performance deteriorates within weeks. Frequent automated updates of predictive models ensure best predictions. Consensus between multiple modeling approaches increases the prediction confidence. Combining qualified and nonqualified data optimally uses all available information. Dose predictions provide a holistic alternative to multiple individual property predictions for reaching complex decisions.

Technology Infusion Challenges from a Decision Support Perspective

NASA Technical Reports Server (NTRS)

Adumitroaie, V.; Weisbin, C. R.

2009-01-01

In a restricted science budget environment and increasingly numerous required technology developments, the technology investment decisions within NASA are objectively more and more difficult to make such that the end results are satisfying the technical objectives and all the organizational constraints. Under these conditions it is rationally desirable to build an investment portfolio, which has the highest possible technology infusion rate. Arguably the path to infusion is subject to many influencing factors, but here only the challenges associated with the very initial stages are addressed: defining the needs and the subsequent investment decision-support process. It is conceivable that decision consistency and possibly its quality suffer when the decision-making process has limited or no traceability. This paper presents a structured decision-support framework aiming to provide traceable, auditable, infusion- driven recommendations towards a selection process in which these recommendations are used as reference points in further discussions among stakeholders. In this framework addressing well-defined requirements, different measures of success can be defined based on traceability to specific selection criteria. As a direct result, even by using simplified decision models the likelihood of infusion can be probed and consequently improved.

To Build on Appleworks and the Apple II, or Not--Seven Points to Guide Your Decision.

ERIC Educational Resources Information Center

Chesebrough, David E.

1993-01-01

Discusses seven factors to consider in deciding whether or not to build on AppleWorks and Apple II technology now that Apple Computer is developing little new software for the system. Factors include the impact of change on users and the existence of mail-order support services, which are listed in a sidebar. (KRN)

Energy disclosure, market behavior, and the building data ecosystem.

PubMed

Kontokosta, Constantine E

2013-08-01

Energy disclosure laws represent one of the most promising public policy tools to accelerate market transformation around building energy efficiency. For this type of information to have an impact on market behavior, it must be collected, analyzed, and disseminated to support the decision-making processes of each end user and influence both the producers and consumers of building performance data. This paper explores the significance of energy disclosure requirements and outlines a framework for utilizing these new sources of transparent, publicly available information. It presents the mechanisms by which information can alter market behavior in the commercial real estate sector and develops a wiring diagram for the flows of information through the building data ecosystem. It concludes with a discussion of the motivations, metrics, and constraints faced by the various stakeholders in the ecosystem and how these factors influence investment decision models. © 2013 New York Academy of Sciences.

Family-building After Breast Cancer: Considering the Effect on Adherence to Adjuvant Endocrine Therapy.

PubMed

Benedict, Catherine; Thom, Bridgette; Teplinsky, Eleonora; Carleton, Jane; Kelvin, Joanne F

2017-06-01

Adherence to endocrine therapy (ET) is a longstanding problem in breast cancer (BC) survivorship care, particularly among younger women. Younger patients have reported lower ET initiation rates and greater rates of early discontinuation and are considered an "at risk" group for nonadherence. For women who hope to have children in the future, concerns about premature menopause and the implications of postponing childbearing for the 5 to 10 years of ET are widespread. Preliminary evidence suggests that prioritizing fertility, along with concerns about side effects, leads to ET noninitiation and early discontinuation. Clinical efforts to improve adherence might need to consider patients' family-building goals during the course of treatment and to appropriately counsel patients according to their priorities and family-building intentions. Educational materials about family building after cancer are still not consistently available or provided. Helping patients to access trusted informational resources and decision support tools, in conjunction with medical counseling, will promote informed decisions regarding ET adherence and pregnancy that are medically appropriate. Such shared patient-provider decision-making about ET adherence and pregnancy could help to maximize patient autonomy by incorporating their values, preferences, and priorities into decisions, using providers' medical expertise. Copyright © 2016 Elsevier Inc. All rights reserved.

USGCRP assessments: Meeting the challenges of climate and global change

NASA Astrophysics Data System (ADS)

Dickinson, T.; Kuperberg, J. M.

2016-12-01

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

a Novel Approach to Support Majority Voting in Spatial Group Mcdm Using Density Induced Owa Operator for Seismic Vulnerability Assessment

NASA Astrophysics Data System (ADS)

Moradi, M.; Delavar, M. R.; Moshiri, B.; Khamespanah, F.

2014-10-01

Being one of the most frightening disasters, earthquakes frequently cause huge damages to buildings, facilities and human beings. Although the prediction of characteristics of an earthquake seems to be impossible, its loss and damage is predictable in advance. Seismic loss estimation models tend to evaluate the extent to which the urban areas are vulnerable to earthquakes. Many factors contribute to the vulnerability of urban areas against earthquakes including age and height of buildings, the quality of the materials, the density of population and the location of flammable facilities. Therefore, seismic vulnerability assessment is a multi-criteria problem. A number of multi criteria decision making models have been proposed based on a single expert. The main objective of this paper is to propose a model which facilitates group multi criteria decision making based on the concept of majority voting. The main idea of majority voting is providing a computational tool to measure the degree to which different experts support each other's opinions and make a decision regarding this measure. The applicability of this model is examined in Tehran metropolitan area which is located in a seismically active region. The results indicate that neglecting the experts which get lower degrees of support from others enables the decision makers to avoid the extreme strategies. Moreover, a computational method is proposed to calculate the degree of optimism in the experts' opinions.

Object-oriented design and programming in medical decision support.

PubMed

Heathfield, H; Armstrong, J; Kirkham, N

1991-12-01

The concept of object-oriented design and programming has recently received a great deal of attention from the software engineering community. This paper highlights the realisable benefits of using the object-oriented approach in the design and development of clinical decision support systems. These systems seek to build a computational model of some problem domain and therefore tend to be exploratory in nature. Conventional procedural design techniques do not support either the process of model building or rapid prototyping. The central concepts of the object-oriented paradigm are introduced, namely encapsulation, inheritance and polymorphism, and their use illustrated in a case study, taken from the domain of breast histopathology. In particular, the dual roles of inheritance in object-oriented programming are examined, i.e., inheritance as a conceptual modelling tool and inheritance as a code reuse mechanism. It is argued that the use of the former is not entirely intuitive and may be difficult to incorporate into the design process. However, inheritance as a means of optimising code reuse offers substantial technical benefits.

The design of patient decision support interventions: addressing the theory-practice gap.

PubMed

Elwyn, Glyn; Stiel, Mareike; Durand, Marie-Anne; Boivin, Jacky

2011-08-01

Although an increasing number of decision support interventions for patients (including decision aids) are produced, few make explicit use of theory. We argue the importance of using theory to guide design. The aim of this work was to address this theory-practice gap and to examine how a range of selected decision-making theories could inform the design and evaluation of decision support interventions. We reviewed the decision-making literature and selected relevant theories. We assessed their key principles, theoretical pathways and predictions in order to determine how they could inform the design of two core components of decision support interventions, namely, information and deliberation components and to specify theory-based outcome measures. Eight theories were selected: (1) the expected utility theory; (2) the conflict model of decision making; (3) prospect theory; (4) fuzzy-trace theory; (5) the differentiation and consolidation theory; (6) the ecological rationality theory; (7) the rational-emotional model of decision avoidance; and finally, (8) the Attend, React, Explain, Adapt model of affective forecasting. Some theories have strong relevance to the information design (e.g. prospect theory); some are more relevant to deliberation processes (conflict theory, differentiation theory and ecological validity). None of the theories in isolation was sufficient to inform the design of all the necessary components of decision support interventions. It was also clear that most work in theory-building has focused on explaining or describing how humans think rather than on how tools could be designed to help humans make good decisions. It is not surprising therefore that a large theory-practice gap exists as we consider decision support for patients. There was no relevant theory that integrated all the necessary contributions to the task of making good decisions in collaborative interactions. Initiatives such as the International Patient Decision Aids Standards Collaboration influence standards for the design of decision support interventions. However, this analysis points to the need to undertake more work in providing theoretical foundations for these interventions. © 2010 Blackwell Publishing Ltd.

Allies Shift Focus toward Promoting Standards Adoption

ERIC Educational Resources Information Center

Gewertz, Catherine

2010-01-01

With the new common standards completed, education leaders in nearly every state face the critical decision of whether to adopt them. To maximize the number of states that do, a core group of advocates is providing information and advice to help build the necessary base of support. The support network includes groups that spearheaded the Common…

Energy Resources for State and Local Governments

EPA Pesticide Factsheets

Hosts capacity building and decision-support tools and data, best practice policy and program implementation information.Technical information tailored to the needs of state, local, and tribal governments use energy efficiency and renewable energy policies

The Will and the Way of Data Use.

ERIC Educational Resources Information Center

Alwin, Lance

2002-01-01

Superintendent of Antigo Unified School District, Antigo, Wisconsin, explains the use of school-level and community-level data to build support for bond and budget referenda. Describes the benefits of data-driven decision-making. (PKP)

Building Energy Consumption Pattern Analysis of Detached Housing for the Policy Decision Simulator

NASA Astrophysics Data System (ADS)

Lim, Jiyoun; Lee, Seung-Eon

2018-03-01

The Korean government announced its plan to raise the previous reduction goal of greenhouse gas emission from buildings by 26.9% until 2020 on July 2015. Therefore, policies regarding efficiency in the building energy are implemented fast, but the level of building owners and market understanding is low in general, and the government service system which supports decision making for implementing low-energy buildings has not been provided yet. The purpose of this study is to present the design direction for establishing user customized building energy database to perform a role to provide autonomous ecosystem of low-energy buildings. In order to reduce energy consumption in buildings, it is necessary to carry out the energy performance analysis based on the characteristics of target building. By analysing about 20-thousand cases of the amount of housing energy consumption in Korea, this study suggested the real energy consumption pattern by building types. Also, the energy performance of a building could be determined by energy consumption, but previous building energy consumption analysis programs required expert knowledge and experience in program usage, so it was difficult for normal building users to use such programs. Therefore, a measure to provide proper default using the level of data which general users with no expert knowledge regarding building energy could enter easily was suggested in this study.

Enhancing Fire Control Decision Making with the Patriot Cognitive Skills Trainer: Development and Validation

DTIC Science & Technology

2017-11-01

existing instruction. In addition, the methodology used to identify decision-triggers may be applied to other Army domains to develop instruction...ADDIE is an instructional design framework used as a descriptive guideline for building effective training and performance support tools. 3 In...and evaluate information, and create a solution—were Level Descriptive Terms Additional Examples Create Generating – hypothesizing Planning

Beyond Wiki to Judgewiki for Transparent Climate Change Decisions

NASA Astrophysics Data System (ADS)

Capron, M. E.

2008-12-01

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

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

PubMed

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

2017-06-21

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

The cornerstone of data warehousing for government applications

NASA Technical Reports Server (NTRS)

Kenbeek, Doug; Rothschild, Jack

1996-01-01

The purpose of this paper is to discuss data warehousing storage issues and the impact of EMC open storage technology for meeting the myriad of challenges government organizations face when building Decision Support/Data Warehouse system.

Metering Best Practices Applied in the National Renewable Energy Laboratory's Research Support Facility: A Primer to the 2011 Measured and Modeled Energy Consumption Datasets

DOE Data Explorer

Sheppy, Michael; Beach, A.; Pless, Shanti

2016-08-09

Modern buildings are complex energy systems that must be controlled for energy efficiency. The Research Support Facility (RSF) at the National Renewable Energy Laboratory (NREL) has hundreds of controllers -- computers that communicate with the building's various control systems -- to control the building based on tens of thousands of variables and sensor points. These control strategies were designed for the RSF's systems to efficiently support research activities. Many events that affect energy use cannot be reliably predicted, but certain decisions (such as control strategies) must be made ahead of time. NREL researchers modeled the RSF systems to predict how they might perform. They then monitor these systems to understand how they are actually performing and reacting to the dynamic conditions of weather, occupancy, and maintenance.

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.

Two-Graph Building Interior Representation for Emergency Response Applications

NASA Astrophysics Data System (ADS)

Boguslawski, P.; Mahdjoubi, L.; Zverovich, V.; Fadli, F.

2016-06-01

Nowadays, in a rapidly developing urban environment with bigger and higher public buildings, disasters causing emergency situations and casualties are unavoidable. Preparedness and quick response are crucial issues saving human lives. Available information about an emergency scene, such as a building structure, helps for decision making and organizing rescue operations. Models supporting decision-making should be available in real, or near-real, time. Thus, good quality models that allow implementation of automated methods are highly desirable. This paper presents details of the recently developed method for automated generation of variable density navigable networks in a 3D indoor environment, including a full 3D topological model, which may be used not only for standard navigation but also for finding safe routes and simulating hazard and phenomena associated with disasters such as fire spread and heat transfer.

Exploring Challenges and Opportunities of Coproduction: USDA Climate Hub Efforts to Integrate Coproduction with Applied Research and Decision Support Tool Development in the Northwest

NASA Astrophysics Data System (ADS)

Roesch-McNally, G.; Prendeville, H. R.

2017-12-01

A lack of coproduction, the joint production of new technologies or knowledge among technical experts and other groups, is arguably one of the reasons why much scientific information and resulting decision support systems are not very usable. Increasingly, public agencies and academic institutions are emphasizing the importance of coproduction of scientific knowledge and decision support systems in order to facilitate greater engagement between the scientific community and key stakeholder groups. Coproduction has been embraced as a way for the scientific community to develop actionable scientific information that will assist end users in solving real-world problems. Increasing the level of engagement and stakeholder buy-in to the scientific process is increasingly necessary, particularly in the context of growing politicization of science and the scientific process. Coproduction can be an effective way to build trust and can build-on and integrate local and traditional knowledge. Employing coproduction strategies may enable the development of more relevant and useful information and decision support tools that address stakeholder challenges at relevant scales. The USDA Northwest Climate Hub has increasingly sought ways to integrate coproduction in the development of both applied research projects and the development of decision support systems. Integrating coproduction, however, within existing institutions is not always simple, given that coproduction is often more focused on process than products and products are, for better or worse, often the primary focus of applied research and tool development projects. The USDA Northwest Climate Hub sought to integrate coproduction into our FY2017 call for proposal process. As a result we have a set of proposals and fledgling projects that fall along the engagement continuum (see Figure 1- attached). We will share the challenges and opportunities that emerged from this purposeful integration of coproduction into the work that we prioritized for funding. This effort highlights strategies for how federal agencies might consider how and whether to codify coproduction tenets into their collaborations and agenda setting.

'Walking the tightrope': The role of peer support workers in facilitating consumers' participation in decision-making.

PubMed

Cleary, Michelle; Raeburn, Toby; Escott, Phil; West, Sancia; Lopez, Violeta

2018-05-09

In adult mental health services, the participation of consumers is essential. The aim of this study was to explore the challenges faced by peer support workers when involving mental health consumers in decision-making about their care and the strategies they employed to overcome these challenges so as to improve mental health consumers' participation in decision-making and recovery. Semi-structured individual interviews were conducted with six peer support workers currently employed in psychiatric hospitals and/or community mental health systems. Thematic analysis identified challenges related to role definition, power imbalance, doctor-centric medical approaches to care, and lack of resources. Strategies to overcome these challenges that were reported, included the following: facilitating meaningful involvement for service users, appropriate use of the lived experience, building relationships and communication, promoting rights and advocacy, and promoting professionalism of peer support workers (PSWs). Nursing staff need ongoing support and education to understand and value the varied roles of PSWs and thereby empower PSWs to engage in enhancing consumer decision-making. The roles of the PSWs should be viewed as complementary, and greater appreciation and understanding of roles would better support recovery-oriented care. © 2018 Australian College of Mental Health Nurses Inc.

Taking precautions at KSC for Hurricane Georges

NASA Technical Reports Server (NTRS)

1998-01-01

Workers put up plywood barriers on the windows of the Operations Support Building (OSB) as part of a precautionary plan in the event that Hurricane Georges threatens Central Florida. In light of the unpredictable nature of hurricanes, the decision was made to minimize risk and provide protection to KSC personnel and to the Space Shuttle national asset. The Vehicle Assembly Building is reflected (left) in the uncovered windows of the OSB.

Examining statewide capacity for school health and mental health promotion: a post hoc application of a district capacity-building framework.

PubMed

Maras, Melissa A; Weston, Karen J; Blacksmith, Jennifer; Brophy, Chelsey

2015-03-01

Schools must possess a variety of capacities to effectively support comprehensive and coordinated school health promotion activities, and researchers have developed a district-level capacity-building framework specific to school health promotion. State-level school health coalitions often support such capacity-building efforts and should embed this work within a data-based, decision-making model. However, there is a lack of guidance for state school health coalitions on how they should collect and use data. This article uses a district-level capacity-building framework to interpret findings from a statewide coordinated school health needs/resource assessment in order to examine statewide capacity for school health promotion. Participants included school personnel (N = 643) from one state. Descriptive statistics were calculated for survey items, with further examination of subgroup differences among school administrators and nurses. Results were then interpreted via a post hoc application of a district-level capacity-building framework. Findings across districts revealed statewide strengths and gaps with regard to leadership and management capacities, internal and external supports, and an indicator of global capacity. Findings support the utility of using a common framework across local and state levels to align efforts and embed capacity-building activities within a data-driven, continuous improvement model. © 2014 Society for Public Health Education.

Believable Social and Emotional Agents.

DTIC Science & Technology

1996-05-01

While building tools to support the creation of believable emotional agents, I had to make a number of important design decisions . Before describing...processing systems, it is difficult to give an artist direct control over the emotion - al aspects of the character. By making these decisions explicit, I hope...Woody on “Cheers”). Believable Agents BELIEVABLE SOCIAL AND EMOTIONAL AGENTS 11 Lesson: We don’t want agent architectures that enforce rationality and

Challenges in building intelligent systems for space mission operations

NASA Technical Reports Server (NTRS)

Hartman, Wayne

1991-01-01

The purpose here is to provide a top-level look at the stewardship functions performed in space operations, and to identify the major issues and challenges that must be addressed to build intelligent systems that can realistically support operations functions. The focus is on decision support activities involving monitoring, state assessment, goal generation, plan generation, and plan execution. The bottom line is that problem solving in the space operations domain is a very complex process. A variety of knowledge constructs, representations, and reasoning processes are necessary to support effective human problem solving. Emulating these kinds of capabilities in intelligent systems offers major technical challenges that the artificial intelligence community is only beginning to address.

Using ILOG OPL-CPLEX and ILOG Optimization Decision Manager (ODM) to Develop Better Models

NASA Astrophysics Data System (ADS)

2008-10-01

This session will provide an in-depth overview on building state-of-the-art decision support applications and models. You will learn how to harness the full power of the ILOG OPL-CPLEX-ODM Development System (ODMS) to develop optimization models and decision support applications that solve complex problems ranging from near real-time scheduling to long-term strategic planning. We will demonstrate how to use ILOG's Open Programming Language (OPL) to quickly model problems solved by ILOG CPLEX, and how to use ILOG ODM to gain further insight about the model. By the end of the session, attendees will understand how to take advantage of the powerful combination of ILOG OPL (to describe an optimization model) and ILOG ODM (to understand the relationships between data, decision variables and constraints).

Research utilization in the building industry: decision model and preliminary assessment

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

Watts, R.L.; Johnson, D.R.; Smith, S.A.

1985-10-01

The Research Utilization Program was conceived as a far-reaching means for managing the interactions of the private sector and the federal research sector as they deal with energy conservation in buildings. The program emphasizes a private-public partnership in planning a research agenda and in applying the results of ongoing and completed research. The results of this task support the hypothesis that the transfer of R and D results to the buildings industry can be accomplished more efficiently and quickly by a systematic approach to technology transfer. This systematic approach involves targeting decision makers, assessing research and information needs, properly formatingmore » information, and then transmitting the information through trusted channels. The purpose of this report is to introduce elements of a market-oriented knowledge base, which would be useful to the Building Systems Division, the Office of Buildings and Community Systems and their associated laboratories in managing a private-public research partnership on a rational systematic basis. This report presents conceptual models and data bases that can be used in formulating a technology transfer strategy and in planning technology transfer programs.« less

Building a Lego wall: Sequential action selection.

PubMed

Arnold, Amy; Wing, Alan M; Rotshtein, Pia

2017-05-01

The present study draws together two distinct lines of enquiry into the selection and control of sequential action: motor sequence production and action selection in everyday tasks. Participants were asked to build 2 different Lego walls. The walls were designed to have hierarchical structures with shared and dissociated colors and spatial components. Participants built 1 wall at a time, under low and high load cognitive states. Selection times for correctly completed trials were measured using 3-dimensional motion tracking. The paradigm enabled precise measurement of the timing of actions, while using real objects to create an end product. The experiment demonstrated that action selection was slowed at decision boundary points, relative to boundaries where no between-wall decision was required. Decision points also affected selection time prior to the actual selection window. Dual-task conditions increased selection errors. Errors mostly occurred at boundaries between chunks and especially when these required decisions. The data support hierarchical control of sequenced behavior. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Flu Diagnosis System Using Jaccard Index and Rough Set Approaches

NASA Astrophysics Data System (ADS)

Efendi, Riswan; Azah Samsudin, Noor; Mat Deris, Mustafa; Guan Ting, Yip

2018-04-01

Jaccard index and rough set approaches have been frequently implemented in decision support systems with various domain applications. Both approaches are appropriate to be considered for categorical data analysis. This paper presents the applications of sets operations for flu diagnosis systems based on two different approaches, such as, Jaccard index and rough set. These two different approaches are established using set operations concept, namely intersection and subset. The step-by-step procedure is demonstrated from each approach in diagnosing flu system. The similarity and dissimilarity indexes between conditional symptoms and decision are measured using Jaccard approach. Additionally, the rough set is used to build decision support rules. Moreover, the decision support rules are established using redundant data analysis and elimination of unclassified elements. A number data sets is considered to attempt the step-by-step procedure from each approach. The result has shown that rough set can be used to support Jaccard approaches in establishing decision support rules. Additionally, Jaccard index is better approach for investigating the worst condition of patients. While, the definitely and possibly patients with or without flu can be determined using rough set approach. The rules may improve the performance of medical diagnosis systems. Therefore, inexperienced doctors and patients are easier in preliminary flu diagnosis.

75 FR 51815 - Decision To Evaluate a Petition To Designate a Class of Employees From the Norton Company...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-08-23

..., Massachusetts. Job Titles and/or Job Duties: All employees who worked in any building or area. Period of..., Interim Director, Division of Compensation Analysis and Support, National Institute for Occupational...

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

PubMed Central

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

2011-01-01

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

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

PubMed

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

2012-04-01

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

Service-Oriented Architecture Approach to MAGTF Logistics Support Systems

DTIC Science & Technology

2013-09-01

Support System-Marine Corps IT Information Technology KPI Key Performance Indicators LCE Logistics Command Element ITV In-transit Visibility LCM...building blocks, options, KPI (key performance indicators), design decisions and the corresponding; the physical attributes which is the second attribute... KPI ) that they impact. h. Layer 8 (Information Architecture) The business intelligence layer and information architecture safeguards the inclusion

A Buyer Behaviour Framework for the Development and Design of Software Agents in E-Commerce.

ERIC Educational Resources Information Center

Sproule, Susan; Archer, Norm

2000-01-01

Software agents are computer programs that run in the background and perform tasks autonomously as delegated by the user. This paper blends models from marketing research and findings from the field of decision support systems to build a framework for the design of software agents to support in e-commerce buying applications. (Contains 35…

How Leaders Can Support Teachers with Data-Driven Decision Making: A Framework for Understanding Capacity Building

ERIC Educational Resources Information Center

Marsh, Julie A.; Farrell, Caitlin C.

2015-01-01

As accountability systems have increased demands for evidence of student learning, the use of data in education has become more prevalent in many countries. Although school and administrative leaders are recognizing the need to provide support to teachers on how to interpret and respond to data, there is little theoretically sound research on…

Two Dilemmas in Communicating Mathematics in Adult Basic Courses: "How To Support Pre-Knowledge of Adult Learners" and "How To Support Democratic Classroom Decisions."

ERIC Educational Resources Information Center

Lindenskov, Lena; Hansen, Eigil Peter

This study explores how adults' perspectives, intentions, blockages, resistance, and fascinations are reconstructed during a mathematics course in adult basic education. These aspects are discussed as important building blocks for developing theory in adult educational research. Adult mathematics education was compared in different institutional…

Watershed System Model: The Essentials to Model Complex Human-Nature System at the River Basin Scale

NASA Astrophysics Data System (ADS)

Li, Xin; Cheng, Guodong; Lin, Hui; Cai, Ximing; Fang, Miao; Ge, Yingchun; Hu, Xiaoli; Chen, Min; Li, Weiyue

2018-03-01

Watershed system models are urgently needed to understand complex watershed systems and to support integrated river basin management. Early watershed modeling efforts focused on the representation of hydrologic processes, while the next-generation watershed models should represent the coevolution of the water-land-air-plant-human nexus in a watershed and provide capability of decision-making support. We propose a new modeling framework and discuss the know-how approach to incorporate emerging knowledge into integrated models through data exchange interfaces. We argue that the modeling environment is a useful tool to enable effective model integration, as well as create domain-specific models of river basin systems. The grand challenges in developing next-generation watershed system models include but are not limited to providing an overarching framework for linking natural and social sciences, building a scientifically based decision support system, quantifying and controlling uncertainties, and taking advantage of new technologies and new findings in the various disciplines of watershed science. The eventual goal is to build transdisciplinary, scientifically sound, and scale-explicit watershed system models that are to be codesigned by multidisciplinary communities.

GSA's Green Proving Ground: Identifying, Testing and Evaluating Innovative Technologies (Presentation)

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

Kandt, A.; Lowell, M.

2012-05-01

GSA's Green Proving Ground (GPG) program utilizes GSA's real estate portfolio to test and evaluate innovative and underutilized sustainable building technologies and practices. Findings are used to support the development of GSA performance specifications and inform decision making within GSA, other federal agencies, and the real estate industry. The program aims to drive innovation in environmental performance in federal buildings and help lead market transformation through deployment of new technologies.

Building a Foreign Military Sales Construction Delivery Strategy Decision Support System

DTIC Science & Technology

1991-09-01

DSS, formulates it into a computer model and produces solutions using information and expert heuristics. Using the Expert Systeic Process to Build a DSS...computer model . There are five stages in the development of an expert system. They are: 1) Identify and characterize the important aspects of the problem...and Steven A. Hidreth. U.S. Security Assistance: The Political Process. Massachusetts: Heath and Company, 1985. 19. Guirguis , Amir A., Program

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.

A Recommendation Algorithm for Automating Corollary Order Generation

PubMed Central

Klann, Jeffrey; Schadow, Gunther; McCoy, JM

2009-01-01

Manual development and maintenance of decision support content is time-consuming and expensive. We explore recommendation algorithms, e-commerce data-mining tools that use collective order history to suggest purchases, to assist with this. In particular, previous work shows corollary order suggestions are amenable to automated data-mining techniques. Here, an item-based collaborative filtering algorithm augmented with association rule interestingness measures mined suggestions from 866,445 orders made in an inpatient hospital in 2007, generating 584 potential corollary orders. Our expert physician panel evaluated the top 92 and agreed 75.3% were clinically meaningful. Also, at least one felt 47.9% would be directly relevant in guideline development. This automated generation of a rough-cut of corollary orders confirms prior indications about automated tools in building decision support content. It is an important step toward computerized augmentation to decision support development, which could increase development efficiency and content quality while automatically capturing local standards. PMID:20351875

A recommendation algorithm for automating corollary order generation.

PubMed

Klann, Jeffrey; Schadow, Gunther; McCoy, J M

2009-11-14

Manual development and maintenance of decision support content is time-consuming and expensive. We explore recommendation algorithms, e-commerce data-mining tools that use collective order history to suggest purchases, to assist with this. In particular, previous work shows corollary order suggestions are amenable to automated data-mining techniques. Here, an item-based collaborative filtering algorithm augmented with association rule interestingness measures mined suggestions from 866,445 orders made in an inpatient hospital in 2007, generating 584 potential corollary orders. Our expert physician panel evaluated the top 92 and agreed 75.3% were clinically meaningful. Also, at least one felt 47.9% would be directly relevant in guideline development. This automated generation of a rough-cut of corollary orders confirms prior indications about automated tools in building decision support content. It is an important step toward computerized augmentation to decision support development, which could increase development efficiency and content quality while automatically capturing local standards.

Social Stigma and Childbearing for Women Living With HIV/AIDS.

PubMed

Cuca, Yvette P; Rose, Carol Dawson

2016-09-01

As more women become infected with HIV, the issue of childbearing becomes increasingly salient. A more nuanced understanding of women's situations is needed to provide high-quality and relevant services and support. We examined reproductive decision making among 20 women living with HIV through in-depth interviews. These women made decisions within situations of chaos, instability, and trauma, which often limited their ability to make truly informed choices about their lives and childbearing. Despite their HIV, many of the women wanted children, but experienced stigmatization related both to their HIV and to their decisions to have children. This stigmatization came from multiple sources, including health care providers, some of whom encouraged their patients to abort pregnancies because of their HIV. Participants, however, demonstrated resistance to stigmatization, through building supportive communities and developing trusting relationships with HIV providers. These results support the need for specialized HIV care for women of childbearing age. © The Author(s) 2015.

SERVIR Science Applications for Capacity Building

NASA Technical Reports Server (NTRS)

Limaye, Ashutosh; Searby, Nancy D.; Irwin, Daniel

2012-01-01

SERVIR is a regional visualization and monitoring system using Earth observations to support environmental management, climate adaptation, and disaster response in developing countries. SERVIR is jointly sponsored by NASA and the U.S. Agency for International Development (USAID). SERVIR has been instrumental in development of science applications to support the decision-making and capacity building in the developing countries with the help of SERVIR Hubs. In 2011, NASA Research Opportunities in Space and Earth Sciences (ROSES) included a call for proposals to form SERVIR Applied Sciences Team (SERVIR AST) under Applied Sciences Capacity Building Program. Eleven proposals were selected, the Principal Investigators of which comprise the core of the SERVIR AST. The expertise on the Team span several societal benefit areas including agriculture, disasters, public health and air quality, water, climate and terrestrial carbon assessments. This presentation will cover the existing SERVIR science applications, capacity building components, overview of SERVIR AST projects, and anticipated impacts.

Has your greenhouse gone virtual?

USDA-ARS?s Scientific Manuscript database

Virtual Grower is a free decision-support software program available from USDA-ARS that allows growers to build a virtual greenhouse. It was initially designed to help greenhouse growers estimate heating costs and conduct simple simulations to figure out where heat savings could be achieved. Featu...

Toward patient-centered, personalized and personal decision support and knowledge management: a survey.

PubMed

Leong, T-Y

2012-01-01

This paper summarizes the recent trends and highlights the challenges and opportunities in decision support and knowledge management for patient-centered, personalized, and personal health care. The discussions are based on a broad survey of related references, focusing on the most recent publications. Major advances are examined in the areas of i) shared decision making paradigms, ii) continuity of care infrastructures and architectures, iii) human factors and system design approaches, iv) knowledge management innovations, and v) practical deployment and change considerations. Many important initiatives, projects, and plans with promising results have been identified. The common themes focus on supporting the individual patients who are playing an increasing central role in their own care decision processes. New collaborative decision making paradigms and information infrastructures are required to ensure effective continuity of care. Human factors and usability are crucial for the successful development and deployment of the relevant systems, tools, and aids. Advances in personalized medicine can be achieved through integrating genomic, phenotypic and other biological, individual, and population level information, and gaining useful insights from building and analyzing biological and other models at multiple levels of abstraction. Therefore, new Information and Communication Technologies and evaluation approaches are needed to effectively manage the scale and complexity of biomedical and health information, and adapt to the changing nature of clinical decision support. Recent research in decision support and knowledge management combines heterogeneous information and personal data to provide cost-effective, calibrated, personalized support in shared decision making at the point of care. Current and emerging efforts concentrate on developing or extending conventional paradigms, techniques, systems, and architectures for the new predictive, preemptive, and participatory health care model for patient-centered, personalized medicine. There is also an increasing emphasis on managing complexity with changing care models, processes, and settings.

US residential building air exchange rates: new perspectives to improve decision making at vapor intrusion sites.

PubMed

Reichman, Rivka; Shirazi, Elham; Colliver, Donald G; Pennell, Kelly G

2017-02-22

Vapor intrusion (VI) is well-known to be difficult to characterize because indoor air (IA) concentrations exhibit considerable temporal and spatial variability in homes throughout impacted communities. To overcome this and other limitations, most VI science has focused on subsurface processes; however there is a need to understand the role of aboveground processes, especially building operation, in the context of VI exposure risks. This tutorial review focuses on building air exchange rates (AERs) and provides a review of literature related building AERs to inform decision making at VI sites. Commonly referenced AER values used by VI regulators and practitioners do not account for the variability in AER values that have been published in indoor air quality studies. The information presented herein highlights that seasonal differences, short-term weather conditions, home age and air conditioning status, which are well known to influence AERs, are also likely to influence IA concentrations at VI sites. Results of a 3D VI model in combination with relevant AER values reveal that IA concentrations can vary more than one order of magnitude due to air conditioning status and one order of magnitude due to house age. Collectively, the data presented strongly support the need to consider AERs when making decisions at VI sites.

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.

EnergyIQ

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

MILLS, EVAN; MATTHE, PAUL; STOUFER, MARTIN

2016-10-06

EnergyIQ-the first "action-oriented" benchmarking tool for non-residential buildings-provides a standardized opportunity assessment based on benchmarking results. along with decision-support information to help refine action plans. EnergyIQ offers a wide array of benchmark metrics, with visuall as well as tabular display. These include energy, costs, greenhouse-gas emissions, and a large array of characteristics (e.g. building components or operational strategies). The tool supports cross-sectional benchmarking for comparing the user's building to it's peers at one point in time, as well as longitudinal benchmarking for tracking the performance of an individual building or enterprise portfolio over time. Based on user inputs, the toolmore » generates a list of opportunities and recommended actions. Users can then explore the "Decision Support" module for helpful information on how to refine action plans, create design-intent documentation, and implement improvements. This includes information on best practices, links to other energy analysis tools and more. The variety of databases are available within EnergyIQ from which users can specify peer groups for comparison. Using the tool, this data can be visually browsed and used as a backdrop against which to view a variety of energy benchmarking metrics for the user's own building. User can save their project information and return at a later date to continue their exploration. The initial database is the CA Commercial End-Use Survey (CEUS), which provides details on energy use and characteristics for about 2800 buildings (and 62 building types). CEUS is likely the most thorough survey of its kind every conducted. The tool is built as a web service. The EnergyIQ web application is written in JSP with pervasive us of JavaScript and CSS2. EnergyIQ also supports a SOAP based web service to allow the flow of queries and data to occur with non-browser implementations. Data are stored in an Oracle 10g database. References: Mills, Mathew, Brook and Piette. 2008. "Action Oriented Benchmarking: Concepts and Tools." Energy Engineering, Vol.105, No. 4, pp 21-40. LBNL-358E; Mathew, Mills, Bourassa, Brook. 2008. "Action-Oriented Benchmarking: Using the CEUS Database to Benchmark Commercial Buildings in California." Energy Engineering, Vol 105, No. 5, pp 6-18. LBNL-502E.« less

An Ontology of Therapies

NASA Astrophysics Data System (ADS)

Eccher, Claudio; Ferro, Antonella; Pisanelli, Domenico M.

Ontologies are the essential glue to build interoperable systems and the talk of the day in the medical community. In this paper we present the ontology of medical therapies developed in the course of the Oncocure project, aimed at building a guideline based decision support integrated with a legacy Electronic Patient Record (EPR). The therapy ontology is based upon the DOLCE top level ontology. It is our opinion that our ontology, besides constituting a model capturing the precise meaning of therapy-related concepts, can serve for several practical purposes: interfacing automatic support systems with a legacy EPR, allowing the automatic data analysis, and controlling possible medical errors made during EPR data input.

Decision Support System for Determining Scholarship Selection using an Analytical Hierarchy Process

NASA Astrophysics Data System (ADS)

Puspitasari, T. D.; Sari, E. O.; Destarianto, P.; Riskiawan, H. Y.

2018-01-01

Decision Support System is a computer program application that analyzes data and presents it so that users can make decision more easily. Determining Scholarship Selection study case in Senior High School in east Java wasn’t easy. It needed application to solve the problem, to improve the accuracy of targets for prospective beneficiaries of poor students and to speed up the screening process. This research will build system uses the method of Analytical Hierarchy Process (AHP) is a method that solves a complex and unstructured problem into its group, organizes the groups into a hierarchical order, inputs numerical values instead of human perception in comparing relative and ultimately with a synthesis determined elements that have the highest priority. The accuracy system for this research is 90%.

Building a Decision Support System for Inpatient Admission Prediction With the Manchester Triage System and Administrative Check-in Variables.

PubMed

Zlotnik, Alexander; Alfaro, Miguel Cuchí; Pérez, María Carmen Pérez; Gallardo-Antolín, Ascensión; Martínez, Juan Manuel Montero

2016-05-01

The usage of decision support tools in emergency departments, based on predictive models, capable of estimating the probability of admission for patients in the emergency department may give nursing staff the possibility of allocating resources in advance. We present a methodology for developing and building one such system for a large specialized care hospital using a logistic regression and an artificial neural network model using nine routinely collected variables available right at the end of the triage process.A database of 255.668 triaged nonobstetric emergency department presentations from the Ramon y Cajal University Hospital of Madrid, from January 2011 to December 2012, was used to develop and test the models, with 66% of the data used for derivation and 34% for validation, with an ordered nonrandom partition. On the validation dataset areas under the receiver operating characteristic curve were 0.8568 (95% confidence interval, 0.8508-0.8583) for the logistic regression model and 0.8575 (95% confidence interval, 0.8540-0. 8610) for the artificial neural network model. χ Values for Hosmer-Lemeshow fixed "deciles of risk" were 65.32 for the logistic regression model and 17.28 for the artificial neural network model. A nomogram was generated upon the logistic regression model and an automated software decision support system with a Web interface was built based on the artificial neural network model.

Building a Predictive Capability for Decision-Making that Supports MultiPEM

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

Carmichael, Joshua Daniel

Multi-phenomenological explosion monitoring (multiPEM) is a developing science that uses multiple geophysical signatures of explosions to better identify and characterize their sources. MultiPEM researchers seek to integrate explosion signatures together to provide stronger detection, parameter estimation, or screening capabilities between different sources or processes. This talk will address forming a predictive capability for screening waveform explosion signatures to support multiPEM.

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

Hunsberger, Randolph; Tomberlin, Gregg; Gaul, Chris

As part of the Army Net-Zero Energy Installation program, the Fort Carson Army Base requested that NREL evaluate the feasibility of adding a biomass boiler to the district heating system served by Building 1860. We have also developed an Excel-spreadsheet-based decision support tool--specific to the historic loads served by Building 1860--with which users can perform what-if analysis on gas costs, biomass costs, and other parameters. For economic reasons, we do not recommend adding a biomass system at this time.

Adequate Facilities for All: Reforming New York State's System for Providing Building Aid to School Districts and for Meeting Schools' Urgent Capital Needs. Part II. [Sound Basic Education Task Force Proposal

ERIC Educational Resources Information Center

Campaign for Fiscal Equity, Inc., 2004

2004-01-01

In recent years, court mandates in education adequacy cases have resulted in substantial increases in state-level support for local building needs in a number of states. The Court of Appeals' decision in "CFE v. State of New York" has made clear that extensive facilities deficiencies in New York City constitute a major constitutional…

How One Teacher Uses Student Records. Profiles/Dolly Lambdin.

ERIC Educational Resources Information Center

Locke, Lawrence F.; Dodds, Patt

1982-01-01

A physical education teacher has created a recordkeeping system which maintains a continuous record of each student's progress in fitness tests, basic motor skills, specific play skills, and interpersonal behavior. The system helps with student motivation, administration, decision making, and building parental support. (PP)

Empowering genomic medicine by establishing critical sequencing result data flows: the eMERGE example.

PubMed

Aronson, Samuel; Babb, Lawrence; Ames, Darren; Gibbs, Richard A; Venner, Eric; Connelly, John J; Marsolo, Keith; Weng, Chunhua; Williams, Marc S; Hartzler, Andrea L; Liang, Wayne H; Ralston, James D; Devine, Emily Beth; Murphy, Shawn; Chute, Christopher G; Caraballo, Pedro J; Kullo, Iftikhar J; Freimuth, Robert R; Rasmussen, Luke V; Wehbe, Firas H; Peterson, Josh F; Robinson, Jamie R; Wiley, Ken; Overby Taylor, Casey

2018-05-31

The eMERGE Network is establishing methods for electronic transmittal of patient genetic test results from laboratories to healthcare providers across organizational boundaries. We surveyed the capabilities and needs of different network participants, established a common transfer format, and implemented transfer mechanisms based on this format. The interfaces we created are examples of the connectivity that must be instantiated before electronic genetic and genomic clinical decision support can be effectively built at the point of care. This work serves as a case example for both standards bodies and other organizations working to build the infrastructure required to provide better electronic clinical decision support for clinicians.

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

PubMed

Jbilou, Jalila; Amara, Nabil; Landry, Réjean

2007-06-01

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

Cortical and Hippocampal Correlates of Deliberation during Model-Based Decisions for Rewards in Humans

PubMed Central

Bornstein, Aaron M.; Daw, Nathaniel D.

2013-01-01

How do we use our memories of the past to guide decisions we've never had to make before? Although extensive work describes how the brain learns to repeat rewarded actions, decisions can also be influenced by associations between stimuli or events not directly involving reward — such as when planning routes using a cognitive map or chess moves using predicted countermoves — and these sorts of associations are critical when deciding among novel options. This process is known as model-based decision making. While the learning of environmental relations that might support model-based decisions is well studied, and separately this sort of information has been inferred to impact decisions, there is little evidence concerning the full cycle by which such associations are acquired and drive choices. Of particular interest is whether decisions are directly supported by the same mnemonic systems characterized for relational learning more generally, or instead rely on other, specialized representations. Here, building on our previous work, which isolated dual representations underlying sequential predictive learning, we directly demonstrate that one such representation, encoded by the hippocampal memory system and adjacent cortical structures, supports goal-directed decisions. Using interleaved learning and decision tasks, we monitor predictive learning directly and also trace its influence on decisions for reward. We quantitatively compare the learning processes underlying multiple behavioral and fMRI observables using computational model fits. Across both tasks, a quantitatively consistent learning process explains reaction times, choices, and both expectation- and surprise-related neural activity. The same hippocampal and ventral stream regions engaged in anticipating stimuli during learning are also engaged in proportion to the difficulty of decisions. These results support a role for predictive associations learned by the hippocampal memory system to be recalled during choice formation. PMID:24339770

Information management to enable personalized medicine: stakeholder roles in building clinical decision support.

PubMed

Downing, Gregory J; Boyle, Scott N; Brinner, Kristin M; Osheroff, Jerome A

2009-10-08

Advances in technology and the scientific understanding of disease processes are presenting new opportunities to improve health through individualized approaches to patient management referred to as personalized medicine. Future health care strategies that deploy genomic technologies and molecular therapies will bring opportunities to prevent, predict, and pre-empt disease processes but will be dependent on knowledge management capabilities for health care providers that are not currently available. A key cornerstone to the potential application of this knowledge will be effective use of electronic health records. In particular, appropriate clinical use of genomic test results and molecularly-targeted therapies present important challenges in patient management that can be effectively addressed using electronic clinical decision support technologies. Approaches to shaping future health information needs for personalized medicine were undertaken by a work group of the American Health Information Community. A needs assessment for clinical decision support in electronic health record systems to support personalized medical practices was conducted to guide health future development activities. Further, a suggested action plan was developed for government, researchers and research institutions, developers of electronic information tools (including clinical guidelines, and quality measures), and standards development organizations to meet the needs for personalized approaches to medical practice. In this article, we focus these activities on stakeholder organizations as an operational framework to help identify and coordinate needs and opportunities for clinical decision support tools to enable personalized medicine. This perspective addresses conceptual approaches that can be undertaken to develop and apply clinical decision support in electronic health record systems to achieve personalized medical care. In addition, to represent meaningful benefits to personalized decision-making, a comparison of current and future applications of clinical decision support to enable individualized medical treatment plans is presented. If clinical decision support tools are to impact outcomes in a clear and positive manner, their development and deployment must therefore consider the needs of the providers, including specific practice needs, information workflow, and practice environment.

Information management to enable personalized medicine: stakeholder roles in building clinical decision support

PubMed Central

2009-01-01

Background Advances in technology and the scientific understanding of disease processes are presenting new opportunities to improve health through individualized approaches to patient management referred to as personalized medicine. Future health care strategies that deploy genomic technologies and molecular therapies will bring opportunities to prevent, predict, and pre-empt disease processes but will be dependent on knowledge management capabilities for health care providers that are not currently available. A key cornerstone to the potential application of this knowledge will be effective use of electronic health records. In particular, appropriate clinical use of genomic test results and molecularly-targeted therapies present important challenges in patient management that can be effectively addressed using electronic clinical decision support technologies. Discussion Approaches to shaping future health information needs for personalized medicine were undertaken by a work group of the American Health Information Community. A needs assessment for clinical decision support in electronic health record systems to support personalized medical practices was conducted to guide health future development activities. Further, a suggested action plan was developed for government, researchers and research institutions, developers of electronic information tools (including clinical guidelines, and quality measures), and standards development organizations to meet the needs for personalized approaches to medical practice. In this article, we focus these activities on stakeholder organizations as an operational framework to help identify and coordinate needs and opportunities for clinical decision support tools to enable personalized medicine. Summary This perspective addresses conceptual approaches that can be undertaken to develop and apply clinical decision support in electronic health record systems to achieve personalized medical care. In addition, to represent meaningful benefits to personalized decision-making, a comparison of current and future applications of clinical decision support to enable individualized medical treatment plans is presented. If clinical decision support tools are to impact outcomes in a clear and positive manner, their development and deployment must therefore consider the needs of the providers, including specific practice needs, information workflow, and practice environment. PMID:19814826

Review of retrofit strategies decision system in historic perspective

NASA Astrophysics Data System (ADS)

Bostenaru Dan, M. D.

2004-06-01

Urban development is a process. In structuring and developing its phases different actors are implied, who act under different, sometimes opposite, dynamic conditions and within different reference systems. This paper aims to explore the contribution of participatism to disaster mitigation, when this concerns earthquake impact on urban settlements, through the support provided to multi-criteria decision in matters of retrofit. The research broadness in field of decision making on one side and the lack of a specific model for the retrofit of existing buildings on another side led to an extensive review of the state of the art in related models to address the issue. Core idea in the selection of existing models has been the preoccupation for collaborative issues, in other words, the consideration for the different actors implied in the planning process. The historic perspective on participative planning models is made from the view of two generations of citizen implication. The first approaches focus on the participation of the building owner/inhabitant in the planning process of building construction. As current strategies building rehabilitation and selection from alternative retrofit strategies are presented. New developments include innovative models using the internet or spatial databases. The investigated participation approaches show, that participation and communication as a more comprehensive term are an old topic in the field politics-democratisation-urbanism. In all cases it can be talked of "successful learning processes", of the improvement of the level of the professional debate. More than 30 years history of participation marked a transition in understanding the concept: from participation, based on a central decision process leading to a solution controlled and steered by the political-administrative system, to communication, characterised by simultaneous decision processes taking place outside politics and administration in co-operative procedures.

Decisional needs assessment of patients with complex care needs in primary care: a participatory systematic mixed studies review protocol

PubMed Central

Pluye, Pierre; Légaré, France; Haggerty, Jeannie; Gore, Genevieve C; Sherif, Reem El; Poitras, Marie-Ève; Beaulieu, Marie-Claude; Beaulieu, Marie-Dominique; Bush, Paula L; Couturier, Yves; Débarges, Béatrice; Gagnon, Justin; Giguère, Anik; Grad, Roland; Granikov, Vera; Goulet, Serge; Hudon, Catherine; Kremer, Bernardo; Kröger, Edeltraut; Kudrina, Irina; Lebouché, Bertrand; Loignon, Christine; Lussier, Marie-Thérèse; Martello, Cristiano; Nguyen, Quynh; Pratt, Rebekah; Rihoux, Benoit; Rosenberg, Ellen; Samson, Isabelle; Senn, Nicolas; Li Tang, David; Tsujimoto, Masashi; Vedel, Isabelle; Ventelou, Bruno; Wensing, Michel; Bigras, Magali

2017-01-01

Introduction Patients with complex care needs (PCCNs) often suffer from combinations of multiple chronic conditions, mental health problems, drug interactions and social vulnerability, which can lead to healthcare services overuse, underuse or misuse. Typically, PCCNs face interactional issues and unmet decisional needs regarding possible options in a cascade of interrelated decisions involving different stakeholders (themselves, their families, their caregivers, their healthcare practitioners). Gaps in knowledge, values clarification and social support in situations where options need to be deliberated hamper effective decision support interventions. This review aims to (1) assess decisional needs of PCCNs from the perspective of stakeholders, (2) build a taxonomy of these decisional needs and (3) prioritise decisional needs with knowledge users (clinicians, patients and managers). Methods and analysis This review will be based on the interprofessional shared decision making (IP-SDM) model and the Ottawa Decision Support Framework. Applying a participatory research approach, we will identify potentially relevant studies through a comprehensive literature search; select relevant ones using eligibility criteria inspired from our previous scoping review on PCCNs; appraise quality using the Mixed Methods Appraisal Tool; conduct a three-step synthesis (sequential exploratory mixed methods design) to build taxonomy of key decisional needs; and integrate these results with those of a parallel PCCNs’ qualitative decisional need assessment (semistructured interviews and focus group with stakeholders). Ethics and dissemination This systematic review, together with the qualitative study (approved by the Centre Intégré Universitaire de Santé et Service Sociaux du Saguenay-Lac-Saint-Jean ethical committee), will produce a working taxonomy of key decisional needs (ontological contribution), to inform the subsequent user-centred design of a support tool for addressing PCCNs’ decisional needs (practical contribution). We will adapt the IP-SDM model, normally dealing with a single decision, for PCCNs who experience cascade of decisions involving different stakeholders (theoretical contribution). Knowledge users will facilitate dissemination of the results in the Canadian primary care network. PROSPERO registration number CRD42015020558. PMID:29133314

Decisional needs assessment of patients with complex care needs in primary care: a participatory systematic mixed studies review protocol.

PubMed

Bujold, Mathieu; Pluye, Pierre; Légaré, France; Haggerty, Jeannie; Gore, Genevieve C; Sherif, Reem El; Poitras, Marie-Eve; Beaulieu, Marie-Claude; Beaulieu, Marie-Dominique; Bush, Paula L; Couturier, Yves; Débarges, Beatrice; Gagnon, Justin; Giguère, Anik; Grad, Roland; Granikov, Vera; Goulet, Serge; Hudon, Catherine; Kremer, Bernardo; Kröger, Edeltraut; Kudrina, Irina; Lebouché, Bertrand; Loignon, Christine; Lussier, Marie-Therese; Martello, Cristiano; Nguyen, Quynh; Pratt, Rebekah; Rihoux, Benoit; Rosenberg, Ellen; Samson, Isabelle; Senn, Nicolas; Li Tang, David; Tsujimoto, Masashi; Vedel, Isabelle; Ventelou, Bruno; Wensing, Michel

2017-11-12

Patients with complex care needs (PCCNs) often suffer from combinations of multiple chronic conditions, mental health problems, drug interactions and social vulnerability, which can lead to healthcare services overuse, underuse or misuse. Typically, PCCNs face interactional issues and unmet decisional needs regarding possible options in a cascade of interrelated decisions involving different stakeholders (themselves, their families, their caregivers, their healthcare practitioners). Gaps in knowledge, values clarification and social support in situations where options need to be deliberated hamper effective decision support interventions. This review aims to (1) assess decisional needs of PCCNs from the perspective of stakeholders, (2) build a taxonomy of these decisional needs and (3) prioritise decisional needs with knowledge users (clinicians, patients and managers). This review will be based on the interprofessional shared decision making (IP-SDM) model and the Ottawa Decision Support Framework. Applying a participatory research approach, we will identify potentially relevant studies through a comprehensive literature search; select relevant ones using eligibility criteria inspired from our previous scoping review on PCCNs; appraise quality using the Mixed Methods Appraisal Tool; conduct a three-step synthesis (sequential exploratory mixed methods design) to build taxonomy of key decisional needs; and integrate these results with those of a parallel PCCNs' qualitative decisional need assessment (semistructured interviews and focus group with stakeholders). This systematic review, together with the qualitative study (approved by the Centre Intégré Universitaire de Santé et Service Sociaux du Saguenay-Lac-Saint-Jean ethical committee), will produce a working taxonomy of key decisional needs (ontological contribution), to inform the subsequent user-centred design of a support tool for addressing PCCNs' decisional needs (practical contribution). We will adapt the IP-SDM model, normally dealing with a single decision, for PCCNs who experience cascade of decisions involving different stakeholders (theoretical contribution). Knowledge users will facilitate dissemination of the results in the Canadian primary care network. CRD42015020558. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Requirements, model and prototype for a multi-utility locational and security information hub.

DOT National Transportation Integrated Search

2015-11-01

This project lays the foundation for building an exchange hub for locational and security data and risk assessment of potential excavation work. It acts primarily at 2 stages: upstream of the mark-out process, as a decision support tool to help strea...

78 FR 69839 - Building Technologies Office Prioritization Tool

Federal Register 2010, 2011, 2012, 2013, 2014

2013-11-21

... innovative and cost-effective energy saving solutions: Supporting research and development of high impact... Description The tool was designed to inform programmatic decision-making and facilitate the setting of... quantitative analysis to assure only the highest impact measures are the focus of further effort. The approach...

Constructive systems, load-bearing and enclosing structures of high-rise buildings

NASA Astrophysics Data System (ADS)

Anatol'evna Korol', Elena; Olegovna Kustikova, Yuliya

2018-03-01

As the height of the building increases, loads on load-carrying structures increase dramatically, and as a result of the development of high-rise construction, several structural systems of such buildings have been developed: frame, frame-frame, cross-wall, barrel, box-type, box-to-wall ("pipe in pipe", "Trumpet in the farm"), etc. In turn, the barrel systems have their own versions: cantilever support of the ceilings on the trunk, suspension of the outer part of the overlap to the upper carrying console "hanging house" or its support by means of the walls on the lower bearing cantilever, intermediate position of the supporting cantilevers in height to the floor, from a part of floors. The object of the study are the structural solutions of high-rise buildings. The subject of the study is the layout of structural schemes of high-rise buildings, taking into account the main parameters - altitude (height), natural climatic conditions of construction, materials of structural elements and their physical and mechanical characteristics. The purpose of the study is to identify the features and systematization of structural systems of high-rise buildings and the corresponding structural elements. The results of the research make it possible, at the stage of making design decisions, to establish rational parameters for the correspondence between the structural systems of high-rise buildings and their individual elements.

Longitudinal Data Systems to Support Data-Informed Decision Making: A Tri-State Partnership between Michigan, Minnesota, and Wisconsin. WCER Working Paper No. 2006-1

ERIC Educational Resources Information Center

Thorn, Christopher A.; Meyer, Robert H.

2006-01-01

The U.S. Department of Education recently held a competition for grants to support states in their efforts to build longitudinal data systems to track and analyze student and school performance. The Value-Added Research Center (VARC) at the Wisconsin Center for Education Research, University of Wisconsin-Madison, proposed a Tri-State Partnership…

What supports do health system organizations have in place to facilitate evidence-informed decision-making? a qualitative study

PubMed Central

2013-01-01

Background Decisions regarding health systems are sometimes made without the input of timely and reliable evidence, leading to less than optimal health outcomes. Healthcare organizations can implement tools and infrastructures to support the use of research evidence to inform decision-making. Objectives The purpose of this study was to profile the supports and instruments (i.e., programs, interventions, instruments or tools) that healthcare organizations currently have in place and which ones were perceived to facilitate evidence-informed decision-making. Methods In-depth semi-structured telephone interviews were conducted with individuals in three different types of positions (i.e., a senior management team member, a library manager, and a ‘knowledge broker’) in three types of healthcare organizations (i.e., regional health authorities, hospitals and primary care practices) in two Canadian provinces (i.e., Ontario and Quebec). The interviews were taped, transcribed, and then analyzed thematically using NVivo 9 qualitative data analysis software. Results A total of 57 interviews were conducted in 25 organizations in Ontario and Quebec. The main findings suggest that, for the healthcare organizations that participated in this study, the following supports facilitate evidence-informed decision-making: facilitating roles that actively promote research use within the organization; establishing ties to researchers and opinion leaders outside the organization; a technical infrastructure that provides access to research evidence, such as databases; and provision and participation in training programs to enhance staff’s capacity building. Conclusions This study identified the need for having a receptive climate, which laid the foundation for the implementation of other tangible initiatives and supported the use of research in decision-making. This study adds to the literature on organizational efforts that can increase the use of research evidence in decision-making. Some of the identified supports may increase the use of research evidence by decision-makers, which may then lead to more informed decisions, and hopefully to a strengthened health system and improved health. PMID:23915278

What supports do health system organizations have in place to facilitate evidence-informed decision-making? A qualitative study.

PubMed

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

2013-08-06

Decisions regarding health systems are sometimes made without the input of timely and reliable evidence, leading to less than optimal health outcomes. Healthcare organizations can implement tools and infrastructures to support the use of research evidence to inform decision-making. The purpose of this study was to profile the supports and instruments (i.e., programs, interventions, instruments or tools) that healthcare organizations currently have in place and which ones were perceived to facilitate evidence-informed decision-making. In-depth semi-structured telephone interviews were conducted with individuals in three different types of positions (i.e., a senior management team member, a library manager, and a 'knowledge broker') in three types of healthcare organizations (i.e., regional health authorities, hospitals and primary care practices) in two Canadian provinces (i.e., Ontario and Quebec). The interviews were taped, transcribed, and then analyzed thematically using NVivo 9 qualitative data analysis software. A total of 57 interviews were conducted in 25 organizations in Ontario and Quebec. The main findings suggest that, for the healthcare organizations that participated in this study, the following supports facilitate evidence-informed decision-making: facilitating roles that actively promote research use within the organization; establishing ties to researchers and opinion leaders outside the organization; a technical infrastructure that provides access to research evidence, such as databases; and provision and participation in training programs to enhance staff's capacity building. This study identified the need for having a receptive climate, which laid the foundation for the implementation of other tangible initiatives and supported the use of research in decision-making. This study adds to the literature on organizational efforts that can increase the use of research evidence in decision-making. Some of the identified supports may increase the use of research evidence by decision-makers, which may then lead to more informed decisions, and hopefully to a strengthened health system and improved health.

Utilization of a Multi-Disciplinary Approach to Building Effective Command Centers: Process and Products

DTIC Science & Technology

2005-06-01

cognitive task analysis , organizational information dissemination and interaction, systems engineering, collaboration and communications processes, decision-making processes, and data collection and organization. By blending these diverse disciplines command centers can be designed to support decision-making, cognitive analysis, information technology, and the human factors engineering aspects of Command and Control (C2). This model can then be used as a baseline when dealing with work in areas of business processes, workflow engineering, information management,

A Decision Support System for Planning, Control and Auditing of DoD Software Cost Estimation.

DTIC Science & Technology

1986-03-01

is frequently used in U. S. Air Force software cost estimates. Barry Boehm’s Constructive Cost Estimation Model (COCOMO) was recently selected for use...are considered basic to the proper development of software. Pressman , [Ref. 11], addresses these basic elements in a manner which attempts to integrate...H., Jr., and Carlson, Eric D., Building E fective Decision SUDDOrt Systems, Prentice-Hal, EnglewoodNJ, 1982 11. Pressman , Roger S., o A Practioner’s A

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Building a model-based decision support system for solving vehicle routing and driver scheduling problems under hours of service regulations.

DOT National Transportation Integrated Search

2011-08-27

"In principle, hours-of-service (HOS) regulations are intended to help truck drivers ensure get adequate rest and perform safe operations. The new HOS regulations, however, may lead to substantial cost increases for regional common carriers which hav...

Growing Student Voice in Curriculum Decisions at the University

ERIC Educational Resources Information Center

Rojas Pernia, Susana; Haya Salmón, Ignacio; Susinos Rada, Teresa

2016-01-01

This paper is a result of the development of the R+D Project "Schools that are moving towards inclusive education: working with the local community, the student voice and educational support for promoting change" in conjunction with the Innovation Project "Building Bridges. An Educational Innovation Project in the European Higher…

Strategic Capacity and Organisational Capabilities: A Challenge for Universities

ERIC Educational Resources Information Center

Thoenig, Jean-Claude; Paradeise, Catherine

2016-01-01

Are universities able to operate as strategic actors? An organisational sociology based approach supported by a comparative field research project identifies three types of social, cultural and cognitive processes that play a decisive role in building and implementing local capabilities required to mobilise a strategic capacity. The paper…

A web-based Decision Support System for the optimal management of construction and demolition waste.

PubMed

Banias, G; Achillas, Ch; Vlachokostas, Ch; Moussiopoulos, N; Papaioannou, I

2011-12-01

Wastes from construction activities constitute nowadays the largest by quantity fraction of solid wastes in urban areas. In addition, it is widely accepted that the particular waste stream contains hazardous materials, such as insulating materials, plastic frames of doors, windows, etc. Their uncontrolled disposal result to long-term pollution costs, resource overuse and wasted energy. Within the framework of the DEWAM project, a web-based Decision Support System (DSS) application - namely DeconRCM - has been developed, aiming towards the identification of the optimal construction and demolition waste (CDW) management strategy that minimises end-of-life costs and maximises the recovery of salvaged building materials. This paper addresses both technical and functional structure of the developed web-based application. The web-based DSS provides an accurate estimation of the generated CDW quantities of twenty-one different waste streams (e.g. concrete, bricks, glass, etc.) for four different types of buildings (residential, office, commercial and industrial). With the use of mathematical programming, the DeconRCM provides also the user with the optimal end-of-life management alternative, taking into consideration both economic and environmental criteria. The DSS's capabilities are illustrated through a real world case study of a typical five floor apartment building in Thessaloniki, Greece. Copyright © 2011 Elsevier Ltd. All rights reserved.

Optimizing Distributed Energy Resources and building retrofits with the strategic DER-CAModel

DOE PAGES

Stadler, M.; Groissböck, M.; Cardoso, G.; ...

2014-08-05

The pressuring need to reduce the import of fossil fuels as well as the need to dramatically reduce CO 2 emissions in Europe motivated the European Commission (EC) to implement several regulations directed to building owners. Most of these regulations focus on increasing the number of energy efficient buildings, both new and retrofitted, since retrofits play an important role in energy efficiency. Overall, this initiative results from the realization that buildings will have a significant impact in fulfilling the 20/20/20-goals of reducing the greenhouse gas emissions by 20%, increasing energy efficiency by 20%, and increasing the share of renewables tomore » 20%, all by 2020. The Distributed Energy Resources Customer Adoption Model (DER-CAM) is an optimization tool used to support DER investment decisions, typically by minimizing total annual costs or CO 2 emissions while providing energy services to a given building or microgrid site. This document shows enhancements made to DER-CAM to consider building retrofit measures along with DER investment options. Specifically, building shell improvement options have been added to DER-CAM as alternative or complementary options to investments in other DER such as PV, solar thermal, combined heat and power, or energy storage. The extension of the mathematical formulation required by the new features introduced in DER-CAM is presented and the resulting model is demonstrated at an Austrian Campus building by comparing DER-CAM results with and without building shell improvement options. Strategic investment results are presented and compared to the observed investment decision at the test site. Results obtained considering building shell improvement options suggest an optimal weighted average U value of about 0.53 W/(m 2K) for the test site. This result is approximately 25% higher than what is currently observed in the building, suggesting that the retrofits made in 2002 were not optimal. Furthermore, the results obtained with DER-CAM illustrate the complexity of interactions between DER and passive measure options, showcasing the need for a holistic optimization approach to effectively optimize energy costs and CO 2 emissions. Lastly, the simultaneous optimization of building shell improvements and DER investments enables building owners to take one step further towards nearly zero energy buildings (nZEB) or nearly zero carbon emission buildings (nZCEB), and therefore support the 20/20/20 goals.« less

Optimizing Distributed Energy Resources and building retrofits with the strategic DER-CAModel

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

Stadler, M.; Groissböck, M.; Cardoso, G.

The pressuring need to reduce the import of fossil fuels as well as the need to dramatically reduce CO 2 emissions in Europe motivated the European Commission (EC) to implement several regulations directed to building owners. Most of these regulations focus on increasing the number of energy efficient buildings, both new and retrofitted, since retrofits play an important role in energy efficiency. Overall, this initiative results from the realization that buildings will have a significant impact in fulfilling the 20/20/20-goals of reducing the greenhouse gas emissions by 20%, increasing energy efficiency by 20%, and increasing the share of renewables tomore » 20%, all by 2020. The Distributed Energy Resources Customer Adoption Model (DER-CAM) is an optimization tool used to support DER investment decisions, typically by minimizing total annual costs or CO 2 emissions while providing energy services to a given building or microgrid site. This document shows enhancements made to DER-CAM to consider building retrofit measures along with DER investment options. Specifically, building shell improvement options have been added to DER-CAM as alternative or complementary options to investments in other DER such as PV, solar thermal, combined heat and power, or energy storage. The extension of the mathematical formulation required by the new features introduced in DER-CAM is presented and the resulting model is demonstrated at an Austrian Campus building by comparing DER-CAM results with and without building shell improvement options. Strategic investment results are presented and compared to the observed investment decision at the test site. Results obtained considering building shell improvement options suggest an optimal weighted average U value of about 0.53 W/(m 2K) for the test site. This result is approximately 25% higher than what is currently observed in the building, suggesting that the retrofits made in 2002 were not optimal. Furthermore, the results obtained with DER-CAM illustrate the complexity of interactions between DER and passive measure options, showcasing the need for a holistic optimization approach to effectively optimize energy costs and CO 2 emissions. Lastly, the simultaneous optimization of building shell improvements and DER investments enables building owners to take one step further towards nearly zero energy buildings (nZEB) or nearly zero carbon emission buildings (nZCEB), and therefore support the 20/20/20 goals.« less

Supporting Building Portfolio Investment and Policy Decision Making through an Integrated Building Utility Data Platform

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

Aziz, Azizan; Lasternas, Bertrand; Alschuler, Elena

The American Recovery and Reinvestment Act stimulus funding of 2009 for smart grid projects resulted in the tripling of smart meters deployment. In 2012, the Green Button initiative provided utility customers with access to their real-time1 energy usage. The availability of finely granular data provides an enormous potential for energy data analytics and energy benchmarking. The sheer volume of time-series utility data from a large number of buildings also poses challenges in data collection, quality control, and database management for rigorous and meaningful analyses. In this paper, we will describe a building portfolio-level data analytics tool for operational optimization, businessmore » investment and policy assessment using 15-minute to monthly intervals utility data. The analytics tool is developed on top of the U.S. Department of Energy’s Standard Energy Efficiency Data (SEED) platform, an open source software application that manages energy performance data of large groups of buildings. To support the significantly large volume of granular interval data, we integrated a parallel time-series database to the existing relational database. The time-series database improves on the current utility data input, focusing on real-time data collection, storage, analytics and data quality control. The fully integrated data platform supports APIs for utility apps development by third party software developers. These apps will provide actionable intelligence for building owners and facilities managers. Unlike a commercial system, this platform is an open source platform funded by the U.S. Government, accessible to the public, researchers and other developers, to support initiatives in reducing building energy consumption.« less

Next generation capacity building for the GEOSS community - an European approach

NASA Astrophysics Data System (ADS)

Bye, B. L.

2016-12-01

The Group on Earth observation embarked on the next 10 year phase with an ambition to streamline and futher develop its achievements in building the Global Earth Observing System of Systems (GEOSS). The NextGEOSS project evolves the European vision of GEOSS data exploitation for innovation and business, relying on the three main pillars of engaging communities, delivering technological developments and advocating the use of GEOSS, in order to support the creation and deployment of Earth observation based innovative research activities and commercial services. In this presentation we will present the new integrated approach to capacity building engaging the various actors involved in the entire value-chain from data providers to decision-makers. A presentation of the general approach together with concrete pilot cases will be included.In this work it will be shown how we integrate new technological development and societial change enabling GEO and GEOSS to adapt to the current environment. The result is important for better decision-making and better use of our limited resources to manage our planet.

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

PubMed

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

2017-01-01

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

Ontology-based configuration of problem-solving methods and generation of knowledge-acquisition tools: application of PROTEGE-II to protocol-based decision support.

PubMed

Tu, S W; Eriksson, H; Gennari, J H; Shahar, Y; Musen, M A

1995-06-01

PROTEGE-II is a suite of tools and a methodology for building knowledge-based systems and domain-specific knowledge-acquisition tools. In this paper, we show how PROTEGE-II can be applied to the task of providing protocol-based decision support in the domain of treating HIV-infected patients. To apply PROTEGE-II, (1) we construct a decomposable problem-solving method called episodic skeletal-plan refinement, (2) we build an application ontology that consists of the terms and relations in the domain, and of method-specific distinctions not already captured in the domain terms, and (3) we specify mapping relations that link terms from the application ontology to the domain-independent terms used in the problem-solving method. From the application ontology, we automatically generate a domain-specific knowledge-acquisition tool that is custom-tailored for the application. The knowledge-acquisition tool is used for the creation and maintenance of domain knowledge used by the problem-solving method. The general goal of the PROTEGE-II approach is to produce systems and components that are reusable and easily maintained. This is the rationale for constructing ontologies and problem-solving methods that can be composed from a set of smaller-grained methods and mechanisms. This is also why we tightly couple the knowledge-acquisition tools to the application ontology that specifies the domain terms used in the problem-solving systems. Although our evaluation is still preliminary, for the application task of providing protocol-based decision support, we show that these goals of reusability and easy maintenance can be achieved. We discuss design decisions and the tradeoffs that have to be made in the development of the system.

41 CFR 102-74.520 - How much time does the Regional Officer have to affirm or reverse the Federal agency buildings...

Code of Federal Regulations, 2010 CFR

2010-07-01

... Regional Officer have to affirm or reverse the Federal agency buildings manager's decision after receiving... buildings manager's decision after receiving the notification of appeal from the affected person or organization? The Regional Officer must affirm or reverse the Federal agency buildings manager's decision...

A text-based data mining and toxicity prediction modeling system for a clinical decision support in radiation oncology: A preliminary study

NASA Astrophysics Data System (ADS)

Kim, Kwang Hyeon; Lee, Suk; Shim, Jang Bo; Chang, Kyung Hwan; Yang, Dae Sik; Yoon, Won Sup; Park, Young Je; Kim, Chul Yong; Cao, Yuan Jie

2017-08-01

The aim of this study is an integrated research for text-based data mining and toxicity prediction modeling system for clinical decision support system based on big data in radiation oncology as a preliminary research. The structured and unstructured data were prepared by treatment plans and the unstructured data were extracted by dose-volume data image pattern recognition of prostate cancer for research articles crawling through the internet. We modeled an artificial neural network to build a predictor model system for toxicity prediction of organs at risk. We used a text-based data mining approach to build the artificial neural network model for bladder and rectum complication predictions. The pattern recognition method was used to mine the unstructured toxicity data for dose-volume at the detection accuracy of 97.9%. The confusion matrix and training model of the neural network were achieved with 50 modeled plans (n = 50) for validation. The toxicity level was analyzed and the risk factors for 25% bladder, 50% bladder, 20% rectum, and 50% rectum were calculated by the artificial neural network algorithm. As a result, 32 plans could cause complication but 18 plans were designed as non-complication among 50 modeled plans. We integrated data mining and a toxicity modeling method for toxicity prediction using prostate cancer cases. It is shown that a preprocessing analysis using text-based data mining and prediction modeling can be expanded to personalized patient treatment decision support based on big data.

Big data analytics in the building industry

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

Berger, Michael A.; Mathew, Paul A.; Walter, Travis

Catalyzed by recent market, technology, and policy trends, energy data collection in the building industry is becoming more widespread. This wealth of information allows more data-driven decision-making by designers, commissioning agents, facilities staff, and energy service providers during the course of building design, operation and retrofit. The U.S. Department of Energy’s Building Performance Database (BPD) has taken advantage of this wealth of building asset- and energy-related data by collecting, cleansing, and standardizing data from across the U.S. on over 870,00 buildings, and is designed to support building benchmarking, energy efficiency project design, and buildings-related policy development with real-world data. Here,more » this article explores the promises and perils energy professionals are faced with when leveraging such tools, presenting example analyses for commercial and residential buildings, highlighting potential issues, and discussing solutions and best practices that will enable designers, operators and commissioning agents to make the most of ‘big data’ resources such as the BPD.« less

Big data analytics in the building industry

DOE PAGES

Berger, Michael A.; Mathew, Paul A.; Walter, Travis

2016-07-01

Catalyzed by recent market, technology, and policy trends, energy data collection in the building industry is becoming more widespread. This wealth of information allows more data-driven decision-making by designers, commissioning agents, facilities staff, and energy service providers during the course of building design, operation and retrofit. The U.S. Department of Energy’s Building Performance Database (BPD) has taken advantage of this wealth of building asset- and energy-related data by collecting, cleansing, and standardizing data from across the U.S. on over 870,00 buildings, and is designed to support building benchmarking, energy efficiency project design, and buildings-related policy development with real-world data. Here,more » this article explores the promises and perils energy professionals are faced with when leveraging such tools, presenting example analyses for commercial and residential buildings, highlighting potential issues, and discussing solutions and best practices that will enable designers, operators and commissioning agents to make the most of ‘big data’ resources such as the BPD.« less

Decision Support Model for Mosque Renovation and Rehabilitation (Case Study: Ten Mosques in Jakarta Barat, Indonesia)

NASA Astrophysics Data System (ADS)

Utama, D. N.; Triana, Y. S.; Iqbal, M. M.; Iksal, M.; Fikri, I.; Dharmawan, T.

2018-03-01

Mosque, for Muslim, is not only a place for daily worshipping, however as a center of culture as well. It is an important and valuable building to be well managed. For a responsible department or institution (such as Religion or Plan Department in Indonesia), to practically manage a lot of mosques is not simple task to handle. The challenge is in relation to data number and characteristic problems tackled. Specifically for renovating and rehabilitating the damaged mosques, a decision to determine the first damaged mosque priority to be renovated and rehabilitated is problematic. Through two types of optimization method, simulated-annealing and hill-climbing, a decision support model for mosque renovation and rehabilitation was systematically constructed. The method fuzzy-logic was also operated to establish the priority of eleven selected parameters. The constructed model is able to simulate an efficiency comparison between two optimization methods used and suggest the most objective decision coming from 196 generated alternatives.

Implementation of a scalable, web-based, automated clinical decision support risk-prediction tool for chronic kidney disease using C-CDA and application programming interfaces.

PubMed

Samal, Lipika; D'Amore, John D; Bates, David W; Wright, Adam

2017-11-01

Clinical decision support tools for risk prediction are readily available, but typically require workflow interruptions and manual data entry so are rarely used. Due to new data interoperability standards for electronic health records (EHRs), other options are available. As a clinical case study, we sought to build a scalable, web-based system that would automate calculation of kidney failure risk and display clinical decision support to users in primary care practices. We developed a single-page application, web server, database, and application programming interface to calculate and display kidney failure risk. Data were extracted from the EHR using the Consolidated Clinical Document Architecture interoperability standard for Continuity of Care Documents (CCDs). EHR users were presented with a noninterruptive alert on the patient's summary screen and a hyperlink to details and recommendations provided through a web application. Clinic schedules and CCDs were retrieved using existing application programming interfaces to the EHR, and we provided a clinical decision support hyperlink to the EHR as a service. We debugged a series of terminology and technical issues. The application was validated with data from 255 patients and subsequently deployed to 10 primary care clinics where, over the course of 1 year, 569 533 CCD documents were processed. We validated the use of interoperable documents and open-source components to develop a low-cost tool for automated clinical decision support. Since Consolidated Clinical Document Architecture-based data extraction extends to any certified EHR, this demonstrates a successful modular approach to clinical decision support. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association.

Multi-Sector Sustainability Browser (MSSB) User Manual: A ...

EPA Pesticide Factsheets

EPA’s Sustainable and Healthy Communities (SHC) Research Program is developing methodologies, resources, and tools to assist community members and local decision makers in implementing policy choices that facilitate sustainable approaches in managing their resources affecting the built environment, natural environment, and human health. In order to assist communities and decision makers in implementing sustainable practices, EPA is developing computer-based systems including models, databases, web tools, and web browsers to help communities decide upon approaches that support their desired outcomes. Communities need access to resources that will allow them to achieve their sustainability objectives through intelligent decisions in four key sustainability areas: • Land Use • Buildings and Infrastructure • Transportation • Materials Management (i.e., Municipal Solid Waste [MSW] processing and disposal) The Multi-Sector Sustainability Browser (MSSB) is designed to support sustainable decision-making for communities, local and regional planners, and policy and decision makers. Document is an EPA Technical Report, which is the user manual for the Multi-Sector Sustainability Browser (MSSB) tool. The purpose of the document is to provide basic guidance on use of the tool for users

Benefit-Risk Analysis for Decision-Making: An Approach.

PubMed

Raju, G K; Gurumurthi, K; Domike, R

2016-12-01

The analysis of benefit and risk is an important aspect of decision-making throughout the drug lifecycle. In this work, the use of a benefit-risk analysis approach to support decision-making was explored. The proposed approach builds on the qualitative US Food and Drug Administration (FDA) approach to include a more explicit analysis based on international standards and guidance that enables aggregation and comparison of benefit and risk on a common basis and a lifecycle focus. The approach is demonstrated on six decisions over the lifecycle (e.g., accelerated approval, withdrawal, and traditional approval) using two case studies: natalizumab for multiple sclerosis (MS) and bedaquiline for multidrug-resistant tuberculosis (MDR-TB). © 2016 American Society for Clinical Pharmacology and Therapeutics.

DOE Voluntary Partnership Program with Utilities and Local Governments Supports the Design of New Data Access Solutions

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

Shah, Monisha; Burr, Andrew; Schulte, Andrew

2016-08-26

The Better Buildings Energy Data Accelerator (BBEDA) is a unique effort that has supported 22 pairs of local governments and their utility companies to help building owners gain access to their whole-building energy data. Municipal and Utility BBEDA Partners committed to develop streamlined and easy-to-use solutions to provide whole-building energy data, especially for multitenant commercial buildings, by the end of 2015. As a result, building owners would be able to make data-driven decisions about their buildings by utilizing readily available energy consumption data for entire buildings. Traditionally, data access was difficult to implement due to technical barriers and the lackmore » of clear value propositions for the utilities. During the past two years, BBEDA has taken a hands-on approach to overcome these barriers by offering a platform for the partners to discuss their challenges and solutions. Customized support was also provided to Partners building their local strategies. Based on the lessons learned from the partners, BBEDA developed a final toolkit with guiding documents that addressed key barriers and served as a resource for the other cities and utilities attempting to establish whole-building data access, including an exploration of opportunities to apply the whole-building data to various aspects of utility demand-side management (DSM) programs. BBEDA has been a catalyst for market transformation by addressing the upstream (to efficiency implementation) barrier of data access, demonstrated through the success of the BBEDA partners to address policy, engagement, and technical hurdles and arrive at replicable solutions to make data access a standard practice nationwide. As a result of best practices identified by the BBEDA, 18 utilities serving more than 2.6 million commercial customers nationwide will provide whole-building energy data access to building owners by 2017. This historic expansion of data accessibility will increase building energy benchmarking, the first step many building owners take to improve the energy efficiency of their buildings.« less

Participatory health impact assessment used to support decision-making in waste management planning: A replicable experience from Italy.

PubMed

Linzalone, Nunzia; Coi, Alessio; Lauriola, Paolo; Luise, Daniela; Pedone, Alessandra; Romizi, Roberto; Sallese, Domenico; Bianchi, Fabrizio

2017-01-01

The lack of participatory tools in Health Impact Assessment (HIA) to support decision-makers is a critical factor that negatively affects the impacts of waste policies. This study describes the participatory HIA used in deciding on the possible doubling of the municipal solid waste incinerating plant located near the city of Arezzo, Italy. Within the framework of the new waste management plan, a methodology for the democratic participation of stakeholders was designed adopting the Local Agenda 21 methodology. Communication and participation events with the stakeholders were set up from the plan's development to its implementation. Eleven different categories of stakeholders including individual citizens were involved in 21 local events, reaching over 500 participants in three years. Actions were performed to build the commitment and ownership of the local administrators. Then, together with the environment and health agencies and a representative from the local committees, the local administrators collaborated with scientists and technicians in the knowledge-building and scoping stages. Focus groups of voluntary citizens worked together with the researchers to provide qualitative and quantitative evidence in the assessment stage. Periodic public forums were held to discuss processes, methods and findings. The local government authority considered the HIA results in the final decision and a new waste strategy was adopted both in the short term (increased curbside collection, waste sustainability program) and in the long term (limited repowering of the incinerator, new targets for separate collection). In conclusion, an effective participatory HIA was carried out at the municipal level to support decision makers in the waste management plan. The HIA21 study contributed to evidence-based decisions and to make a broadly participatory experience. The authors are confident that these achievements may improve the governance of the waste cycle and the trust in the public administration. Copyright © 2016 Elsevier Ltd. All rights reserved.

Flood Resilient Systems and their Application for Flood Resilient Planning

NASA Astrophysics Data System (ADS)

Manojlovic, N.; Gabalda, V.; Antanaskovic, D.; Gershovich, I.; Pasche, E.

2012-04-01

Following the paradigm shift in flood management from traditional to more integrated approaches, and considering the uncertainties of future development due to drivers such as climate change, one of the main emerging tasks of flood managers becomes the development of (flood) resilient cities. It can be achieved by application of non-structural - flood resilience measures, summarised in the 4As: assistance, alleviation, awareness and avoidance (FIAC, 2007). As a part of this strategy, the key aspect of development of resilient cities - resilient built environment can be reached by efficient application of Flood Resilience Technology (FReT) and its meaningful combination into flood resilient systems (FRS). FRS are given as [an interconnecting network of FReT which facilitates resilience (including both restorative and adaptive capacity) to flooding, addressing physical and social systems and considering different flood typologies] (SMARTeST, http://www.floodresilience.eu/). Applying the system approach (e.g. Zevenbergen, 2008), FRS can be developed at different scales from the building to the city level. Still, a matter of research is a method to define and systematise different FRS crossing those scales. Further, the decision on which resilient system is to be applied for the given conditions and given scale is a complex task, calling for utilisation of decision support tools. This process of decision-making should follow the steps of flood risk assessment (1) and development of a flood resilience plan (2) (Manojlovic et al, 2009). The key problem in (2) is how to match the input parameters that describe physical&social system and flood typology to the appropriate flood resilient system. Additionally, an open issue is how to integrate the advances in FReT and findings on its efficiency into decision support tools. This paper presents a way to define, systematise and make decisions on FRS at different scales of an urban system developed within the 7th FP Project SMARTeST. A web based three tier advisory system FLORETO-KALYPSO (http://floreto.wb.tu-harburg.de/, Manojlovic et al, 2009) devoted to support decision-making process at the building level has been further developed to support multi-scale decision making on resilient systems, improving the existing data mining algorithms of the Business Logic tier. Further tuning of the algorithms is to be performed based on the new developments and findings in applicability and efficiency of different FRe Technology for different flood typologies. The first results obtained at the case studies in Greater Hamburg, Germany indicate the potential of this approach to contribute to the multiscale resilient planning on the road to flood resilient cities. FIAC (2007): "Final report form the Awareness and Assistance Sub-committee", FIAC, Scottish Government Zevenbergen C. et al (2008) "Challenges in urban flood management: travelling across spatial and temporal scales", Journal of FRM Volume 1 Issue 2, p 81-88 Manojlovic N., et al (2009): "Capacity Building in FRM through a DSS Utilising Data Mining Approach", Proceed. 8th HIC, Concepcion, Chile, January, 2009

Maximizing Energy Savings for Small Businesses | Buildings | NREL

Science.gov Websites

significant amounts of money and energy, increase profits, promote their business, and cut greenhouse gas goals and save money: NREL's four-page lender's guide with discussion on timing and low-cost methods for information and design and decision support guides, available for free download The USDA's Business and

Marketing decision support systems for strategy building.

PubMed

Rao, S K

2000-01-01

Brand teams charged with the commercialization of pharmaceutical products in the pipeline operate in an uncertain environment. Market, customer and competitive interrelationships undergo changes, often in ways that are unpredictable with conventional research practices. This article describes a framework whereby such uncertainty can be managed more effectively in the context of ongoing business needs.

Eight Issues for Learning Scientists about Education and the Economy

ERIC Educational Resources Information Center

Roschelle, Jeremy; Bakia, Marianne; Toyama, Yukie; Patton, Charles

2011-01-01

Linking research to a compelling societal interest can build financial commitments to research, bring increased attention to findings, and grow support for scaling up impacts. Among many compelling societal interests that learning scientists can cite--such as increasing the quality of life, preparing citizens to make decisions in a complex world,…

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…

Building Support for Student Success: A Framework for Achieving the Dream's State Policy Work

ERIC Educational Resources Information Center

Jobs for the Future, 2005

2005-01-01

This document is designed to help accelerate and strengthen state policy initiatives that promote student success; and derive lessons from this work about strategies for influencing the allocation of resources, the transparency of and accountability for results, and the rules that shape how institutions make decisions about priorities and…

Strengthening national decision-making on immunization by building capacity for economic evaluation: Implementing ProVac in Europe.

PubMed

Blau, Julia; Hoestlandt, Céline; D Clark, Andrew; Baxter, Louise; Felix Garcia, Ana Gabriela; Mounaud, Bérénice; Mosina, Liudmila

2015-05-07

For many years, low- and middle-income countries have made efforts to strengthen national decision-making on immunization. The Pan American Health Organization (PAHO) ProVac Initiative was established to help expedite the use of evidence-based decision-making around new vaccine introduction. This initiative provides training in user-friendly cost-effectiveness models and supports the development of country-led economic evaluations. Due to the success of the ProVac Initiative in the Americas, and following requests from countries from outside the Americas, the Bill & Melinda Gates Foundation funded a two-year pilot effort to expand the initiative to other world regions. Called the ProVac International Working Group (IWG), this endeavor took place in 2012 and 2013. It was coordinated by PAHO and carried out in collaboration with several international partners, including the Agence de Médecine Préventive (AMP), London School of Hygiene & Tropical Medicine (LSHTM), Program for Appropriate Technology in Health, Sabin Vaccine Institute, United States Centers for Disease Control and Prevention, and the World Health Organization (WHO). In the WHO European Region, technical support was provided by AMP, in close collaboration with the WHO Regional Office for Europe and other ProVac IWG partners. In 2012, AMP, the WHO Regional Office for Europe, and other partners held a training workshop in Dubrovnik, Croatia, for 31 participants from four countries of the WHO European Region. The aim was to train health professionals in standard methods of economic evaluation and to assess regional demand for economic studies to support decision-making on immunization. AMP and the other organizations also supported four national cost-effectiveness studies in the WHO European Region. The assistance included country visits and support over a period of six months, the establishment of multidisciplinary teams of experts, ongoing training on the TRIVAC decision-support model for new-vaccine economic analysis, review of local evidence, recommending key data inputs, and support in presenting results to national decision makers. National cost-effectiveness studies were conducted in four countries: Albania (rotavirus vaccine [RV]), Azerbaijan (pneumococcal conjugate vaccine [PCV]), Croatia (PCV), and Georgia (PCV). All four countries improved their estimates of the burden of disease preventable by the new vaccines. National advisory bodies and ministries of health obtained economic evidence that helped Albania and Croatia to make decisions on introducing the new vaccines. Azerbaijan and Georgia used economic evidence to confirm previously made preliminary decisions to introduce PCV and make corresponding financial commitments. The study helped Albania to obtain access to affordable prices for rotavirus vaccines through participation in the UNICEF procurement mechanism for middle-income countries. Croatia was able to define the PCV price that would make its introduction cost-effective, and can use this figure as a basis for price negotiations. Despite some challenges due to competing national priorities, tight budgets for immunization, and lack of available national data, the ProVac IWG helped to build capacity of national health professionals, support decision-making for the introduction of new vaccines, and promote utilization of economic evidence for making decisions on immunization. This type of strong collaboration among international partners and countries should be scaled up, given that many other countries in the WHO European Region have expressed interest in receiving assistance from the ProVac IWG. Copyright © 2015. Published by Elsevier Ltd.

The Lenfest Ocean Program's experience in building institutional support for connecting science and decision-making in marine systems

NASA Astrophysics Data System (ADS)

Bednarek, A.; Close, S.; Curran, K.; Hudson, C.

2017-12-01

Addressing contemporary sustainability challenges requires attention to the integration of scientific knowledge into decision-making and deliberation. However, this remains a challenge in practice. We contend that careful stewardship of this process of integration can result in positive, durable outcomes by reconciling the production and use of scientific knowledge, and improve its relevance and utility to decision-makers. We will share lessons learned from a grantmaking program that has addressed this challenge through programmatic innovations, including by supporting staff devoted to an intermediary role. Over the past 13 years, the Lenfest Ocean Program served in a boundary spanning role by integrating decision-makers into the scoping and outreach of program supported scientific research grants. Program staff engage with decision-makers and influencers to identify policy-relevant research questions and approaches, ensuring that the research direction addresses users' needs. As research progresses, the staff monitor the grant's progress to improve the match between the research and user needs. The process is resource-intensive, however, and raises interesting questions about the role and development of this kind of specialist within different kinds of institutions, including funding agencies. We suggest that nurturing this role as a practice and profession could ultimately help the scientific community more efficiently respond to sustainability challenges.

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

NASA Astrophysics Data System (ADS)

Steinberg, N.

2017-12-01

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

Supporting UK adaptation: building services for the next set of UK climate projections

NASA Astrophysics Data System (ADS)

Fung, Fai; Lowe, Jason

2016-04-01

As part of the Climate Change Act 2008, the UK Government sets out a national adaptation programme to address the risks and opportunities identified in a national climate change risk assessment (CCRA) every five years. The last risk assessment in 2012 was based on the probabilistic projections for the UK published in 2009 (UKCP09). The second risk assessment will also use information from UKCP09 alongside other evidence on climate projections. However, developments in the science of climate projeciton, and evolving user needs (based partly on what has been learnt about the diverse user requirements of the UK adaptation community from the seven years of delivering and managing UKCP09 products, market research and the peer-reviewed literature) suggest now is an appropriate time to update the projections and how they are delivered. A new set of UK climate projections are now being produced to upgrade UKCP09 to reflect the latest developments in climate science, the first phase of which will be delivered in 2018 to support the third CCRA. A major component of the work is the building of a tailored service to support users of the new projections during their development and to involve users in key decisions so that the projections are of most use. We will set out the plan for the new climate projections that seek to address the evolving user need. We will also present a framework which aims to (i) facilitate the dialogue between users, boundary organisations and producers, reflecting their different decision-making roles (ii) produce scientifically robust, user-relevant climate information (iii) provide the building blocks for developing further climate services to support adaptation activities in the UK.

Agile Acceptance Test–Driven Development of Clinical Decision Support Advisories: Feasibility of Using Open Source Software

PubMed Central

Baldwin, Krystal L; Kannan, Vaishnavi; Flahaven, Emily L; Parks, Cassandra J; Ott, Jason M; Willett, Duwayne L

2018-01-01

Background Moving to electronic health records (EHRs) confers substantial benefits but risks unintended consequences. Modern EHRs consist of complex software code with extensive local configurability options, which can introduce defects. Defects in clinical decision support (CDS) tools are surprisingly common. Feasible approaches to prevent and detect defects in EHR configuration, including CDS tools, are needed. In complex software systems, use of test–driven development and automated regression testing promotes reliability. Test–driven development encourages modular, testable design and expanding regression test coverage. Automated regression test suites improve software quality, providing a “safety net” for future software modifications. Each automated acceptance test serves multiple purposes, as requirements (prior to build), acceptance testing (on completion of build), regression testing (once live), and “living” design documentation. Rapid-cycle development or “agile” methods are being successfully applied to CDS development. The agile practice of automated test–driven development is not widely adopted, perhaps because most EHR software code is vendor-developed. However, key CDS advisory configuration design decisions and rules stored in the EHR may prove amenable to automated testing as “executable requirements.” Objective We aimed to establish feasibility of acceptance test–driven development of clinical decision support advisories in a commonly used EHR, using an open source automated acceptance testing framework (FitNesse). Methods Acceptance tests were initially constructed as spreadsheet tables to facilitate clinical review. Each table specified one aspect of the CDS advisory’s expected behavior. Table contents were then imported into a test suite in FitNesse, which queried the EHR database to automate testing. Tests and corresponding CDS configuration were migrated together from the development environment to production, with tests becoming part of the production regression test suite. Results We used test–driven development to construct a new CDS tool advising Emergency Department nurses to perform a swallowing assessment prior to administering oral medication to a patient with suspected stroke. Test tables specified desired behavior for (1) applicable clinical settings, (2) triggering action, (3) rule logic, (4) user interface, and (5) system actions in response to user input. Automated test suite results for the “executable requirements” are shown prior to building the CDS alert, during build, and after successful build. Conclusions Automated acceptance test–driven development and continuous regression testing of CDS configuration in a commercial EHR proves feasible with open source software. Automated test–driven development offers one potential contribution to achieving high-reliability EHR configuration. Vetting acceptance tests with clinicians elicits their input on crucial configuration details early during initial CDS design and iteratively during rapid-cycle optimization. PMID:29653922

Agile Acceptance Test-Driven Development of Clinical Decision Support Advisories: Feasibility of Using Open Source Software.

PubMed

Basit, Mujeeb A; Baldwin, Krystal L; Kannan, Vaishnavi; Flahaven, Emily L; Parks, Cassandra J; Ott, Jason M; Willett, Duwayne L

2018-04-13

Moving to electronic health records (EHRs) confers substantial benefits but risks unintended consequences. Modern EHRs consist of complex software code with extensive local configurability options, which can introduce defects. Defects in clinical decision support (CDS) tools are surprisingly common. Feasible approaches to prevent and detect defects in EHR configuration, including CDS tools, are needed. In complex software systems, use of test-driven development and automated regression testing promotes reliability. Test-driven development encourages modular, testable design and expanding regression test coverage. Automated regression test suites improve software quality, providing a "safety net" for future software modifications. Each automated acceptance test serves multiple purposes, as requirements (prior to build), acceptance testing (on completion of build), regression testing (once live), and "living" design documentation. Rapid-cycle development or "agile" methods are being successfully applied to CDS development. The agile practice of automated test-driven development is not widely adopted, perhaps because most EHR software code is vendor-developed. However, key CDS advisory configuration design decisions and rules stored in the EHR may prove amenable to automated testing as "executable requirements." We aimed to establish feasibility of acceptance test-driven development of clinical decision support advisories in a commonly used EHR, using an open source automated acceptance testing framework (FitNesse). Acceptance tests were initially constructed as spreadsheet tables to facilitate clinical review. Each table specified one aspect of the CDS advisory's expected behavior. Table contents were then imported into a test suite in FitNesse, which queried the EHR database to automate testing. Tests and corresponding CDS configuration were migrated together from the development environment to production, with tests becoming part of the production regression test suite. We used test-driven development to construct a new CDS tool advising Emergency Department nurses to perform a swallowing assessment prior to administering oral medication to a patient with suspected stroke. Test tables specified desired behavior for (1) applicable clinical settings, (2) triggering action, (3) rule logic, (4) user interface, and (5) system actions in response to user input. Automated test suite results for the "executable requirements" are shown prior to building the CDS alert, during build, and after successful build. Automated acceptance test-driven development and continuous regression testing of CDS configuration in a commercial EHR proves feasible with open source software. Automated test-driven development offers one potential contribution to achieving high-reliability EHR configuration. Vetting acceptance tests with clinicians elicits their input on crucial configuration details early during initial CDS design and iteratively during rapid-cycle optimization. ©Mujeeb A Basit, Krystal L Baldwin, Vaishnavi Kannan, Emily L Flahaven, Cassandra J Parks, Jason M Ott, Duwayne L Willett. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 13.04.2018.

TreePOD: Sensitivity-Aware Selection of Pareto-Optimal Decision Trees.

PubMed

Muhlbacher, Thomas; Linhardt, Lorenz; Moller, Torsten; Piringer, Harald

2018-01-01

Balancing accuracy gains with other objectives such as interpretability is a key challenge when building decision trees. However, this process is difficult to automate because it involves know-how about the domain as well as the purpose of the model. This paper presents TreePOD, a new approach for sensitivity-aware model selection along trade-offs. TreePOD is based on exploring a large set of candidate trees generated by sampling the parameters of tree construction algorithms. Based on this set, visualizations of quantitative and qualitative tree aspects provide a comprehensive overview of possible tree characteristics. Along trade-offs between two objectives, TreePOD provides efficient selection guidance by focusing on Pareto-optimal tree candidates. TreePOD also conveys the sensitivities of tree characteristics on variations of selected parameters by extending the tree generation process with a full-factorial sampling. We demonstrate how TreePOD supports a variety of tasks involved in decision tree selection and describe its integration in a holistic workflow for building and selecting decision trees. For evaluation, we illustrate a case study for predicting critical power grid states, and we report qualitative feedback from domain experts in the energy sector. This feedback suggests that TreePOD enables users with and without statistical background a confident and efficient identification of suitable decision trees.

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

Haapio, Appu, E-mail: appu.haapio@vtt.fi

Requirements for the assessment tools of buildings have increased, assessing of building components or separate buildings is not enough. Neighbourhoods, built environment, public transportations, and services, should be considered simultaneously. Number of population living in urban areas is high and increasing rapidly. Urbanisation is a major concern due to its detrimental effects on the environment. The aim of this study is to clarify the field of assessment tools for urban communities by analysing the current situation. The focus is on internationally well known assessment tools; BREEAM Communities, CASBEE for Urban Development and LEED for Neigborhood Development. The interest towards certificationmore » systems is increasing amongst the authorities, and especially amongst the global investors and property developers. Achieved certifications are expected to bring measureable publicity for the developers. The assessment of urban areas enables the comparison of municipalities and urban areas, and notably supports decision making processes. Authorities, city planners, and designers would benefit most from the use of the tools during the decision making process. - Highlights: Black-Right-Pointing-Pointer The urban assessment tools have strong linkage to the region. Black-Right-Pointing-Pointer The tools promote complementary building and retrofitting existing sites. Black-Right-Pointing-Pointer Sharing knowledge and experiences is important in the development of the tools.« less

Building Information Management as a Tool for Managing Knowledge throughout whole Building Life Cycle

NASA Astrophysics Data System (ADS)

Nývlt, Vladimír; Prušková, Kristýna

2017-10-01

BIM today is much more than drafting in 3D only, and project participants are further challenging, what is the topic of both this paper, and further research. Knowledge of objects, their behaviour, and other characteristics has high impact on whole building life cycle. Other structured and unstructured knowledge is rightfully added (e.g. historically based experience, needs and requirements of users, investors, needs for project and objects revisions) Grasping of all attributes into system for collection, managing and time control of knowledge. Further important findings lie in the necessity of understanding how to manage knowledge needs with diverse and variable ways, when BIM maturity levels are advanced, as defined by Bew and Richards (2008). All decisions made would always rely on good, timely, and correct data. Usage of BIM models in terms of Building Information Management can support all decisions through data gathering, sharing, and using across all disciplines and all Life Cycle steps. It particularly significantly improves possibilities and level of life cycle costing. Experience and knowledge stored in data models of BIM, describing user requirements, best practices derived from other projects and/or research outputs will help to understand sustainability in its complexity and wholeness.

Making the purchase decision: factors other than price.

PubMed

Lyons, D M

1992-05-01

Taking price out of the limelight and concentrating on customer relations, mutual respect, and build-in/buy-in; involving the user; developing communication and evaluation processes; and being process oriented to attain the results needed require commitment on the part of administration and materiel management. There must be a commitment of time to develop the process, commitment of resources to work through the process, and a commitment of support to enhance the process. With those three parameters in place, price will no longer be the only factor in the purchasing decision.

The role of emotion in decision-making: a cognitive neuroeconomic approach towards understanding sexual risk behavior.

PubMed

Gutnik, Lily A; Hakimzada, A Forogh; Yoskowitz, Nicole A; Patel, Vimla L

2006-12-01

Models of decision-making usually focus on cognitive, situational, and socio-cultural variables in accounting for human performance. However, the emotional component is rarely addressed within these models. This paper reviews evidence for the emotional aspect of decision-making and its role within a new framework of investigation, called neuroeconomics. The new approach aims to build a comprehensive theory of decision-making, through the unification of theories and methods from economics, psychology, and neuroscience. In this paper, we review these integrative research methods and their applications to issues of public health, with illustrative examples from our research on young adults' safe sex practices. This approach promises to be valuable as a comprehensively descriptive and possibly, better predictive model for construction and customization of decision support tools for health professionals and consumers.

Greening Federal Facilities: An Energy, Environmental, and Economic Resource Guide for Federal Facility Managers and Designers; Second Edition

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

Wilson, A.

2001-05-16

Greening Federal Facilities, Second Edition, is a nuts-and-bolts resource guide compiled to increase energy and resource efficiency, cut waste, and improve the performance of Federal buildings and facilities. The guide highlights practical actions that facility managers, design and construction staff, procurement officials, and facility planners can take to save energy and money, improve the comfort and productivity of employees, and benefit the environment. It supports a national effort to promote energy and environmental efficiency in the nation's 500,000 Federal buildings and facilities. Topics covered include current Federal regulations; environmental and energy decision-making; site and landscape issues; building design; energy systems;more » water and wastewater; materials; waste management, and recycling; indoor environmental quality; and managing buildings.« less

Bayesian Decision Support for Adaptive Lung Treatments

NASA Astrophysics Data System (ADS)

McShan, Daniel; Luo, Yi; Schipper, Matt; TenHaken, Randall

2014-03-01

Purpose: A Bayesian Decision Network will be demonstrated to provide clinical decision support for adaptive lung response-driven treatment management based on evidence that physiologic metrics may correlate better with individual patient response than traditional (population-based) dose and volume-based metrics. Further, there is evidence that information obtained during the course of radiation therapy may further improve response predictions. Methods: Clinical factors were gathered for 58 patients including planned mean lung dose, and the bio-markers IL-8 and TGF-β1 obtained prior to treatment and two weeks into treatment along with complication outcomes for these patients. A Bayesian Decision Network was constructed using Netica 5.0.2 from Norsys linking these clinical factors to obtain a prediction of radiation induced lung disese (RILD) complication. A decision node was added to the network to provide a plan adaption recommendation based on the trade-off between the RILD prediction and complexity of replanning. A utility node provides the weighting cost between the competing factors. Results: The decision node predictions were optimized against the data for the 58 cases. With this decision network solution, one can consider the decision result for a new patient with specific findings to obtain a recommendation to adaptively modify the originally planned treatment course. Conclusions: A Bayesian approach allows handling and propagating probabilistic data in a logical and principled manner. Decision networks provide the further ability to provide utility-based trade-offs, reflecting non-medical but practical cost/benefit analysis. The network demonstrated illustrates the basic concept, but many other factors may affect these decisions and work on building better models are being designed and tested. Acknowledgement: Supported by NIH-P01-CA59827

A multi-criteria model for the comparison of building envelope energy retrofits

NASA Astrophysics Data System (ADS)

Donnarumma, Giuseppe; Fiore, Pierfrancesco

2017-02-01

In light of the current EU guidelines in the energy field, improving building envelope performance cannot be separated from the context of satisfying the environmental sustainability requirements, reducing the costs associated with the life cycle of the building as well as economic and financial feasibility. Therefore, identifying the "optimal" energy retrofit solutions requires the simultaneous assessment of several factors and thus becomes a problem of choice between several possible alternatives. To facilitate the work of the decision-makers, public or private, adequate decision support tools are of great importance. Starting from this need, a model based on the multi-criteria analysis "AHP" technique is proposed, along with the definition of three synthetic indices associated with the three requirements of "Energy Performance", "Sustainability Performance" and "Cost". From the weighted aggregation of the three indices, a global index of preference is obtained that allows to "quantify" the satisfaction level of the i-th alternative from the point of view of a particular group of decision-makers. The model is then applied, by way of example, to the case-study of the energetic redevelopment of a former factory, assuming its functional conversion. Twenty possible alternative interventions on the opaque vertical closures, resulting from the combination of three thermal insulators families (synthetic, natural and mineral) with four energy retrofitting techniques are compared and the results obtained critically discussed by considering the point of view of the three different groups of decision-makers.

Implementation of marine spatial planning in shellfish aquaculture management: modeling studies in a Norwegian fjord.

PubMed

Filgueira, Ramon; Grant, Jon; Strand, Øivind

2014-06-01

Shellfish carrying capacity is determined by the interaction of a cultured species with its ecosystem, which is strongly influenced by hydrodynamics. Water circulation controls the exchange of matter between farms and the adjacent areas, which in turn establishes the nutrient supply that supports phytoplankton populations. The complexity of water circulation makes necessary the use of hydrodynamic models with detailed spatial resolution in carrying capacity estimations. This detailed spatial resolution also allows for the study of processes that depend on specific spatial arrangements, e.g., the most suitable location to place farms, which is crucial for marine spatial planning, and consequently for decision support systems. In the present study, a fully spatial physical-biogeochemical model has been combined with scenario building and optimization techniques as a proof of concept of the use of ecosystem modeling as an objective tool to inform marine spatial planning. The object of this exercise was to generate objective knowledge based on an ecosystem approach to establish new mussel aquaculture areas in a Norwegian fjord. Scenario building was used to determine the best location of a pump that can be used to bring nutrient-rich deep waters to the euphotic layer, increasing primary production, and consequently, carrying capacity for mussel cultivation. In addition, an optimization tool, parameter estimation (PEST), was applied to the optimal location and mussel standing stock biomass that maximize production, according to a preestablished carrying capacity criterion. Optimization tools allow us to make rational and transparent decisions to solve a well-defined question, decisions that are essential for policy makers. The outcomes of combining ecosystem models with scenario building and optimization facilitate planning based on an ecosystem approach, highlighting the capabilities of ecosystem modeling as a tool for marine spatial planning.

Decision making and coping in healthcare: the Coping in Deliberation (CODE) framework.

PubMed

Witt, Jana; Elwyn, Glyn; Wood, Fiona; Brain, Kate

2012-08-01

To develop a framework of decision making and coping in healthcare that describes the twin processes of appraisal and coping faced by patients making preference-sensitive healthcare decisions. We briefly review the literature for decision making theories and coping theories applicable to preference-sensitive decisions in healthcare settings. We describe first decision making, then coping and finally attempt to integrate these processes by building on current theory. Deliberation in healthcare may be described as a six step process, comprised of the presentation of a health threat, choice, options, preference construction, the decision itself and consolidation post-decision. Coping can be depicted in three stages, beginning with a threat, followed by primary and secondary appraisal and ultimately resulting in a coping effort. Drawing together concepts from prominent decision making theories and coping theories, we propose a multidimensional, interactive framework which integrates both processes and describes coping in deliberation. The proposed framework offers an insight into the complexity of decision making in preference-sensitive healthcare contexts from a patient perspective and may act as theoretical basis for decision support. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Building sustainable multi-functional prospective electronic clinical data systems.

PubMed

Randhawa, Gurvaneet S; Slutsky, Jean R

2012-07-01

A better alignment in the goals of the biomedical research enterprise and the health care delivery system can help fill the large gaps in our knowledge of the impact of clinical interventions on patient outcomes in the real world. There are several initiatives underway to align the research priorities of patients, providers, researchers, and policy makers. These include Agency for Healthcare Research and Quality (AHRQ)-supported projects to build flexible prospective clinical electronic data infrastructure that meet the needs of these diverse users. AHRQ has previously supported the creation of 2 distributed research networks as a new approach to conduct comparative effectiveness research (CER) while protecting a patient's confidential information and the proprietary needs of a clinical organization. It has applied its experience in building these networks in directing the American Recovery and Reinvestment Act funds for CER to support new clinical electronic infrastructure projects that can be used for several purposes including CER, quality improvement, clinical decision support, and disease surveillance. In addition, AHRQ has funded a new Electronic Data Methods forum to advance the methods in clinical informatics, research analytics, and governance by actively engaging investigators from the American Recovery and Reinvestment Act-funded projects and external stakeholders.

Advanced building energy management system demonstration for Department of Defense buildings.

PubMed

O'Neill, Zheng; Bailey, Trevor; Dong, Bing; Shashanka, Madhusudana; Luo, Dong

2013-08-01

This paper presents an advanced building energy management system (aBEMS) that employs advanced methods of whole-building performance monitoring combined with statistical methods of learning and data analysis to enable identification of both gradual and discrete performance erosion and faults. This system assimilated data collected from multiple sources, including blueprints, reduced-order models (ROM) and measurements, and employed advanced statistical learning algorithms to identify patterns of anomalies. The results were presented graphically in a manner understandable to facilities managers. A demonstration of aBEMS was conducted in buildings at Naval Station Great Lakes. The facility building management systems were extended to incorporate the energy diagnostics and analysis algorithms, producing systematic identification of more efficient operation strategies. At Naval Station Great Lakes, greater than 20% savings were demonstrated for building energy consumption by improving facility manager decision support to diagnose energy faults and prioritize alternative, energy-efficient operation strategies. The paper concludes with recommendations for widespread aBEMS success. © 2013 New York Academy of Sciences.

78 FR 14110 - Announcement of Funding Awards for the Section 4 Capacity Building for Community Development and...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-04

... funding decisions made by the Department in a competition for funding under the 2012 Notice of Funding... activities such as training, education, support, loans, grants, and development assistance. The Fiscal Year 2012 competition was announced on http://www.hud.gov on April 12, 2012. The NOFA provided $35 million...

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

Federal Register 2010, 2011, 2012, 2013, 2014

2010-09-14

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

Manpower Impact Assessment Model (MIAM). An Analytic Model for Assessing the Effect of Supply Policy Changes on Manpower Requirements at Retail Supply Activities

DTIC Science & Technology

1984-09-01

to Management Science (Third Edition). St. Paul: West Publishing Co., 1982. 2. Bennett, John L. (Editor). Building Decision Support Systems. Reading...Starts 700 DCCs 5000 Units Inventoried 50000 103 * * Bibliography /, 1. Anderson, David R., Dennis J. Sweeney, and Thomas A. Williams. An Introduction

Computer-Mediated Counter-Arguments and Individual Learning

ERIC Educational Resources Information Center

Hsu, Jack Shih-Chieh; Huang, Hsieh-Hong; Linden, Lars P.

2011-01-01

This study explores a de-bias function for a decision support systems (DSS) that is designed to help a user avoid confirmation bias by increasing the user's learning opportunities. Grounded upon the theory of mental models, the use of DSS is viewed as involving a learning process, whereby a user is directed to build mental models so as to reduce…

Valuing people in the landscape: Re-thinking conservation approaches

Treesearch

Peter Taylor

2015-01-01

When Australian Governments committed to building a National Reserve System (NRS) for Australia in 1991 they didn't anticipate that some of the most important conservation gains were to be made on Indigenous owned land. An innovative Federal Government policy decision in 1996 to support Indigenous landowners to establish Indigenous Protected Areas (IPA# on their...

Evidence-based decision-making for vaccine introductions: Overview of the ProVac International Working Group’s experience

PubMed Central

Jauregui, Barbara; Garcia, Ana Gabriela Felix; Janusz, Cara Bess; Blau, Julia; Munier, Aline; Atherly, Deborah; Mvundura, Mercy; Hajjeh, Rana; Lopman, Benjamin; Clark, Andrew David; Baxter, Louise; Hutubessy, Raymond; de Quadros, Ciro; Andrus, Jon Kim

2015-01-01

Introduction Pan American Health Organization’s (PAHO) ProVac Initiative aims to strengthen countries’ technical capacity to make evidence-based immunization policy. With financial support from the Bill and Melinda Gates Foundation, PAHO established the ProVac International Working Group (IWG), a platform created for two years to transfer the ProVac Initiative’s tools and methods to support decisions in non-PAHO regions. Methods In 2011, WHO Regional Offices and partner agencies established the IWG to transfer the ProVac framework for new vaccine decision support, including tools and trainings to other regions of the world. During the two year period, PAHO served as the coordinating secretariat and partner agencies played implementing or advisory roles. Results Fifty nine national professionals from 17 countries received training on the use of economic evaluations to aid vaccine policy making through regional workshops. The IWG provided direct technical support to nine countries to develop cost-effectiveness analyses to inform decisions. All nine countries introduced the new vaccine evaluated or their NITAGs have made a recommendation to the Ministry of Health to introduce the new vaccine. Discussion Developing countries around the world are increasingly interested in weighing the potential health impact due to new vaccine introduction against the investments required. During the two years, the ProVac approach proved valuable and timely to aid the national decision making processes, even despite the different challenges and idiosyncrasies encountered in each region. The results of this work suggest that: (1) there is great need and demand for technical support and for capacity building around economic evaluations; and (2) the ProVac method of supporting country-owned analyses is as effective in other regions as it has been in the PAHO region. Conclusion Decision support for new vaccine introduction in low- and middle-income countries is critical to guiding the efficient use of resources and prioritizing high impact vaccination programs. PMID:25919170

Evidence-based decision-making for vaccine introductions: Overview of the ProVac International Working Group's experience.

PubMed

Jauregui, Barbara; Garcia, Ana Gabriela Felix; Bess Janusz, Cara; Blau, Julia; Munier, Aline; Atherly, Deborah; Mvundura, Mercy; Hajjeh, Rana; Lopman, Benjamin; Clark, Andrew David; Baxter, Louise; Hutubessy, Raymond; de Quadros, Ciro; Andrus, Jon Kim

2015-05-07

Pan American Health Organization's (PAHO) ProVac Initiative aims to strengthen countries' technical capacity to make evidence-based immunization policy. With financial support from the Bill and Melinda Gates Foundation, PAHO established the ProVac International Working Group (IWG), a platform created for two years to transfer the ProVac Initiative's tools and methods to support decisions in non-PAHO regions. In 2011, WHO Regional Offices and partner agencies established the IWG to transfer the ProVac framework for new vaccine decision support, including tools and trainings to other regions of the world. During the two year period, PAHO served as the coordinating secretariat and partner agencies played implementing or advisory roles. Fifty nine national professionals from 17 countries received training on the use of economic evaluations to aid vaccine policy making through regional workshops. The IWG provided direct technical support to nine countries to develop cost-effectiveness analyses to inform decisions. All nine countries introduced the new vaccine evaluated or their NITAGs have made a recommendation to the Ministry of Health to introduce the new vaccine. Developing countries around the world are increasingly interested in weighing the potential health impact due to new vaccine introduction against the investments required. During the two years, the ProVac approach proved valuable and timely to aid the national decision making processes, even despite the different challenges and idiosyncrasies encountered in each region. The results of this work suggest that: (1) there is great need and demand for technical support and for capacity building around economic evaluations; and (2) the ProVac method of supporting country-owned analyses is as effective in other regions as it has been in the PAHO region. Decision support for new vaccine introduction in low- and middle-income countries is critical to guiding the efficient use of resources and prioritizing high impact vaccination programs. Copyright © 2015. Published by Elsevier Ltd.

Medical Student Self-Efficacy with Family-Centered Care during Bedside Rounds

PubMed Central

Young, Henry N.; Schumacher, Jayna B.; Moreno, Megan A.; Brown, Roger L.; Sigrest, Ted D.; McIntosh, Gwen K.; Schumacher, Daniel J.; Kelly, Michelle M.; Cox, Elizabeth D.

2012-01-01

Purpose Factors that support self-efficacy must be understood in order to foster family-centered care (FCC) during rounds. Based on social cognitive theory, this study examined (1) how 3 supportive experiences (observing role models, having mastery experiences, and receiving feedback) influence self-efficacy with FCC during rounds and (2) whether the influence of these supportive experiences was mediated by self-efficacy with 3 key FCC tasks (relationship building, exchanging information, and decision making). Method Researchers surveyed 184 students during pediatric clerkship rotations during the 2008–2011 academic years. Surveys assessed supportive experiences and students’ self-efficacy with FCC during rounds and with key FCC tasks. Measurement models were constructed via exploratory and confirmatory factor analyses. Composite indicator structural equation (CISE) models evaluated whether supportive experiences influenced self-efficacy with FCC during rounds and whether self-efficacy with key FCC tasks mediated any such influences. Results Researchers obtained surveys from 172 eligible students who were 76% (130) White and 53% (91) female. Observing role models and having mastery experiences supported self-efficacy with FCC during rounds (each p<0.01), while receiving feedback did not. Self-efficacy with two specific FCC tasks, relationship building and decision making (each p < 0.05), mediated the effects of these two supportive experiences on self-efficacy with FCC during rounds. Conclusions Observing role models and having mastery experiences foster students’ self-efficacy with FCC during rounds, operating through self-efficacy with key FCC tasks. Results suggest the importance of helping students gain self-efficacy in key FCC tasks before the rounds experience and helping educators implement supportive experiences during rounds. PMID:22534602

Synergy Between Individual and Institutional Capacity Building: Examples from the NASA DEVELOP National Program

NASA Astrophysics Data System (ADS)

Ross, K. W.; Childs-Gleason, L. M.; Favors, J.; Rogers, L.; Ruiz, M. L.; Allsbrook, K. N.

2016-12-01

The NASA DEVELOP National Program seeks to simultaneously build capacity to use Earth observations in early career and transitioning professionals while building capacity with institutional partners to apply Earth observations in conducting operations, making decisions, or informing policy. Engaging professionals in this manner lays the foundation of the NASA DEVELOP experience and provides a fresh perspective into institutional challenges. This energetic engagement of people in the emerging workforce elicits heightened attention and greater openness to new resources and processes from project partners. This presentation will describe how NASA DEVELOP provides over 350 opportunities for individuals to engage with over 140 partners per year. It will discuss how the program employs teaming approaches, logistical support, and access to science expertise to facilitate increased awareness and use of NASA geospatial information. It will conclude with examples of how individual/institutional capacity building synergies have led to useful capacity building outcomes.

The prefabricated building risk decision research of DM technology on the basis of Rough Set

NASA Astrophysics Data System (ADS)

Guo, Z. L.; Zhang, W. B.; Ma, L. H.

2017-08-01

With the resources crises and more serious pollution, the green building has been strongly advocated by most countries and become a new building style in the construction field. Compared with traditional building, the prefabricated building has its own irreplaceable advantages but is influenced by many uncertainties. So far, a majority of scholars have been studying based on qualitative researches from all of the word. This paper profoundly expounds its significance about the prefabricated building. On the premise of the existing research methods, combined with rough set theory, this paper redefines the factors which affect the prefabricated building risk. Moreover, it quantifies risk factors and establish an expert knowledge base through assessing. And then reduced risk factors about the redundant attributes and attribute values, finally form the simplest decision rule. This simplest decision rule, which is based on the DM technology of rough set theory, provides prefabricated building with a controllable new decision-making method.

Embedding technology into inter-professional best practices in home safety evaluation.

PubMed

Burns, Suzanne Perea; Pickens, Noralyn Davel

2017-08-01

To explore inter-professional home evaluators' perspectives and needs for building useful and acceptable decision-support tools for the field of home modifications. Twenty semi-structured interviews were conducted with a range of home modification professionals from different regions of the United States. The interview transcripts were analyzed with a qualitative, descriptive, perspective approach. Technology supports current best practice and has potential to inform decision making through features that could enhance home evaluation processes, quality, efficiency and inter-professional communication. Technological advances with app design have created numerous opportunities for the field of home modifications. Integrating technology and inter-professional best practices will improve home safety evaluation and intervention development to meet client-centred and societal needs. Implications for rehabilitation Understanding home evaluators technology needs for home safety evaluations contributes to the development of app-based assessments. Integrating inter-professional perspectives of best practice and technological needs in an app for home assessments improves processes. Novice and expert home evaluators would benefit from decision support systems embedded in app-based assessments. Adoption of app-based assessment would improve efficiency while remaining client-centred.

Building leadership capacity in advanced nurse practitioners - the role of organisational management.

PubMed

Elliott, Naomi

2017-01-01

To highlight the organisation-level management's role in building leadership capacity in advanced nurse practitioners and the need for appropriate supports to increase their becoming leaders. Little is published about the role of organisation-level management in building leadership capacity and in developing the next generation of nurse leaders. In times of economic constraint, organisations need to focus their efforts on targeted leadership initiatives. Advanced nurse practitioners are ideally positioned to act as leaders both within and beyond the health care organisation. From the available research evidence, several support structures and mechanisms are identified as enablers for advanced nurse practitioners to enact their leadership role. Health care organisations need to include building leadership capacity as a priority in their strategic plan and take action to build-up the level of advanced nurse practitioner leadership. Nurse executives have a vital role in influencing the organisation's strategic plan and making a business case for prioritising leadership capacity building within advanced nurse practitioners. A challenge for nurse executives faced with competing service and leadership development demands, involves strategic decision-making regarding whether the advanced nurse practitioner's role is limited to service delivery or its potential in leading health care reforms is realised. © 2016 John Wiley & Sons Ltd.

Merging building maintainability and sustainability assessment: A multicriteria decision making approach

NASA Astrophysics Data System (ADS)

Asmone, A. S.; Chew, M. Y. L.

2018-02-01

Accurately predicting maintainability has been a challenge due to the complex nature of buildings, yet it is an important research area with a rising necessity. This paper explores the use of multicriteria decision making approach for merging maintainability and sustainability elements into building grading systems to attain long-term sustainability in the building industry. The paper conducts a systematic literature review on multicriteria decision analysis approach and builds on the existing knowledge of maintainability to achieve this. A conceptual framework is developed to bridge the gap between building operations and maintenance with green facilities management by forecasting green maintainability at the design stage.

Capacity for Preferences: Respecting Patients with Compromised Decision-Making.

PubMed

Wasserman, Jason Adam; Navin, Mark Christopher

2018-05-01

When a patient lacks decision-making capacity, then according to standard clinical ethics practice in the United States, the health care team should seek guidance from a surrogate decision-maker, either previously selected by the patient or appointed by the courts. If there are no surrogates willing or able to exercise substituted judgment, then the team is to choose interventions that promote a patient's best interests. We argue that, even when there is input from a surrogate, patient preferences should be an additional source of guidance for decisions about patients who lack decision-making capacity. Our proposal builds on other efforts to help patients who lack decision-making capacity provide input into decisions about their care. For example, "supported," "assisted," or "guided" decision-making models reflect a commitment to humanistic patient engagement and create a more supportive process for patients, families, and health care teams. But often, they are supportive processes for guiding a patient toward a decision that the surrogate or team believes to be in the patient's medical best interests. Another approach holds that taking seriously the preferences of such a patient can help surrogates develop a better account of what the patient's treatment choices would have been if the patient had retained decision-making capacity; the surrogate then must try to integrate features of the patient's formerly rational self with the preferences of the patient's currently compromised self. Patients who lack decision-making capacity are well served by these efforts to solicit and use their preferences to promote best interests or to craft would-be autonomous patient images for use by surrogates. However, we go further: the moral reasons for valuing the preferences of patients without decision-making capacity are not reducible to either best-interests or (surrogate) autonomy considerations but can be grounded in the values of liberty and respect for persons. This has important consequences for treatment decisions involving these vulnerable patients. © 2018 The Hastings Center.

Neural mechanisms underlying human consensus decision-making

PubMed Central

Suzuki, Shinsuke; Adachi, Ryo; Dunne, Simon; Bossaerts, Peter; O'Doherty, John P.

2015-01-01

SUMMARY Consensus building in a group is a hallmark of animal societies, yet little is known about its underlying computational and neural mechanisms. Here, we applied a novel computational framework to behavioral and fMRI data from human participants performing a consensus decision-making task with up to five other participants. We found that participants reached consensus decisions through integrating their own preferences with information about the majority of group-members’ prior choices, as well as inferences about how much each option was stuck to by the other people. These distinct decision variables were separately encoded in distinct brain areas: the ventromedial prefrontal cortex, posterior superior temporal sulcus/temporoparietal junction and intraparietal sulcus, and were integrated in the dorsal anterior cingulate cortex. Our findings provide support for a theoretical account in which collective decisions are made through integrating multiple types of inference about oneself, others and environments, processed in distinct brain modules. PMID:25864634

Neural mechanisms underlying human consensus decision-making.

PubMed

Suzuki, Shinsuke; Adachi, Ryo; Dunne, Simon; Bossaerts, Peter; O'Doherty, John P

2015-04-22

Consensus building in a group is a hallmark of animal societies, yet little is known about its underlying computational and neural mechanisms. Here, we applied a computational framework to behavioral and fMRI data from human participants performing a consensus decision-making task with up to five other participants. We found that participants reached consensus decisions through integrating their own preferences with information about the majority group members' prior choices, as well as inferences about how much each option was stuck to by the other people. These distinct decision variables were separately encoded in distinct brain areas-the ventromedial prefrontal cortex, posterior superior temporal sulcus/temporoparietal junction, and intraparietal sulcus-and were integrated in the dorsal anterior cingulate cortex. Our findings provide support for a theoretical account in which collective decisions are made through integrating multiple types of inference about oneself, others, and environments, processed in distinct brain modules. Copyright © 2015 Elsevier Inc. All rights reserved.

Exploring Scientific Information for Policy Making under Deep Uncertainty

NASA Astrophysics Data System (ADS)

Forni, L.; Galaitsi, S.; Mehta, V. K.; Escobar, M.; Purkey, D. R.; Depsky, N. J.; Lima, N. A.

2016-12-01

Each actor evaluating potential management strategies brings her/his own distinct set of objectives to a complex decision space of system uncertainties. The diversity of these objectives require detailed and rigorous analyses that responds to multifaceted challenges. However, the utility of this information depends on the accessibility of scientific information to decision makers. This paper demonstrates data visualization tools for presenting scientific results to decision makers in two case studies, La Paz/ El Alto, Bolivia, and Yuba County,California. Visualization output from the case studies combines spatiotemporal, multivariate and multirun/multiscenario information to produce information corresponding to the objectives defined by key actors and stakeholders. These tools can manage complex data and distill scientific information into accessible formats. Using the visualizations, scientists and decision makers can navigate the decision space and potential objective trade-offs to facilitate discussion and consensus building. These efforts can support identifying stable negotiatedagreements between different stakeholders.

To Stay or to Leave: Factors Influencing Victims' Decisions to Stay or Leave a Domestic Violence Emergency Shelter.

PubMed

Fisher, Elisa M; Stylianou, Amanda M

2016-04-28

Domestic violence (DV) emergency shelters play a vital role in supporting victims who seek to leave abusive partners and gain independence. Research indicates that numerous positive outcomes for victims and their children are associated with utilization of DV shelter programs. Yet, research also suggests that DV shelter programs may be unable to comprehensively meet the needs of all victims, and many choose to leave shelters soon after their arrival. To better understand the ways in which DV shelter programs support victims but also fail to meet their needs, this article explores the factors that influence victims' decisions to stay or leave a DV emergency shelter program through qualitative interviews with 33 DV shelter residents. Study participants indicate that three types of factors influence their decision to stay or leave the shelter program: (a) contextual factors, (b) partner or family relationship factors, and (c) shelter-specific factors. Shelter-specific factors cited as important contributors to satisfaction or dissatisfaction with shelter living include policies, staff and services, displacement from one's home community, and facilities. Findings provide information from the perspective of victims on the factors that influence one's decision to stay or leave a DV program and can be used to support service providers and advocates in building programs that are both supportive of victims' needs and conductive to longer shelter stays. © The Author(s) 2016.

Demonstration of reduced-order urban scale building energy models

DOE PAGES

Heidarinejad, Mohammad; Mattise, Nicholas; Dahlhausen, Matthew; ...

2017-09-08

The aim of this study is to demonstrate a developed framework to rapidly create urban scale reduced-order building energy models using a systematic summary of the simplifications required for the representation of building exterior and thermal zones. These urban scale reduced-order models rely on the contribution of influential variables to the internal, external, and system thermal loads. OpenStudio Application Programming Interface (API) serves as a tool to automate the process of model creation and demonstrate the developed framework. The results of this study show that the accuracy of the developed reduced-order building energy models varies only up to 10% withmore » the selection of different thermal zones. In addition, to assess complexity of the developed reduced-order building energy models, this study develops a novel framework to quantify complexity of the building energy models. Consequently, this study empowers the building energy modelers to quantify their building energy model systematically in order to report the model complexity alongside the building energy model accuracy. An exhaustive analysis on four university campuses suggests that the urban neighborhood buildings lend themselves to simplified typical shapes. Specifically, building energy modelers can utilize the developed typical shapes to represent more than 80% of the U.S. buildings documented in the CBECS database. One main benefits of this developed framework is the opportunity for different models including airflow and solar radiation models to share the same exterior representation, allowing a unifying exchange data. Altogether, the results of this study have implications for a large-scale modeling of buildings in support of urban energy consumption analyses or assessment of a large number of alternative solutions in support of retrofit decision-making in the building industry.« less

Demonstration of reduced-order urban scale building energy models

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

Heidarinejad, Mohammad; Mattise, Nicholas; Dahlhausen, Matthew

The aim of this study is to demonstrate a developed framework to rapidly create urban scale reduced-order building energy models using a systematic summary of the simplifications required for the representation of building exterior and thermal zones. These urban scale reduced-order models rely on the contribution of influential variables to the internal, external, and system thermal loads. OpenStudio Application Programming Interface (API) serves as a tool to automate the process of model creation and demonstrate the developed framework. The results of this study show that the accuracy of the developed reduced-order building energy models varies only up to 10% withmore » the selection of different thermal zones. In addition, to assess complexity of the developed reduced-order building energy models, this study develops a novel framework to quantify complexity of the building energy models. Consequently, this study empowers the building energy modelers to quantify their building energy model systematically in order to report the model complexity alongside the building energy model accuracy. An exhaustive analysis on four university campuses suggests that the urban neighborhood buildings lend themselves to simplified typical shapes. Specifically, building energy modelers can utilize the developed typical shapes to represent more than 80% of the U.S. buildings documented in the CBECS database. One main benefits of this developed framework is the opportunity for different models including airflow and solar radiation models to share the same exterior representation, allowing a unifying exchange data. Altogether, the results of this study have implications for a large-scale modeling of buildings in support of urban energy consumption analyses or assessment of a large number of alternative solutions in support of retrofit decision-making in the building industry.« less

Environmental Resilience: Exploring Scientific Concepts for ...

EPA Pesticide Factsheets

Report This report summarizes two Community Environmental Resilience Index workshops held at EPA in May and July of 2014. The workshops explored scientific concepts for building an index of indicators of community environmental resilience to natural or human-caused disasters. The index could be used to support disaster decision-making. Key workshop outcomes include: a working definition of environmental resilience and insight into how it relates to EPA's mission and Strategic Goals, a call for an inventory of EPA resiliency tools, a preliminary list of indicators and CERI structure, identification of next steps for index development, and emergence of a network of collaborators. The report can be used to support EPA's work in resilience under PPD-8, PPD-21, and the national response and disaster recovery frameworks. It can feed into interagency efforts on building community resilience.

Mean-variance portfolio analysis data for optimizing community-based photovoltaic investment.

PubMed

Shakouri, Mahmoud; Lee, Hyun Woo

2016-03-01

The amount of electricity generated by Photovoltaic (PV) systems is affected by factors such as shading, building orientation and roof slope. To increase electricity generation and reduce volatility in generation of PV systems, a portfolio of PV systems can be made which takes advantages of the potential synergy among neighboring buildings. This paper contains data supporting the research article entitled: PACPIM: new decision-support model of optimized portfolio analysis for community-based photovoltaic investment [1]. We present a set of data relating to physical properties of 24 houses in Oregon, USA, along with simulated hourly electricity data for the installed PV systems. The developed Matlab code to construct optimized portfolios is also provided in . The application of these files can be generalized to variety of communities interested in investing on PV systems.

32 CFR 176.45 - Disposal of buildings and property.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 32 National Defense 1 2010-07-01 2010-07-01 false Disposal of buildings and property. 176.45... HOMELESS ASSISTANCE § 176.45 Disposal of buildings and property. (a) Puglic benefit transfer screening. Not... shall dispose of buildings and property in accordance with the record of decision or other decision...

Toward a multi-objective decision support framework to support regulations of unconventional oil and gas development

NASA Astrophysics Data System (ADS)

Alongi, M.; Howard, C.; Kasprzyk, J. R.; Ryan, J. N.

2015-12-01

Unconventional oil and gas development (UOGD) using hydraulic fracturing and horizontal drilling has recently fostered an unprecedented acceleration in energy development. Regulations seek to protect environmental quality of areas surrounding UOGD, while maintaining economic benefits. One such regulation is a setback distance, which dictates the minimum proximity between an oil and gas well and an object such as a residential or commercial building, property line, or water source. In general, most setback regulations have been strongly politically motivated without a clear scientific basis for understanding the relationship between the setback distance and various performance outcomes. This presentation discusses a new decision support framework for setback regulations, as part of a large NSF-funded sustainability research network (SRN) on UOGD. The goal of the decision support framework is to integrate a wide array of scientific information from the SRN into a coherent framework that can help inform policy regarding UOGD. The decision support framework employs multiobjective evolutionary algorithm (MOEA) optimization coupled with simulation models of air quality and other performance-based outcomes on UOGD. The result of the MOEA optimization runs are quantitative tradeoff curves among different objectives. For example, one such curve could demonstrate air pollution concentrations versus estimates of energy development profits, for different levels of setback distance. Our results will also inform policy-relevant discussions surrounding UOGD such as comparing single- and multi-well pads, as well as regulations on the density of well development over a spatial area.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Semantic-Web Technology: Applications at NASA

NASA Technical Reports Server (NTRS)

Ashish, Naveen

2004-01-01

We provide a description of work at the National Aeronautics and Space Administration (NASA) on building system based on semantic-web concepts and technologies. NASA has been one of the early adopters of semantic-web technologies for practical applications. Indeed there are several ongoing 0 endeavors on building semantics based systems for use in diverse NASA domains ranging from collaborative scientific activity to accident and mishap investigation to enterprise search to scientific information gathering and integration to aviation safety decision support We provide a brief overview of many applications and ongoing work with the goal of informing the external community of these NASA endeavors.

Driving out errors through tight integration between software and automation.

PubMed

Reifsteck, Mark; Swanson, Thomas; Dallas, Mary

2006-01-01

A clear case has been made for using clinical IT to improve medication safety, particularly bar-code point-of-care medication administration and computerized practitioner order entry (CPOE) with clinical decision support. The equally important role of automation has been overlooked. When the two are tightly integrated, with pharmacy information serving as a hub, the distinctions between software and automation become blurred. A true end-to-end medication management system drives out errors from the dockside to the bedside. Presbyterian Healthcare Services in Albuquerque has been building such a system since 1999, beginning by automating pharmacy operations to support bar-coded medication administration. Encouraged by those results, it then began layering on software to further support clinician workflow and improve communication, culminating with the deployment of CPOE and clinical decision support. This combination, plus a hard-wired culture of safety, has resulted in a dramatically lower mortality and harm rate that could not have been achieved with a partial solution.

New decision support tool for acute lymphoblastic leukemia classification

NASA Astrophysics Data System (ADS)

Madhukar, Monica; Agaian, Sos; Chronopoulos, Anthony T.

2012-03-01

In this paper, we build up a new decision support tool to improve treatment intensity choice in childhood ALL. The developed system includes different methods to accurately measure furthermore cell properties in microscope blood film images. The blood images are exposed to series of pre-processing steps which include color correlation, and contrast enhancement. By performing K-means clustering on the resultant images, the nuclei of the cells under consideration are obtained. Shape features and texture features are then extracted for classification. The system is further tested on the classification of spectra measured from the cell nuclei in blood samples in order to distinguish normal cells from those affected by Acute Lymphoblastic Leukemia. The results show that the proposed system robustly segments and classifies acute lymphoblastic leukemia based on complete microscopic blood images.

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

USGS Publications Warehouse

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

2010-01-01

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

Forecast Mekong 2012: Building scientific capacity

USGS Publications Warehouse

Stefanov, James E.

2012-01-01

In 2009, U.S. Secretary of State Hillary R. Clinton joined the Foreign Ministers of Cambodia, Laos, Thailand, and Vietnam in launching the Lower Mekong Initiative to enhance U.S. engagement with the countries of the Lower Mekong River Basin in the areas of environment, health, education, and infrastructure. The U.S. Geological Survey Forecast Mekong supports the Lower Mekong Initiative through a variety of activities. The principal objectives of Forecast Mekong include the following: * Build scientific capacity in the Lower Mekong Basin and promote cooperation and collaboration among scientists working in the region. * Provide data, information, and scientific models to help resource managers there make informed decisions. * Produce forecasting and visualization tools to support basin planning, including climate change adaptation. The focus of this product is Forecast Mekong accomplishments and current activities related to the development of scientific capacity at organizations and institutions in the region. Building on accomplishments in 2010 and 2011, Forecast Mekong continues to enhance scientific capacity in the Lower Mekong Basin with a suite of activities in 2012.

Building Fire Behavior Analyst (FBAN) capability and capacity: Lessons learned From Victoria, Australia's Bushfire Behavior Predictive Services Strategy

Treesearch

K. E. Gibos; A. Slijepcevic; T. Wells; L. Fogarty

2015-01-01

Wildland fire managers must frequently make meaning from chaos in order to protect communities and infrastructure from the negative impacts of fire. Fire management personnel are increasingly turning to science to support their experience-based decision-making processes and to provide clear, confident leadership for communities frequently exposed to risk from wildfire...

Every Voice Counts: Holding a Shared Leadership Event To Make Decisions Together.

ERIC Educational Resources Information Center

Strauss, Jessica

Shared leadership is a process empowering parents to exercise their civil rights, build leadership skills, and guide the design of policy positions and programs meant to improve their lives and the well-being of their children. Based on principles of family support practice, this book describes how to plan and host a 1- to 3-day shared leadership…

Building Research-Practice Partnerships as a District-Led Initiative: A High-Leverage Strategy for System Improvement

ERIC Educational Resources Information Center

Muñoz, Marco A.

2016-01-01

Research-Practice Partnerships (RPP) can enable and support an evidence-based school culture for decision-making in districts across the nation. Based on our experiences in a large urban district, a key element for a successful RPP is to understand that school districts have their own research needs/agenda typically articulated in strategic plans.…

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.

[Use of the computer as a tool for the implementation of the nursing process--the experience of the Sâo Paulo/UNIFESP].

PubMed

de Barros, Alba Lúcia; Fakih, Flávio Trevisani; Michel, Jeanne Liliane

2002-01-01

This article reports the pathway used to build a prototype of a computer nurse's clinical decision making support system, using NANDA, NIC and NOC classifications, as an auxiliary tool in the insertion of nursing data in the computerized patient record of Hospital São Paulo/UNIFESP.

A Grant Project to Initiate School Counselors' Development of a Multi-Tiered System of Supports Based on Social-Emotional Data

ERIC Educational Resources Information Center

Harrington, Karen; Griffith, Catherine; Gray, Katharine; Greenspan, Scott

2016-01-01

This article provides an overview of a grant project designed to create a district-wide elementary school counseling program with a strong data-based decision-making process. Project goals included building data literacy skills among school counselors and developing the infrastructure to efficiently collect important social-emotional indicators…

Emotional engagement with participatory simulations as a tool for learning and decision-support for coupled human-natural systems: Flood hazards and urban development

NASA Astrophysics Data System (ADS)

Gilligan, J. M.; Corey, B.; Camp, J. V.; John, N. J.; Sengupta, P.

2015-12-01

The complex interactions between land use and natural hazards pose serious challenges in education, research, and public policy. Where complex nonlinear interactions produce unintuitive results, interactive computer simulations can be useful tools for education and decision support. Emotions play important roles in cognition and learning, especially where risks are concerned. Interactive simulations have the potential to harness emotional engagement to enhance learning and understanding of risks in coupled human-natural systems. We developed a participatory agent-based simulation of cities at risk of river flooding. Participants play the role of managers of neighboring cities along a flood-prone river and make choices about building flood walls to protect their inhabitants. Simulated agents participate in dynamic real estate markets in which demand for property, and thus values and decisions to build, respond to experience with flooding over time. By reducing high-frequency low-magnitude flooding, flood walls may stimulate development, thus increasing tax revenues but also increasing vulnerability to uncommon floods that overtop the walls. Flood waves are launched stochastically and propagate downstream. Flood walls that restrict overbank flow at one city can increase the amplitude of a flood wave at neighboring cities, both up and downstream. We conducted a pilot experiment with a group of three pre-service teachers. The subjects successfully learned key concepts of risk tradeoffs and unintended consequences that can accompany flood-control measures. We also observed strong emotional responses, including hope, fear, and sense of loss. This emotional engagement with a model of coupled human-natural systems was very different from previous experiments on participatory simulations of purely natural systems for physics pedagogy. We conducted a second session in which the participants were expert engineers. We will present the results of these experiments and the prospects for using such models for middle-school, high-school, and post-secondary environmental science pedagogy, for improving public understanding of flood risks, and as decision support tools for planners.

Bridging the Gap Between NASA Earth Observations and Decision Makers Through the NASA Develop National Program

NASA Astrophysics Data System (ADS)

Remillard, C. M.; Madden, M.; Favors, J.; Childs-Gleason, L.; Ross, K. W.; Rogers, L.; Ruiz, M. L.

2016-06-01

The NASA DEVELOP National Program bridges the gap between NASA Earth Science and society by building capacity in both participants and partner organizations that collaborate to conduct projects. These rapid feasibility projects highlight the capabilities of satellite and aerial Earth observations. Immersion of decision and policy makers in these feasibility projects increases awareness of the capabilities of Earth observations and contributes to the tools and resources available to support enhanced decision making. This paper will present the DEVELOP model, best practices, and two case studies, the Colombia Ecological Forecasting project and the Miami-Dade County Ecological Forecasting project, that showcase the successful adoption of tools and methods for decision making. Through over 90 projects each year, DEVELOP is always striving for the innovative, practical, and beneficial use of NASA Earth science data.

Perspectives of decision-making in requests for euthanasia: a qualitative research among patients, relatives and treating physicians in the Netherlands.

PubMed

Dees, Marianne K; Vernooij-Dassen, Myrra J; Dekkers, Wim J; Elwyn, Glyn; Vissers, Kris C; van Weel, Chris

2013-01-01

Euthanasia has been legally performed in the Netherlands since 2002. Respect for patient's autonomy is the underpinning ethical principal. However, patients have no right to euthanasia, and physicians have no obligation to provide it. Although over 3000 cases are conducted per year in the Netherlands, there is little known about how decision-making occurs and no guidance to support this difficult aspect of clinical practice. To explore the decision-making process in cases where patients request euthanasia and understand the different themes relevant to optimise this decision-making process. A qualitative thematic analysis of interviews with patients making explicit requests for euthanasia, most-involved relative(s) and treating physician. Thirty-two cases, 31 relatives and 28 treating physicians. Settings were patients' and relatives' homes and physicians' offices. Five main themes emerged: (1) initiation of sharing views and values about euthanasia, (2) building relationships as part of the negotiation, (3) fulfilling legal requirements, (4) detailed work of preparing and performing euthanasia and (5) aftercare and closing. A patient's request for euthanasia entails a complex process that demands emotional work by all participants. It is characterised by an intensive period of sharing information, relationship building and negotiation in order to reach agreement. We hypothesise that making decisions about euthanasia demands a proactive approach towards participants' preferences and values regarding end of life, towards the needs of relatives, towards the burden placed on physicians and a careful attention to shared decision-making. Future research should address the communicational skills professionals require for such complex decision-making.

Explaining Moral Behavior.

PubMed

Osman, Magda; Wiegmann, Alex

2017-03-01

In this review we make a simple theoretical argument which is that for theory development, computational modeling, and general frameworks for understanding moral psychology researchers should build on domain-general principles from reasoning, judgment, and decision-making research. Our approach is radical with respect to typical models that exist in moral psychology that tend to propose complex innate moral grammars and even evolutionarily guided moral principles. In support of our argument we show that by using a simple value-based decision model we can capture a range of core moral behaviors. Crucially, the argument we propose is that moral situations per se do not require anything specialized or different from other situations in which we have to make decisions, inferences, and judgments in order to figure out how to act.

Image-guided decision support system for pulmonary nodule classification in 3D thoracic CT images

NASA Astrophysics Data System (ADS)

Kawata, Yoshiki; Niki, Noboru; Ohmatsu, Hironobu; Kusumoto, Masahiro; Kakinuma, Ryutaro; Mori, Kiyoshi; Yamada, Kozo; Nishiyama, Hiroyuki; Eguchi, Kenji; Kaneko, Masahiro; Moriyama, Noriyuki

2004-05-01

The purpose of this study is to develop an image-guided decision support system that assists decision-making in clinical differential diagnosis of pulmonary nodules. This approach retrieves and displays nodules that exhibit morphological and internal profiles consistent to the nodule in question. It uses a three-dimensional (3-D) CT image database of pulmonary nodules for which diagnosis is known. In order to build the system, there are following issues that should be solved: 1) to categorize the nodule database with respect to morphological and internal features, 2) to quickly search nodule images similar to an indeterminate nodule from a large database, and 3) to reveal malignancy likelihood computed by using similar nodule images. Especially, the first problem influences the design of other issues. The successful categorization of nodule pattern might lead physicians to find important cues that characterize benign and malignant nodules. This paper focuses on an approach to categorize the nodule database with respect to nodule shape and CT density patterns inside nodule.

Collaboration and co-production of climate knowledge: lessons from a network on the front-line

NASA Astrophysics Data System (ADS)

Kettle, N.

2016-12-01

The science-practice gap is broadly considered a major barrier to the production and application of decision-relevant science. This study uses a social network analysis, based on 126 interviews, to analyze the roles and network ties among climate scientists, service providers, and decision makers in Alaska. Our research highlights the importance of key actors and significant differences in bonding and bridging ties across roles - structural characteristics that provide a basis for informing recommendations to build adaptive capacity and support the co-production of knowledge. Our findings also illustrate that some individuals in the network engage in multiple roles, suggesting that conceptualizing the science-practice interface as consisting of "producers" and "consumers" oversimplifies how individuals engage in climate science, services, and decision making. This research supports the notion that the development and use of climate information is a networked phenomenon. It also emphasizes the importance of centralized individuals who are capable of engaging in multiple roles for the transition of knowledge action.

Developing User-Driven Climate Information Services to Build Resilience Amongst Groups at Risk of Drought and Flood in Arid and Semi-Arid Land Counties in Kenya

NASA Astrophysics Data System (ADS)

Githungo, W. N.; Shaka, A.; Kniveton, D.; Muithya, L.; Powell, R.; Visman, E. L.

2014-12-01

The Arid and Semi-Arid Land (ASAL) counties of Kitui and Makueni in Kenya are experiencing increasing climate variability in seasonal rainfall, including changes in the onset, cessation and distribution of the two principal rains upon which the majority of the population's small-holder farmers and livestock keepers depend. Food insecurity is prevalent with significant numbers also affected by flooding during periods of intense rainfall. As part of a multi-partner Adaptation Consortium, Kenya Meteorological Services (KMS) are developing Climate Information Services (CIS) which can better support decision making amongst the counties' principal livelihoods groups and across County Government ministries. Building on earlier pilots and stakeholder discussion, the system combines the production of climate information tailored for transmission via regional and local radio stations with the establishment of a new SMS service. SMS are provided through a network of CIS intermediaries drawn from across key government ministries, religious networks, non-governmental and community groups, aiming to achieve one SMS recipient per 3-500 people. It also introduces a demand-led, premium-rate SMS weather information service which is designed to be self-financing in the long term. Supporting the ongoing process of devolution, KMS is downscaling national forecasts for each county, and providing seasonal, monthly, weekly and daily forecasts, as well as warnings of weather-related hazards. Through collaboration with relevant ministries, government bodies and research institutions, including livestock, agriculture, drought management and health, technical advisories are developed to provide guidance on application of the climate information. The system seeks to provide timely, relevant information which can enable people to use weather and climate information to support decisions which protect life and property and build resilience to ongoing climate variability and future change.

Gain Modulation by an Urgency Signal Controls the Speed–Accuracy Trade-Off in a Network Model of a Cortical Decision Circuit

PubMed Central

Standage, Dominic; You, Hongzhi; Wang, Da-Hui; Dorris, Michael C.

2011-01-01

The speed–accuracy trade-off (SAT) is ubiquitous in decision tasks. While the neural mechanisms underlying decisions are generally well characterized, the application of decision-theoretic methods to the SAT has been difficult to reconcile with experimental data suggesting that decision thresholds are inflexible. Using a network model of a cortical decision circuit, we demonstrate the SAT in a manner consistent with neural and behavioral data and with mathematical models that optimize speed and accuracy with respect to one another. In simulations of a reaction time task, we modulate the gain of the network with a signal encoding the urgency to respond. As the urgency signal builds up, the network progresses through a series of processing stages supporting noise filtering, integration of evidence, amplification of integrated evidence, and choice selection. Analysis of the network's dynamics formally characterizes this progression. Slower buildup of urgency increases accuracy by slowing down the progression. Faster buildup has the opposite effect. Because the network always progresses through the same stages, decision-selective firing rates are stereotyped at decision time. PMID:21415911

Gain modulation by an urgency signal controls the speed-accuracy trade-off in a network model of a cortical decision circuit.

PubMed

Standage, Dominic; You, Hongzhi; Wang, Da-Hui; Dorris, Michael C

2011-01-01

The speed-accuracy trade-off (SAT) is ubiquitous in decision tasks. While the neural mechanisms underlying decisions are generally well characterized, the application of decision-theoretic methods to the SAT has been difficult to reconcile with experimental data suggesting that decision thresholds are inflexible. Using a network model of a cortical decision circuit, we demonstrate the SAT in a manner consistent with neural and behavioral data and with mathematical models that optimize speed and accuracy with respect to one another. In simulations of a reaction time task, we modulate the gain of the network with a signal encoding the urgency to respond. As the urgency signal builds up, the network progresses through a series of processing stages supporting noise filtering, integration of evidence, amplification of integrated evidence, and choice selection. Analysis of the network's dynamics formally characterizes this progression. Slower buildup of urgency increases accuracy by slowing down the progression. Faster buildup has the opposite effect. Because the network always progresses through the same stages, decision-selective firing rates are stereotyped at decision time.

Personalization and Patient Involvement in Decision Support Systems: Current Trends

PubMed Central

Sacchi, L.; Lanzola, G.; Viani, N.

2015-01-01

Summary Objectives This survey aims at highlighting the latest trends (2012-2014) on the development, use, and evaluation of Information and Communication Technologies (ICT) based decision support systems (DSSs) in medicine, with a particular focus on patient-centered and personalized care. Methods We considered papers published on scientific journals, by querying PubMed and Web of Science™. Included studies focused on the implementation or evaluation of ICT-based tools used in clinical practice. A separate search was performed on computerized physician order entry systems (CPOEs), since they are increasingly embedding patient-tailored decision support. Results We found 73 papers on DSSs (53 on specific ICT tools) and 72 papers on CPOEs. Although decision support through the delivery of recommendations is frequent (28/53 papers), our review highlighted also DSSs only based on efficient information presentation (25/53). Patient participation in making decisions is still limited (9/53), and mostly focused on risk communication. The most represented medical area is cancer (12%). Policy makers are beginning to be included among stakeholders (6/73), but integration with hospital information systems is still low. Concerning knowledge representation/management issues, we identified a trend towards building inference engines on top of standard data models. Most of the tools (57%) underwent a formal assessment study, even if half of them aimed at evaluating usability and not effectiveness. Conclusions Overall, we have noticed interesting evolutions of medical DSSs to improve communication with the patient, consider the economic and organizational impact, and use standard models for knowledge representation. However, systems focusing on patient-centered care still do not seem to be available at large. PMID:26293857

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

Jones, D.W.

In previous reports, we have identified two potentially important issues, solutions to which would increase the attractiveness of DOE-developed technologies in commercial buildings energy systems. One issue concerns the fact that in addition to saving energy, many new technologies offer non-energy benefits that contribute to building productivity (firm profitability). The second issue is that new technologies are typically unproven in the eyes of decision makers and must bear risk premiums that offset cost advantages resulting from laboratory calculations. Even though a compelling case can be made for the importance of these issues, for building decision makers to incorporate them inmore » business decisions and for DOE to use them in R&D program planning there must be robust empirical evidence of their existence and size. This paper investigates how such measurements could be made and offers recommendations as to preferred options. There is currently little systematic information on either of these concepts in the literature. Of the two there is somewhat more information on non-energy benefits, but little as regards office buildings. Office building productivity impacts can be observed casually, but must be estimated statistically, because buildings have many interacting attributes and observations based on direct behavior can easily confuse the process of attribution. For example, absenteeism can be easily observed. However, absenteeism may be down because a more healthy space conditioning system was put into place, because the weather was milder, or because firm policy regarding sick days had changed. There is also a general dearth of appropriate information for purposes of estimation. To overcome these difficulties, we propose developing a new data base and applying the technique of hedonic price analysis. This technique has been used extensively in the analysis of residential dwellings. There is also a literature on its application to commercial and industrial buildings. Commercially available data bases exist that, if supplemented with engineering survey for equipment and materials use, could be analyzed statistically with a hedonic price model for the valuation of both the energy-saving and productivity effects of building technologies. Uncertainties about technology performance can cause investors to delay deploying new technologies. This behavior is explained by the ''investment under uncertainty'' literature. This literature suggests that under conditions of irrecoverable (''sunk'') costs, uncertain outcomes, and the ability to defer deployment, decision makers focus on potential losses and demand risk premiums and a few support the notion of focusing on losses, the so-called ''bad news principle.'' We describe a series of approaches to isolating buyer perceptions of uncertainty and means for reducing uncertainty.« less

Facility Design and Health Management Program at the Sinnhuber Aquatic Research Laboratory

PubMed Central

Barton, Carrie L.; Johnson, Eric W.

2016-01-01

Abstract The number of researchers and institutions moving to the utilization of zebrafish for biomedical research continues to increase because of the recognized advantages of this model. Numerous factors should be considered before building a new or retooling an existing facility. Design decisions will directly impact the management and maintenance costs. We and others have advocated for more rigorous approaches to zebrafish health management to support and protect an increasingly diverse portfolio of important research. The Sinnhuber Aquatic Research Laboratory (SARL) is located ∼3 miles from the main Oregon State University campus in Corvallis, Oregon. This facility supports several research programs that depend heavily on the use of adult, larval, and embryonic zebrafish. The new zebrafish facility of the SARL began operation in 2007 with a commitment to build and manage an efficient facility that diligently protects human and fish health. An important goal was to ensure that the facility was free of Pseudoloma neurophilia (Microsporidia), which is very common in zebrafish research facilities. We recognize that there are certain limitations in space, resources, and financial support that are institution dependent, but in this article, we describe the steps taken to build and manage an efficient specific pathogen-free facility. PMID:26981844

Facility Design and Health Management Program at the Sinnhuber Aquatic Research Laboratory.

PubMed

Barton, Carrie L; Johnson, Eric W; Tanguay, Robert L

2016-07-01

The number of researchers and institutions moving to the utilization of zebrafish for biomedical research continues to increase because of the recognized advantages of this model. Numerous factors should be considered before building a new or retooling an existing facility. Design decisions will directly impact the management and maintenance costs. We and others have advocated for more rigorous approaches to zebrafish health management to support and protect an increasingly diverse portfolio of important research. The Sinnhuber Aquatic Research Laboratory (SARL) is located ∼3 miles from the main Oregon State University campus in Corvallis, Oregon. This facility supports several research programs that depend heavily on the use of adult, larval, and embryonic zebrafish. The new zebrafish facility of the SARL began operation in 2007 with a commitment to build and manage an efficient facility that diligently protects human and fish health. An important goal was to ensure that the facility was free of Pseudoloma neurophilia (Microsporidia), which is very common in zebrafish research facilities. We recognize that there are certain limitations in space, resources, and financial support that are institution dependent, but in this article, we describe the steps taken to build and manage an efficient specific pathogen-free facility.

Mean-variance portfolio analysis data for optimizing community-based photovoltaic investment

PubMed Central

Shakouri, Mahmoud; Lee, Hyun Woo

2016-01-01

The amount of electricity generated by Photovoltaic (PV) systems is affected by factors such as shading, building orientation and roof slope. To increase electricity generation and reduce volatility in generation of PV systems, a portfolio of PV systems can be made which takes advantages of the potential synergy among neighboring buildings. This paper contains data supporting the research article entitled: PACPIM: new decision-support model of optimized portfolio analysis for community-based photovoltaic investment [1]. We present a set of data relating to physical properties of 24 houses in Oregon, USA, along with simulated hourly electricity data for the installed PV systems. The developed Matlab code to construct optimized portfolios is also provided in Supplementary materials. The application of these files can be generalized to variety of communities interested in investing on PV systems. PMID:26937458

Military Interoperable Digital Hospital Testbed (MIDHT)

DTIC Science & Technology

2010-02-01

note build and system setup. There was significant progress in identifying workflows and processes. A sample note for a patient visit can be seen...between EMR systems did not exist when surveys were completed in early 2009. There is a significant opportunity to enhance patient care of military...interpret the provider’s handwriting . Many EHRs have included decision support into their functionality to help alert physicians to medication conflicts

RECOVER - An Automated Burned Area Emergency Response Decision Support System for Post-fire Rehabilitation Management of Savanna Ecosystems in the Western US

NASA Astrophysics Data System (ADS)

Weber, K.; Schnase, J. L.; Carroll, M.; Brown, M. E.; Gill, R.; Haskett, G.; Gardner, T.

2013-12-01

In partnership with the Department of Interior's Bureau of Land Management (BLM) and the Idaho Department of Lands (IDL), we are building and evaluating the RECOVER decision support system. RECOVER - which stands for Rehabilitation Capability Convergence for Ecosystem Recovery - is an automatically deployable, context-aware decision support system for savanna wildfires that brings together in a single application the information necessary for post-fire rehabilitation decision-making and long-term ecosystem monitoring. RECOVER uses state-of-the-art cloud-based data management technologies to improve performance, reduce cost, and provide site-specific flexibility for each fire. The RECOVER Server uses Integrated Rule-Oriented Data System (iRODS) data grid technology deployed in the Amazon Elastic Compute Cloud (EC2). The RECOVER Client is an Adobe Flex web map application that is able to provide a suite of convenient GIS analytical capabilities. In a typical use scenario, the RECOVER Server is provided a wildfire name and geospatial extent. The Server then automatically gathers Earth observational data and other relevant products from various geographically distributed data sources. The Server creates a database in the cloud where all relevant information about the wildfire is stored. This information is made available to the RECOVER Client and ultimately to fire managers through their choice of web browser. The Server refreshes the data throughout the burn and subsequent recovery period (3-5 years) with each refresh requiring two minutes to complete. Since remediation plans must be completed within 14 days of a fire's containment, RECOVER has the potential to significantly improve the decision-making process. RECOVER adds an important new dimension to post-fire decision-making by focusing on ecosystem rehabilitation in semiarid savannas. A novel aspect of RECOVER's approach involves the use of soil moisture estimates, which are an important but difficult-to-obtain element of post-fire rehabilitation planning. We will use downscaled soil moisture data from three primary observational sources to begin evaluation of soil moisture products and build the technology needed for RECOVER to use future SMAP products. As a result, RECOVER, BLM, and the fire applications community will be ready customers for data flowing out of new NASA missions, such as NPP, LDCM, and SMAP.

Towards a Decision Support System for Space Flight Operations

NASA Technical Reports Server (NTRS)

Meshkat, Leila; Hogle, Charles; Ruszkowski, James

2013-01-01

The Mission Operations Directorate (MOD) at the Johnson Space Center (JSC) has put in place a Model Based Systems Engineering (MBSE) technological framework for the development and execution of the Flight Production Process (FPP). This framework has provided much added value and return on investment to date. This paper describes a vision for a model based Decision Support System (DSS) for the development and execution of the FPP and its design and development process. The envisioned system extends the existing MBSE methodology and technological framework which is currently in use. The MBSE technological framework currently in place enables the systematic collection and integration of data required for building an FPP model for a diverse set of missions. This framework includes the technology, people and processes required for rapid development of architectural artifacts. It is used to build a feasible FPP model for the first flight of spacecraft and for recurrent flights throughout the life of the program. This model greatly enhances our ability to effectively engage with a new customer. It provides a preliminary work breakdown structure, data flow information and a master schedule based on its existing knowledge base. These artifacts are then refined and iterated upon with the customer for the development of a robust end-to-end, high-level integrated master schedule and its associated dependencies. The vision is to enhance this framework to enable its application for uncertainty management, decision support and optimization of the design and execution of the FPP by the program. Furthermore, this enhanced framework will enable the agile response and redesign of the FPP based on observed system behavior. The discrepancy of the anticipated system behavior and the observed behavior may be due to the processing of tasks internally, or due to external factors such as changes in program requirements or conditions associated with other organizations that are outside of MOD. The paper provides a roadmap for the three increments of this vision. These increments include (1) hardware and software system components and interfaces with the NASA ground system, (2) uncertainty management and (3) re-planning and automated execution. Each of these increments provide value independently; but some may also enable building of a subsequent increment.

A Multi-Tiered Approach for Building Capacity in Hydrologic Modeling for Water Resource Management in Developing Regions

NASA Astrophysics Data System (ADS)

Markert, K. N.; Limaye, A. S.; Rushi, B. R.; Adams, E. C.; Anderson, E.; Ellenburg, W. L.; Mithieu, F.; Griffin, R.

2017-12-01

Water resource management is the process by which governments, businesses and/or individuals reach and implement decisions that are intended to address the future quantity and/or quality of water for societal benefit. The implementation of water resource management typically requires the understanding of the quantity and/or timing of a variety of hydrologic variables (e.g. discharge, soil moisture and evapotranspiration). Often times these variables for management are simulated using hydrologic models particularly in data sparse regions. However, there are several large barriers to entry in learning how to use models, applying best practices during the modeling process, and selecting and understanding the most appropriate model for diverse applications. This presentation focuses on a multi-tiered approach to bring the state-of-the-art hydrologic modeling capabilities and methods to developing regions through the SERVIR program, a joint NASA and USAID initiative that builds capacity of regional partners and their end users on the use of Earth observations for environmental decision making. The first tier is a series of trainings on the use of multiple hydrologic models, including the Variable Infiltration Capacity (VIC) and Ensemble Framework For Flash Flood Forecasting (EF5), which focus on model concepts and steps to successfully implement the models. We present a case study for this in a pilot area, the Nyando Basin in Kenya. The second tier is focused on building a community of practice on applied hydrology modeling aimed at creating a support network for hydrologists in SERVIR regions and promoting best practices. The third tier is a hydrologic inter-comparison project under development in the SERVIR regions. The objective of this step is to understand model performance under specific decision-making scenarios, and to share knowledge among hydrologists in SERVIR regions. The results of these efforts include computer programs, training materials, and new scientific understanding, all of which are shared in an open and collaborative environment for transparency and subsequent capacity building in SERVIR regions and beyond. The outcome of this work is increased awareness and capacity on the use of hydrologic models in developing regions to support water resource management and water security.

Capacity Building to Support Governmental Meteorological and Agricultural Communities in East Africa

NASA Astrophysics Data System (ADS)

Granger, S. L.; Macharia, D.; Das, N.; Andreadis, K.; Ines, A.

2016-12-01

There is a recognized need for data to support decision-making and planning in East Africa where people and national economies depend on rain fed agriculture and are vulnerable to a changing climate and extreme weather events. However, capacity to use existing global data stores and transition promising tools is a gap that severely limits the use and adoption of these data and tools. Although most people think of capacity building as simply training, it is really much more than that and has been more thoroughly described in the public health community as…."the process of developing and strengthening the skills, instincts, abilities, processes and resources that organizations and communities need to survive, adapt, and thrive in the fast-changing world." Data and tools from NASA and other providers are often not used as they could be for technical and institutional reasons. On the technical side, there is the perception that global data stores are impenetrable requiring special expertise to access them, even if the data can be accessed, the technical expertise to understand and use the data and tools may be lacking, and there can be a mismatch between science data and existing user tools. On the institutional side, it may be perceived that remote sensing data and tools are too "expensive", support from upper management may be non-existent due to limited resources or lack of interest, and there can be a lack of appreciation of data and statistics in decision making. How do we overcome some of these barriers to advance the use of remote sensing for applications and to ease transition of data and tools to stakeholders? Experience from recent capacity building efforts in East Africa in support of a NASA-SERVIR Applied Science Project to provide estimates of hydrologic extremes tied to crop yield will be discussed.

“Kinect-ing” With Clinicians: A Knowledge Translation Resource to Support Decision Making About Video Game Use in Rehabilitation

PubMed Central

Levac, Danielle; Espy, Deborah; Fox, Emily; Pradhan, Sujata

2015-01-01

Microsoft's Kinect for Xbox 360 virtual reality (VR) video games are promising rehabilitation options because they involve motivating, full-body movement practice. However, these games were designed for recreational use, which creates challenges for clinical implementation. Busy clinicians require decision-making support to inform game selection and implementation that address individual therapeutic goals. This article describes the development and preliminary evaluation of a knowledge translation (KT) resource to support clinical decision making about selection and use of Kinect games in physical therapy. The knowledge-to-action framework guided the development of the Kinecting With Clinicians (KWiC) resource. Five physical therapists with VR and video game expertise analyzed the Kinect Adventure games. A consensus-building method was used to arrive at categories to organize clinically relevant attributes guiding game selection and game play. The process and results of an exploratory usability evaluation of the KWiC resource by clinicians through interviews and focus groups at 4 clinical sites is described. Subsequent steps in the evaluation and KT process are proposed, including making the KWiC resource Web-based and evaluating the utility of the online resource in clinical practice. PMID:25256741

Detection of cyst using image segmentation and building knowledge-based intelligent decision support system as an aid to telemedicine

NASA Astrophysics Data System (ADS)

Janet, J.; Natesan, T. R.; Santhosh, Ramamurthy; Ibramsha, Mohideen

2005-02-01

An intelligent decision support tool to the Radiologist in telemedicine is described. Medical prescriptions are given based on the images of cyst that has been transmitted over computer networks to the remote medical center. The digital image, acquired by sonography, is converted into an intensity image. This image is then subjected to image preprocessing which involves correction methods to eliminate specific artifacts. The image is resized into a 256 x 256 matrix by using bilinear interpolation method. The background area is detected using distinct block operation. The area of the cyst is calculated by removing the background area from the original image. Boundary enhancement and morphological operations are done to remove unrelated pixels. This gives us the cyst volume. This segmented image of the cyst is sent to the remote medical center for analysis by Knowledge based artificial Intelligent Decision Support System (KIDSS). The type of cyst is detected and reported to the control mechanism of KIDSS. Then the inference engine compares this with the knowledge base and gives appropriate medical prescriptions or treatment recommendations by applying reasoning mechanisms at the remote medical center.

"Kinect-ing" with clinicians: a knowledge translation resource to support decision making about video game use in rehabilitation.

PubMed

Levac, Danielle; Espy, Deborah; Fox, Emily; Pradhan, Sujata; Deutsch, Judith E

2015-03-01

Microsoft's Kinect for Xbox 360 virtual reality (VR) video games are promising rehabilitation options because they involve motivating, full-body movement practice. However, these games were designed for recreational use, which creates challenges for clinical implementation. Busy clinicians require decision-making support to inform game selection and implementation that address individual therapeutic goals. This article describes the development and preliminary evaluation of a knowledge translation (KT) resource to support clinical decision making about selection and use of Kinect games in physical therapy. The knowledge-to-action framework guided the development of the Kinecting With Clinicians (KWiC) resource. Five physical therapists with VR and video game expertise analyzed the Kinect Adventure games. A consensus-building method was used to arrive at categories to organize clinically relevant attributes guiding game selection and game play. The process and results of an exploratory usability evaluation of the KWiC resource by clinicians through interviews and focus groups at 4 clinical sites is described. Subsequent steps in the evaluation and KT process are proposed, including making the KWiC resource Web-based and evaluating the utility of the online resource in clinical practice. © 2015 American Physical Therapy Association.

Elements of an environmental decision support system for seasonal wetland salt management in a river basin subjected to water quality regulation

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

Quinn, N.W.T.

Seasonally managed wetlands in the Grasslands Basin on the west-side of California's San Joaquin Valley provide food and shelter for migratory wildfowl during winter months and sport for waterfowl hunters during the annual duck season. Surface water supply to these wetlands contain salt which, when drained to the San Joaquin River during the annual drawdown period, can negatively impact water quality and cause concern to downstream agricultural riparian water diverters. Recent environmental regulation, limiting discharges salinity to the San Joaquin River and primarily targeting agricultural non-point sources, now also targets return flows from seasonally managed wetlands. Real-time water quality managementmore » has been advocated as a means of continuously matching salt loads discharged from agricultural, wetland and municipal operations to the assimilative capacity of the San Joaquin River. Past attempts to build environmental monitoring and decision support systems (EDSS's) to implement this concept have enjoyed limited success for reasons that are discussed in this paper. These reasons are discussed in the context of more general challenges facing the successful implementation of a comprehensive environmental monitoring, modelling and decision support system for the San Joaquin River Basin.« less

How to Choose? Using the Delphi Method to Develop Consensus Triggers and Indicators for Disaster Response.

PubMed

Lis, Rebecca; Sakata, Vicki; Lien, Onora

2017-08-01

To identify key decisions along the continuum of care (conventional, contingency, and crisis) and the critical triggers and data elements used to inform those decisions concerning public health and health care response during an emergency. A classic Delphi method, a consensus-building survey technique, was used with clinicians around Washington State to identify regional triggers and indicators. Additionally, using a modified Delphi method, we combined a workshop and single-round survey with panelists from public health (state and local) and health care coalitions to identify consensus state-level triggers and indicators. In the clinical survey, 122 of 223 proposed triggers or indicators (43.7%) reached consensus and were deemed important in regional decision-making during a disaster. In the state-level survey, 110 of 140 proposed triggers or indicators (78.6%) reached consensus and were deemed important in state-level decision-making during a disaster. The identification of consensus triggers and indicators for health care emergency response is crucial in supporting a comprehensive health care situational awareness process. This can inform the creation of standardized questions to ask health care, public health, and other partners to support decision-making during a response. (Disaster Med Public Health Preparedness. 2017;11:467-472).

[How to decide with precision, justice, and equity? Reflections on decision-making in the context of extreme prematurity. Part two: moving toward making the best possible decision: defining conditions for putting decisions into practice].

PubMed

Azria, E; Tsatsaris, V; Moriette, G; Hirsch, E; Schmitz, T; Cabrol, D; Goffinet, F

2007-05-01

Extreme premature child's long-term prognostic is getting better and better known, and if a resuscitation procedure is possible at birth, it won't guarantee survival or a survival free of disability. Incertitude toward individual prognosis and outcome for those children remains considerable. In this field, we are at the frontier of medical knowledge and the answer to the question, "how to decide the ante and postnatal care" is crucial. This work is focused on this problematic of decision-making in the context of extreme prematurity. It attempts to deconstruct this concept and to explicit its stakes. Thus, with the support of the medical sources and of philosophical debates, we tried to build a decision-making procedure that complies with the ethical requirements of medical care, accuracy, justice and equity. This decision-making procedure is primarily concerned with the singularity of each decision situation and it intends to link it closely to the notions of rationality and responsibility.

Design and implementation of a structural health monitoring and alerting system for hospital buildings in the United States

USGS Publications Warehouse

Ulusoy, Hasan S.; Kalkan, Erol; Fletcher, Jon Peter B.; Friberg, Paul; Leith, W. K.; Banga, Krishna

2012-01-01

This paper describes the current progress in the development of a structural health monitoring and alerting system to meet the needs of the U.S. Department of Veterans Affairs to monitor hospital buildings instrumented in high and very high seismic hazard regions in the U.S. The system, using the measured vibration data, is primarily designed for post-earthquake condition assessment of the buildings. It has two essential components – sensing and analysis. The sensing component includes all necessary firmware and sensors to measure the response of the building; while the analysis component consists of several data processing modules integrated into an open source software package which compresses a large amount of measured data into useful information to assess the building’s condition before and after an event. The information can be used for a rapid building safety assessment, and to support decisions for necessary repairs, replacements, and other maintenance and rehabilitation measures.

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

NASA Astrophysics Data System (ADS)

Pierce, S. A.

2014-12-01

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

Critical care physicians’ approaches to negotiating with surrogate decision makers: a qualitative study

PubMed Central

Brush, David R.; Brown, Crystal E.; Alexander, G. Caleb

2013-01-01

Objective To describe how critical care physicians manage conflicts with surrogates about withdrawing or withholding patients’ life support. Design Qualitative analysis of key informant interviews with critical care physicians during 2010. We transcribed interviews verbatim and used grounded theory to code and revise a taxonomy of themes and to identify illustrative quotes. Setting 3 academic medical centers, 1 academic-affiliated medical center and 4 private practice groups or private hospitals in a large Midwestern city Subjects 14 critical care physicians Measurements and main results Physicians reported tailoring their approach to address specific reasons for disagreement with surrogates. Five common approaches were identified: (1) building trust, (2) educating and informing, (3) providing surrogates more time, (4) adjusting surrogate and physician roles, and (5) highlighting specific values. When mistrust was an issue, physicians endeavored to build a more trusting relationship with the surrogate before re-addressing decision making. Physicians also reported correcting misunderstandings by providing targeted education, and some reported highlighting specific patient, surrogate, or physician values that they hoped would guide surrogates to agree with them. When surrogates struggled with decision making roles, physicians attempted to reinforce the concept of substituted judgment. Physicians noted that some surrogates needed time to “come to terms” with the patent’s illness before agreeing with physicians. Many physicians had witnessed colleagues negotiate in ways they found objectionable, such as providing misleading information, injecting their own values into the negotiation, or behaving unprofessionally towards surrogates. While some physicians viewed their efforts to encourage surrogates’ agreement as persuasive, others strongly denied persuading surrogates and described their actions as “guiding” or “negotiating.” Conclusions Physicians reported using a tailored approach to resolve decisional conflicts about life support; and attempted to change surrogates’ decisions in accordance with what the physician thought was in the patients’ best interests. While physicians acknowledged their efforts to change surrogate’s decisions, many physicians did not perceive these as persuasive. PMID:22080645

Examining key design decisions involved in developing a serious game for child sexual abuse prevention.

PubMed

Stieler-Hunt, Colleen; Jones, Christian M; Rolfe, Ben; Pozzebon, Kay

2014-01-01

This paper presents a case study of the key decisions made in the design of Orbit, a child sexual abuse prevention computer game targeted at school students between 8 and 10 years of age. Key decisions include providing supported delivery for the target age group, featuring adults in the program, not over-sanitizing game content, having a focus on building healthy self-concept of players, making the game engaging and relatable for all players and evaluating the program. This case study has implications for the design of Serious Games more generally, including that research should underpin game design decisions, game designers should consider ways of bridging the game to real life, the learning that arises from the game should go beyond rote-learning, designers should consider how the player can make the game-world their own and comprehensive evaluations of Serious Games should be undertaken.

Quick Fix for Managing Risks

NASA Technical Reports Server (NTRS)

2002-01-01

Under a Phase II SBIR contract, Kennedy and Lumina Decision Systems, Inc., jointly developed the Schedule and Cost Risk Analysis Modeling (SCRAM) system, based on a version of Lumina's flagship software product, Analytica(R). Acclaimed as "the best single decision-analysis program yet produced" by MacWorld magazine, Analytica is a "visual" tool used in decision-making environments worldwide to build, revise, and present business models, minus the time-consuming difficulty commonly associated with spreadsheets. With Analytica as their platform, Kennedy and Lumina created the SCRAM system in response to NASA's need to identify the importance of major delays in Shuttle ground processing, a critical function in project management and process improvement. As part of the SCRAM development project, Lumina designed a version of Analytica called the Analytica Design Engine (ADE) that can be easily incorporated into larger software systems. ADE was commercialized and utilized in many other developments, including web-based decision support.

Examining key design decisions involved in developing a serious game for child sexual abuse prevention

PubMed Central

Stieler-Hunt, Colleen; Jones, Christian M.; Rolfe, Ben; Pozzebon, Kay

2014-01-01

This paper presents a case study of the key decisions made in the design of Orbit, a child sexual abuse prevention computer game targeted at school students between 8 and 10 years of age. Key decisions include providing supported delivery for the target age group, featuring adults in the program, not over-sanitizing game content, having a focus on building healthy self-concept of players, making the game engaging and relatable for all players and evaluating the program. This case study has implications for the design of Serious Games more generally, including that research should underpin game design decisions, game designers should consider ways of bridging the game to real life, the learning that arises from the game should go beyond rote-learning, designers should consider how the player can make the game-world their own and comprehensive evaluations of Serious Games should be undertaken. PMID:24550880

Towards a Decision Support Tool for 3d Visualisation: Application to Selectivity Purpose of Single Object in a 3d City Scene

NASA Astrophysics Data System (ADS)

Neuville, R.; Pouliot, J.; Poux, F.; Hallot, P.; De Rudder, L.; Billen, R.

2017-10-01

This paper deals with the establishment of a comprehensive methodological framework that defines 3D visualisation rules and its application in a decision support tool. Whilst the use of 3D models grows in many application fields, their visualisation remains challenging from the point of view of mapping and rendering aspects to be applied to suitability support the decision making process. Indeed, there exists a great number of 3D visualisation techniques but as far as we know, a decision support tool that facilitates the production of an efficient 3D visualisation is still missing. This is why a comprehensive methodological framework is proposed in order to build decision tables for specific data, tasks and contexts. Based on the second-order logic formalism, we define a set of functions and propositions among and between two collections of entities: on one hand static retinal variables (hue, size, shape…) and 3D environment parameters (directional lighting, shadow, haze…) and on the other hand their effect(s) regarding specific visual tasks. It enables to define 3D visualisation rules according to four categories: consequence, compatibility, potential incompatibility and incompatibility. In this paper, the application of the methodological framework is demonstrated for an urban visualisation at high density considering a specific set of entities. On the basis of our analysis and the results of many studies conducted in the 3D semiotics, which refers to the study of symbols and how they relay information, the truth values of propositions are determined. 3D visualisation rules are then extracted for the considered context and set of entities and are presented into a decision table with a colour coding. Finally, the decision table is implemented into a plugin developed with three.js, a cross-browser JavaScript library. The plugin consists of a sidebar and warning windows that help the designer in the use of a set of static retinal variables and 3D environment parameters.

Neural network modeling for surgical decisions on traumatic brain injury patients.

PubMed

Li, Y C; Liu, L; Chiu, W T; Jian, W S

2000-01-01

Computerized medical decision support systems have been a major research topic in recent years. Intelligent computer programs were implemented to aid physicians and other medical professionals in making difficult medical decisions. This report compares three different mathematical models for building a traumatic brain injury (TBI) medical decision support system (MDSS). These models were developed based on a large TBI patient database. This MDSS accepts a set of patient data such as the types of skull fracture, Glasgow Coma Scale (GCS), episode of convulsion and return the chance that a neurosurgeon would recommend an open-skull surgery for this patient. The three mathematical models described in this report including a logistic regression model, a multi-layer perceptron (MLP) neural network and a radial-basis-function (RBF) neural network. From the 12,640 patients selected from the database. A randomly drawn 9480 cases were used as the training group to develop/train our models. The other 3160 cases were in the validation group which we used to evaluate the performance of these models. We used sensitivity, specificity, areas under receiver-operating characteristics (ROC) curve and calibration curves as the indicator of how accurate these models are in predicting a neurosurgeon's decision on open-skull surgery. The results showed that, assuming equal importance of sensitivity and specificity, the logistic regression model had a (sensitivity, specificity) of (73%, 68%), compared to (80%, 80%) from the RBF model and (88%, 80%) from the MLP model. The resultant areas under ROC curve for logistic regression, RBF and MLP neural networks are 0.761, 0.880 and 0.897, respectively (P < 0.05). Among these models, the logistic regression has noticeably poorer calibration. This study demonstrated the feasibility of applying neural networks as the mechanism for TBI decision support systems based on clinical databases. The results also suggest that neural networks may be a better solution for complex, non-linear medical decision support systems than conventional statistical techniques such as logistic regression.

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.

Application GIS on university planning: building a spatial database aided spatial decision

NASA Astrophysics Data System (ADS)

Miao, Lei; Wu, Xiaofang; Wang, Kun; Nong, Yu

2007-06-01

With the development of university and its size enlarging, kinds of resource need to effective management urgently. Spacial database is the right tool to assist administrator's spatial decision. And it's ready for digital campus with integrating existing OMS. It's researched about the campus planning in detail firstly. Following instanced by south china agriculture university it is practiced that how to build the geographic database of the campus building and house for university administrator's spatial decision.

Multi-level intervention to prevent influenza infections in older low income and minority adults.

PubMed

Schensul, Jean J; Radda, Kim; Coman, Emil; Vazquez, Elsie

2009-06-01

In this paper we describe a successful multi-level participatory intervention grounded in principles of individual and group empowerment, and guided by social construction theory. The intervention addressed known and persistent inequities in influenza vaccination among African American and Latino older adults, and associated infections, hospitalizations and mortality. It was designed to increase resident ability to make informed decisions about vaccination, and to build internal and external infrastructure to support sustainability over time. The intervention brought a group of social scientists, vaccine researchers, geriatricians, public health nurses, elder services providers and advocates together with senior housing management and activist African American and Latino residents living in public senior housing in a small east coast city. Two buildings of equal size and similar ethnic composition were randomized as intervention and control buildings. Pre and post intervention surveys were conducted in both buildings, measuring knowledge, attitudes and peer norms. Processes and outcomes were documented at four levels: Influenza Strategic Alliance (macro and exo levels), building management (meso level), building resident committee (meso level) and individual residents. The Influenza Strategic Alliance (I.S.A.) provided ongoing resources, information and vaccine; the building management provided economic and other in-kind resources and supported residents to continue flu clinics in the building. The V.I.P. Resident Committee conducted flu campaigns with flu clinics in English and Spanish. The vaccination rate in the intervention building at post test exceeded the study goal of 70% and showed a significant improvement over the control building. The intervention achieved desired outcomes at all four levels and resulted in a significant increase in influenza vaccination, and improvements in pro-vaccination knowledge, beliefs, and understanding of health consequences.

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

PubMed

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

2014-01-01

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

Physician Information Needs in Managing Delirium

PubMed Central

Taft, Teresa; Nelsen, Scott D; Slager, Stacey; Weir, Charlene

2017-01-01

Delirium has the highest occurrence rate of any complication in hospitalized adults over the age of 65. The study objective was to determine physician information needs for use in the development of electronic clinical decision support for physicians managing the care of patients with delirium. Critical incident interviews were conducted with 8 experienced internal medicine physicians and 1 cardiologist. Thematic analysis revealed the following 6 themes: 1) Clinician’s experience an impoverished information field for mental status, 2) Uncertainty is pervasive, 3) Extensive information foraging effort is required for cohesive story building, 4) Goal Conflict leads to missed diagnosis and early closure, 5) Diffusion of Responsibility for treating delirium is common, and 6) Use of structured delirium resources is minimal. Elicited information needs were identified and physician recommendations for improving access to information needed in managing the care of patient’s with delirium are reported. Information elicited in this study is useful for designing delirium clinical decision support that supports physician cognition.

Improving accountability in vaccine decision-making.

PubMed

Timmis, James Kenneth; Black, Steven; Rappuoli, Rino

2017-11-01

Healthcare decisions, in particular those affecting entire populations, should be evidence-based and taken by decision-makers sharing broad alignment with affected stakeholders. However, criteria, priorities and procedures for decision-making are sometimes non-transparent, frequently vary considerably across equivalent decision-bodies, do not always consider the broader benefits of new health-measures, and therefore do not necessarily adequately represent the relevant stakeholder-spectrum. Areas covered: To address these issues in the context of the evaluation of new vaccines, we have proposed a first baseline set of core evaluation criteria, primarily selected by members of the vaccine research community, and suggested their implementation in vaccine evaluation procedures. In this communication, we review the consequences and utility of stakeholder-centered core considerations to increase transparency in and accountability of decision-making procedures, in general, and of the benefits gained by their inclusion in Multi-Criteria-Decision-Analysis tools, exemplified by SMART Vaccines, specifically. Expert commentary: To increase effectiveness and comparability of health decision outcomes, decision procedures should be properly standardized across equivalent (national) decision bodies. To this end, including stakeholder-centered criteria in decision procedures would significantly increase their transparency and accountability, support international capacity building to improve health, and reduce societal costs and inequity resulting from suboptimal health decision-making.

School Mapping and Geospatial Analysis of the Schools in Jasra Development Block of India

NASA Astrophysics Data System (ADS)

Agrawal, S.; Gupta, R. D.

2016-06-01

GIS is a collection of tools and techniques that works on the geospatial data and is used in the analysis and decision making. Education is an inherent part of any civil society. Proper educational facilities generate the high quality human resource for any nation. Therefore, government needs an efficient system that can help in analysing the current state of education and its progress. Government also needs a system that can support in decision making and policy framing. GIS can serve the mentioned requirements not only for government but also for the general public. In order to meet the standards of human development, it is necessary for the government and decision makers to have a close watch on the existing education policy and its implementation condition. School mapping plays an important role in this aspect. School mapping consists of building the geospatial database of schools that supports in the infrastructure development, policy analysis and decision making. The present research work is an attempt for supporting Right to Education (RTE) and Sarv Sikha Abhiyaan (SSA) programmes run by Government of India through the use of GIS. School mapping of the study area is performed which is followed by the geospatial analysis. This research work will help in assessing the present status of educational infrastructure in Jasra block of Allahabad district, India.

An integrated science-based methodology to assess potential risks and implications of engineered nanomaterials.

PubMed

Tolaymat, Thabet; El Badawy, Amro; Sequeira, Reynold; Genaidy, Ash

2015-11-15

There is an urgent need for broad and integrated studies that address the risks of engineered nanomaterials (ENMs) along the different endpoints of the society, environment, and economy (SEE) complex adaptive system. This article presents an integrated science-based methodology to assess the potential risks of engineered nanomaterials. To achieve the study objective, two major tasks are accomplished, knowledge synthesis and algorithmic computational methodology. The knowledge synthesis task is designed to capture "what is known" and to outline the gaps in knowledge from ENMs risk perspective. The algorithmic computational methodology is geared toward the provision of decisions and an understanding of the risks of ENMs along different endpoints for the constituents of the SEE complex adaptive system. The approach presented herein allows for addressing the formidable task of assessing the implications and risks of exposure to ENMs, with the long term goal to build a decision-support system to guide key stakeholders in the SEE system towards building sustainable ENMs and nano-enabled products. Published by Elsevier B.V.

Building capacity for national carbon measurements for reducing emissions from deforestation and forest degradation

NASA Astrophysics Data System (ADS)

Goetz, S. J.; Laporte, N.; Horning, N.; Pelletier, J.; Jantz, P.; Ndunda, P.

2014-12-01

Many tropical countries are now working on developing their strategies for reducing emissions from deforestation and forest degradation, including activities that result in conservation or enhancement of forest carbon stocks and sustainable management of forests to effectively decrease atmospheric carbon emissions (i.e. REDD+). A new international REDD+ agreement is at the heart of recent negotiations of the parties to the UN Framework Convention on Climate Change (UNFCCC). REDD+ mechanisms could provide an opportunity to not only diminish an important source of emissions, but also to promote large-scale conservation of tropical forests and establish incentives and opportunities to alleviate poverty. Most tropical countries still lack basic information for developing and implementing their forest carbon stock assessments, including the extent of forest area and the rate at which forests are being cleared and/or degraded, and the carbon amounts associated with these losses. These same countries also need support to conduct integrated assessments of the most promising approaches for reducing emissions, and in identifying those policy options that hold the greatest potential while minimizing potential negative impacts of REDD+ policies. The WHRC SERVIR project in East Africa is helping to provide these data sets to countries via best practice tools and methods to support cost effective forest carbon monitoring solutions and more informed decision making processes under REDD+. We will present the results of our capacity building activites in the region and planned future efforts being coordinated with the NASA-SERVIR Hub in Kenya to support to REDD+ decision support.

The choice of primary energy source including PV installation for providing electric energy to a public utility building - a case study

NASA Astrophysics Data System (ADS)

Radomski, Bartosz; Ćwiek, Barbara; Mróz, Tomasz M.

2017-11-01

The paper presents multicriteria decision aid analysis of the choice of PV installation providing electric energy to a public utility building. From the energy management point of view electricity obtained by solar radiation has become crucial renewable energy source. Application of PV installations may occur a profitable solution from energy, economic and ecologic point of view for both existing and newly erected buildings. Featured variants of PV installations have been assessed by multicriteria analysis based on ANP (Analytic Network Process) method. Technical, economical, energy and environmental criteria have been identified as main decision criteria. Defined set of decision criteria has an open character and can be modified in the dialog process between the decision-maker and the expert - in the present case, an expert in planning of development of energy supply systems. The proposed approach has been used to evaluate three variants of PV installation acceptable for existing educational building located in Poznań, Poland - the building of Faculty of Chemical Technology, Poznań University of Technology. Multi-criteria analysis based on ANP method and the calculation software Super Decisions has proven to be an effective tool for energy planning, leading to the indication of the recommended variant of PV installation in existing and newly erected public buildings. Achieved results show prospects and possibilities of rational renewable energy usage as complex solution to public utility buildings.

Decision Support Systems for Launch and Range Operations Using Jess

NASA Technical Reports Server (NTRS)

Thirumalainambi, Rajkumar

2007-01-01

The virtual test bed for launch and range operations developed at NASA Ames Research Center consists of various independent expert systems advising on weather effects, toxic gas dispersions and human health risk assessment during space-flight operations. An individual dedicated server supports each expert system and the master system gather information from the dedicated servers to support the launch decision-making process. Since the test bed is based on the web system, reducing network traffic and optimizing the knowledge base is critical to its success of real-time or near real-time operations. Jess, a fast rule engine and powerful scripting environment developed at Sandia National Laboratory has been adopted to build the expert systems providing robustness and scalability. Jess also supports XML representation of knowledge base with forward and backward chaining inference mechanism. Facts added - to working memory during run-time operations facilitates analyses of multiple scenarios. Knowledge base can be distributed with one inference engine performing the inference process. This paper discusses details of the knowledge base and inference engine using Jess for a launch and range virtual test bed.

Construction of technological artifacts and teaching strategies to promote flexible scientific understanding

NASA Astrophysics Data System (ADS)

Spitulnik, Michele Wisnudel

Science education reforms advocate inquiry as a way to build explanations and make informed decisions. Based on this call this dissertation (1) defines flexible scientific understanding by elaborating on content, inquiry and epistemic understandings; (2) describes an inquiry based unit that integrates dynamic modeling software; (3) examines students' understandings as they construct models; and (4) identifies instructional strategies that support inquiry and model building. A curriculum unit was designed to engage students in inquiry by identifying problems and constructing models to represent, explain and predict phenomena. Ninth grade students in a public mid-western high school worked in teams of 2-3 to ask questions, find information and reflect on the purposes of models. Data sources including classroom video, observations, interviews, student models and handouts were used to formulate cases that examine how two groups construct understanding. A teacher case study identifies the teaching strategies that support understanding. Categories within content, inquiry and epistemic understandings were used to analyze student understandings and teaching supports. The findings demonstrate that students can build flexible understanding by constructing models. Students built: (1) content understanding by identifying key ideas and building relationships and explanations of phenomena; (2) inquiry understanding by defining problems, constructing models and developing positions; and (3) epistemic understanding by describing the purposes of models as generalizing phenomena, testing hypotheses and making predictions. However, students demonstrated difficulty in using evidence to defend scientific arguments. Strategies that support flexible understanding were also identified. Content supports include: setting expectations for explanations; using examples to illustrate explanations; modeling questions; and providing feedback that prompts detailed explanations. Supports for inquiry are setting expectations for data gathering; using examples that illustrate model building; modeling the development of an argument; and providing feedback to promote coherent models. Epistemic supports include: using examples to illustrate purposes and assumptions within models, and providing feedback as students evaluate their models. The dissertation demonstrates that teaching strategies impact student understanding but are challenging to implement. When strategies are not used, students do not necessarily construct desired outcomes such as, using evidence to support arguments.

A cross-sectional survey of supports for evidence-informed decision-making in healthcare organisations: a research protocol.

PubMed

Ouimet, Mathieu; Lavis, John N; Léon, Grégory; Ellen, Moriah E; Bédard, Pierre-Olivier; Grimshaw, Jeremy M; Gagnon, Marie-Pierre

2014-10-09

This protocol builds on the development of a) a framework that identified the various supports (i.e. positions, activities, interventions) that a healthcare organisation or health system can implement for evidence-informed decision-making (EIDM) and b) a qualitative study that showed the current mix of supports that some Canadian healthcare organisations have in place and the ones that are perceived to facilitate the use of research evidence in decision-making. Based on these findings, we developed a web survey to collect cross-sectional data about the specific supports that regional health authorities and hospitals in two Canadian provinces (Ontario and Quebec) have in place to facilitate EIDM. This paper describes the methods for a cross-sectional web survey among 32 regional health authorities and 253 hospitals in the provinces of Quebec and Ontario (Canada) to collect data on the current mix of organisational supports that these organisations have in place to facilitate evidence-informed decision-making. The data will be obtained through a two-step survey design: a 10-min survey among CEOs to identify key units and individuals in regard to our objectives (step 1) and a 20-min survey among managers of the key units identified in step 1 to collect information about the activities performed by their unit regarding the acquisition, assessment, adaptation and/or dissemination of research evidence in decision-making (step 2). The study will target three types of informants: CEOs, library/documentation centre managers and all other key managers whose unit is involved in the acquisition, assessment, adaptation/packaging and/or dissemination of research evidence in decision-making. We developed an innovative data collection system to increase the likelihood that only the best-informed respondent available answers each survey question. The reporting of the results will be done using descriptive statistics of supports by organisation type and by province. This study will be the first to collect and report large-scale cross-sectional data on the current mix of supports health system organisations in the two most populous Canadian provinces have in place for evidence-informed decision-making. The study will also provide useful information to researchers on how to collect organisation-level data with reduced risk of self-reporting bias.

Survivability as a Tool for Evaluating Open Source Software

DTIC Science & Technology

2015-06-01

the thesis limited the program development, so it is only able to process project issues (bugs or feature requests), which is an important metric for...Ideally, these insights may provide an analytic framework to generate guidance for decision makers that may support the inclusion of OSS to more...refine their efforts to build quality software and to strengthen their software development communities. 1.4 Research Questions This thesis addresses

Visual Sample Plan Version 7.0 User's Guide

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

Matzke, Brett D.; Newburn, Lisa LN; Hathaway, John E.

2014-03-01

User's guide for VSP 7.0 This user's guide describes Visual Sample Plan (VSP) Version 7.0 and provides instructions for using the software. VSP selects the appropriate number and location of environmental samples to ensure that the results of statistical tests performed to provide input to risk decisions have the required confidence and performance. VSP Version 7.0 provides sample-size equations or algorithms needed by specific statistical tests appropriate for specific environmental sampling objectives. It also provides data quality assessment and statistical analysis functions to support evaluation of the data and determine whether the data support decisions regarding sites suspected of contamination.more » The easy-to-use program is highly visual and graphic. VSP runs on personal computers with Microsoft Windows operating systems (XP, Vista, Windows 7, and Windows 8). Designed primarily for project managers and users without expertise in statistics, VSP is applicable to two- and three-dimensional populations to be sampled (e.g., rooms and buildings, surface soil, a defined layer of subsurface soil, water bodies, and other similar applications) for studies of environmental quality. VSP is also applicable for designing sampling plans for assessing chem/rad/bio threat and hazard identification within rooms and buildings, and for designing geophysical surveys for unexploded ordnance (UXO) identification.« less

Peer engagement in harm reduction strategies and services: a critical case study and evaluation framework from British Columbia, Canada.

PubMed

Greer, Alissa M; Luchenski, Serena A; Amlani, Ashraf A; Lacroix, Katie; Burmeister, Charlene; Buxton, Jane A

2016-05-27

Engaging people with drug use experience, or 'peers,' in decision-making helps to ensure harm reduction services reflect current need. There is little published on the implementation, evaluation, and effectiveness of meaningful peer engagement. This paper aims to describe and evaluate peer engagement in British Columbia from 2010-2014. A process evaluation framework specific to peer engagement was developed and used to assess progress made, lessons learned, and future opportunities under four domains: supportive environment, equitable participation, capacity building and empowerment, and improved programming and policy. The evaluation was conducted by reviewing primary and secondary qualitative data including focus groups, formal documents, and meeting minutes. Peer engagement was an iterative process that increased and improved over time as a consequence of reflexive learning. Practical ways to develop trust, redress power imbalances, and improve relationships were crosscutting themes. Lack of support, coordination, and building on existing capacity were factors that could undermine peer engagement. Peers involved across the province reviewed and provided feedback on these results. Recommendations from this evaluation can be applied to other peer engagement initiatives in decision-making settings to improve relationships between peers and professionals and to ensure programs and policies are relevant and equitable.

Building capacity for evidence informed decision making in public health: a case study of organizational change.

PubMed

Peirson, Leslea; Ciliska, Donna; Dobbins, Maureen; Mowat, David

2012-02-20

Core competencies for public health in Canada require proficiency in evidence informed decision making (EIDM). However, decision makers often lack access to information, many workers lack knowledge and skills to conduct systematic literature reviews, and public health settings typically lack infrastructure to support EIDM activities. This research was conducted to explore and describe critical factors and dynamics in the early implementation of one public health unit's strategic initiative to develop capacity to make EIDM standard practice. This qualitative case study was conducted in one public health unit in Ontario, Canada between 2008 and 2010. In-depth information was gathered from two sets of semi-structured interviews and focus groups (n = 27) with 70 members of the health unit, and through a review of 137 documents. Thematic analysis was used to code the key informant and document data. The critical factors and dynamics for building EIDM capacity at an organizational level included: clear vision and strong leadership, workforce and skills development, ability to access research (library services), fiscal investments, acquisition and development of technological resources, a knowledge management strategy, effective communication, a receptive organizational culture, and a focus on change management. With leadership, planning, commitment and substantial investments, a public health department has made significant progress, within the first two years of a 10-year initiative, towards achieving its goal of becoming an evidence informed decision making organization.

Interactive and Participatory Decision Support: Linking Cyberinfrastructure, Multi-Touch Interfaces, and Substantive Dialogue for Geothermal Systems

NASA Astrophysics Data System (ADS)

Malin, R.; Pierce, S. A.; Bass, B. J.

2012-12-01

Socio-technical approaches to complex, ill-structured decision problems are needed to identify adaptive responses for earth resource management. This research presents a hybrid approach to create decision tools and engender dialogue among stakeholders for geothermal development in Idaho, United States and El Tatio, Chile. Based on the scarcity of data, limited information availability, and tensions across stakeholder interests we designed and constructed a decision support model that allows stakeholders to rapidly collect, input, and visualize geoscientific data to assess geothermal system impacts and possible development strategies. We have integrated this decision support model into multi-touch interfaces that can be easily used by scientists and stakeholders alike. This toolkit is part of a larger cyberinfrastructure project designed to collect and present geoscientific information to support decision making processes. Consultation with stakeholders at the El Tatio geothermal complex of northern Chile—indigenous communities, local and national government agencies, developers, and geoscientists - informed the implementation of a sustained dialogue process. The El Tatio field case juxtaposes basic parameters such as pH, spring temperature, geochemical content, and FLIR imagery with stakeholder perceptions of risks due to mineral extraction and energy exploration efforts. The results of interviews and a participatory workshop are driving the creation of three initiatives within an indigenous community group; 1) microentrepreneurial efforts for science-based tourism, 2) design of a citizen-led environmental monitoring network in the Altiplano, and 3) business planning for an indigenous renewable energy cooperative. This toolkit is also being applied in the Snake River Plain of Idaho has as part of the DOE sponsored National Student Geothermal Competition. The Idaho case extends results from the Chilean case to implement a more streamlined system to analyze geothermal resource potential as well as integrate the decision support system with multi-touch interfaces which allow multiple stakeholders to view and interact with data. Beyond visual and tactile appeal, these interfaces also allow participants to dynamically update decision variables and decision preferences to create multiple scenarios and evaluate potential outcomes. Through this interactive scenario building, potential development sites can be targeted and stakeholders can interact with data to engage in substantive dialogue for related long-term planning or crisis response.

Development of a patient decision aid for people with refractory angina: protocol for a three-phase pilot study

PubMed Central

2014-01-01

Background Refractory angina is a severe chronic disease, defined as angina which cannot be controlled by usual treatments for heart disease. This disease is frightening, debilitating, and difficult to manage. Many people suffering refractory have inadequate pain relief, continually revisit emergency departments for help, undergo repeated cardiac investigations, and struggle with obtaining appropriate care. There is no clear framework to help people understand the risks and benefits of available treatment options in Canada. Some treatments for refractory angina are invasive, while others are not covered by provincial health insurance plans. Effective care for refractory angina sufferers in Canada is critically underdeveloped; it is important that healthcare professionals and refractory angina sufferers alike understand the treatment options and their implications. This proposal builds on the recent Canadian practice guidelines for the management of refractory angina. We propose to develop a decision support tool in order to help people suffering from refractory angina make well-informed decisions about their healthcare and reduce their uncertainty about treatment options. Methods This project will be conducted in three phases: a) development of the support tool with input from clinical experts, the Canadian refractory angina guidelines, and people living with refractory angina, b) pilot testing of the usability of the tool, and c) formal preliminary evaluation of the effectiveness of the support tool to help people make informed decisions about treatment options. Discussion A decision support tool for refractory angina is needed and the available data suggest that by developing such a tool, we may be able to help refractory angina sufferers better understand their condition and the effectiveness of available treatment options (in their respective clinical settings) as well as their implications (e.g. risks vs. benefits). By virtue of this tool, we may also be able to facilitate identification and inclusion of patients’ values and preferences in the decision making process. This is particularly important as refractory angina is an intractable condition, necessitating that the selected course of treatment be lifelong. This study will yield a much needed patient decision aid for people living with refractory angina and pilot data to support a subsequent effectiveness study. PMID:24920518

A Distributed Ensemble Approach for Mining Healthcare Data under Privacy Constraints

PubMed Central

Li, Yan; Bai, Changxin; Reddy, Chandan K.

2015-01-01

In recent years, electronic health records (EHRs) have been widely adapted at many healthcare facilities in an attempt to improve the quality of patient care and increase the productivity and efficiency of healthcare delivery. These EHRs can accurately diagnose diseases if utilized appropriately. While the EHRs can potentially resolve many of the existing problems associated with disease diagnosis, one of the main obstacles in effectively using them is the patient privacy and sensitivity of the medical information available in the EHR. Due to these concerns, even if the EHRs are available for storage and retrieval purposes, sharing of the patient records between different healthcare facilities has become a major concern and has hampered some of the effective advantages of using EHRs. Due to this lack of data sharing, most of the facilities aim at building clinical decision support systems using limited amount of patient data from their own EHR systems to provide important diagnosis related decisions. It becomes quite infeasible for a newly established healthcare facility to build a robust decision making system due to the lack of sufficient patient records. However, to make effective decisions from clinical data, it is indispensable to have large amounts of data to train the decision models. In this regard, there are conflicting objectives of preserving patient privacy and having sufficient data for modeling and decision making. To handle such disparate goals, we develop two adaptive distributed privacy-preserving algorithms based on a distributed ensemble strategy. The basic idea of our approach is to build an elegant model for each participating facility to accurately learn the data distribution, and then can transfer the useful healthcare knowledge acquired on their data from these participators in the form of their own decision models without revealing and sharing the patient-level sensitive data, thus protecting patient privacy. We demonstrate that our approach can successfully build accurate and robust prediction models, under privacy constraints, using the healthcare data collected from different geographical locations. We demonstrate the performance of our method using the Type-2 diabetes EHRs accumulated from multiple sources from all fifty states in the U.S. Our method was evaluated on diagnosing diabetes in the presence of insufficient number of patient records from certain regions without revealing the actual patient data from other regions. Using the proposed approach, we also discovered the important biomarkers, both universal and region-specific, and validated the selected biomarkers using the biomedical literature. PMID:26681811

A Distributed Ensemble Approach for Mining Healthcare Data under Privacy Constraints.

PubMed

Li, Yan; Bai, Changxin; Reddy, Chandan K

2016-02-10

In recent years, electronic health records (EHRs) have been widely adapted at many healthcare facilities in an attempt to improve the quality of patient care and increase the productivity and efficiency of healthcare delivery. These EHRs can accurately diagnose diseases if utilized appropriately. While the EHRs can potentially resolve many of the existing problems associated with disease diagnosis, one of the main obstacles in effectively using them is the patient privacy and sensitivity of the medical information available in the EHR. Due to these concerns, even if the EHRs are available for storage and retrieval purposes, sharing of the patient records between different healthcare facilities has become a major concern and has hampered some of the effective advantages of using EHRs. Due to this lack of data sharing, most of the facilities aim at building clinical decision support systems using limited amount of patient data from their own EHR systems to provide important diagnosis related decisions. It becomes quite infeasible for a newly established healthcare facility to build a robust decision making system due to the lack of sufficient patient records. However, to make effective decisions from clinical data, it is indispensable to have large amounts of data to train the decision models. In this regard, there are conflicting objectives of preserving patient privacy and having sufficient data for modeling and decision making. To handle such disparate goals, we develop two adaptive distributed privacy-preserving algorithms based on a distributed ensemble strategy. The basic idea of our approach is to build an elegant model for each participating facility to accurately learn the data distribution, and then can transfer the useful healthcare knowledge acquired on their data from these participators in the form of their own decision models without revealing and sharing the patient-level sensitive data, thus protecting patient privacy. We demonstrate that our approach can successfully build accurate and robust prediction models, under privacy constraints, using the healthcare data collected from different geographical locations. We demonstrate the performance of our method using the Type-2 diabetes EHRs accumulated from multiple sources from all fifty states in the U.S. Our method was evaluated on diagnosing diabetes in the presence of insufficient number of patient records from certain regions without revealing the actual patient data from other regions. Using the proposed approach, we also discovered the important biomarkers, both universal and region-specific, and validated the selected biomarkers using the biomedical literature.

Developing and Transitioning Numerical Air Quality Models to Improve Air Quality and Public Health Decision-Making in El Salvador and Costa Rica As Part of the Servir Applied Sciences Team

NASA Astrophysics Data System (ADS)

Thomas, A.; Huff, A. K.; Gomori, S. G.; Sadoff, N.

2014-12-01

In order to enhance the capacity for air quality modeling and improve air quality monitoring and management in the SERVIR Mesoamerica region, members of SERVIR's Applied Sciences Team (AST) are developing national numerical air quality models for El Salvador and Costa Rica. We are working with stakeholders from the El Salvador Ministry of the Environment and Natural Resources (MARN); National University of Costa Rica (UNA); the Costa Rica Ministry of the Environment, Energy, and Telecommunications (MINAET); and Costa Rica National Meteorological Institute (IMN), who are leaders in air quality monitoring and management in the Mesoamerica region. Focusing initially on these institutions will build sustainability in regional modeling activities by developing air quality modeling capability that can be shared with other countries in Mesoamerica. The air quality models are based on the Community Multi-scale Air Quality (CMAQ) model and incorporate meteorological inputs from the Weather Research and Forecasting (WRF) model, as well as national emissions inventories from El Salvador and Costa Rica. The models are being optimized for urban air quality, which is a priority of decision-makers in Mesoamerica. Once experimental versions of the modeling systems are complete, they will be transitioned to servers run by stakeholders in El Salvador and Costa Rica. The numerical air quality models will provide decision support for stakeholders to identify 1) high-priority areas for expanding national ambient air monitoring networks, 2) needed revisions to national air quality regulations, and 3) gaps in national emissions inventories. This project illustrates SERVIR's goal of the transition of science to support decision-making through capacity building in Mesoamerica, and it aligns with the Group on Earth Observations' health societal benefit theme. This presentation will describe technical aspects of the development of the models and outline key steps in our successful collaboration with the Mesoamerican stakeholders, including the processes of identifying and engaging decision-makers, understanding their requirements and limitations, communicating status updates on a regular basis, and providing sufficient training for end users to be able to utilize the models in a decision-making context.

LC Data QUEST: A Technical Architecture for Community Federated Clinical Data Sharing.

PubMed

Stephens, Kari A; Lin, Ching-Ping; Baldwin, Laura-Mae; Echo-Hawk, Abigail; Keppel, Gina A; Buchwald, Dedra; Whitener, Ron J; Korngiebel, Diane M; Berg, Alfred O; Black, Robert A; Tarczy-Hornoch, Peter

2012-01-01

The University of Washington Institute of Translational Health Sciences is engaged in a project, LC Data QUEST, building data sharing capacity in primary care practices serving rural and tribal populations in the Washington, Wyoming, Alaska, Montana, Idaho region to build research infrastructure. We report on the iterative process of developing the technical architecture for semantically aligning electronic health data in primary care settings across our pilot sites and tools that will facilitate linkages between the research and practice communities. Our architecture emphasizes sustainable technical solutions for addressing data extraction, alignment, quality, and metadata management. The architecture provides immediate benefits to participating partners via a clinical decision support tool and data querying functionality to support local quality improvement efforts. The FInDiT tool catalogues type, quantity, and quality of the data that are available across the LC Data QUEST data sharing architecture. These tools facilitate the bi-directional process of translational research.

LC Data QUEST: A Technical Architecture for Community Federated Clinical Data Sharing

PubMed Central

Stephens, Kari A.; Lin, Ching-Ping; Baldwin, Laura-Mae; Echo-Hawk, Abigail; Keppel, Gina A.; Buchwald, Dedra; Whitener, Ron J.; Korngiebel, Diane M.; Berg, Alfred O.; Black, Robert A.; Tarczy-Hornoch, Peter

2012-01-01

The University of Washington Institute of Translational Health Sciences is engaged in a project, LC Data QUEST, building data sharing capacity in primary care practices serving rural and tribal populations in the Washington, Wyoming, Alaska, Montana, Idaho region to build research infrastructure. We report on the iterative process of developing the technical architecture for semantically aligning electronic health data in primary care settings across our pilot sites and tools that will facilitate linkages between the research and practice communities. Our architecture emphasizes sustainable technical solutions for addressing data extraction, alignment, quality, and metadata management. The architecture provides immediate benefits to participating partners via a clinical decision support tool and data querying functionality to support local quality improvement efforts. The FInDiT tool catalogues type, quantity, and quality of the data that are available across the LC Data QUEST data sharing architecture. These tools facilitate the bi-directional process of translational research. PMID:22779052

[How to decide with precision, justice, and equity? Reflections on decision-making in the context of extreme prematurity. Part one: the problematics of decision-making in the context of extreme prematurity].

PubMed

Azria, E; Tsatsaris, V; Moriette, G; Hirsch, E; Schmitz, T; Cabrol, D; Goffinet, F

2007-05-01

Extreme premature child's long-term prognostic is getting better and better known, and if a resuscitation procedure is possible at birth, it won't guarantee survival or a survival free of disability. Incertitude toward individual prognosis and outcome for those childs remains considerable. In this field, we are at the frontier of medical knowledge and the answer to the question, "how to decide the ante and postnatal care?" is crucial. This work is focused on this problematic of decision making in the context of extreme prematurity. It attempts to deconstruct this concept and to explicit its stakes. Thus, with the support of the medical sources and of philosophical debates, we tried to build a decision-making procedure that complies with the ethical requirements of medical care, accuracy, justice and equity. This decision-making procedure is primarily concerned with the singularity of each decision situation and it intends to link it closely to the notions of rationality and responsibility.

Standardized data collection to build prediction models in oncology: a prototype for rectal cancer.

PubMed

Meldolesi, Elisa; van Soest, Johan; Damiani, Andrea; Dekker, Andre; Alitto, Anna Rita; Campitelli, Maura; Dinapoli, Nicola; Gatta, Roberto; Gambacorta, Maria Antonietta; Lanzotti, Vito; Lambin, Philippe; Valentini, Vincenzo

2016-01-01

The advances in diagnostic and treatment technology are responsible for a remarkable transformation in the internal medicine concept with the establishment of a new idea of personalized medicine. Inter- and intra-patient tumor heterogeneity and the clinical outcome and/or treatment's toxicity's complexity, justify the effort to develop predictive models from decision support systems. However, the number of evaluated variables coming from multiple disciplines: oncology, computer science, bioinformatics, statistics, genomics, imaging, among others could be very large thus making traditional statistical analysis difficult to exploit. Automated data-mining processes and machine learning approaches can be a solution to organize the massive amount of data, trying to unravel important interaction. The purpose of this paper is to describe the strategy to collect and analyze data properly for decision support and introduce the concept of an 'umbrella protocol' within the framework of 'rapid learning healthcare'.

Learning Collaboratives: Insights And A New Taxonomy From AHRQ's Two Decades Of Experience.

PubMed

Nix, Mary; McNamara, Peggy; Genevro, Janice; Vargas, Natalia; Mistry, Kamila; Fournier, Alaina; Shofer, Margie; Lomotan, Edwin; Miller, Therese; Ricciardi, Richard; Bierman, Arlene S

2018-02-01

Learning collaboratives are increasingly used as mechanisms to support and hasten the diffusion and implementation of innovation, clinical evidence, and effective models of care. Factors contributing to the collaboratives' success or failure are poorly understood. The Agency for Healthcare Research and Quality (AHRQ) has sponsored collaboratives for nearly two decades to support improvements in health care quality and value by accelerating the diffusion and implementation of innovation. We examined AHRQ's experience with these collaboratives to characterize their attributes, identify factors that might contribute to their success or failure, and assess the challenges they encountered. Building on the literature and insights from AHRQ's experience, we propose a taxonomy that can offer guidance to decision makers and funders about the factors they should consider in developing collaboratives and planning their evaluation, as well as to researchers who seek to conduct research that will ultimately help decision makers make better investments in diffusing innovation and evidence.

A high resolution agent-based model to support walk-bicycle infrastructure investment decisions: A case study with New York City

DOE PAGES

Aziz, H. M. Abdul; Park, Byung H.; Morton, April M.; ...

2017-11-24

Active transportation modes--walk and bicycle--are central for low carbon transport, healthy living, and complete streets initiative. Building a community with amenable walk and bicycle facilities asks for smart planning and investments. It is critical to investigate the impact of infrastructure building or expansion on the overall walk and bicycle mode usage prior to making investment choices utilizing public tax money. This research developed an agent-based model to support investment decisions that allows to assess the impact of changes in walk-bike infrastructures at a high spatial resolution (e.g., block group level). The agent-based model (ABM) utilizes data from a synthetic populationmore » simulator generating agents with corresponding socio-demographic characteristics, and integrates facility attributes regarding walking and bicycling (e.g., sidewalk width, bike lane length) into the mode choice decision making process. Moreover, the ABM accounts for the effect of social interactions among agents who live and work at the same geographic locations. Finally, GIS-based maps are developed at block group resolution that allows exploring the effect of walk-bike infrastructure related investments. The results from New York City case study indicate that infrastructure investments such as widening sidewalk and increasing bike lane network can positively influence the active transportation mode choices. In addition, the level of impact varies with geographic locations--different boroughs of New York City will have different impacts. Lastly, social promotions resulting in higher social interaction among agents can reinforce the impacts of infrastructure changes.« less

A high resolution agent-based model to support walk-bicycle infrastructure investment decisions: A case study with New York City

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

Aziz, H. M. Abdul; Park, Byung H.; Morton, April M.

Active transportation modes--walk and bicycle--are central for low carbon transport, healthy living, and complete streets initiative. Building a community with amenable walk and bicycle facilities asks for smart planning and investments. It is critical to investigate the impact of infrastructure building or expansion on the overall walk and bicycle mode usage prior to making investment choices utilizing public tax money. This research developed an agent-based model to support investment decisions that allows to assess the impact of changes in walk-bike infrastructures at a high spatial resolution (e.g., block group level). The agent-based model (ABM) utilizes data from a synthetic populationmore » simulator generating agents with corresponding socio-demographic characteristics, and integrates facility attributes regarding walking and bicycling (e.g., sidewalk width, bike lane length) into the mode choice decision making process. Moreover, the ABM accounts for the effect of social interactions among agents who live and work at the same geographic locations. Finally, GIS-based maps are developed at block group resolution that allows exploring the effect of walk-bike infrastructure related investments. The results from New York City case study indicate that infrastructure investments such as widening sidewalk and increasing bike lane network can positively influence the active transportation mode choices. In addition, the level of impact varies with geographic locations--different boroughs of New York City will have different impacts. Lastly, social promotions resulting in higher social interaction among agents can reinforce the impacts of infrastructure changes.« less

Preserving professional credibility: grounded theory study of medical trainees' requests for clinical support.

PubMed

Kennedy, Tara J T; Regehr, Glenn; Baker, G Ross; Lingard, Lorelei

2009-02-09

To develop a conceptual framework of the influences on medical trainees' decisions regarding requests for clinical support from a supervisor. Phase 1: members of teaching teams in internal and emergency medicine were observed during regular clinical activities (216 hours) and subsequently completed brief interviews. Phase 2: 36 in depth interviews were conducted using videotaped vignettes to probe tacit influences on decisions to request support. Data collection and analysis used grounded theory methods. Three teaching hospitals in an urban setting in Canada. 124 members of teaching teams on general internal medicine wards and in the emergency department, comprising 31 attending physicians, 57 junior and senior residents, 28 medical students, and eight nurses. Purposeful sampling to saturation was conducted. Trainees' decisions about whether or not to seek clinical support were influenced by three issues: the clinical question (clinical importance, scope of practice), supervisor factors (availability, approachability), and trainee factors (skill, desire for independence, evaluation). Trainees perceived that requesting frequent/inappropriate support threatened their credibility and used rhetorical strategies to preserve credibility. These strategies included building a case for the importance of requests, saving requests for opportune moments, making a plan before requesting support, and targeting requests to specific team members. Trainees consider not only clinical implications but also professional credibility when requesting support from clinical supervisors. Exposing the complexity of this process provides the opportunity to make changes to training programmes to promote timely supervision and provides a framework for further exploration of the impact of clinical training on quality of care of patients.

Development of a decision analytic model to support decision making and risk communication about thrombolytic treatment.

PubMed

McMeekin, Peter; Flynn, Darren; Ford, Gary A; Rodgers, Helen; Gray, Jo; Thomson, Richard G

2015-11-11

Individualised prediction of outcomes can support clinical and shared decision making. This paper describes the building of such a model to predict outcomes with and without intravenous thrombolysis treatment following ischaemic stroke. A decision analytic model (DAM) was constructed to establish the likely balance of benefits and risks of treating acute ischaemic stroke with thrombolysis. Probability of independence, (modified Rankin score mRS ≤ 2), dependence (mRS 3 to 5) and death at three months post-stroke was based on a calibrated version of the Stroke-Thrombolytic Predictive Instrument using data from routinely treated stroke patients in the Safe Implementation of Treatments in Stroke (SITS-UK) registry. Predictions in untreated patients were validated using data from the Virtual International Stroke Trials Archive (VISTA). The probability of symptomatic intracerebral haemorrhage in treated patients was incorporated using a scoring model from Safe Implementation of Thrombolysis in Stroke-Monitoring Study (SITS-MOST) data. The model predicts probabilities of haemorrhage, death, independence and dependence at 3-months, with and without thrombolysis, as a function of 13 patient characteristics. Calibration (and inclusion of additional predictors) of the Stroke-Thrombolytic Predictive Instrument (S-TPI) addressed issues of under and over prediction. Validation with VISTA data confirmed that assumptions about treatment effect were just. The C-statistics for independence and death in treated patients in the DAM were 0.793 and 0.771 respectively, and 0.776 for independence in untreated patients from VISTA. We have produced a DAM that provides an estimation of the likely benefits and risks of thrombolysis for individual patients, which has subsequently been embedded in a computerised decision aid to support better decision-making and informed consent.

Building Capacity for Actionable Science and Decision Making in Alaska

NASA Astrophysics Data System (ADS)

Timm, K.; Kettle, N.; Buxbaum, T. M.; Trainor, S.; Walsh, J. E.; York, A.

2017-12-01

Investigations of the processes for developing actionable science and supporting partnerships between researchers and practitioners has received increasing attention over the past decade. These studies highlight the importance of leveraging existing relationships and trust, supporting iterative interactions, and dedicating sufficient financial and human capital to the development of usable climate science. However, significant gaps remain in our understanding of how to build capacity for more effective partnerships. To meet these ends, the Alaska Center for Climate Assessment and Policy (ACCAP) is developing a series of trainings for scientists and practitioners to build capacity for producing actionable science. This process includes three phases: scoping and development, training, and evaluation. This presentation reports on the scoping and development phase of the project, which draws on an extensive web-based search of past and present capacity building and training activities, document analysis, and surveys of trainers. A synthesis of successful formats (e.g., training, placements, etc.), curriculum topics (e.g., climate science, interpersonal communication), and approaches to recruitment and curriculum development will be outlined. We then outline our approach for co-developing trainings in three different sectors, which engages other boundary organizations to leverage trust and exiting network connections to tailor the training activities. Through this effort we ultimately seek to understand how the processes and outcomes for co-developing trainings in actionable science vary across sectors and their implications for building capacity.

A Possible Approach for Addressing Neglected Human Factors Issues of Systems Engineering

NASA Technical Reports Server (NTRS)

Johnson, Christopher W.; Holloway, C. Michael

2011-01-01

The increasing complexity of safety-critical applications has led to the introduction of decision support tools in the transportation and process industries. Automation has also been introduced to support operator intervention in safety-critical applications. These innovations help reduce overall operator workload, and filter application data to maximize the finite cognitive and perceptual resources of system operators. However, these benefits do not come without a cost. Increased computational support for the end-users of safety-critical applications leads to increased reliance on engineers to monitor and maintain automated systems and decision support tools. This paper argues that by focussing on the end-users of complex applications, previous research has tended to neglect the demands that are being placed on systems engineers. The argument is illustrated through discussing three recent accidents. The paper concludes by presenting a possible strategy for building and using highly automated systems based on increased attention by management and regulators, improvements in competency and training for technical staff, sustained support for engineering team resource management, and the development of incident reporting systems for infrastructure failures. This paper represents preliminary work, about which we seek comments and suggestions.

Mobilizing women for minority health and social justice in california.

PubMed

Littlefield, Diane; Robison, Connie Chan; Engelbrecht, Luz; González, Belma; Hutcheson, Heather

2002-04-01

Women's Health Leadership is building the leadership capacity of diverse community leaders in California committed to promoting health and social justice in their communities. This program provides opportunities for cross-cultural exchanges of ideas, resources, and expertise. Graduates continue to receive technical support and to engage in peer learning via an alumnae network. The network is dedicated to advancing social justice issues and to addressing health disparities. It is also a way to mobilize trained grassroots leaders to provide expertise to influence policy decisions, to provide technical support and resources to local communities, and to foster new partnerships across the state.

An actuarial approach to retrofit savings in buildings

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

Subbarao, Krishnappa; Etingov, Pavel V.; Reddy, T. A.

An actuarial method has been developed for determining energy savings from retrofits from energy use data for a number of buildings. This method should be contrasted with the traditional method of using pre- and post-retrofit data on the same building. This method supports the U.S. Department of Energy Building Performance Database of real building performance data and related tools that enable engineering and financial practitioners to evaluate retrofits. The actuarial approach derives, from the database, probability density functions (PDFs) for energy savings from retrofits by creating peer groups for the user’s pre post buildings. From the energy use distribution ofmore » the two groups, the savings PDF is derived. This provides the basis for engineering analysis as well as financial risk analysis leading to investment decisions. Several technical issues are addressed: The savings PDF is obtained from the pre- and post-PDF through a convolution. Smoothing using kernel density estimation is applied to make the PDF more realistic. The low data density problem can be mitigated through a neighborhood methodology. Correlations between pre and post buildings are addressed to improve the savings PDF. Sample size effects are addressed through the Kolmogorov--Smirnov tests and quantile-quantile plots.« less

a Statistical Texture Feature for Building Collapse Information Extraction of SAR Image

NASA Astrophysics Data System (ADS)

Li, L.; Yang, H.; Chen, Q.; Liu, X.

2018-04-01

Synthetic Aperture Radar (SAR) has become one of the most important ways to extract post-disaster collapsed building information, due to its extreme versatility and almost all-weather, day-and-night working capability, etc. In view of the fact that the inherent statistical distribution of speckle in SAR images is not used to extract collapsed building information, this paper proposed a novel texture feature of statistical models of SAR images to extract the collapsed buildings. In the proposed feature, the texture parameter of G0 distribution from SAR images is used to reflect the uniformity of the target to extract the collapsed building. This feature not only considers the statistical distribution of SAR images, providing more accurate description of the object texture, but also is applied to extract collapsed building information of single-, dual- or full-polarization SAR data. The RADARSAT-2 data of Yushu earthquake which acquired on April 21, 2010 is used to present and analyze the performance of the proposed method. In addition, the applicability of this feature to SAR data with different polarizations is also analysed, which provides decision support for the data selection of collapsed building information extraction.

Delivering patient decision aids on the Internet: definitions, theories, current evidence, and emerging research areas

PubMed Central

2013-01-01

Background In 2005, the International Patient Decision Aids Standards Collaboration identified twelve quality dimensions to guide assessment of patient decision aids. One dimension—the delivery of patient decision aids on the Internet—is relevant when the Internet is used to provide some or all components of a patient decision aid. Building on the original background chapter, this paper provides an updated definition for this dimension, outlines a theoretical rationale, describes current evidence, and discusses emerging research areas. Methods An international, multidisciplinary panel of authors examined the relevant theoretical literature and empirical evidence through 2012. Results The updated definition distinguishes Internet-delivery of patient decision aids from online health information and clinical practice guidelines. Theories in cognitive psychology, decision psychology, communication, and education support the value of Internet features for providing interactive information and deliberative support. Dissemination and implementation theories support Internet-delivery for providing the right information (rapidly updated), to the right person (tailored), at the right time (the appropriate point in the decision making process). Additional efforts are needed to integrate the theoretical rationale and empirical evidence from health technology perspectives, such as consumer health informatics, user experience design, and human-computer interaction. Despite Internet usage ranging from 74% to 85% in developed countries and 80% of users searching for health information, it is unknown how many individuals specifically seek patient decision aids on the Internet. Among the 86 randomized controlled trials in the 2011 Cochrane Collaboration’s review of patient decision aids, only four studies focused on Internet-delivery. Given the limited number of published studies, this paper particularly focused on identifying gaps in the empirical evidence base and identifying emerging areas of research. Conclusions As of 2012, the updated theoretical rationale and emerging evidence suggest potential benefits to delivering patient decision aids on the Internet. However, additional research is needed to identify best practices and quality metrics for Internet-based development, evaluation, and dissemination, particularly in the areas of interactivity, multimedia components, socially-generated information, and implementation strategies. PMID:24625064

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.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Development strategy research of low-carbon tourist city

NASA Astrophysics Data System (ADS)

Dong, Xiaohong

2017-04-01

Construction of low-carbon tourist city has become a strategic choice for the development of city construction in our country, becoming the direction and goal of future city development in China. In this paper, the development strategy of low-carbon tourist city is put forward from the aspects of building low-carbon tourism culture, strengthening and perfecting the relevant rules and regulations, establishing and perfecting the decision-making management mechanism of low-carbon tourist city construction, establishing accurate, timely, efficient and comprehensive ecological environment monitoring and supervision network, building economical resource utilization system, strengthening science and technology supporting of low-carbon city construction, establishing low-carbon tourism scenic spot, low-carbon community or low-carbon demonstration area, etc.

The thinking of Cloud computing in the digital construction of the oil companies

NASA Astrophysics Data System (ADS)

CaoLei, Qizhilin; Dengsheng, Lei

In order to speed up digital construction of the oil companies and enhance productivity and decision-support capabilities while avoiding the disadvantages from the waste of the original process of building digital and duplication of development and input. This paper presents a cloud-based models for the build in the digital construction of the oil companies that National oil companies though the private network will join the cloud data of the oil companies and service center equipment integrated into a whole cloud system, then according to the needs of various departments to prepare their own virtual service center, which can provide a strong service industry and computing power for the Oil companies.

IAI Capacity Building Activities in the Americas: Fostering Multinational and Multidisciplinary Research

NASA Astrophysics Data System (ADS)

Ohira, M. S.

2007-05-01

The IAI's Training and Education (T&E) activities are designed to encourage capacity building in the Americas and are developed within and in parallel with the IAI research programs in global environmental change (GEC). The IAI has various training priorities: (1) support for graduate students in the form of fellowships through research programs; (2) development of IAI Training Institutes in Interdisciplinary Sciences and Science-Policy Fora; and (3) support for technical workshops, scientific meetings, and seminars. It becomes increasingly evident that institutions such as IAI must provide training and support to policy and decision makers who deal with environmental issues. The IAI Training Institutes emphasize an exchange of information about the various scientific languages, needs, and methodologies of disciplines that study GEC. Particular attention is given to socio-economic impacts and ways in which nations can gain a better understanding of the complex mechanisms, degrees of change, causes, and consequences - and therefore, plan sound public and private policies to minimize problems and maximize opportunities. The IAI has also implemented a Training Institute Seed Grant (TISG) Program as an assessment activity of the Training Institutes to further encourage network building and multinational and multidisciplinary collaboration among its 19 member countries in the Americas. By fostering the development of such new multidisciplinary, multinational teams, the IAI ensures a future generation of professionals who will be engaged in IAI research programs and networks and will lead the integrated science programs in the next decades. Furthermore, IAI has organized Science-Policy Fora, which focus on the science- policy interface and ways to incorporate scientific information into policy and decision-making processes. Participants discussed what scientific information is available, what aspects need to be better understood, translation of scientific information for the nonscientific community, potential uses of technical information, and policy issues that should be incorporated into the scientific community's agenda. Participants are individuals from governmental agencies, national and international organizations, nongovernmental organizations (NGO), universities, and private companies. Various other T&E-based initiatives that contribute to the building of scientific capacity in the Americas are supported by the IAI. Workshops, seminars, conferences, and other venues encourage the exchange of information and data providing scientists and professionals in global change related fields many opportunities to interact and benefit from multinational, multidisciplinary collaborations.

Strategic Planning in Population Health and Public Health Practice: A Call to Action for Higher Education

PubMed Central

PHELPS, CHARLES; RAPPUOLI, RINO; LEVIN, SCOTT; SHORTLIFFE, EDWARD; COLWELL, RITA

2016-01-01

Policy Points: Scarce resources, especially in population health and public health practice, underlie the importance of strategic planning.Public health agencies’ current planning and priority setting efforts are often narrow, at times opaque, and focused on single metrics such as cost‐effectiveness.As demonstrated by SMART Vaccines, a decision support software system developed by the Institute of Medicine and the National Academy of Engineering, new approaches to strategic planning allow the formal incorporation of multiple stakeholder views and multicriteria decision making that surpass even those sophisticated cost‐effectiveness analyses widely recommended and used for public health planning.Institutions of higher education can and should respond by building on modern strategic planning tools as they teach their students how to improve population health and public health practice. Context Strategic planning in population health and public health practice often uses single indicators of success or, when using multiple indicators, provides no mechanism for coherently combining the assessments. Cost‐effectiveness analysis, the most complex strategic planning tool commonly applied in public health, uses only a single metric to evaluate programmatic choices, even though other factors often influence actual decisions. Methods Our work employed a multicriteria systems analysis approach—specifically, multiattribute utility theory—to assist in strategic planning and priority setting in a particular area of health care (vaccines), thereby moving beyond the traditional cost‐effectiveness analysis approach. Findings (1) Multicriteria systems analysis provides more flexibility, transparency, and clarity in decision support for public health issues compared with cost‐effectiveness analysis. (2) More sophisticated systems‐level analyses will become increasingly important to public health as disease burdens increase and the resources to deal with them become scarcer. Conclusions The teaching of strategic planning in public health must be expanded in order to fill a void in the profession's planning capabilities. Public health training should actively incorporate model building, promote the interactive use of software tools, and explore planning approaches that transcend restrictive assumptions of cost‐effectiveness analysis. The Strategic Multi‐Attribute Ranking Tool for Vaccines (SMART Vaccines), which was recently developed by the Institute of Medicine and the National Academy of Engineering to help prioritize new vaccine development, is a working example of systems analysis as a basis for decision support. PMID:26994711

Strategic Planning in Population Health and Public Health Practice: A Call to Action for Higher Education.

PubMed

Phelps, Charles; Madhavan, Guruprasad; Rappuoli, Rino; Levin, Scott; Shortliffe, Edward; Colwell, Rita

2016-03-01

Scarce resources, especially in population health and public health practice, underlie the importance of strategic planning. Public health agencies' current planning and priority setting efforts are often narrow, at times opaque, and focused on single metrics such as cost-effectiveness. As demonstrated by SMART Vaccines, a decision support software system developed by the Institute of Medicine and the National Academy of Engineering, new approaches to strategic planning allow the formal incorporation of multiple stakeholder views and multicriteria decision making that surpass even those sophisticated cost-effectiveness analyses widely recommended and used for public health planning. Institutions of higher education can and should respond by building on modern strategic planning tools as they teach their students how to improve population health and public health practice. Strategic planning in population health and public health practice often uses single indicators of success or, when using multiple indicators, provides no mechanism for coherently combining the assessments. Cost-effectiveness analysis, the most complex strategic planning tool commonly applied in public health, uses only a single metric to evaluate programmatic choices, even though other factors often influence actual decisions. Our work employed a multicriteria systems analysis approach--specifically, multiattribute utility theory--to assist in strategic planning and priority setting in a particular area of health care (vaccines), thereby moving beyond the traditional cost-effectiveness analysis approach. (1) Multicriteria systems analysis provides more flexibility, transparency, and clarity in decision support for public health issues compared with cost-effectiveness analysis. (2) More sophisticated systems-level analyses will become increasingly important to public health as disease burdens increase and the resources to deal with them become scarcer. The teaching of strategic planning in public health must be expanded in order to fill a void in the profession's planning capabilities. Public health training should actively incorporate model building, promote the interactive use of software tools, and explore planning approaches that transcend restrictive assumptions of cost-effectiveness analysis. The Strategic Multi-Attribute Ranking Tool for Vaccines (SMART Vaccines), which was recently developed by the Institute of Medicine and the National Academy of Engineering to help prioritize new vaccine development, is a working example of systems analysis as a basis for decision support. © 2016 Milbank Memorial Fund.

Policy Decisions for Strategic Shipyard Survival

DTIC Science & Technology

1992-12-01

a shipyard mobilization base should: 1. Ensure that ships of the Naval fleet can be maintained in a high degree of material readiness and...capability to build combatants and cargo ship to wartime requirements and to support the goal of a merchant marine that is suitable in time of war or...guarantees, cargo reservation, the tax treatment of a ship operator’s construction reserve fund, and the Shipbuilding Trade Act of 1992. It will be shown

Battle Group Asset Management Decision Support System.

DTIC Science & Technology

1984-03-01

3.141 Terminal Display - Battle Group Missile Sys . 202 3.142 Battle Group Gun Systems . . . . . . . . . . . 204 3.143 Force missile and Gun Systems...with the sys -.6e, and/or the battle group has nct, as yet, been 61 * (MAIN MENU CC¢TI.) * SENSCR --- GRAPHICALLY DISPLAY UNIT/FORCE SENSCR *COVERAGE...BUILD A DATABASE OF THE CAPABILITIES OF THE UNITS IN YOUR BATTLE GROUP. THESE I CAPAEILITIES WILL INCLUDE ALL SENSOR AND WEAPONS SYS - TEES CNBCARD, AS

Establishing a regional network of academic centers to support decision making for new vaccine introduction in Latin America and the Caribbean: the ProVac experience.

PubMed

Toscano, C M; Jauregui, B; Janusz, C B; Sinha, A; Clark, A D; Sanderson, C; Resch, S; Ruiz Matus, C; Andrus, J K

2013-07-02

The Pan American Health Organization's ProVac Initiative, designed to strengthen national decision making regarding the introduction of new vaccines, was initiated in 2004. Central to realizing ProVac's vision of regional capacity building, the ProVac Network of Centers of Excellence (CoEs) was established in 2010 to provide research support to the ProVac Initiative, leveraging existing capacity at Latin American and Caribbean (LAC) universities. We describe the process of establishing the ProVac Network of CoEs and its initial outcomes and challenges. A survey was sent to academic, not-for-profit institutions in LAC that had recently published work in the areas of clinical decision sciences and health economic analysis. Centers invited to join the Network were selected by an international committee on the basis of the survey results. Selection criteria included academic productivity in immunization-related work, team size and expertise, successful collaboration with governmental agencies and international organizations, and experience in training and education. The Network currently includes five academic institutions across LAC. Through open dialog and negotiation, specific projects were assigned to centers according to their areas of expertise. Collaboration among centers was highly encouraged. Faculty from ProVac's technical partners were assigned as focal points for each project. The resulting work led to the development and piloting of tools, methodological guides, and training materials that support countries in assessing existing evidence and generating new evidence on vaccine introduction. The evidence generated is shared with country-level decision makers and the scientific community. As the ProVac Initiative expands to other regions of the world with support from immunization and public health partners, the establishment of other regional and global networks of CoEs will be critical. The experience of LAC in creating the current network could benefit the formation of similar structures that support evidence-based decisions regarding new public health interventions. Copyright © 2013 Elsevier Ltd. All rights reserved.

Decision Support to Combined Joint Task Force and Component Commanders (L’aide a la prise de decisions pour les commandants de composantes et de groupes de forces interarmees multinationales)

DTIC Science & Technology

2004-12-01

RTO-TR-SAS-044 4 Stapler 4 in total 5 Hole punch 4 in total 6 Long ruler 4 in total 7 Protractor and set squares 4 in total 8 Compass 4 in...ESPAGNE 00187 Roma Information Centre, Building 247 SDG TECEN / DGAM Dstl Porton Down C/ Arturo Soria 289 LUXEMBOURG Salisbury Madrid 28033 Voir...CZECH REPUBLIC H-1525 Budapest P O Box 26 SDG TECEN / DGAM LOM PRAHA s.p. C/ Arturo Soria 289 VTÚL a PVO o.z. ICELAND Madrid 28033 DIS ČR – NATO RTO

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

NASA Astrophysics Data System (ADS)

Kenney, M. A.

2014-12-01

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

A systematic approach to embedded biomedical decision making.

PubMed

Song, Zhe; Ji, Zhongkai; Ma, Jian-Guo; Sputh, Bernhard; Acharya, U Rajendra; Faust, Oliver

2012-11-01

An embedded decision making is a key feature for many biomedical systems. In most cases human life directly depends on correct decisions made by these systems, therefore they have to work reliably. This paper describes how we applied systems engineering principles to design a high performance embedded classification system in a systematic and well structured way. We introduce the structured design approach by discussing requirements capturing, specifications refinement, implementation and testing. Thereby, we follow systems engineering principles and execute each of these processes as formal as possible. The requirements, which motivate the system design, describe an automated decision making system for diagnostic support. These requirements are refined into the implementation of a support vector machine (SVM) algorithm which enables us to integrate automated decision making in embedded systems. With a formal model we establish functionality, stability and reliability of the system. Furthermore, we investigated different parallel processing configurations of this computationally complex algorithm. We found that, by adding SVM processes, an almost linear speedup is possible. Once we established these system properties, we translated the formal model into an implementation. The resulting implementation was tested using XMOS processors with both normal and failure cases, to build up trust in the implementation. Finally, we demonstrated that our parallel implementation achieves the speedup, predicted by the formal model. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Developing an electronic health record (EHR) for methadone treatment recording and decision support

PubMed Central

2011-01-01

Background In this paper, we give an overview of methadone treatment in Ireland and outline the rationale for designing an electronic health record (EHR) with extensibility, interoperability and decision support functionality. Incorporating several international standards, a conceptual model applying a problem orientated approach in a hierarchical structure has been proposed for building the EHR. Methods A set of archetypes has been designed in line with the current best practice and clinical guidelines which guide the information-gathering process. A web-based data entry system has been implemented, incorporating elements of the paper-based prescription form, while at the same time facilitating the decision support function. Results The use of archetypes was found to capture the ever changing requirements in the healthcare domain and externalises them in constrained data structures. The solution is extensible enabling the EHR to cover medicine management in general as per the programme of the HRB Centre for Primary Care Research. Conclusions The data collected via this Irish system can be aggregated into a larger dataset, if necessary, for analysis and evidence-gathering, since we adopted the openEHR standard. It will be later extended to include the functionalities of prescribing drugs other than methadone along with the research agenda at the HRB Centre for Primary Care Research in Ireland. PMID:21284849

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.

Referral criteria and clinical decision support: radiological protection aspects for justification.

PubMed

Pérez, M del Rosario

2015-06-01

Advanced imaging technology has opened new horizons for medical diagnostics and improved patient care. However, many procedures are unjustified and do not provide a net benefit. An area of particular concern is the unnecessary use of radiation when clinical evaluation or other imaging modalities could provide an accurate diagnosis. Referral criteria for medical imaging are consensus statements based on the best-available evidence to assist the decision-making process when choosing the best imaging procedure for a given patient. Although they are advisory rather than compulsory, physicians should have good reasons for deviation from these criteria. Voluntary use of referral criteria has shown limited success compared with integration into clinical decision support systems. These systems support good medical practice, can improve health service delivery, and foster safer, more efficient, fair, cost-effective care, thus contributing to the strengthening of health systems. Justification of procedures and optimisation of protection, the two pillars of radiological protection in health care, are implicit in the notion of good medical practice. However, some health professionals are not familiar with these principles, and have low awareness of radiological protection aspects of justification. A stronger collaboration between radiation protection and healthcare communities could contribute to improve the radiation protection culture in medical practice. © The Chartered Institution of Building Services Engineers 2014.

Use (and abuse) of expert elicitation in support of decision making for public policy

PubMed Central

Morgan, M. Granger

2014-01-01

The elicitation of scientific and technical judgments from experts, in the form of subjective probability distributions, can be a valuable addition to other forms of evidence in support of public policy decision making. This paper explores when it is sensible to perform such elicitation and how that can best be done. A number of key issues are discussed, including topics on which there are, and are not, experts who have knowledge that provides a basis for making informed predictive judgments; the inadequacy of only using qualitative uncertainty language; the role of cognitive heuristics and of overconfidence; the choice of experts; the development, refinement, and iterative testing of elicitation protocols that are designed to help experts to consider systematically all relevant knowledge when they make their judgments; the treatment of uncertainty about model functional form; diversity of expert opinion; and when it does or does not make sense to combine judgments from different experts. Although it may be tempting to view expert elicitation as a low-cost, low-effort alternative to conducting serious research and analysis, it is neither. Rather, expert elicitation should build on and use the best available research and analysis and be undertaken only when, given those, the state of knowledge will remain insufficient to support timely informed assessment and decision making. PMID:24821779

Building Stakeholder Trust: Defensible Government Decisions - 13110

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

Franklin, Victor A.

Administrative decisions must be grounded in reasonable expectations, founded on sound principles, and bounded by societal norms. Without these first principles, attaining and retaining public trust is a Herculean task. Decisions made by governmental administrators must be both transparent and defensible: without the former the agency will lose the public's trust and support (possibly prompting a legal challenge to the decision) and without the latter the decision may fail to withstand judicial scrutiny. This presentation and accompanying paper delves into the process by which governmental decisions can achieve both defensibility and openness through building stakeholder trust with transparency. Achieving andmore » maintaining stakeholder trust is crucial, especially in the environs of nuclear waste management. Proving confidence, stability, and security to the surrounding citizenry as well as those throughout the country is the goal of governmental nuclear waste remediation. Guiding administrative decision-making processes and maintaining a broad bandwidth of communication are of incalculable importance to all those charged with serving the public, but are especially essential to those whose decisional impacts will be felt for millennia. A strong, clear, and concise administrative record documenting discrete decisions and overarching policy choices is the strongest defense to a decisional challenge. However, this can be accomplished using transparency as the fundamental building block. This documentation allows the decision-makers to demonstrate the synthesis of legal and technical challenges and fortifies the ground from which challenges will be defended when necessary. Further, administrative actions which capture the public's interest and captivate that interest throughout the process will result in a better-informed, more deeply-involved, and more heavily-invested group of interested parties. Management of information, involvement, and investment on the front-end of the process reaps rewards far more efficiently than attempts to assuage and mitigate the concerns of those parties after the fact and there are a number of tools Savannah River Remediation (SRR) has deployed that render transparency an ally in this context. The makers, applicators, and beneficiaries of policies and decisions will all benefit from strong administrative records which document decisional choices in an open and transparent manner and from timely, up-front management of concerns of interested parties. The strongest defense to decisional challenges is an ability to demonstrate the basis of the decision and the reason(s) that the decision was chosen over other alternatives. Providing a sound basis for defending challenges rather than avoiding or fighting over them allows the deciding entity the greatest opportunity to produce value for its customer. Often, a transparent process that invites public participation and is open for public review and comment will thwart challenge genesis. An entity that has to devote resources to defending its choices obviously cannot utilize those resources to further its mission. (authors)« less

Multi-criteria group decision making for evaluating the performance of e-waste recycling programs under uncertainty.

PubMed

Wibowo, Santoso; Deng, Hepu

2015-06-01

This paper presents a multi-criteria group decision making approach for effectively evaluating the performance of e-waste recycling programs under uncertainty in an organization. Intuitionistic fuzzy numbers are used for adequately representing the subjective and imprecise assessments of the decision makers in evaluating the relative importance of evaluation criteria and the performance of individual e-waste recycling programs with respect to individual criteria in a given situation. An interactive fuzzy multi-criteria decision making algorithm is developed for facilitating consensus building in a group decision making environment to ensure that all the interest of individual decision makers have been appropriately considered in evaluating alternative e-waste recycling programs with respect to their corporate sustainability performance. The developed algorithm is then incorporated into a multi-criteria decision support system for making the overall performance evaluation process effectively and simple to use. Such a multi-criteria decision making system adequately provides organizations with a proactive mechanism for incorporating the concept of corporate sustainability into their regular planning decisions and business practices. An example is presented for demonstrating the applicability of the proposed approach in evaluating the performance of e-waste recycling programs in organizations. Copyright © 2015 Elsevier Ltd. All rights reserved.

Atrium building study

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

Not Available

1990-01-01

The CIGNA design team was faced with creating a new 500,000 square foot office building on a pastoral 610 acre corporate campus in Bloomfield, Connecticut, just outside of Hartford. Challenges abounded during the design process, from the selection of a specific building site on the sprawling campus to the evolution of a building form incorporating an atrium, to the selection of building systems and materials, to the design to the office interiors and atrium landscape. This document summarizes the original design problem, focusing on design criteria and performance standards that led to the decision to design an atrium building asmore » well as decision concerning its function, its form, its building systems and materials, and its passive energy strategies.« less

Towards sustainable infrastructure management: knowledge-based service-oriented computing framework for visual analytics

NASA Astrophysics Data System (ADS)

Vatcha, Rashna; Lee, Seok-Won; Murty, Ajeet; Tolone, William; Wang, Xiaoyu; Dou, Wenwen; Chang, Remco; Ribarsky, William; Liu, Wanqiu; Chen, Shen-en; Hauser, Edd

2009-05-01

Infrastructure management (and its associated processes) is complex to understand, perform and thus, hard to make efficient and effective informed decisions. The management involves a multi-faceted operation that requires the most robust data fusion, visualization and decision making. In order to protect and build sustainable critical assets, we present our on-going multi-disciplinary large-scale project that establishes the Integrated Remote Sensing and Visualization (IRSV) system with a focus on supporting bridge structure inspection and management. This project involves specific expertise from civil engineers, computer scientists, geographers, and real-world practitioners from industry, local and federal government agencies. IRSV is being designed to accommodate the essential needs from the following aspects: 1) Better understanding and enforcement of complex inspection process that can bridge the gap between evidence gathering and decision making through the implementation of ontological knowledge engineering system; 2) Aggregation, representation and fusion of complex multi-layered heterogeneous data (i.e. infrared imaging, aerial photos and ground-mounted LIDAR etc.) with domain application knowledge to support machine understandable recommendation system; 3) Robust visualization techniques with large-scale analytical and interactive visualizations that support users' decision making; and 4) Integration of these needs through the flexible Service-oriented Architecture (SOA) framework to compose and provide services on-demand. IRSV is expected to serve as a management and data visualization tool for construction deliverable assurance and infrastructure monitoring both periodically (annually, monthly, even daily if needed) as well as after extreme events.

An Advanced IoT-based System for Intelligent Energy Management in Buildings.

PubMed

Marinakis, Vangelis; Doukas, Haris

2018-02-16

The energy sector is closely interconnected with the building sector and integrated Information and Communication Technologies (ICT) solutions for effective energy management supporting decision-making at building, district and city level are key fundamental elements for making a city Smart. The available systems are designed and intended exclusively for a predefined number of cases and systems without allowing for expansion and interoperability with other applications that is partially due to the lack of semantics. This paper presents an advanced Internet of Things (IoT) based system for intelligent energy management in buildings. A semantic framework is introduced aiming at the unified and standardised modelling of the entities that constitute the building environment. Suitable rules are formed, aiming at the intelligent energy management and the general modus operandi of Smart Building. In this context, an IoT-based system was implemented, which enhances the interactivity of the buildings' energy management systems. The results from its pilot application are presented and discussed. The proposed system extends existing approaches and integrates cross-domain data, such as the building's data (e.g., energy management systems), energy production, energy prices, weather data and end-users' behaviour, in order to produce daily and weekly action plans for the energy end-users with actionable personalised information.

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.

Modeling aesthetics to support an ecosystem services approach for natural resource management decision making.

PubMed

Booth, Pieter N; Law, Sheryl A; Ma, Jane; Buonagurio, John; Boyd, James; Turnley, Jessica

2017-09-01

This paper reviews literature on aesthetics and describes the development of vista and landscape aesthetics models. Spatially explicit variables were chosen to represent physical characteristics of natural landscapes that are important to aesthetic preferences. A vista aesthetics model evaluates the aesthetics of natural landscapes viewed from distances of more than 1000 m, and a landscape aesthetics model evaluates the aesthetic value of wetlands and forests within 1000 m from the viewer. Each of the model variables is quantified using spatially explicit metrics on a pixel-specific basis within EcoAIM™, a geographic information system (GIS)-based ecosystem services (ES) decision analysis support tool. Pixel values are "binned" into ranked categories, and weights are assigned to select variables to represent stakeholder preferences. The final aesthetic score is the weighted sum of all variables and is assigned ranked values from 1 to 10. Ranked aesthetic values are displayed on maps by patch type and integrated within EcoAIM. The response of the aesthetic scoring in the models was tested by comparing current conditions in a discrete area of the facility with a Development scenario in the same area. The Development scenario consisted of two 6-story buildings and a trail replacing natural areas. The results of the vista aesthetic model indicate that the viewshed area variable had the greatest effect on the aesthetics overall score. Results from the landscape aesthetics model indicate a 10% increase in overall aesthetics value, attributed to the increase in landscape diversity. The models are sensitive to the weights assigned to certain variables by the user, and these weights should be set to reflect regional landscape characteristics as well as stakeholder preferences. This demonstration project shows that natural landscape aesthetics can be evaluated as part of a nonmonetary assessment of ES, and a scenario-building exercise provides end users with a tradeoff analysis in support of natural resource management decisions. Integr Environ Assess Manag 2017;13:926-938. © 2017 SETAC. © 2017 SETAC.

[Parameter of evidence-based medicine in health care economics].

PubMed

Wasem, J; Siebert, U

1999-08-01

In the view of scarcity of resources, economic evaluations in health care, in which not only effects but also costs related to a medical intervention are examined and a incremental cost-outcome-ratio is build, are an important supplement to the program of evidence based medicine. Outcomes of a medical intervention can be measured by clinical effectiveness, quality-adjusted life years, and monetary evaluation of benefits. As far as costs are concerned, direct medical costs, direct non-medical costs and indirect costs have to be considered in an economic evaluation. Data can be used from primary studies or secondary analysis; metaanalysis for synthesizing of data may be adequate. For calculation of incremental cost-benefit-ratios, models of decision analysis (decision tree models, Markov-models) often are necessary. Methodological and ethical limits for application of the results of economic evaluation in resource allocation decision in health care have to be regarded: Economic evaluations and the calculation of cost-outcome-rations should only support decision making but cannot replace it.

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

NASA Technical Reports Server (NTRS)

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

2014-01-01

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

Mixture-based gatekeeping procedures in adaptive clinical trials.

PubMed

Kordzakhia, George; Dmitrienko, Alex; Ishida, Eiji

2018-01-01

Clinical trials with data-driven decision rules often pursue multiple clinical objectives such as the evaluation of several endpoints or several doses of an experimental treatment. These complex analysis strategies give rise to "multivariate" multiplicity problems with several components or sources of multiplicity. A general framework for defining gatekeeping procedures in clinical trials with adaptive multistage designs is proposed in this paper. The mixture method is applied to build a gatekeeping procedure at each stage and inferences at each decision point (interim or final analysis) are performed using the combination function approach. An advantage of utilizing the mixture method is that it enables powerful gatekeeping procedures applicable to a broad class of settings with complex logical relationships among the hypotheses of interest. Further, the combination function approach supports flexible data-driven decisions such as a decision to increase the sample size or remove a treatment arm. The paper concludes with a clinical trial example that illustrates the methodology by applying it to develop an adaptive two-stage design with a mixture-based gatekeeping procedure.

Getting Beyond First Base: Science-Society Communication for Climate Adaptation

NASA Astrophysics Data System (ADS)

Garfin, G. M.

2010-12-01

At a 2009 international workshop on transboundary climate and water issues, a former World Bank official and current academic mentioned that “crisis, risk and uncertainty” are the three words that motivate decision-makers to act. However, decade-scale climate variability and trend-driven climate changes are phenomena characterized by creeping onset, diffuse and non-synchronous impacts, and complexity. Thus, there is a balancing act to addressing the complexity of uncertainties, while adequately assessing risk, and keeping the potential for crisis in focus without creating a “Chicken Little” situation. This presentation examines translational science approaches to three stages in the continuum from initial communication to societal action: raising awareness, building capacity, and making progress toward action. We examine the roles of scientists, knowledge brokers, decision makers, and the general public in the context of climate services. Although there is no “one size fits all” science communication method, we argue that best practices require that scientists pay particular attention to cultural and political sensitivities associated with decision contexts. We give examples from seasonal forecast communication, drought planning, climate literacy and education needs assessments, and the nexus of climate adaptation planning and uncertainty. In general, we find that constructive approaches make use of alliances with early adopters and opinion leaders, and make strong links between (a) predictions, impacts and solutions and (b) global to regional to local spatial scales. Often building partnerships for moving science information from observations to knowledge to decisions requires discussion support, a concept borrowed from Australian colleagues, which describes a multi-faceted and undervalued aspect of moving forward in adaptation planning: clarifying plausible cascades of interactions leading to potential impacts. Discussion support also fosters examination of how others confronting similar issues have both adapted well-known management strategies and developed outside-the-box ideas to move beyond “uncertainty paralysis.” Some preliminary conclusions from our work include the following: (a) iterative and ongoing engagements are necessary to build trust and bolster science credibility; (b) uncertainty, formerly a topic to avoided, forms the foundation for constructive progress in adaptation planning and improving forecast use, and (c) candid exploration of the array of uncertainties, which includes those due to modeling, institutional, policy and economic factors - with decision-making peers, science translators, and subject experts, is needed to stimulate constructive thinking on adaptation strategies. For scientists, gaining insight into how decisions are made is the most important part of scientist-stakeholder interactions. For managers, the most important factors are holistic, cross-sectoral, examination of both climate and non-climate factors affecting resources, and the diversity of public values regarding resource management.

An empirical analysis of executive behaviour with hospital executive information systems in Taiwan.

PubMed

Huang, Wei-Min

2013-01-01

Existing health information systems largely only support the daily operations of a medical centre, and are unable to generate the information required by executives for decision-making. Building on past research concerning information retrieval behaviour and learning through mental models, this study examines the use of information systems by hospital executives in medical centres. It uses a structural equation model to help find ways hospital executives might use information systems more effectively. The results show that computer self-efficacy directly affects the maintenance of mental models, and that system characteristics directly impact learning styles and information retrieval behaviour. Other results include the significant impact of perceived environmental uncertainty on scan searches; information retrieval behaviour and focused searches on mental models and perceived efficiency; scan searches on mental model building; learning styles and model building on perceived efficiency; and finally the impact of mental model maintenance on perceived efficiency and effectiveness.

Capturing the Impact of Storage and Other Flexible Technologies on Electric System Planning

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

Hale, Elaine; Stoll, Brady; Mai, Trieu

Power systems of the future are likely to require additional flexibility. This has been well studied from an operational perspective, but has been more difficult to incorporate into capacity expansion models (CEMs) that study investment decisions on the decadal scale. There are two primary reasons for this. First, the necessary input data, including cost and resource projections, for flexibility options like demand response and storage are significantly uncertain. Second, it is computationally difficult to represent both investment and operational decisions in detail, the latter being necessary to properly value system flexibility, in CEMs for realistically sized systems. In this work,more » we extend a particular CEM, NREL's Resource Planning Model (RPM), to address the latter issue by better representing variable generation impacts on operations, and then adding two flexible technologies to RPM's suite of investment decisions: interruptible load and utility-scale storage. This work does not develop full suites of input data for these technologies, but is rather methodological and exploratory in nature. We thus exercise these new investment decisions in the context of exploring price points and value streams needed for significant deployment in the Western Interconnection by 2030. Our study of interruptible load finds significant variation by location, year, and overall system conditions. Some locations find no system need for interruptible load even with low costs, while others build the most expensive resources offered. System needs can include planning reserve capacity needs to ensure resource adequacy, but there are also particular cases in which spinning reserve requirements drive deployment. Utility-scale storage is found to require deep cost reductions to achieve wide deployment and is found to be more valuable in some locations with greater renewable deployment. Differences between more solar- and wind-reliant regions are also found: Storage technologies with lower energy capacities are deployed to support solar deployment, and higher energy capacity technologies support wind. Finally, we identify potential future research and areas of improvement to build on this initial analysis.« less

Critical care physicians' approaches to negotiating with surrogate decision makers: a qualitative study.

PubMed

Brush, David R; Brown, Crystal E; Alexander, G Caleb

2012-04-01

To describe how critical care physicians manage conflicts with surrogates about withdrawing or withholding patients' life support. Qualitative analysis of key informant interviews with critical care physicians during 2010. We transcribed interviews verbatim and used grounded theory to code and revise a taxonomy of themes and to identify illustrative quotes. Three academic medical centers, one academic-affiliated medical center, and four private practice groups or private hospitals in a large Midwestern city Fourteen critical care physicians. None. Physicians reported tailoring their approach to address specific reasons for disagreement with surrogates. Five common approaches were identified: 1) building trust; 2) educating and informing; 3) providing surrogates more time; 4) adjusting surrogate and physician roles; and 5) highlighting specific values. When mistrust was an issue, physicians endeavored to build a more trusting relationship with the surrogate before readdressing decision making. Physicians also reported correcting misunderstandings by providing targeted education, and some reported highlighting specific patient, surrogate, or physician values that they hoped would guide surrogates to agree with them. When surrogates struggled with decisionmaking roles, physicians attempted to reinforce the concept of substituted judgment. Physicians noted that some surrogates needed time to "come to terms" with the patent's illness before agreeing with physicians. Many physicians had witnessed colleagues negotiate in ways they found objectionable such as providing misleading information, injecting their own values into the negotiation or behaving unprofessionally toward surrogates. Although some physicians viewed their efforts to encourage surrogates' agreement as persuasive, others strongly denied persuading surrogates and described their actions as "guiding" or "negotiating." Physicians reported using a tailored approach to resolve decisional conflicts about life support and attempted to change surrogates' decisions in accordance with what the physician thought was in the patients' best interests. Although physicians acknowledged their efforts to change surrogates' decisions, many physicians did not perceive these efforts as persuasive.

Sociotechnical Challenges and Progress in Using Social Media for Health

PubMed Central

Cavusoglu, Hasan; Frisch, Larry; Fels, Sidney

2013-01-01

Social media tools that connect patients, caregivers, and health providers offer great potential for helping people access health advice, receive and give social support, manage or cope with chronic conditions, and make day-to-day health decisions. These systems have seen widespread adoption, but often fail to support the goals as fully as designers and users would like. Through Ackerman’s lens of the “sociotechnical gap” and computer supported cooperative work (CSCW) as a science of the artificial, we review contemporary sociotechnical challenges and progress for using social media to support health. These challenges include a tension between privacy and sharing, policy information credibility, accessibility, and tailoring in social spaces. Those studying, building, deploying, and using social media systems to further health goals will benefit from approaching this work by borrowing from Ackerman’s framing of CSCW. In particular, this requires acknowledgment that technical systems will not fully meet our social goals, and then adopting design and educational approaches that are appropriate to fill this gap, building less-nuanced systems as partial solutions and tools for advancing our understanding, and by working with the CSCW research community to develop and pursue key lines of inquiry. PMID:24148206

Building capacity for evidence informed decision making in public health: a case study of organizational change

PubMed Central

2012-01-01

Background Core competencies for public health in Canada require proficiency in evidence informed decision making (EIDM). However, decision makers often lack access to information, many workers lack knowledge and skills to conduct systematic literature reviews, and public health settings typically lack infrastructure to support EIDM activities. This research was conducted to explore and describe critical factors and dynamics in the early implementation of one public health unit's strategic initiative to develop capacity to make EIDM standard practice. Methods This qualitative case study was conducted in one public health unit in Ontario, Canada between 2008 and 2010. In-depth information was gathered from two sets of semi-structured interviews and focus groups (n = 27) with 70 members of the health unit, and through a review of 137 documents. Thematic analysis was used to code the key informant and document data. Results The critical factors and dynamics for building EIDM capacity at an organizational level included: clear vision and strong leadership, workforce and skills development, ability to access research (library services), fiscal investments, acquisition and development of technological resources, a knowledge management strategy, effective communication, a receptive organizational culture, and a focus on change management. Conclusion With leadership, planning, commitment and substantial investments, a public health department has made significant progress, within the first two years of a 10-year initiative, towards achieving its goal of becoming an evidence informed decision making organization. PMID:22348688

Decision support system in an international-voice-services business company

NASA Astrophysics Data System (ADS)

Hadianti, R.; Uttunggadewa, S.; Syamsuddin, M.; Soewono, E.

2017-01-01

We consider a problem facing by an international telecommunication services company in maximizing its profit. From voice services by controlling cost and business partnership. The competitiveness in this industry is very high, so that any efficiency from controlling cost and business partnership can help the company to survive in the very high competitiveness situation. The company trades voice traffic with a large number of business partners. There are four trading schemes that can be chosen by this company, namely, flat rate, class tiering, volume commitment, and revenue capped. Each scheme has a specific characteristic on the rate and volume deal, where the last three schemes are regarded as strategic schemes to be offered to business partner to ensure incoming traffic volume for both parties. This company and each business partner need to choose an optimal agreement in a certain period of time that can maximize the company’s profit. In this agreement, both parties agree to use a certain trading scheme, rate and rate/volume/revenue deal. A decision support system is then needed in order to give a comprehensive information to the sales officers to deal with the business partners. This paper discusses the mathematical model of the optimal decision for incoming traffic volume control, which is a part of the analysis needed to build the decision support system. The mathematical model is built by first performing data analysis to see how elastic the incoming traffic volume is. As the level of elasticity is obtained, we then derive a mathematical modelling that can simulate the impact of any decision on trading to the revenue of the company. The optimal decision can be obtained from these simulations results. To evaluate the performance of the proposed method we implement our decision model to the historical data. A software tool incorporating our methodology is currently in construction.

Evaluation of decision making and negotiation processes under uncertainties regarding the water management of Peiros-Parapeiros Dam, in Achaia Region (Greece).

NASA Astrophysics Data System (ADS)

Podimata, Marianthi V.; Yannopoulos, Panayotis C.

2015-04-01

Water managers, decision-makers, water practitioners and others involved in Integrated Water Resources Management often encounter the problem of finding a joint agreement among stakeholders concerning the management of a common water body. Handling conflict situations/disputes over water issues and finding an acceptable joint solution remain a thorny issue in water negotiation processes, since finding a formula for wise, fair and sustainable management of a water resource is a complex process that includes environmental, economic, technical, socio-political criteria and their uncertainties. Decision Support Systems and Adaptive Management are increasingly used in that direction. To assist decision makers in handling water disputes and execute negotiations, a conceptual tool is required. The Graph Model for Conflict Resolution is a Decision Support flexible tool for negotiation support regarding water conflicts. It includes efficient algorithms for estimating strategic moves of water stakeholders, even though there is a lack of detail concerning their real motives and prospects. It calculates the stability of their states and encourages what-if analyses. This paper presents a case study of water decision makers' evaluations concerning the management of up-coming technical infrastructure Peiros-Parapeiros Dam, in Achaia Region (Greece). The continuous consultations between institutions and representatives revealed that the formation of a joint agreement between stakeholders is not easy, due to arising conflicts and contradictions regarding the jurisdiction and legal status of the dam operator and the cost undertaking of the dam operation. This paper analyzes the positions of the parties involved in the consultation process and examines possible conflict resolution states, using GMCR II. This methodology tries to minimize uncertainty to a certain extent concerning the possible moves/decisions of involved parties regarding the operation and management of the dam by developing and simulating potential strategic interactions and multilateral negotiations and finding confidence-building cooperation schemes (cooperative arrangements) over water use and management.

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.

[Building bridges between research and policy to extend social protection in health in Latin America and the Caribbean: a strategy for cooperation].

PubMed

Bazzani, Roberto; Levcovitz, Eduardo; Urrutia, Soledad; Zarowsky, Christina

2006-01-01

The Pan American Health Organization (PAHO) and International Development Research Centre (IDRC) have promoted a joint initiative to design, implement, and evaluate innovative strategies for the Extension of Social Protection in Health (SPH) in Latin America and the Caribbean (LAC), involving active partnership between researchers and research users. This initiative was based on a previous review of research on health sector reforms and the recommendations of the workshop on "Health Sector Reforms in the Americas: Strengthening the Links between Research and Policy" (Montreal, Canada, 2001). In its first phase, the initiative supported the development of proposals aiming to extend SPH, elaborated jointly by researchers and decision-makers. In the second phase, the implementation of five of these proposals was supported in order to promote the development of new SPH strategies and new stakeholder interaction models. In this edition of the journal, the process of linking researchers and decision-makers will be analyzed in the context of the five projects supported by this initiative.

Information system building of the urban electromagnetic environment

NASA Astrophysics Data System (ADS)

Wang, Jiechen; Rui, Yikang; Shen, Dingtao; Yu, Qing

2007-06-01

The pollution of urban electromagnetic radiation has become more serious, however, there is still lack of a perfect and interactive User System to manage, analyze and issue the information. In this study, taking the electromagnetic environment of Nanjing as an example, an information system based on WebGIS with the techniques of ArcIMS and JSP has been developed, in order to provide the services and technique supports for information query of public and decision making of relevant departments.

A Renovation Decision-Support Model for Evaluating the Functional Condition of Army Facilities

DTIC Science & Technology

1994-04-01

PAGES Buildings--Remodeling for others use cost effectiveness 90 Army facilities RENMOD 16 . PRICE CODE 17. SECURITY CLASSIFICATION 18. SECURITY...7540-01-280-5500 StndWd Form 296 (Rev. 2-80) Preaus by ANSI 80 23.- 16 2010 FOREWORD This research was conducted for the Assistant Chief of Staff for...it means any home improvement. To an economist, it is any investment designed to forestall the capital depreciation of a structure. To an architect

Designing and Implementation of River Classification Assistant Management System

NASA Astrophysics Data System (ADS)

Zhao, Yinjun; Jiang, Wenyuan; Yang, Rujun; Yang, Nan; Liu, Haiyan

2018-03-01

In an earlier publication, we proposed a new Decision Classifier (DCF) for Chinese river classification based on their structures. To expand, enhance and promote the application of the DCF, we build a computer system to support river classification named River Classification Assistant Management System. Based on ArcEngine and ArcServer platform, this system implements many functions such as data management, extraction of river network, river classification, and results publication under combining Client / Server with Browser / Server framework.

Tips for daylighting with windows

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

Robinson, Alastair; Selkowitz, Stephen

2013-10-01

These guidelines provide an integrated approach to the cost-effective design of perimeter zones in new commercial buildings and existing building retrofits. They function as a quick reference for building designers, through a set of easy steps and rules-of-thumb, emphasizing “how-to” practical details. References are given to more detailed sources of information, should the reader wish to go further. The design method used in this document emphasizes that building decisions should be made within the context of the whole building as a single functioning system rather than as an assembly of distinct parts. This integrated design approach looks at the ramificationsmore » of each individual system decision on the whole building. For example, the decision on glazing selection will have an effect on lighting, mechanical systems, and interior design. Therefore, the entire design team should participate and influence this glazing decision—which typically rests with the architect alone. The benefit of an integrated design approach is a greater chance of success towards long-term comfort and sustained energy savings in the building.« less

Modeling of afforestation possibilities on one part of Hungary

NASA Astrophysics Data System (ADS)

Bozsik, Éva; Riczu, Péter; Tamás, János; Burriel, Charles; Helilmeier, Hermann

2015-04-01

Agroforestry systems are part of the history of the European Union rural landscapes, but the regional increase of size of agricultural parcels had a significant effect on European land use in the 20th century, thereby it has radically reduced the coverage of natural forest. However, this cause conflicts between interest of agricultural and forestry sectors. The agroforestry land uses could be a solution of this conflict management. One real - ecological - problem with the remnant forests and new forest plantation is the partly missing of network function without connecting ecological green corridors, the other problem is verifiability for the agroforestry payment system, monitoring the arable lands and plantations. Remote sensing methods are currently used to supervise European Union payments. Nowadays, next to use satellite imagery the airborne hyperspectral and LiDAR (Light Detection And Ranging) remote sensing technologies are becoming more widespread use for nature, environmental, forest, agriculture protection, conservation and monitoring and it is an effective tool for monitoring biomass production. In this Hungarian case study we made a Spatial Decision Support System (SDSS) to create agroforestry site selection model. The aim of model building was to ensure the continuity of ecological green corridors, maintain the appropriate land use of regional endowments. The investigation tool was the more widely used hyperspectral and airborne LiDAR remote sensing technologies which can provide appropriate data acquisition and data processing tools to build a decision support system

Promoting the rights and responsibilities of children: a South Australian example.

PubMed

George, Emma; Schmidt, Casey; Vella, Grace; McDonagh, Imelda

2017-03-01

In 2014, the Parafield Gardens Children's Centre for Early Childhood Development and Parenting was recognised as a Global Peace School - Early Years (GPSEY). During the recognition process, a project promoting the rights and responsibilities of children and families was facilitated. Partnering with children and families in decision making was a project priority. Young children had an active role in decision making. Through age-appropriate activities and discussions, children and families developed deeper understanding of child rights, peace building, global awareness and social inclusion. Educational staff were supported to enhance this child rights focus. A GPSEY recognition celebration acknowledged child rights and the community's cultural diversity. The outcome of GPSEY recognition is significant but the process that fostered community ownership, participation and social inclusion is worth noting. Involving children in decision making and development promotes their rights and responsibilities; this can make a positive difference for children locally, and globally.

Modeling good research practices--overview: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force-1.

PubMed

Caro, J Jaime; Briggs, Andrew H; Siebert, Uwe; Kuntz, Karen M

2012-01-01

Models-mathematical frameworks that facilitate estimation of the consequences of health care decisions-have become essential tools for health technology assessment. Evolution of the methods since the first ISPOR modeling task force reported in 2003 has led to a new task force, jointly convened with the Society for Medical Decision Making, and this series of seven papers presents the updated recommendations for best practices in conceptualizing models; implementing state-transition approaches, discrete event simulations, or dynamic transmission models; dealing with uncertainty; and validating and reporting models transparently. This overview introduces the work of the task force, provides all the recommendations, and discusses some quandaries that require further elucidation. The audience for these papers includes those who build models, stakeholders who utilize their results, and, indeed, anyone concerned with the use of models to support decision making.

Dynamic simulation modelling of policy responses to reduce alcohol-related harms: rationale and procedure for a participatory approach.

PubMed

Atkinson, Jo-An; O'Donnell, Eloise; Wiggers, John; McDonnell, Geoff; Mitchell, Jo; Freebairn, Louise; Indig, Devon; Rychetnik, Lucie

2017-02-15

Development of effective policy responses to address complex public health problems can be challenged by a lack of clarity about the interaction of risk factors driving the problem, differing views of stakeholders on the most appropriate and effective intervention approaches, a lack of evidence to support commonly implemented and acceptable intervention approaches, and a lack of acceptance of effective interventions. Consequently, political considerations, community advocacy and industry lobbying can contribute to a hotly contested debate about the most appropriate course of action; this can hinder consensus and give rise to policy resistance. The problem of alcohol misuse and its associated harms in New South Wales (NSW), Australia, provides a relevant example of such challenges. Dynamic simulation modelling is increasingly being valued by the health sector as a robust tool to support decision making to address complex problems. It allows policy makers to ask 'what-if' questions and test the potential impacts of different policy scenarios over time, before solutions are implemented in the real world. Participatory approaches to modelling enable researchers, policy makers, program planners, practitioners and consumer representatives to collaborate with expert modellers to ensure that models are transparent, incorporate diverse evidence and perspectives, are better aligned to the decision-support needs of policy makers, and can facilitate consensus building for action. This paper outlines a procedure for embedding stakeholder engagement and consensus building in the development of dynamic simulation models that can guide the development of effective, coordinated and acceptable policy responses to complex public health problems, such as alcohol-related harms in NSW.

The Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES): Enhancing Collaboration to Support Science-Based Decision-Making

NASA Astrophysics Data System (ADS)

Duke, C. S.; Quach, K.; Jackson, S. T.

2015-12-01

The Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES) offers major opportunities to enhance scientific collaboration and advance global environmental sustainability. IPBES was established in 2012 as an independent intergovernmental body dedicated to assessing the state of the planet's biodiversity, its ecosystems, and the essential services they provide to society. IPBES has four functions: 1) identify and prioritize key scientific information needed for policymakers and catalyze efforts to generate new knowledge by engaging relevant scientific, policy and funding organizations; 2) perform regular and timely assessments of knowledge on biodiversity and ecosystem services and their interlinkages; 3) support policy formulation and implementation by identifying policy-relevant tools and methodologies; and 4) prioritize key capacity-building needs to improve the science-policy interface and catalyze related financing. To date, IPBES has brought together representatives of 124 countries at three annual plenary meetings and numerous panel meetings about specific assessments. This presentation will summarize IPBES' opportunities and achievements to date. These include a conceptual framework for IPBES processes and products, an assessment of the status of pollination and pollinators associated with food production, draft reports on scenario analyses and capacity building, and scoping for assessments of land degradation and restoration and of biodiversity in five regions of the world. IPBES provides natural and social scientists and other experts with important opportunities to support collaborative, science-based environmental decision-making at global to local scales. The presentation will conclude by describing opportunities to participate as expert panel members, contributors to assessments, and reviewers.

Enhancing access and usage of earth observations to support environmental decision making in Eastern and Southern Africa

NASA Astrophysics Data System (ADS)

Shukla, S.; Husak, G. J.; Macharia, D.; Peterson, P.; Landsfeld, M. F.; Funk, C.; Flores, A.

2017-12-01

Remote sensing, reanalysis and model based earth observations (EOs) are crucial for environmental decision making, particularly in a region like Eastern and Southern Africa, where ground-based observations are sparse. NASA and the Famine Early Warning System Network (FEWS NET) provide several EOs relevant for monitoring, providing early warning of agroclimatic conditions. Nonetheless, real-time application of those EOs for decision making in the region is still limited. This presentation reports on an ongoing SERVIR-supported Applied Science Team (AST) project that aims to fill that gap by working in close collaboration with Regional Centre for Mapping of Resources for Development (RCMRD), the NASA SERVIR regional hub. The three main avenues being taken to enhance access and usage of EOs in the region are: (1) Transition and implementation of web-based tools to RCMRD to allow easy processing and visualization of EOs (2) Capacity building of personnel from regional and national agroclimate service agencies in using EOs, through training using targeted case studies, and (3) Development of new datasets to meet the specific needs of RCMRD and regional stakeholders. The presentation will report on the initial success, lessons learned, and feedback thus far in this project regarding the implementation of web-based tool and capacity building efforts. It will also briefly describe three new datasets, currently in development, to improve agroclimate monitoring in the region, which are: (1) Satellite infrared and stations based temperature maximum dataset (CHIRTS) (2) NASA's GEOS5 and NCEP's CFSv2 based seasonal scale reference evapotranspiration forecasts and (3) NCEP's GEFS based medium range weather forecasts which are bias-corrected to USGS and UCSB's rainfall monitoring dataset (CHIRPS).

3D Virtual Environment Used to Support Lighting System Management in a Building

NASA Astrophysics Data System (ADS)

Sampaio, A. Z.; Ferreira, M. M.; Rosário, D. P.

The main aim of the research project, which is in progress at the UTL, is to develop a virtual interactive model as a tool to support decision-making in the planning of construction maintenance and facilities management. The virtual model gives the capacity to allow the user to transmit, visually and interactively, information related to the components of a building, defined as a function of the time variable. In addition, the analysis of solutions for repair work/substitution and inherent cost are predicted, the results being obtained interactively and visualized in the virtual environment itself. The first component of the virtual prototype concerns the management of lamps in a lighting system. It was applied in a study case. The interactive application allows the examination of the physical model, visualizing, for each element modeled in 3D and linked to a database, the corresponding technical information concerned with the use of the material, calculated for different points in time during their life. The control of a lamp stock, the constant updating of lifetime information and the planning of periodical local inspections are attended on the prototype. This is an important mean of cooperation between collaborators involved in the building management.

The Invasive Species Forecasting System

NASA Technical Reports Server (NTRS)

Schnase, John; Most, Neal; Gill, Roger; Ma, Peter

2011-01-01

The Invasive Species Forecasting System (ISFS) provides computational support for the generic work processes found in many regional-scale ecosystem modeling applications. Decision support tools built using ISFS allow a user to load point occurrence field sample data for a plant species of interest and quickly generate habitat suitability maps for geographic regions of management concern, such as a national park, monument, forest, or refuge. This type of decision product helps resource managers plan invasive species protection, monitoring, and control strategies for the lands they manage. Until now, scientists and resource managers have lacked the data-assembly and computing capabilities to produce these maps quickly and cost efficiently. ISFS focuses on regional-scale habitat suitability modeling for invasive terrestrial plants. ISFS s component architecture emphasizes simplicity and adaptability. Its core services can be easily adapted to produce model-based decision support tools tailored to particular parks, monuments, forests, refuges, and related management units. ISFS can be used to build standalone run-time tools that require no connection to the Internet, as well as fully Internet-based decision support applications. ISFS provides the core data structures, operating system interfaces, network interfaces, and inter-component constraints comprising the canonical workflow for habitat suitability modeling. The predictors, analysis methods, and geographic extents involved in any particular model run are elements of the user space and arbitrarily configurable by the user. ISFS provides small, lightweight, readily hardened core components of general utility. These components can be adapted to unanticipated uses, are tailorable, and require at most a loosely coupled, nonproprietary connection to the Web. Users can invoke capabilities from a command line; programmers can integrate ISFS's core components into more complex systems and services. Taken together, these features enable a degree of decentralization and distributed ownership that have helped other types of scientific information services succeed in recent years.

Decision insight into stakeholder conflict for ERN.

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

Siirola, John; Tidwell, Vincent Carroll; Benz, Zachary O.

Participatory modeling has become an important tool in facilitating resource decision making and dispute resolution. Approaches to modeling that are commonly used in this context often do not adequately account for important human factors. Current techniques provide insights into how certain human activities and variables affect resource outcomes; however, they do not directly simulate the complex variables that shape how, why, and under what conditions different human agents behave in ways that affect resources and human interactions related to them. Current approaches also do not adequately reveal how the effects of individual decisions scale up to have systemic level effectsmore » in complex resource systems. This lack of integration prevents the development of more robust models to support decision making and dispute resolution processes. Development of integrated tools is further hampered by the fact that collection of primary data for decision-making modeling is costly and time consuming. This project seeks to develop a new approach to resource modeling that incorporates both technical and behavioral modeling techniques into a single decision-making architecture. The modeling platform is enhanced by use of traditional and advanced processes and tools for expedited data capture. Specific objectives of the project are: (1) Develop a proof of concept for a new technical approach to resource modeling that combines the computational techniques of system dynamics and agent based modeling, (2) Develop an iterative, participatory modeling process supported with traditional and advance data capture techniques that may be utilized to facilitate decision making, dispute resolution, and collaborative learning processes, and (3) Examine potential applications of this technology and process. The development of this decision support architecture included both the engineering of the technology and the development of a participatory method to build and apply the technology. Stakeholder interaction with the model and associated data capture was facilitated through two very different modes of engagement, one a standard interface involving radio buttons, slider bars, graphs and plots, while the other utilized an immersive serious gaming interface. The decision support architecture developed through this project was piloted in the Middle Rio Grande Basin to examine how these tools might be utilized to promote enhanced understanding and decision-making in the context of complex water resource management issues. Potential applications of this architecture and its capacity to lead to enhanced understanding and decision-making was assessed through qualitative interviews with study participants who represented key stakeholders in the basin.« less

Understanding the Needs of Young Women Regarding Breast Cancer Risk Assessment and Genetic Testing: Convergence and Divergence among Patient-Counselor Perceptions and the Promise of Peer Support.

PubMed

Evans, Chalanda; Hamilton, Rebekah J; Tercyak, Kenneth P; Peshkin, Beth N; Rabemananjara, Kantoniony; Isaacs, Claudine; O'Neill, Suzanne C

2016-06-28

Young women from hereditary breast and ovarian cancer (HBOC) families face a series of medical decisions regarding their cancer risk management and integrating this information into their life planning. This presents unique medical and psychosocial challenges that exist without comprehensive intervention. To help lay the groundwork for intervention, we conducted a qualitative study among young women from HBOC families (N = 12; Mean age = 22) and cancer genetic counselors (N = 12) to explicate domains most critical to caring for this population. Women and counselors were interviewed by telephone. The predominant interview themes included preventative care planning and risk management, decision making around the pros and cons of cancer risk assessment, medical management, and psychosocial stresses experienced. Young women endorsed psychosocial stress significantly more frequently than did counselors. Both groups noted the short- and long-term decision making challenges and the support and conflict engendered among familial relationships. Our results suggest young women value the support they receive from their families and their genetic counselors, but additional, external supports are needed to facilitate adaptation to HBOC risk. In feedback interviews focused on intervention planning with a subset of these young women (N = 9), they endorsed the predominant interview themes discovered as important intervention content, a structure that would balance discussion of medical information and psychosocial skill-building that could be tailored to the young women's needs, and delivery by trained peers familiar with HBOC risk.

Understanding the Needs of Young Women Regarding Breast Cancer Risk Assessment and Genetic Testing: Convergence and Divergence among Patient-Counselor Perceptions and the Promise of Peer Support

PubMed Central

Evans, Chalanda; Hamilton, Rebekah J.; Tercyak, Kenneth P.; Peshkin, Beth N.; Rabemananjara, Kantoniony; Isaacs, Claudine; O’Neill, Suzanne C.

2016-01-01

Young women from hereditary breast and ovarian cancer (HBOC) families face a series of medical decisions regarding their cancer risk management and integrating this information into their life planning. This presents unique medical and psychosocial challenges that exist without comprehensive intervention. To help lay the groundwork for intervention, we conducted a qualitative study among young women from HBOC families (N = 12; Mean age = 22) and cancer genetic counselors (N = 12) to explicate domains most critical to caring for this population. Women and counselors were interviewed by telephone. The predominant interview themes included preventative care planning and risk management, decision making around the pros and cons of cancer risk assessment, medical management, and psychosocial stresses experienced. Young women endorsed psychosocial stress significantly more frequently than did counselors. Both groups noted the short- and long-term decision making challenges and the support and conflict engendered among familial relationships. Our results suggest young women value the support they receive from their families and their genetic counselors, but additional, external supports are needed to facilitate adaptation to HBOC risk. In feedback interviews focused on intervention planning with a subset of these young women (N = 9), they endorsed the predominant interview themes discovered as important intervention content, a structure that would balance discussion of medical information and psychosocial skill-building that could be tailored to the young women’s needs, and delivery by trained peers familiar with HBOC risk. PMID:27417623

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.

The story of rising voices: Facilitating collaboration between indigenous and western ways of knowing

USGS Publications Warehouse

Maldonado, Julie; Lazrus, Heather; Bennett, Shiloh-Kay; Chief, Karletta; Dhillon, Carla May; Gough, Bob; Kruger, Linda; Morisette, Jeffrey T.; Petrovic, Stefan; Whyte, Kyle P.; Companion, Michele; Chaiken, Miriam S.

2016-01-01

Indigenous community self-determination, cultures, and ways of life are at high risk from climate change impacts and ecological dispossession. Partnerships between experts with backgrounds in Indigenous and western knowledge may be productive and effective ways to reduce vulnerability and foster resilience. This chapter examines collaborations among scientific and Native American, Alaska Native, and Pacific Island communities to support climate solutions. We draw examples from the "Rising Voices: Collaborative Science with Indigenous Knowledge for Climate Solutions" program (Rising Voices) to examine how boundary organizations function cross-culturally to increase communities' adaptive capacity through knowledge exchange, as well as building the decision-making capacity needed to exercise sovereignty and make adaptive decisions in a changing climate.

Building a standards-based and collaborative e-prescribing tool: MyRxPad.

PubMed

Nelson, Stuart J; Zeng, Kelly; Kilbourne, John

2011-01-01

MyRxPad (rxp.nlm.nih.gov) is a prototype application intended to enable a practitioner-patient collaborative approach towards e-prescribing: patients play an active role by maintaining up-to-date and accurate medication lists. Prescribers make well-informed and safe prescribing decisions based on personal medication records contributed by patients. MyRxPad is thus the vehicle for collaborations with patients using MyMedicationList (MML). Integration with personal medication records in the context of e-prescribing is thus enabled. We present our experience in applying RxNorm in an e-prescribing setting: using standard names and codes to capture prescribed medication as well as extracting information from RxNorm to support medication-related clinical decision.

Life insurance risk assessment using a fuzzy logic expert system

NASA Technical Reports Server (NTRS)

Carreno, Luis A.; Steel, Roy A.

1992-01-01

In this paper, we present a knowledge based system that combines fuzzy processing with rule-based processing to form an improved decision aid for evaluating risk for life insurance. This application illustrates the use of FuzzyCLIPS to build a knowledge based decision support system possessing fuzzy components to improve user interactions and KBS performance. The results employing FuzzyCLIPS are compared with the results obtained from the solution of the problem using traditional numerical equations. The design of the fuzzy solution consists of a CLIPS rule-based system for some factors combined with fuzzy logic rules for others. This paper describes the problem, proposes a solution, presents the results, and provides a sample output of the software product.

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.

Building Training Curricula for Accelerating the Use of NOAA Climate Products and Tools

NASA Astrophysics Data System (ADS)

Timofeyeva-Livezey, M. M.; Meyers, J. C.; Stevermer, A.; Abshire, W. E.; Beller-Simms, N.; Herring, D.

2016-12-01

The National Oceanic and Atmospheric Administration (NOAA) plays a leading role in U.S. intergovernmental efforts on the Climate Data Initiative and the Climate Resilience Toolkit (CRT). CRT (http://toolkit.climate.gov/) is a valuable resource that provides tools, information, and subject matter expertise to decision makers in various sectors, such as agriculture, water resources and transportation, to help them build resilience to our changing climate. In order to make best use of the toolkit and all the resources within it, a training component is critical. The training section helps building users' understanding of the data, science, and impacts of climate variability and change. CRT identifies five steps in building resilience that includes use of appropriate tools to support decision makers depending on their needs. One tool that can be potentially integrated into CRT is NOAA's Local Climate Analysis Tool (LCAT), which provides access to trusted NOAA data and scientifically-sound analysis techniques for doing regional and local climate studies on climate variability and climate change. However, in order for LCAT to be used effectively, we have found an iterative learning approach using specific examples to train users. For example, for LCAT application in analysis of water resources, we use existing CRT case studies for Arizona and Florida water supply users. The Florida example demonstrates primary sensitivity to climate variability impacts, whereas the Arizona example takes into account longer- term climate change. The types of analyses included in LCAT are time series analysis of local climate and the estimated rate of change in the local climate. It also provides a composite analysis to evaluate the relationship between local climate and climate variability events such as El Niño Southern Oscillation, the Pacific North American Index, and other modes of climate variability. This paper will describe the development of a training module for use of LCAT and its integration into CRT. An iterative approach was used that incorporates specific examples of decision making while working with subject matter experts within the water supply community. The recommended strategy is to use a "stepping stone" learning structure to build users knowledge of best practices for use of LCAT.

Decision support system and medical liability.

PubMed Central

Allaërt, F. A.; Dusserre, L.

1992-01-01

Expert systems, which are going to be an essential tool in Medicine, are evolving in terms of sophistication of both knowledge representation and types of reasoning models used. The more efficient they are, the more often they will be used and professional liability will be involved. So after giving a short survey of configuration and working of expert systems, the authors will study the liabilities of people building and the using expert systems regarding some various dysfunctions. Of course the expert systems have to be considered only for human support and they should not possess any authority themselves, therefore the doctors must keep in mind that it is their own responsibility and as such keep their judgment and criticism. However other professionals could be involved, if they have participated in the building of expert systems. The different liabilities and the burden of proof are discussed according to some possible dysfunctions. In any case the final proof is inside the expert system by itself through re-computation of data. PMID:1482972

Trial of an electronic decision support system to facilitate shared decision making in community mental health.

PubMed

Woltmann, Emily M; Wilkniss, Sandra M; Teachout, Alexandra; McHugo, Gregory J; Drake, Robert E

2011-01-01

Involvement of community mental health consumers in mental health decision making has been consistently associated with improvements in health outcomes. Electronic decision support systems (EDSSs) that support both consumer and provider decision making may be a sustainable way to improve dyadic communication in a field with approximately 50% workforce turnover per year. This study examined the feasibility of such a system and investigated proximal outcomes of the system's performance. A cluster randomized design was used to evaluate an EDSS at three urban community mental health sites. Case managers (N=20) were randomly assigned to the EDSS-supported planning group or to the usual care planning group. Consumers (N=80) were assigned to the same group as their case managers. User satisfaction with the care planning process was assessed for consumers and case managers (possible scores range from 1 to 5, with higher summary scores indicating more satisfaction). Recall of the care plan was assessed for consumers. Linear regression with adjustment for grouping by worker was used to assess satisfaction scores. A Wilcoxon rank-sum test was used to examine knowledge of the care plan. Compared with case managers in the control group, those in the intervention group were significantly more satisfied with the care planning process (mean ± SD score=4.0 ± .5 versus 3.3 ± .5; adjusted p=.01). Compared with consumers in the control group, those in the intervention group had significantly greater recall of their care plans three days after the planning session (mean proportion of plan goals recalled=75% ± 28% versus 57% ± 32%; p=.02). There were no differences between the clients in the intervention and control groups regarding satisfaction. This study demonstrated that clients can build their own care plans and negotiate and revise them with their case managers using an EDSS.

Knowledge mobilisation for policy development: implementing systems approaches through participatory dynamic simulation modelling.

PubMed

Freebairn, Louise; Rychetnik, Lucie; Atkinson, Jo-An; Kelly, Paul; McDonnell, Geoff; Roberts, Nick; Whittall, Christine; Redman, Sally

2017-10-02

Evidence-based decision-making is an important foundation for health policy and service planning decisions, yet there remain challenges in ensuring that the many forms of available evidence are considered when decisions are being made. Mobilising knowledge for policy and practice is an emergent process, and one that is highly relational, often messy and profoundly context dependent. Systems approaches, such as dynamic simulation modelling can be used to examine both complex health issues and the context in which they are embedded, and to develop decision support tools. This paper reports on the novel use of participatory simulation modelling as a knowledge mobilisation tool in Australian real-world policy settings. We describe how this approach combined systems science methodology and some of the core elements of knowledge mobilisation best practice. We describe the strategies adopted in three case studies to address both technical and socio-political issues, and compile the experiential lessons derived. Finally, we consider the implications of these knowledge mobilisation case studies and provide evidence for the feasibility of this approach in policy development settings. Participatory dynamic simulation modelling builds on contemporary knowledge mobilisation approaches for health stakeholders to collaborate and explore policy and health service scenarios for priority public health topics. The participatory methods place the decision-maker at the centre of the process and embed deliberative methods and co-production of knowledge. The simulation models function as health policy and programme dynamic decision support tools that integrate diverse forms of evidence, including research evidence, expert knowledge and localised contextual information. Further research is underway to determine the impact of these methods on health service decision-making.

Towards global environmental information and data management

NASA Astrophysics Data System (ADS)

Gurney, Robert; Allison, Lee; Cesar, Roberto; Cossu, Roberto; Dietz, Volkmar; Gemeinholzer, Birgit; Koike, Toshio; Mokrane, Mustapha; Peters, Dale; Thaller-Honold, Svetlana; Treloar, Andrew; Vilotte, Jean-Pierre; Waldmann, Christoph

2014-05-01

The Belmont Forum, a coalition of national science agencies from 13 countries, is supporting an 18-month effort to implement a 'Knowledge Hub' community-building and strategy development program as a first step to coordinate and streamline international efforts on community governance, interoperability and system architectures so that environmental data and information can be exchanged internationally and across subject domains easily and efficiently. This initiative represents a first step to build collaboratively an international capacity and e-infrastructure framework to address societally relevant global environmental change challenges. The project will deliver a community-owned strategy and implementation plan, which will prioritize international funding opportunities for Belmont Forum members to build pilots and exemplars in order to accelerate delivery of end-to end global change decision support systems. In 2012, the Belmont Forum held a series of public town hall meetings, and a two-day scoping meeting of scientists and program officers, which concluded that transformative approaches and innovative technologies are needed for heterogeneous data/information to be integrated and made interoperable for researchers in disparate fields and for myriad uses across international, institutional, disciplinary, spatial and temporal boundaries. Pooling Belmont Forum members' resources to bring communities together for further integration, cooperation, and leveraging of existing initiatives and resources has the potential to develop the e-infrastructure framework necessary to solve pressing environmental problems, and to support the aims of many international data sharing initiatives. The plan is expected to serve as the foundation of future Belmont Forum calls for proposals for e-Infrastructures and Data Management. The Belmont Forum is uniquely able to align resources of major national funders to support global environmental change research on specific technical and governance challenges, and the development of focused pilot systems that could be complementary to other initiatives such as GEOSS, ICSU World Data System, and Global Framework for Climate Services (GFCS). The development of this Belmont Forum Knowledge Hub represents an extraordinary effort to bring together international leaders in interoperability, governance and other fields pertinent to decision-support systems in global environmental change research. It is also addressing related issues such as ensuring a cohort of environmental scientists who can use up-to-date computing techniques for data and information management, and investigating which legal issues need common international attention.

Structured representation for core elements of common clinical decision support interventions to facilitate knowledge sharing.

PubMed

Zhou, Li; Hongsermeier, Tonya; Boxwala, Aziz; Lewis, Janet; Kawamoto, Kensaku; Maviglia, Saverio; Gentile, Douglas; Teich, Jonathan M; Rocha, Roberto; Bell, Douglas; Middleton, Blackford

2013-01-01

At present, there are no widely accepted, standard approaches for representing computer-based clinical decision support (CDS) intervention types and their structural components. This study aimed to identify key requirements for the representation of five widely utilized CDS intervention types: alerts and reminders, order sets, infobuttons, documentation templates/forms, and relevant data presentation. An XML schema was proposed for representing these interventions and their core structural elements (e.g., general metadata, applicable clinical scenarios, CDS inputs, CDS outputs, and CDS logic) in a shareable manner. The schema was validated by building CDS artifacts for 22 different interventions, targeted toward guidelines and clinical conditions called for in the 2011 Meaningful Use criteria. Custom style sheets were developed to render the XML files in human-readable form. The CDS knowledge artifacts were shared via a public web portal. Our experience also identifies gaps in existing standards and informs future development of standards for CDS knowledge representation and sharing.

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.

The California Central Coast Research Partnership: Building Relationships, Partnerships and Paradigms for University-Industry Research Collaboration

DTIC Science & Technology

2005-10-14

of the decision-support systems that underlie and are key to these strategies. Cal Poly’s Collaborative Agent Design (CAD) Research Center is the...architect and lead developer of one of the first such systems: IMMACCS (Integrated Marine Multi- Agent Command and Control System), with JPL, SPAWAR...presented later in this document. An overview of accomplishments to date on the project follows: " Research carried out by the CADRC (Cooperative Agent

An iterative requirements specification procedure for decision support systems.

PubMed

Brookes, C H

1987-08-01

Requirements specification is a key element in a DSS development project because it not only determines what is to be done, it also drives the evolution process. A procedure for requirements elicitation is described that is based on the decomposition of the DSS design task into a number of functions, subfunctions, and operators. It is postulated that the procedure facilitates the building of a DSS that is complete and integrates MIS, modelling and expert system components. Some examples given are drawn from the health administration field.

Integration of evidence-based knowledge management in microsystems: a tele-ICU experience.

PubMed

Rincon, Teresa A

2012-01-01

The Institute of Medicine's proposed 6 aims to improve health care are timely, safe, effective, efficient, equitable, and patient-centered care. Unfortunately, it also asserts that improvements in these 6 dimensions cannot be achieved within the existing framework of care systems. These systems are based on unrealistic expectations on human cognition and vigilance, and demonstrate a lack of dependence on computerized systems to support care processes and put information at the point of use. Knowledge-based care and evidence-based clinical decision-making need to replace the unscientific care that is being delivered in health care. Building care practices on evidence within an information technology platform is needed to support sound clinical decision-making and to influence organizational adoption of evidence-based practice in health care. Despite medical advances and evidence-based recommendations for treatment of severe sepsis, it remains a significant cause of mortality and morbidity in the world. It is a complex disease state that has proven difficult to define, diagnose, and treat. Supporting bedside teams with real-time knowledge and expertise to target early identification of severe sepsis and compliance to Surviving Sepsis Campaign, evidence-based practice bundles are important to improving outcomes. Using a centralized, remote team of expert nurses and an open-source software application to advance clinical decision-making and execution of the severe sepsis bundle will be examined.

Granular support vector machines with association rules mining for protein homology prediction.

PubMed

Tang, Yuchun; Jin, Bo; Zhang, Yan-Qing

2005-01-01

Protein homology prediction between protein sequences is one of critical problems in computational biology. Such a complex classification problem is common in medical or biological information processing applications. How to build a model with superior generalization capability from training samples is an essential issue for mining knowledge to accurately predict/classify unseen new samples and to effectively support human experts to make correct decisions. A new learning model called granular support vector machines (GSVM) is proposed based on our previous work. GSVM systematically and formally combines the principles from statistical learning theory and granular computing theory and thus provides an interesting new mechanism to address complex classification problems. It works by building a sequence of information granules and then building support vector machines (SVM) in some of these information granules on demand. A good granulation method to find suitable granules is crucial for modeling a GSVM with good performance. In this paper, we also propose an association rules-based granulation method. For the granules induced by association rules with high enough confidence and significant support, we leave them as they are because of their high "purity" and significant effect on simplifying the classification task. For every other granule, a SVM is modeled to discriminate the corresponding data. In this way, a complex classification problem is divided into multiple smaller problems so that the learning task is simplified. The proposed algorithm, here named GSVM-AR, is compared with SVM by KDDCUP04 protein homology prediction data. The experimental results show that finding the splitting hyperplane is not a trivial task (we should be careful to select the association rules to avoid overfitting) and GSVM-AR does show significant improvement compared to building one single SVM in the whole feature space. Another advantage is that the utility of GSVM-AR is very good because it is easy to be implemented. More importantly and more interestingly, GSVM provides a new mechanism to address complex classification problems.

Development of a computer-based clinical decision support tool for selecting appropriate rehabilitation interventions for injured workers.

PubMed

Gross, Douglas P; Zhang, Jing; Steenstra, Ivan; Barnsley, Susan; Haws, Calvin; Amell, Tyler; McIntosh, Greg; Cooper, Juliette; Zaiane, Osmar

2013-12-01

To develop a classification algorithm and accompanying computer-based clinical decision support tool to help categorize injured workers toward optimal rehabilitation interventions based on unique worker characteristics. Population-based historical cohort design. Data were extracted from a Canadian provincial workers' compensation database on all claimants undergoing work assessment between December 2009 and January 2011. Data were available on: (1) numerous personal, clinical, occupational, and social variables; (2) type of rehabilitation undertaken; and (3) outcomes following rehabilitation (receiving time loss benefits or undergoing repeat programs). Machine learning, concerned with the design of algorithms to discriminate between classes based on empirical data, was the foundation of our approach to build a classification system with multiple independent and dependent variables. The population included 8,611 unique claimants. Subjects were predominantly employed (85 %) males (64 %) with diagnoses of sprain/strain (44 %). Baseline clinician classification accuracy was high (ROC = 0.86) for selecting programs that lead to successful return-to-work. Classification performance for machine learning techniques outperformed the clinician baseline classification (ROC = 0.94). The final classifiers were multifactorial and included the variables: injury duration, occupation, job attachment status, work status, modified work availability, pain intensity rating, self-rated occupational disability, and 9 items from the SF-36 Health Survey. The use of machine learning classification techniques appears to have resulted in classification performance better than clinician decision-making. The final algorithm has been integrated into a computer-based clinical decision support tool that requires additional validation in a clinical sample.

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

Summary of Building Protection Factor Studies for External Exposure to Ionizing Radiation

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

Dillon, Michael B.; Kane, Jave; Nasstrom, John

Radiation dose assessments are used to help inform decisions to minimize health risks in the event of an atmospheric release of radioactivity including, for example, from a Radiological Dispersal Device, an Improvised Nuclear Device detonation, or a Nuclear Power Plant accident. During these incidents, radiation dose assessments for both indoor and outdoor populations are needed to make informed decisions. These dose assessments inform emergency plans and decisions including, for example, identifying areas in which people should be sheltered and determining when controlled population evacuations should be made. US dose assessment methodologies allow consideration of the protection, and therefore dose reduction,more » that buildings provide their occupants. However, these methodologies require an understanding of the protection provided by various building types that is currently lacking. To help address this need, Lawrence Livermore National Laboratory, in cooperation with Sandia National Laboratories and the Nuclear Regulatory Commission, was tasked with (a) identifying prior building protection studies, (b) extracting results relevant to US building construction, and (c) summarizing building protection by building type. This report focuses primarily on the protection against radiation from outdoor fallout particles (external gamma radiation).« less

An integrated science-based methodology to assess potential ...

EPA Pesticide Factsheets

There is an urgent need for broad and integrated studies that address the risks of engineered nanomaterials (ENMs) along the different endpoints of the society, environment, and economy (SEE) complex adaptive system. This article presents an integrated science-based methodology to assess the potential risks of engineered nanomaterials. To achieve the study objective, two major tasks are accomplished, knowledge synthesis and algorithmic computational methodology. The knowledge synthesis task is designed to capture “what is known” and to outline the gaps in knowledge from ENMs risk perspective. The algorithmic computational methodology is geared toward the provision of decisions and an understanding of the risks of ENMs along different endpoints for the constituents of the SEE complex adaptive system. The approach presented herein allows for addressing the formidable task of assessing the implications and risks of exposure to ENMs, with the long term goal to build a decision-support system to guide key stakeholders in the SEE system towards building sustainable ENMs and nano-enabled products. The following specific aims are formulated to achieve the study objective: (1) to propose a system of systems (SoS) architecture that builds a network management among the different entities in the large SEE system to track the flow of ENMs emission, fate and transport from the source to the receptor; (2) to establish a staged approach for knowledge synthesis methodo

Energy and Energy Cost Savings Analysis of the 2015 IECC for Commercial Buildings

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

Zhang, Jian; Xie, YuLong; Athalye, Rahul A.

As required by statute (42 USC 6833), DOE recently issued a determination that ANSI/ASHRAE/IES Standard 90.1-2013 would achieve greater energy efficiency in buildings subject to the code compared to the 2010 edition of the standard. Pacific Northwest National Laboratory (PNNL) conducted an energy savings analysis for Standard 90.1-2013 in support of its determination . While Standard 90.1 is the model energy standard for commercial and multi-family residential buildings over three floors (42 USC 6833), many states have historically adopted the International Energy Conservation Code (IECC) for both residential and commercial buildings. This report provides an assessment as to whether buildingsmore » constructed to the commercial energy efficiency provisions of the 2015 IECC would save energy and energy costs as compared to the 2012 IECC. PNNL also compared the energy performance of the 2015 IECC with the corresponding Standard 90.1-2013. The goal of this analysis is to help states and local jurisdictions make informed decisions regarding model code adoption.« less

Boundary work for implementing adaptive management: A water sector application.

PubMed

Adem Esmail, Blal; Geneletti, Davide; Albert, Christian

2017-09-01

Boundary work, defined as effort to mediate between knowledge and action, is a promising approach for facilitating knowledge co-production for sustainable development. Here, we investigate a case study of knowledge co-production, to assess the applicability of boundary work as a conceptual framework to support implementing adaptive management in the water sector. We refer to a boundary work classification recently proposed by Clark et al., (2016), based on three types of knowledge uses, i.e. enlightenment, decision-, and negotiation-support, and three types of sources, i.e. personal expertise, single, and multiple communities of expertise. Our empirical results confirm boundary work has been crucial for the three types of knowledge use. For enlightenment and decision-support, effective interaction among knowledge producers and users was achieved through diverse boundary work practices, including joint agenda setting, and sharing of data and expertise. This initial boundary work eased subsequent knowledge co-production for decision-support and negotiations, in combination with stepping up of cooperation between relevant actors, suitable legislation and pressure for problem solving. Our analysis highlighted the temporal dimension matters - building trust around enlightenment first, and then using this as a basis for managing knowledge co-production for decision-, and negotiation support. We reconfirmed that boundary work is not a single time achievement, rather is a dynamic process, and we emphasized the importance of key actors driving the process, such as water utilities. Our results provide a rich case study of how strategic boundary work can facilitate knowledge co-production for adaptive management in the water sector. The boundary work practices employed here could also be transferred to other cases. Water utilities, as intermediaries between providers and beneficiaries of the important water-related ecosystem service of clean water provision, can indeed serve as key actors for initiating such boundary work practices. Copyright © 2017 Elsevier B.V. All rights reserved.

A decision support system for real-time hydropower scheduling in a competitive power market environment

NASA Astrophysics Data System (ADS)

Shawwash, Ziad Khaled Elias

2000-10-01

The electricity supply market is rapidly changing from a monopolistic to a competitive environment. Being able to operate their system of reservoirs and generating facilities to get maximum benefits out of existing assets and resources is important to the British Columbia Hydro Authority (B.C. Hydro). A decision support system has been developed to help B.C. Hydro operate their system in an optimal way. The system is operational and is one of the tools that are currently used by the B.C. Hydro system operations engineers to determine optimal schedules that meet the hourly domestic load and also maximize the value B.C. Hydro obtains from spot transactions in the Western U.S. and Alberta electricity markets. This dissertation describes the development and implementation of the decision support system in production mode. The decision support system consists of six components: the input data preparation routines, the graphical user interface (GUI), the communication protocols, the hydraulic simulation model, the optimization model, and the results display software. A major part of this work involved the development and implementation of a practical and detailed large-scale optimization model that determines the optimal tradeoff between the long-term value of water and the returns from spot trading transactions in real-time operations. The postmortem-testing phase showed that the gains in value from using the model accounted for 0.25% to 1.0% of the revenues obtained. The financial returns from using the decision support system greatly outweigh the costs of building it. Other benefits are the savings in the time needed to prepare the generation and trading schedules. The system operations engineers now can use the time saved to focus on other important aspects of their job. The operators are currently experimenting with the system in production mode, and are gradually gaining confidence that the advice it provides is accurate, reliable and sensible. The main lesson learned from developing and implementing the system was that there is no alternative to working very closely with the intended end-users of the system, and with the people who have deep knowledge, experience and understanding of how the system is and should be operated.

Strengthening Multipayer Collaboration: Lessons From the Comprehensive Primary Care Initiative.

PubMed

Anglin, Grace; Tu, H A; Liao, Kristie; Sessums, Laura; Taylor, Erin Fries

2017-09-01

Policy Points: Collaboration across payers to align financial incentives, quality measurement, and data feedback to support practice transformation is critical, but challenging due to competitive market dynamics and competing institutional priorities. The Centers for Medicare & Medicaid Services or other entities convening multipayer initiatives can build trust with other participants by clearly outlining each participant's role and the parameters of collaboration at the outset of the initiative. Multipayer collaboration can be improved if participating payers employ neutral, proactive meeting facilitators; develop formal decision-making processes; seek input on decisions from practice representatives; and champion the initiative within their organizations. With increasing frequency, public and private payers are joining forces to align goals and resources for primary care transformation. However, sustaining engagement and achieving coordination among payers can be challenging. The Comprehensive Primary Care (CPC) initiative is one of the largest multipayer initiatives ever tested. Drawing on the experience of the CPC initiative, this paper examines the factors that influence the effectiveness of multipayer collaboration. This paper draws largely on semistructured interviews with CPC-participating payers and payer conveners that facilitated CPC discussions and on observation of payer meetings. We coded and analyzed these qualitative data to describe collaborative dynamics and outcomes and assess the factors influencing them. We found that several factors appeared to increase the likelihood of successful payer collaboration: contracting with effective, neutral payer conveners; leveraging the support of payer champions, and seeking input on decisions from practice representatives. The presence of these factors helped some CPC regions overcome significant initial barriers to achieve common goals. We also found that leadership from the Centers for Medicare & Medicaid Services (CMS) was key to achieving broad payer engagement in CPC, but CMS's dual role as initiative convener and participating payer at times made collaboration challenging. CMS was able to build trust with other payers by clarifying which parts of CPC could be adapted to regional contexts, deferring to other payers for these decisions, and increasing opportunities for payers to meet with CMS representatives. CPC demonstrates that when certain facilitating factors are present, payers can overcome competitive market dynamics and competing institutional priorities to align financial incentives, quality measurement, and data feedback to support practice transformation. Lessons from this large-scale, multipayer initiative may be helpful for other multipayer efforts getting under way. © 2017 Milbank Memorial Fund.

Developing Theory to Guide Building Practitioners’ Capacity to Implement Evidence-Based Interventions

PubMed Central

Leeman, Jennifer; Calancie, Larissa; Kegler, Michelle C.; Escoffery, Cam T.; Herrmann, Alison K.; Thatcher, Esther; Hartman, Marieke A.; Fernandez, Maria

2017-01-01

Public health and other community-based practitioners have access to a growing number of evidence-based interventions (EBIs), and yet EBIs continue to be underused. One reason for this underuse is that practitioners often lack the capacity (knowledge, skills, and motivation) to select, adapt, and implement EBIs. Training, technical assistance, and other capacity-building strategies can be effective at increasing EBI adoption and implementation. However, little is known about how to design capacity-building strategies or tailor them to differences in capacity required across varying EBIs and practice contexts. To address this need, we conducted a scoping study of frameworks and theories detailing variations in EBIs or practice contexts and how to tailor capacity-building to address those variations. Using an iterative process, we consolidated constructs and propositions across 24 frameworks and developed a beginning theory to describe salient variations in EBIs (complexity and uncertainty) and practice contexts (decision-making structure, general capacity to innovate, resource and values fit with EBI, and unity vs. polarization of stakeholder support). The theory also includes propositions for tailoring capacity-building strategies to address salient variations. To have wide-reaching and lasting impact, the dissemination of EBIs needs to be coupled with strategies that build practitioners’ capacity to adopt and implement a variety of EBIs across diverse practice contexts. PMID:26500080

An Advanced IoT-based System for Intelligent Energy Management in Buildings

PubMed Central

Doukas, Haris

2018-01-01

The energy sector is closely interconnected with the building sector and integrated Information and Communication Technologies (ICT) solutions for effective energy management supporting decision-making at building, district and city level are key fundamental elements for making a city Smart. The available systems are designed and intended exclusively for a predefined number of cases and systems without allowing for expansion and interoperability with other applications that is partially due to the lack of semantics. This paper presents an advanced Internet of Things (IoT) based system for intelligent energy management in buildings. A semantic framework is introduced aiming at the unified and standardised modelling of the entities that constitute the building environment. Suitable rules are formed, aiming at the intelligent energy management and the general modus operandi of Smart Building. In this context, an IoT-based system was implemented, which enhances the interactivity of the buildings’ energy management systems. The results from its pilot application are presented and discussed. The proposed system extends existing approaches and integrates cross-domain data, such as the building’s data (e.g., energy management systems), energy production, energy prices, weather data and end-users’ behaviour, in order to produce daily and weekly action plans for the energy end-users with actionable personalised information. PMID:29462957

Developing Theory to Guide Building Practitioners' Capacity to Implement Evidence-Based Interventions.

PubMed

Leeman, Jennifer; Calancie, Larissa; Kegler, Michelle C; Escoffery, Cam T; Herrmann, Alison K; Thatcher, Esther; Hartman, Marieke A; Fernandez, Maria E

2017-02-01

Public health and other community-based practitioners have access to a growing number of evidence-based interventions (EBIs), and yet EBIs continue to be underused. One reason for this underuse is that practitioners often lack the capacity (knowledge, skills, and motivation) to select, adapt, and implement EBIs. Training, technical assistance, and other capacity-building strategies can be effective at increasing EBI adoption and implementation. However, little is known about how to design capacity-building strategies or tailor them to differences in capacity required across varying EBIs and practice contexts. To address this need, we conducted a scoping study of frameworks and theories detailing variations in EBIs or practice contexts and how to tailor capacity-building to address those variations. Using an iterative process, we consolidated constructs and propositions across 24 frameworks and developed a beginning theory to describe salient variations in EBIs (complexity and uncertainty) and practice contexts (decision-making structure, general capacity to innovate, resource and values fit with EBI, and unity vs. polarization of stakeholder support). The theory also includes propositions for tailoring capacity-building strategies to address salient variations. To have wide-reaching and lasting impact, the dissemination of EBIs needs to be coupled with strategies that build practitioners' capacity to adopt and implement a variety of EBIs across diverse practice contexts.

The chiller`s role within a utility`s marketing strategy: Using chiller related products and services to win and retain customers. Final report

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

NONE

1998-04-01

Commercial chillers are used in space and industrial process cooling. Approximately 3% of commercial buildings, representing 19% of all commercial floor space, are cooled by chillers. Consequently, every chiller represents significant electric (or gas) consumption. Chillers can comprise as much as 30% of a large office building`s electrical load. The selection decisions (electric versus gas, standard versus high efficiency, thermal storage or no thermal storage, etc.) for a new or replacement chiller will affect the customer`s energy consumption for twenty to thirty years. Consequently, this decision can play a major role in the customer`s relationship with the energy provider. However,more » even though these chiller decisions have a significant impact on the utility, today the utility has limited influence over these decisions. EPRI commissioned this study to develop understanding that will help utilities increase their influence over chiller decisions. To achieve this objective, this study looks at the customer`s behavior -- how they make chiller decisions, how the customer`s behavior and decisions are influenced today, and how these decisions might change in the future due to the impact of deregulation and changes in customer goals. The output of this project includes a list of product and service offerings that utilities and EPRI could offer to increase their influence over chiller decisions.« less

Development Impact Assessment Highlights Co-benefits of GHG Mitigation Actions

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

2016-06-01

This EC-LEDS document describes the Development Impact Assessment (DIA) process that explores interactions between development goals and the low emission development strategies. DIA aims to support informed decision-making by considering how policies and programs intended to meet one goal may impact other development priorities. Enhancing Capacity for Low Emission Development Strategies (EC-LEDS) is a flagship U.S. government-led effort that assists countries in developing and implementing LEDS. The program enhances partner country efforts by providing targeting technical assistance and building a shared global knowledge base on LEDS. is a flagship U.S. government-led effort that assists countries in developing and implementing LEDS.more » The program enhances partner country efforts by providing targeting technical assistance and building a shared global knowledge base on LEDS.« less

Case study: technology initiative led to advanced lead optimization screening processes at Bristol-Myers Squibb, 2004-2009.

PubMed

Zhang, Litao; Cvijic, Mary Ellen; Lippy, Jonathan; Myslik, James; Brenner, Stephen L; Binnie, Alastair; Houston, John G

2012-07-01

In this paper, we review the key solutions that enabled evolution of the lead optimization screening support process at Bristol-Myers Squibb (BMS) between 2004 and 2009. During this time, technology infrastructure investment and scientific expertise integration laid the foundations to build and tailor lead optimization screening support models across all therapeutic groups at BMS. Together, harnessing advanced screening technology platforms and expanding panel screening strategy led to a paradigm shift at BMS in supporting lead optimization screening capability. Parallel SAR and structure liability relationship (SLR) screening approaches were first and broadly introduced to empower more-rapid and -informed decisions about chemical synthesis strategy and to broaden options for identifying high-quality drug candidates during lead optimization. Copyright © 2012 Elsevier Ltd. All rights reserved.

Citizen Science to Support Community-based Flood Early Warning and Resilience Building

NASA Astrophysics Data System (ADS)

Paul, J. D.; Buytaert, W.; Allen, S.; Ballesteros-Cánovas, J. A.; Bhusal, J.; Cieslik, K.; Clark, J.; Dewulf, A.; Dhital, M. R.; Hannah, D. M.; Liu, W.; Nayaval, J. L.; Schiller, A.; Smith, P. J.; Stoffel, M.; Supper, R.

2017-12-01

In Disaster Risk Management, an emerging shift has been noted from broad-scale, top-down assessments towards more participatory, community-based, bottom-up approaches. Combined with technologies for robust and low-cost sensor networks, a citizen science approach has recently emerged as a promising direction in the provision of extensive, real-time information for flood early warning systems. Here we present the framework and initial results of a major new international project, Landslide EVO, aimed at increasing local resilience against hydrologically induced disasters in western Nepal by exploiting participatory approaches to knowledge generation and risk governance. We identify three major technological developments that strongly support our approach to flood early warning and resilience building in Nepal. First, distributed sensor networks, participatory monitoring, and citizen science hold great promise in complementing official monitoring networks and remote sensing by generating site-specific information with local buy-in, especially in data-scarce regions. Secondly, the emergence of open source, cloud-based risk analysis platforms supports the construction of a modular, distributed, and potentially decentralised data processing workflow. Finally, linking data analysis platforms to social computer networks and ICT (e.g. mobile phones, tablets) allows tailored interfaces and people-centred decision- and policy-support systems to be built. Our proposition is that maximum impact is created if end-users are involved not only in data collection, but also over the entire project life-cycle, including the analysis and provision of results. In this context, citizen science complements more traditional knowledge generation practices, and also enhances multi-directional information provision, risk management, early-warning systems and local resilience building.

Collaborative care: Using six thinking hats for decision making.

PubMed

Cioffi, Jane Marie

2017-12-01

To apply six thinking hats technique for decision making in collaborative care. In collaborative partnerships, effective communications need to occur in patient, family, and health care professional meetings. The effectiveness of these meetings depends on the engagement of participants and the quality of the meeting process. The use of six thinking hats technique to engage all participants in effective dialogue is proposed. Discussion paper. Electronic databases, CINAHL, Pub Med, and Science Direct, were searched for years 1990 to 2017. Using six thinking hats technique in patient family meetings nurses can guide a process of dialogue that focuses decision making to build equal care partnerships inclusive of all participants. Nurses will need to develop the skills for using six thinking hats technique and provide support to all participants during the meeting process. Collaborative decision making can be augmented by six thinking hat technique to provide patients, families, and health professionals with opportunities to make informed decisions about care that considers key issues for all involved. Nurses who are most often advocates for patients and their families are in a unique position to lead this initiative in meetings as they network with all health professionals. © 2017 John Wiley & Sons Australia, Ltd.

Methodological Framework for Analysis of Buildings-Related Programs with BEAMS, 2008

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

Elliott, Douglas B.; Dirks, James A.; Hostick, Donna J.

The U.S. Department of Energy’s (DOE’s) Office of Energy Efficiency and Renewable Energy (EERE) develops official “benefits estimates” for each of its major programs using its Planning, Analysis, and Evaluation (PAE) Team. PAE conducts an annual integrated modeling and analysis effort to produce estimates of the energy, environmental, and financial benefits expected from EERE’s budget request. These estimates are part of EERE’s budget request and are also used in the formulation of EERE’s performance measures. Two of EERE’s major programs are the Building Technologies Program (BT) and the Weatherization and Intergovernmental Program (WIP). Pacific Northwest National Laboratory (PNNL) supports PAEmore » by developing the program characterizations and other market information necessary to provide input to the EERE integrated modeling analysis as part of PAE’s Portfolio Decision Support (PDS) effort. Additionally, PNNL also supports BT by providing line-item estimates for the Program’s internal use. PNNL uses three modeling approaches to perform these analyses. This report documents the approach and methodology used to estimate future energy, environmental, and financial benefits using one of those methods: the Building Energy Analysis and Modeling System (BEAMS). BEAMS is a PC-based accounting model that was built in Visual Basic by PNNL specifically for estimating the benefits of buildings-related projects. It allows various types of projects to be characterized including whole-building, envelope, lighting, and equipment projects. This document contains an overview section that describes the estimation process and the models used to estimate energy savings. The body of the document describes the algorithms used within the BEAMS software. This document serves both as stand-alone documentation for BEAMS, and also as a supplemental update of a previous document, Methodological Framework for Analysis of Buildings-Related Programs: The GPRA Metrics Effort, (Elliott et al. 2004b). The areas most changed since the publication of that previous document are those discussing the calculation of lighting and HVAC interactive effects (for both lighting and envelope/whole-building projects). This report does not attempt to convey inputs to BEAMS or the methodology of their derivation.« less

Family Engagement in Schoolwide Positive Behavioral Interventions and Supports: Barriers and Facilitators to Implementation.

PubMed

Garbacz, S Andrew; Hirano, Kara; McIntosh, Kent; Eagle, John W; Minch, Devon; Vatland, Christopher

2017-11-20

The purpose of this study was to identify barriers and facilitators to family engagement in schools implementing schoolwide positive behavioral interventions and supports (PBIS). Participants consisted of 1 representative member each from 204 school PBIS teams across 3 states. Qualitative analysis guided examination of responses to 1 question regarding barriers and 2 questions about facilitators to family engagement. Survey respondents identified key barriers to family engagement as a lack of resources, inconsistent communication, and reluctance of families and school staff to partner. Specified facilitators included communication, PBIS, shared decision-making, and strategies to build relationships with families. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Participatory Approach to Long-Term Socio-Economic Scenarios as Building Block of a Local Vulnerability and Risk Assessment Tool - The Case Study Lienz (East-Tyrol)

NASA Astrophysics Data System (ADS)

Meyer, Ina; Eder, Brigitte; Hama, Michiko; Leitner, Markus

2016-04-01

Risks associated with climate change are mostly still understood and analyzed in a sector- or hazard-specific and rarely in a systemic, dynamic and scenario-based manner. In addition, socio-economic trends are often neglected in local vulnerability and risk assessments although they represent potential key determinants of risk and vulnerability. The project ARISE (Adaptation and Decision Support via Risk Management Through Local Burning Embers) aims at filling this gap by applying a participatory approach to socio-economic scenario building as building block of a local vulnerability assessment and risk management tool. Overall, ARISE aims at developing a decision support system for climate-sensitive iterative risk management as a key adaptation tool for the local level using Lienz in the East-Tyrol as a test-site City. One central building block is participatory socio-economic scenario building that - together with regionalized climate change scenarios - form a centrepiece in the process-oriented assessment of climate change risks and vulnerability. Major vulnerabilities and risks may stem from the economic performance, the socio-economic or socio-demographic developments or changes in asset exposition and not from climate change impacts themselves. The IPCC 5th assessment report underlines this and states that for most economic sectors, the impact of climate change may be small relative to the impacts of other driving forces such as changes in population growth, age, income, technology, relative prices, lifestyle, regulation, governance and many other factors in the socio-economy (Arent et al., 2014). The paper presents the methodology, process and results with respect to the building of long-term local socio-economic scenarios for the City of Lienz and the surrounding countryside. Scenarios were developed in a participatory approach using a scenario workshop that involved major stakeholders from the region. Participatory approaches are increasingly recognized as an important element in management and decision-making as problems in today's world are complex and require knowledge from many different domains and disciplines. Participation is also said to be a process of collective learning that changes the way people think and act which is a relevant point in forming appropriate region-specific climate adaptation strategies. The scenarios are based on an analysis of data on recent states and trends in major local sector developments concerning absolute and relative employment and value creation as well as on distinct socio-demographic developments in the region. Categories discussed in the scenario workshop cover inter alia institutions and governance, demographics, production and demand, markets, value-chains and trade, scientific and technological innovations, education and health. The derived stakeholder-based socio-economic scenarios were, in a second step, matched with the Shared Socio-economic reference Pathways (SSPs) in order to frame the locally produced scenarios with global narratives. Both strains were, in a third step, combined and backed-up by scientific literature in order to build the local socio-economic scenarios that served as background information in the analysis of risks, vulnerability and appropriate adaptation measures in the case-study region.

Geo-portal as a planning instrument: supporting decision making and fostering market potential of Energy efficiency in buildings

NASA Astrophysics Data System (ADS)

Cuca, Branka; Brumana, Raffaella; Oreni, Daniela; Iannaccone, Giuliana; Sesana, Marta Maria

2014-03-01

Steady technological progress has led to a noticeable advancement in disciplines associated with Earth observation. This has enabled information transition regarding changing scenarios, both natural and urban, to occur in (almost) real time. In particular, the need for integration on a local scale with the wider territorial framework has occurred in analysis and monitoring of built environments over the last few decades. The progress of Geographic Information (GI) science has provided significant advancements when it comes to spatial analysis, while the almost free availability of the internet has ensured a fast and constant exchange of geo-information, even for everyday users' requirements. Due to its descriptive and semantic nature, geo-spatial information is capable of providing a complete overview of a certain phenomenon and of predicting the implications within the natural, social and economic context. However, in order to integrate geospatial data into decision making processes, it is necessary to provide a specific context, which is well supported by verified data. This paper investigates the potentials of geo-portals as planning instruments developed to share multi-temporal/multi-scale spatial data, responding to specific end-users' demands in the case of Energy efficiency in Buildings (EeB) across European countries. The case study regards the GeoCluster geo-portal and mapping tool (Project GE2O, FP7), built upon a GeoClustering methodology for mapping of indicators relevant for energy efficiency technologies in the construction sector.

The role of psychological resilience and positive affect in risky decision-making.

PubMed

Xing, Cai; Sun, Jian-min

2013-01-01

Past studies suggest that positive affect produces a wide range of desirable outcomes because it helps people build lasting resources. It may be assumed that these resources build on positive affect over time, which in turn may explain the beneficial effect of positive affect in stressful encounters. However, this assumption has not been directly tested by empirical studies. This question is important in that it helps clarify the underlying mechanism through which individuals with more positive affect might respond adaptively to adverse situations. Using a stressful task that included 20 rounds of risky investment choices, the current study examined whether psychological resilience, an important personal resource fuelled by positive affect, could account for the beneficial effects of positive affect. Specifically, we examined the relationship between individuals' baseline levels of positive affect, their levels of psychological resilience, their choices in a risky investment decision task, and their levels of positive affect on the final investment task. The results demonstrate that psychological resilience could indeed help explain happier people's enhanced outcomes: They chose higher return although more risky investment options and experienced more positive affect at the end of the task. The current study supports the notion that individuals who experience frequent positive affect thrive through various challenges not simply because they feel good, but because they have resources that they can utilize to deal with these challenges. Findings from the present study support further investigation of the important relationship between specific positive affect, psychological resilience, and performance in risky investment tasks.

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

Velsko, S. P.

The microbial DNA Index System (MiDIS) is a concept for a microbial forensic database and investigative decision support system that can be used to help investigators identify the sources of microbial agents that have been used in a criminal or terrorist incident. The heart of the proposed system is a rigorous method for calculating source probabilities by using certain fundamental sampling distributions associated with the propagation and mutation of microbes on disease transmission networks. This formalism has a close relationship to mitochondrial and Y-chromosomal human DNA forensics, and the proposed decision support system is somewhat analogous to the CODIS andmore » SWGDAM mtDNA databases. The MiDIS concept does not involve the use of opportunistic collections of microbial isolates and phylogenetic tree building as a basis for inference. A staged approach can be used to build MiDIS as an enduring capability, beginning with a pilot demonstration program that must meet user expectations for performance and validation before evolving into a continuing effort. Because MiDIS requires input from a a broad array of expertise including outbreak surveillance, field microbial isolate collection, microbial genome sequencing, disease transmission networks, and laboratory mutation rate studies, it will be necessary to assemble a national multi-laboratory team to develop such a system. The MiDIS effort would lend direction and focus to the national microbial genetics research program for microbial forensics, and would provide an appropriate forensic framework for interfacing to future national and international disease surveillance efforts.« less

A method of building of decision trees based on data from wearable device during a rehabilitation of patients with tibia fractures

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

Kupriyanov, M. S., E-mail: mikhail.kupriyanov@gmail.com; Shukeilo, E. Y., E-mail: eyshukeylo@gmail.com; Shichkina, J. A., E-mail: strange.y@mail.ru

2015-11-17

Nowadays technologies which are used in traumatology are a combination of mechanical, electronic, calculating and programming tools. Relevance of development of mobile applications for an expeditious data processing which are received from medical devices (in particular, wearable devices), and formulation of management decisions increases. Using of a mathematical method of building of decision trees for an assessment of a patient’s health condition using data from a wearable device considers in this article.

A method of building of decision trees based on data from wearable device during a rehabilitation of patients with tibia fractures

NASA Astrophysics Data System (ADS)

Kupriyanov, M. S.; Shukeilo, E. Y.; Shichkina, J. A.

2015-11-01

Nowadays technologies which are used in traumatology are a combination of mechanical, electronic, calculating and programming tools. Relevance of development of mobile applications for an expeditious data processing which are received from medical devices (in particular, wearable devices), and formulation of management decisions increases. Using of a mathematical method of building of decision trees for an assessment of a patient's health condition using data from a wearable device considers in this article.

Research on Application of FMECA in Missile Equipment Maintenance Decision

NASA Astrophysics Data System (ADS)

Kun, Wang

2018-03-01

Fault mode effects and criticality analysis (FMECA) is a method widely used in engineering. Studying the application of FMEA technology in military equipment maintenance decision-making, can help us build a better equipment maintenance support system, and increase the using efficiency of weapons and equipment. Through Failure Modes, Effects and Criticality Analysis (FMECA) of equipment, known and potential failure modes and their causes are found out, and the influence on the equipment performance, operation success, personnel security are determined. Furthermore, according to the synthetical effects of the severity of effects and the failure probability, possible measures for prevention and correction are put forward. Through replacing or adjusting the corresponding parts, corresponding maintenance strategy is decided for preventive maintenance of equipment, which helps improve the equipment reliability.

Assessing Rural Sustainable Development potentialities using a Dominance-based Rough Set Approach.

PubMed

Boggia, Antonio; Rocchi, Lucia; Paolotti, Luisa; Musotti, Francesco; Greco, Salvatore

2014-11-01

Rural Development is a priority in Europe and it is supported by specific, financial programmes. At the same time, sustainability is the key word for the European Union to construct programmes and policies for all human activities. However, measuring sustainability of rural areas is not easy, due to their particular features. The improvement of knowledge on sustainability in rural areas is important to build long term policies and strategies for those territories. The objective of this study is the development of a decision support system based on the Dominance-based Rough Set Approach (DRSA), to assess the level of Rural Sustainable Development in specific areas. We used DRSA to analyze the level of sustainability of the 92 municipalities of the Region of Umbria, Italy. The results were synthesized in a final ranking, taking into account the equilibrium and the integration between development and sustainability of each municipality. DRSA showed a high potential in the context of management or planning, and for supporting Decision Makers. DRSA is able to give a ranking as well as an explanation of the main factors driving sustainable development in rural areas. Copyright © 2014 Elsevier Ltd. All rights reserved.

NOAA's National Water Model - Integration of National Water Model with Geospatial Data creating Water Intelligence

NASA Astrophysics Data System (ADS)

Clark, E. P.; Cosgrove, B.; Salas, F.

2016-12-01

As a significant step forward to transform NOAA's water prediction services, NOAA plans to implement a new National Water Model (NWM) Version 1.0 in August 2016. A continental scale water resources model, the NWM is an evolution of the WRF-Hydro architecture developed by the National Center for Atmospheric Research (NCAR). The NWM will provide analyses and forecasts of flow for the 2.7 million stream reaches nationwide in the National Hydrography Dataset Plus v2 (NHDPlusV2) jointly developed by the USGS and EPA. The NWM also produces high-resolution water budget variables of snow, soil moisture, and evapotranspiration on a 1-km grid. NOAA's stakeholders require additional decision support application to be built on these data. The Geo-intelligence division of the Office of Water Prediction is building new products and services that integrate output from the NWM with geospatial datasets such as infrastructure and demographics to better estimate the impacts dynamic water resource states on community resiliency. This presentation will detail the methods and underlying information to produce prototypes water resources intelligence that is timely, actionable and credible. Moreover, it will to explore the NWM capability to support sector-specific decision support services.

Improving access to shared decision-making for Hispanics/Latinos with inadequately controlled type 2 diabetes mellitus

PubMed Central

Davidson, Jaime A; Rosales, Aracely; Shillington, Alicia C; Bailey, Robert A; Kabir, Chris; Umpierrez, Guillermo E

2015-01-01

Purpose To describe the cultural and linguistic adaptation and Spanish translation of an English-language patient decision aid (PDA) for use in supporting shared decision-making in Hispanics/Latinos with type 2 diabetes mellitus (T2DM), a group at a high risk for complications. Patients and methods A steering committee of endocrinologists, a primary care physician, a certified diabetes educator, and a dietician, each with extensive experience in providing care to Hispanics/Latinos was convened to assess a PDA developed for English-speaking patients with T2DM. English content was reviewed for cultural sensitivity and appropriateness for a Hispanic/Latino population. A consensus-building process and iterative version edits incorporated clinician perspectives. The content was adapted to be consistent with traditional Hispanic/Latino cultural communication precepts (eg, avoidance of hostile confrontation; value for warm interaction; respect for authority; value of family support for decisions). The PDA was translated by native-speaking individuals with diabetes expertise. Results The PDA underwent testing during cognitive interviews with ten Spanish-speaking Hispanics/Latinos with T2DM to ensure that the content is reflective of the experience, understanding, and language Hispanic/Latino patients use to describe diabetes and treatment. Content edits were made to assure a literacy level appropriate to the audience, and the PDA was produced for online video dissemination. Conclusion High-quality, well-developed tools to facilitate shared decision-making in populations with limited access to culturally sensitive information can narrow gaps and align care with individual patient preferences. A newly developed PDA is available for shared decision-making that provides culturally appropriate treatment information for inadequately controlled Hispanics/Latinos with T2DM. The impact on the overall health of patients and care management of T2DM requires further study. PMID:25995623

What is the impact of the Internet on decision-making in pregnancy? A global study.

PubMed

Lagan, Briege M; Sinclair, Marlene; Kernohan, W George

2011-12-01

  Women need access to evidence-based information to make informed choices in pregnancy. A search for health information is one of the major reasons that people worldwide access the Internet. Recent years have witnessed an increase in Internet usage by women seeking pregnancy-related information. The aim of this study was to build on previous quantitative studies to explore women's experiences and perceptions of using the Internet for retrieving pregnancy-related information, and its influence on their decision-making processes.   This global study drew on the interpretive qualitative traditions together with a theoretical model on information seeking, adapted to understand Internet use in pregnancy and its role in relation to decision-making. Thirteen asynchronous online focus groups across five countries were conducted with 92 women who had accessed the Internet for pregnancy-related information over a 3-month period. Data were readily transferred and analyzed deductively.   The overall analysis indicates that the Internet is having a visible impact on women's decision making in regards to all aspects of their pregnancy. The key emergent theme was the great need for information. Four broad themes also emerged: "validate information,"empowerment,"share experiences," and "assisted decision-making." Women also reported how the Internet provided support, its negative and positive aspects, and as a source of accurate, timely information.   Health professionals have a responsibility to acknowledge that women access the Internet for support and pregnancy-related information to assist in their decision-making. Health professionals must learn to work in partnership with women to guide them toward evidence-based websites and be prepared to discuss the ensuing information. © 2011, Copyright the Authors. Journal compilation © 2011, Wiley Periodicals, Inc.

The International Decision Support Initiative Reference Case for Economic Evaluation: An Aid to Thought.

PubMed

Wilkinson, Thomas; Sculpher, Mark J; Claxton, Karl; Revill, Paul; Briggs, Andrew; Cairns, John A; Teerawattananon, Yot; Asfaw, Elias; Lopert, Ruth; Culyer, Anthony J; Walker, Damian G

2016-12-01

Policymakers in high-, low-, and middle-income countries alike face challenging choices about resource allocation in health. Economic evaluation can be useful in providing decision makers with the best evidence of the anticipated benefits of new investments, as well as their expected opportunity costs-the benefits forgone of the options not chosen. To guide the decisions of health systems effectively, it is important that the methods of economic evaluation are founded on clear principles, are applied systematically, and are appropriate to the decision problems they seek to inform. The Bill and Melinda Gates Foundation, a major funder of economic evaluations of health technologies in low- and middle-income countries (LMICs), commissioned a "reference case" through the International Decision Support Initiative (iDSI) to guide future evaluations, and improve both the consistency and usefulness to decision makers. The iDSI Reference Case draws on previous insights from the World Health Organization, the US Panel on Cost-Effectiveness in Health Care, and the UK National Institute for Health and Care Excellence. Comprising 11 key principles, each accompanied by methodological specifications and reporting standards, the iDSI Reference Case also serves as a means of identifying priorities for methods research, and can be used as a framework for capacity building and technical assistance in LMICs. The iDSI Reference Case is an aid to thought, not a substitute for it, and should not be followed slavishly without regard to context, culture, or history. This article presents the iDSI Reference Case and discusses the rationale, approach, components, and application in LMICs. Copyright © 2016 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Improving access to shared decision-making for Hispanics/Latinos with inadequately controlled type 2 diabetes mellitus.

PubMed

Davidson, Jaime A; Rosales, Aracely; Shillington, Alicia C; Bailey, Robert A; Kabir, Chris; Umpierrez, Guillermo E

2015-01-01

To describe the cultural and linguistic adaptation and Spanish translation of an English-language patient decision aid (PDA) for use in supporting shared decision-making in Hispanics/Latinos with type 2 diabetes mellitus (T2DM), a group at a high risk for complications. A steering committee of endocrinologists, a primary care physician, a certified diabetes educator, and a dietician, each with extensive experience in providing care to Hispanics/Latinos was convened to assess a PDA developed for English-speaking patients with T2DM. English content was reviewed for cultural sensitivity and appropriateness for a Hispanic/Latino population. A consensus-building process and iterative version edits incorporated clinician perspectives. The content was adapted to be consistent with traditional Hispanic/Latino cultural communication precepts (eg, avoidance of hostile confrontation; value for warm interaction; respect for authority; value of family support for decisions). The PDA was translated by native-speaking individuals with diabetes expertise. The PDA underwent testing during cognitive interviews with ten Spanish-speaking Hispanics/Latinos with T2DM to ensure that the content is reflective of the experience, understanding, and language Hispanic/Latino patients use to describe diabetes and treatment. Content edits were made to assure a literacy level appropriate to the audience, and the PDA was produced for online video dissemination. High-quality, well-developed tools to facilitate shared decision-making in populations with limited access to culturally sensitive information can narrow gaps and align care with individual patient preferences. A newly developed PDA is available for shared decision-making that provides culturally appropriate treatment information for inadequately controlled Hispanics/Latinos with T2DM. The impact on the overall health of patients and care management of T2DM requires further study.

Five shared decision-making tools in 5 months: use of rapid reviews to develop decision boxes for seniors living with dementia and their caregivers.

PubMed

Lawani, Moulikatou Adouni; Valéra, Béatriz; Fortier-Brochu, Émilie; Légaré, France; Carmichael, Pierre-Hugues; Côté, Luc; Voyer, Philippe; Kröger, Edeltraut; Witteman, Holly; Rodriguez, Charo; Giguere, Anik M C

2017-03-15

Decision support tools build upon comprehensive and timely syntheses of literature. Rapid reviews may allow supporting their development by omitting certain components of traditional systematic reviews. We thus aimed to describe a rapid review approach underlying the development of decision support tools, i.e., five decision boxes (DB) for shared decision-making between seniors living with dementia, their caregivers, and healthcare providers. We included studies based on PICO questions (Participant, Intervention, Comparison, Outcome) describing each of the five specific decision. We gave priority to higher quality evidence (e.g., systematic reviews). For each DB, we first identified secondary sources of literature, namely, clinical summaries, clinical practice guidelines, and systematic reviews. After an initial extraction, we searched for primary studies in academic databases and grey literature to fill gaps in evidence. We extracted study designs, sample sizes, populations, and probabilities of benefits/harms of the health options. A single reviewer conducted the literature search and study selection. The data extracted by one reviewer was verified by a second experienced reviewer. Two reviewers assessed the quality of the evidence. We converted all probabilities into absolute risks for ease of understanding. Two to five experts validated the content of each DB. We conducted descriptive statistical analyses on the review processes and resources required. The approach allowed screening of a limited number of references (range: 104 to 406/review). For each review, we included 15 to 26 studies, 2 to 10 health options, 11 to 62 health outcomes and we conducted 9 to 47 quality assessments. A team of ten reviewers with varying levels of expertise was supported at specific steps by an information specialist, a biostatistician, and a graphic designer. The time required to complete a rapid review varied from 7 to 31 weeks per review (mean ± SD, 19 ± 10 weeks). Data extraction required the most time (8 ± 6.8 weeks). The average estimated cost of a rapid review was C$11,646 (SD = C$10,914). This approach enabled the development of clinical tools more rapidly than with a traditional systematic review. Future studies should evaluate the applicability of this approach to other teams/tools.

Theoretical basis of the DOE-2 building energy use analysis program

NASA Astrophysics Data System (ADS)

Curtis, R. B.

1981-04-01

A user-oriented, public domain, computer program was developed that will enable architects and engineers to perform design and retrofit studies of the energy-use of buildings under realistic weather conditions. The DOE-2.1A has been named by the US DOE as the standard evaluation technique for the Congressionally mandated building energy performance standards (BEPS). A number of program design decisions were made that determine the breadth of applicability of DOE-2.1. Such design decisions are intrinsic to all building energy use analysis computer programs and determine the types of buildings or the kind of HVAC systems that can be modeled. In particular, the weighting factor method used in DOE-2 has both advantages and disadvantages relative to other computer programs.

Supporting virtual enterprise design by a web-based information model

NASA Astrophysics Data System (ADS)

Li, Dong; Barn, Balbir; McKay, Alison; de Pennington, Alan

2001-10-01

Development of IT and its applications have led to significant changes in business processes. To pursue agility, flexibility and best service to customers, enterprises focus on their core competence and dynamically build relationships with partners to form virtual enterprises as customer driven temporary demand chains/networks. Building the networked enterprise needs responsively interactive decisions instead of a single-direction partner selection process. Benefits and risks in the combination should be systematically analysed, and aggregated information about value-adding abilities and risks of networks needs to be derived from interactions of all partners. In this research, a hierarchical information model to assess partnerships for designing virtual enterprises was developed. Internet technique has been applied to the evaluation process so that interactive decisions can be visualised and made responsively during the design process. The assessment is based on the process which allows each partner responds to requirements of the virtual enterprise by planning its operational process as a bidder. The assessment is then produced by making an aggregated value to represent prospect of the combination of partners given current bidding. Final design is a combination of partners with the greatest total value-adding capability and lowest risk.

Modular modeling system for building distributed hydrologic models with a user-friendly software package

NASA Astrophysics Data System (ADS)

Wi, S.; Ray, P. A.; Brown, C.

2015-12-01

A software package developed to facilitate building distributed hydrologic models in a modular modeling system is presented. The software package provides a user-friendly graphical user interface that eases its practical use in water resources-related research and practice. The modular modeling system organizes the options available to users when assembling models according to the stages of hydrological cycle, such as potential evapotranspiration, soil moisture accounting, and snow/glacier melting processes. The software is intended to be a comprehensive tool that simplifies the task of developing, calibrating, validating, and using hydrologic models through the inclusion of intelligent automation to minimize user effort, and reduce opportunities for error. Processes so far automated include the definition of system boundaries (i.e., watershed delineation), climate and geographical input generation, and parameter calibration. Built-in post-processing toolkits greatly improve the functionality of the software as a decision support tool for water resources system management and planning. Example post-processing toolkits enable streamflow simulation at ungauged sites with predefined model parameters, and perform climate change risk assessment by means of the decision scaling approach. The software is validated through application to watersheds representing a variety of hydrologic regimes.

Reducing construction waste: A study of urban infrastructure projects.

PubMed

de Magalhães, Ruane Fernandes; Danilevicz, Ângela de Moura Ferreira; Saurin, Tarcisio Abreu

2017-09-01

The construction industry is well-known for producing waste detrimental to the environment, and its impacts have increased with the development process of cities. Although there are several studies focused on the environmental impact of residential and commercial buildings, less knowledge is available regarding decreasing construction waste (CW) generation in urban infrastructure projects. This study presents best practices to reduce waste in the said projects, stressing the role of decision-making in the design stage and the effective management of construction processes in public sector. The best practices were identified from literature review, document analysis in 14 projects of urban infrastructure, and both qualitative and quantitative survey with 18 experts (architects and engineers) playing different roles on those projects. The contributions of these research are: (i) the identification of the main building techniques related to the urban design typologies analyzed; (ii) the identification of cause-effect relationships between the design choices and the CW generation diagnosis; (iii) the proposal of a checklist to support the decision-making process, that can be used as a control and evaluation instrument when developing urban infrastructure designs, focused on the construction waste minimization (CWM). Copyright © 2017 Elsevier Ltd. All rights reserved.

Building clinical networks: a developmental evaluation framework.

PubMed

Carswell, Peter; Manning, Benjamin; Long, Janet; Braithwaite, Jeffrey

2014-05-01

Clinical networks have been designed as a cross-organisational mechanism to plan and deliver health services. With recent concerns about the effectiveness of these structures, it is timely to consider an evidence-informed approach for how they can be developed and evaluated. To document an evaluation framework for clinical networks by drawing on the network evaluation literature and a 5-year study of clinical networks. We searched literature in three domains: network evaluation, factors that aid or inhibit network development, and on robust methods to measure network characteristics. This material was used to build a framework required for effective developmental evaluation. The framework's architecture identifies three stages of clinical network development; partner selection, network design and network management. Within each stage is evidence about factors that act as facilitators and barriers to network growth. These factors can be used to measure progress via appropriate methods and tools. The framework can provide for network growth and support informed decisions about progress. For the first time in one place a framework incorporating rigorous methods and tools can identify factors known to affect the development of clinical networks. The target user group is internal stakeholders who need to conduct developmental evaluation to inform key decisions along their network's developmental pathway.

Occupational health and safety: Designing and building with MACBETH a value risk-matrix for evaluating health and safety risks

NASA Astrophysics Data System (ADS)

Lopes, D. F.; Oliveira, M. D.; Costa, C. A. Bana e.

2015-05-01

Risk matrices (RMs) are commonly used to evaluate health and safety risks. Nonetheless, they violate some theoretical principles that compromise their feasibility and use. This study describes how multiple criteria decision analysis methods have been used to improve the design and the deployment of RMs to evaluate health and safety risks at the Occupational Health and Safety Unit (OHSU) of the Regional Health Administration of Lisbon and Tagus Valley. ‘Value risk-matrices’ (VRMs) are built with the MACBETH approach in four modelling steps: a) structuring risk impacts, involving the construction of descriptors of impact that link risk events with health impacts and are informed by scientific evidence; b) generating a value measurement scale of risk impacts, by applying the MACBETH-Choquet procedure; c) building a system for eliciting subjective probabilities that makes use of a numerical probability scale that was constructed with MACBETH qualitative judgments on likelihood; d) and defining a classification colouring scheme for the VRM. A VRM built with OHSU members was implemented in a decision support system which will be used by OHSU members to evaluate health and safety risks and to identify risk mitigation actions.

Learning Probabilistic Inference through Spike-Timing-Dependent Plasticity.

PubMed

Pecevski, Dejan; Maass, Wolfgang

2016-01-01

Numerous experimental data show that the brain is able to extract information from complex, uncertain, and often ambiguous experiences. Furthermore, it can use such learnt information for decision making through probabilistic inference. Several models have been proposed that aim at explaining how probabilistic inference could be performed by networks of neurons in the brain. We propose here a model that can also explain how such neural network could acquire the necessary information for that from examples. We show that spike-timing-dependent plasticity in combination with intrinsic plasticity generates in ensembles of pyramidal cells with lateral inhibition a fundamental building block for that: probabilistic associations between neurons that represent through their firing current values of random variables. Furthermore, by combining such adaptive network motifs in a recursive manner the resulting network is enabled to extract statistical information from complex input streams, and to build an internal model for the distribution p (*) that generates the examples it receives. This holds even if p (*) contains higher-order moments. The analysis of this learning process is supported by a rigorous theoretical foundation. Furthermore, we show that the network can use the learnt internal model immediately for prediction, decision making, and other types of probabilistic inference.

Learning Probabilistic Inference through Spike-Timing-Dependent Plasticity123

PubMed Central

Pecevski, Dejan

2016-01-01

Abstract Numerous experimental data show that the brain is able to extract information from complex, uncertain, and often ambiguous experiences. Furthermore, it can use such learnt information for decision making through probabilistic inference. Several models have been proposed that aim at explaining how probabilistic inference could be performed by networks of neurons in the brain. We propose here a model that can also explain how such neural network could acquire the necessary information for that from examples. We show that spike-timing-dependent plasticity in combination with intrinsic plasticity generates in ensembles of pyramidal cells with lateral inhibition a fundamental building block for that: probabilistic associations between neurons that represent through their firing current values of random variables. Furthermore, by combining such adaptive network motifs in a recursive manner the resulting network is enabled to extract statistical information from complex input streams, and to build an internal model for the distribution p* that generates the examples it receives. This holds even if p* contains higher-order moments. The analysis of this learning process is supported by a rigorous theoretical foundation. Furthermore, we show that the network can use the learnt internal model immediately for prediction, decision making, and other types of probabilistic inference. PMID:27419214

Developing and implementing a heart failure data mart for research and quality improvement.

PubMed

Abu-Rish Blakeney, Erin; Wolpin, Seth; Lavallee, Danielle C; Dardas, Todd; Cheng, Richard; Zierler, Brenda

2018-04-19

The purpose of this project was to build and formatively evaluate a near-real time heart failure (HF) data mart. Heart Failure (HF) is a leading cause of hospital readmissions. Increased efforts to use data meaningfully may enable healthcare organizations to better evaluate effectiveness of care pathways and quality improvements, and to prospectively identify risk among HF patients. We followed a modified version of the Systems Development Life Cycle: 1) Conceptualization, 2) Requirements Analysis, 3) Iterative Development, and 4) Application Release. This foundational work reflects the first of a two-phase project. Phase two (in process) involves the implementation and evaluation of predictive analytics for clinical decision support. We engaged stakeholders to build working definitions and established automated processes for creating an HF data mart containing actionable information for diverse audiences. As of December 2017, the data mart contains information from over 175,000 distinct patients and >100 variables from each of their nearly 300,000 visits. The HF data mart will be used to enhance care, assist in clinical decision-making, and improve overall quality of care. This model holds the potential to be scaled and generalized beyond the initial focus and setting.

Pathways: patient-centred decision counselling for women at risk of cancer-related infertility: a protocol for a comparative effectiveness cluster randomised trial.

PubMed

Woodard, Terri Lynn; Hoffman, Aubri S; Crocker, Laura C; Holman, Deborah A; Hoffman, Derek B; Ma, Jusheng; Bassett, Roland L; Leal, Viola B; Volk, Robert J

2018-02-21

National guidelines recommend that all reproductive-age women with cancer be informed of their fertility risks and offered referral to fertility specialists to discuss fertility preservation options. However, reports indicate that only 5% of patients have consultations, and rates of long-term infertility-related distress remain high. Previous studies report several barriers to fertility preservation; however, initial success has been reported using provider education, patient decision aids and navigation support. This protocol will test effects of a multicomponent intervention compared with usual care on women's fertility preservation knowledge and decision-making outcomes. This cluster-randomised trial will compare the multicomponent intervention (provider education, patient decision aid and navigation support) with usual care (consultation and referral, if requested). One hundred newly diagnosed English-speaking women of reproductive age who are at risk of cancer-related infertility will be recruited from four regional oncology clinics.The Pathways patient decision aid website provides (1) up-to-date evidence and descriptions of fertility preservation and other family-building options, tailored to cancer type; (2) structured guidance to support personalising the information and informed decision-making; and (3) a printable summary to help women prepare for discussions with their oncologist and/or fertility specialist. Four sites will be randomly assigned to intervention or control groups. Participants will be recruited after their oncology consultation and asked to complete online questionnaires at baseline, 1 week and 2 months to assess their demographics, fertility preservation knowledge, and decision-making process and quality. The primary outcome (decisional conflict) will be tested using Fisher's exact test. Secondary outcomes will be assessed using generalised linear mixed models, and sensitivity analyses will be conducted, as appropriate. The University of Texas MD Anderson Cancer Center provided approval and ongoing review of this protocol. Results will be presented at relevant scientific meetings and submitted for publication in a peer-reviewed journal. NCT03141437; Pre-results. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Decision-Oriented Health Technology Assessment: One Step Forward in Supporting the Decision-Making Process in Hospitals.

PubMed

Ritrovato, Matteo; Faggiano, Francesco C; Tedesco, Giorgia; Derrico, Pietro

2015-06-01

This article outlines the Decision-Oriented Health Technology Assessment: a new implementation of the European network for Health Technology Assessment Core Model, integrating the multicriteria decision-making analysis by using the analytic hierarchy process to introduce a standardized methodological approach as a valued and shared tool to support health care decision making within a hospital. Following the Core Model as guidance (European network for Health Technology Assessment. HTA core model for medical and surgical interventions. Available from: http://www.eunethta.eu/outputs/hta-core-model-medical-and-surgical-interventions-10r. [Accessed May 27, 2014]), it is possible to apply the analytic hierarchy process to break down a problem into its constituent parts and identify priorities (i.e., assigning a weight to each part) in a hierarchical structure. Thus, it quantitatively compares the importance of multiple criteria in assessing health technologies and how the alternative technologies perform in satisfying these criteria. The verbal ratings are translated into a quantitative form by using the Saaty scale (Saaty TL. Decision making with the analytic hierarchy process. Int J Serv Sci 2008;1:83-98). An eigenvectors analysis is used for deriving the weights' systems (i.e., local and global weights' system) that reflect the importance assigned to the criteria and the priorities related to the performance of the alternative technologies. Compared with the Core Model, this methodological approach supplies a more timely as well as contextualized evidence for a specific technology, making it possible to obtain data that are more relevant and easier to interpret, and therefore more useful for decision makers to make investment choices with greater awareness. We reached the conclusion that although there may be scope for improvement, this implementation is a step forward toward the goal of building a "solid bridge" between the scientific evidence and the final decision maker's choice. Copyright © 2015 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Modeling good research practices--overview: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force--1.

PubMed

Caro, J Jaime; Briggs, Andrew H; Siebert, Uwe; Kuntz, Karen M

2012-01-01

Models--mathematical frameworks that facilitate estimation of the consequences of health care decisions--have become essential tools for health technology assessment. Evolution of the methods since the first ISPOR Modeling Task Force reported in 2003 has led to a new Task Force, jointly convened with the Society for Medical Decision Making, and this series of seven articles presents the updated recommendations for best practices in conceptualizing models; implementing state-transition approaches, discrete event simulations, or dynamic transmission models; and dealing with uncertainty and validating and reporting models transparently. This overview article introduces the work of the Task Force, provides all the recommendations, and discusses some quandaries that require further elucidation. The audience for these articles includes those who build models, stakeholders who utilize their results, and, indeed, anyone concerned with the use of models to support decision making. Copyright © 2012 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

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

PubMed

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

2014-01-01

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

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

PubMed Central

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

2014-01-01

Biomedical research becomes increasingly interdisciplinary and collaborative in nature. Researchers need to efficiently and effectively collaborate and make decisions by meaningfully assembling, mining and analyzing available large-scale volumes of complex multi-faceted data residing in different sources. In line with related research directives revealing that, in spite of the recent advances in data mining and computational analysis, humans can easily detect patterns which computer algorithms may have difficulty in finding, this paper reports on the practical use of an innovative web-based collaboration support platform in a biomedical research context. Arguing that dealing with data-intensive and cognitively complex settings is not a technical problem alone, the proposed platform adopts a hybrid approach that builds on the synergy between machine and human intelligence to facilitate the underlying sense-making and decision making processes. User experience shows that the platform enables more informed and quicker decisions, by displaying the aggregated information according to their needs, while also exploiting the associated human intelligence. PMID:25268270

Sensory integration dynamics in a hierarchical network explains choice probabilities in cortical area MT

PubMed Central

Wimmer, Klaus; Compte, Albert; Roxin, Alex; Peixoto, Diogo; Renart, Alfonso; de la Rocha, Jaime

2015-01-01

Neuronal variability in sensory cortex predicts perceptual decisions. This relationship, termed choice probability (CP), can arise from sensory variability biasing behaviour and from top-down signals reflecting behaviour. To investigate the interaction of these mechanisms during the decision-making process, we use a hierarchical network model composed of reciprocally connected sensory and integration circuits. Consistent with monkey behaviour in a fixed-duration motion discrimination task, the model integrates sensory evidence transiently, giving rise to a decaying bottom-up CP component. However, the dynamics of the hierarchical loop recruits a concurrently rising top-down component, resulting in sustained CP. We compute the CP time-course of neurons in the medial temporal area (MT) and find an early transient component and a separate late contribution reflecting decision build-up. The stability of individual CPs and the dynamics of noise correlations further support this decomposition. Our model provides a unified understanding of the circuit dynamics linking neural and behavioural variability. PMID:25649611

Applications of graphics to support a testbed for autonomous space vehicle operations

NASA Technical Reports Server (NTRS)

Schmeckpeper, K. R.; Aldridge, J. P.; Benson, S.; Horner, S.; Kullman, A.; Mulder, T.; Parrott, W.; Roman, D.; Watts, G.; Bochsler, Daniel C.

1989-01-01

Researchers describe their experience using graphics tools and utilities while building an application, AUTOPS, that uses a graphical Machintosh (TM)-like interface for the input and display of data, and animation graphics to enhance the presentation of results of autonomous space vehicle operations simulations. AUTOPS is a test bed for evaluating decisions for intelligent control systems for autonomous vehicles. Decisions made by an intelligent control system, e.g., a revised mission plan, might be displayed to the user in textual format or he can witness the effects of those decisions via out of window graphics animations. Although a textual description conveys essentials, a graphics animation conveys the replanning results in a more convincing way. Similarily, iconic and menu-driven screen interfaces provide the user with more meaningful options and displays. Presented here are experiences with the SunView and TAE Plus graphics tools used for interface design, and the Johnson Space Center Interactive Graphics Laboratory animation graphics tools used for generating out out of the window graphics.

Effective Team Support: From Modeling to Software Agents

NASA Technical Reports Server (NTRS)

Remington, Roger W. (Technical Monitor); John, Bonnie; Sycara, Katia

2003-01-01

The purpose of this research contract was to perform multidisciplinary research between CMU psychologists, computer scientists and engineers and NASA researchers to design a next generation collaborative system to support a team of human experts and intelligent agents. To achieve robust performance enhancement of such a system, we had proposed to perform task and cognitive modeling to thoroughly understand the impact technology makes on the organization and on key individual personnel. Guided by cognitively-inspired requirements, we would then develop software agents that support the human team in decision making, information filtering, information distribution and integration to enhance team situational awareness. During the period covered by this final report, we made substantial progress in modeling infrastructure and task infrastructure. Work is continuing under a different contract to complete empirical data collection, cognitive modeling, and the building of software agents to support the teams task.

Effective Team Support: From Task and Cognitive Modeling to Software Agents for Time-Critical Complex Work Environments

NASA Technical Reports Server (NTRS)

Remington, Roger W. (Technical Monitor); John, Bonnie E.; Sycara, Katia

2005-01-01

The purpose of this research contract was to perform multidisciplinary research between CMU psychologists, computer scientists and NASA researchers to design a next generation collaborative system to support a team of human experts and intelligent agents. To achieve robust performance enhancement of such a system, we had proposed to perform task and cognitive modeling to thoroughly understand the impact technology makes on the organization and on key individual personnel. Guided by cognitively-inspired requirements, we would then develop software agents that support the human team in decision making, information filtering, information distribution and integration to enhance team situational awareness. During the period covered by this final report, we made substantial progress in completing a system for empirical data collection, cognitive modeling, and the building of software agents to support a team's tasks, and in running experiments for the collection of baseline data.

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 Role of Scientific Studies in Building Consensus in ...

EPA Pesticide Factsheets

We present a new approach for characterizing the potential of scientific studies to reduce conflict among stakeholders in an analytic-deliberative environmental decision-making process. The approach computes a normalized metric, the Expected Consensus Index of New Research (ECINR), for identifying where additional scientific research will best support improved decisions and resolve possible conflicts over preferred management actions. The ECINR reflects the expected change in agreement among parties over preferred management actions with the implementation and consideration of new scientific studies. We demonstrate the ECINR method based on a preliminary application to coral reef protection and restoration in the Gua´nica Bay Watershed, Puerto Rico, focusing on assessing and managing anthropogenic stressors, including sedimentation and pollution from landbased sources such as sewage, agriculture, and development. Structured elicitations of values and beliefs conducted at a coral reef decision support workshop held at La Parguera, Puerto Rico, are used to develop information for illustrating the methodology. The ECINR analysis was focused on a final study group of seven stakeholders, consisting of resource managers and scientists, who were not in agreement on the efficacy and respective benefits of reducing loadings from three sources: sewage, agriculture, and development. The scenario assumed that loadings would be reduced incrementally from each source through

Estimating and communicating prognosis in advanced neurologic disease

PubMed Central

Gramling, Robert; Kelly, Adam G.

2013-01-01

Prognosis can no longer be relegated behind diagnosis and therapy in high-quality neurologic care. High-stakes decisions that patients (or their surrogates) make often rest upon perceptions and beliefs about prognosis, many of which are poorly informed. The new science of prognostication—the estimating and communication “what to expect”—is in its infancy and the evidence base to support “best practices” is lacking. We propose a framework for formulating a prediction and communicating “what to expect” with patients, families, and surrogates in the context of common neurologic illnesses. Because neurologic disease affects function as much as survival, we specifically address 2 important prognostic questions: “How long?” and “How well?” We provide a summary of prognostic information and highlight key points when tailoring a prognosis for common neurologic diseases. We discuss the challenges of managing prognostic uncertainty, balancing hope and realism, and ways to effectively engage surrogate decision-makers. We also describe what is known about the nocebo effects and the self-fulfilling prophecy when communicating prognoses. There is an urgent need to establish research and educational priorities to build a credible evidence base to support best practices, improve communication skills, and optimize decision-making. Confronting the challenges of prognosis is necessary to fulfill the promise of delivering high-quality, patient-centered care. PMID:23420894

What Risk Assessments of Genetically Modified Organisms Can Learn from Institutional Analyses of Public Health Risks

PubMed Central

Rajan, S. Ravi; Letourneau, Deborah K.

2012-01-01

The risks of genetically modified organisms (GMOs) are evaluated traditionally by combining hazard identification and exposure estimates to provide decision support for regulatory agencies. We question the utility of the classical risk paradigm and discuss its evolution in GMO risk assessment. First, we consider the problem of uncertainty, by comparing risk assessment for environmental toxins in the public health domain with genetically modified organisms in the environment; we use the specific comparison of an insecticide to a transgenic, insecticidal food crop. Next, we examine normal accident theory (NAT) as a heuristic to consider runaway effects of GMOs, such as negative community level consequences of gene flow from transgenic, insecticidal crops. These examples illustrate how risk assessments are made more complex and contentious by both their inherent uncertainty and the inevitability of failure beyond expectation in complex systems. We emphasize the value of conducting decision-support research, embracing uncertainty, increasing transparency, and building interdisciplinary institutions that can address the complex interactions between ecosystems and society. In particular, we argue against black boxing risk analysis, and for a program to educate policy makers about uncertainty and complexity, so that eventually, decision making is not the burden that falls upon scientists but is assumed by the public at large. PMID:23193357

What risk assessments of genetically modified organisms can learn from institutional analyses of public health risks.

PubMed

Rajan, S Ravi; Letourneau, Deborah K

2012-01-01

The risks of genetically modified organisms (GMOs) are evaluated traditionally by combining hazard identification and exposure estimates to provide decision support for regulatory agencies. We question the utility of the classical risk paradigm and discuss its evolution in GMO risk assessment. First, we consider the problem of uncertainty, by comparing risk assessment for environmental toxins in the public health domain with genetically modified organisms in the environment; we use the specific comparison of an insecticide to a transgenic, insecticidal food crop. Next, we examine normal accident theory (NAT) as a heuristic to consider runaway effects of GMOs, such as negative community level consequences of gene flow from transgenic, insecticidal crops. These examples illustrate how risk assessments are made more complex and contentious by both their inherent uncertainty and the inevitability of failure beyond expectation in complex systems. We emphasize the value of conducting decision-support research, embracing uncertainty, increasing transparency, and building interdisciplinary institutions that can address the complex interactions between ecosystems and society. In particular, we argue against black boxing risk analysis, and for a program to educate policy makers about uncertainty and complexity, so that eventually, decision making is not the burden that falls upon scientists but is assumed by the public at large.

Clarifying values: an updated review

PubMed Central

2013-01-01

Background Consensus guidelines have recommended that decision aids include a process for helping patients clarify their values. We sought to examine the theoretical and empirical evidence related to the use of values clarification methods in patient decision aids. Methods Building on the International Patient Decision Aid Standards (IPDAS) Collaboration’s 2005 review of values clarification methods in decision aids, we convened a multi-disciplinary expert group to examine key definitions, decision-making process theories, and empirical evidence about the effects of values clarification methods in decision aids. To summarize the current state of theory and evidence about the role of values clarification methods in decision aids, we undertook a process of evidence review and summary. Results Values clarification methods (VCMs) are best defined as methods to help patients think about the desirability of options or attributes of options within a specific decision context, in order to identify which option he/she prefers. Several decision making process theories were identified that can inform the design of values clarification methods, but no single “best” practice for how such methods should be constructed was determined. Our evidence review found that existing VCMs were used for a variety of different decisions, rarely referenced underlying theory for their design, but generally were well described in regard to their development process. Listing the pros and cons of a decision was the most common method used. The 13 trials that compared decision support with or without VCMs reached mixed results: some found that VCMs improved some decision-making processes, while others found no effect. Conclusions Values clarification methods may improve decision-making processes and potentially more distal outcomes. However, the small number of evaluations of VCMs and, where evaluations exist, the heterogeneity in outcome measures makes it difficult to determine their overall effectiveness or the specific characteristics that increase effectiveness. PMID:24625261

Communal Participation in Payment for Environmental Services (PES): Unpacking the Collective Decision to Enroll

NASA Astrophysics Data System (ADS)

Murtinho, Felipe; Hayes, Tanya

2017-06-01

Payment for Environmental Service programs are increasingly applied in communal settings where resource users collectively join the program and agree to limit their shared use of a common-property resource. Who decides to join PES and the degree to which community members agree with the collective decision is critical for the success of said programs. Yet, we have limited understanding of the factors that influence communal participation and the collective decision process. This paper examines communal participation in a national payment for conservation program in Ecuador. We use quantitative and qualitative analysis to (i) identify the attributes of the communities that participate (or not), and factors that facilitate participation ( n = 67), and (ii) assess household preference and alignment with the collective decision to participate ( n = 212). Household participation preferences indicate varying degrees of consensus with the collective decision to participate, with those using the resource less likely to support participation. At the communal level, however, our results indicate that over time, those communities that depend more heavily on their resource systems may ultimately choose to participate. Our findings suggest that communal governance structures and outside organizations may be instrumental in gaining participation in resource-dependent communities and building consensus. Findings also point to the need for further research on communal decision-processes to ensure that the collective decision is based on an informed and democratic process.

Collaborative Workshops for Assessment and Creation of Multi-Objective Decision Support for Multiple Sectors

NASA Astrophysics Data System (ADS)

Kasprzyk, J. R.; Smith, R.; Raseman, W. J.; DeRousseau, M. A.; Dilling, L.; Ozekin, K.; Summers, R. S.; Balaji, R.; Livneh, B.; Rosario-Ortiz, F.; Sprain, L.; Srubar, W. V., III

2017-12-01

This presentation will report on three projects that used interactive workshops with stakeholders to develop problem formulations for Multi-Objective Evolutionary Algorithm (MOEA)-based decision support in diverse fields - water resources planning, water quality engineering under climate extremes, and sustainable materials design. When combined with a simulation model of a system, MOEAs use intelligent search techniques to provide new plans or designs. This approach is gaining increasing prominence in design and planning for environmental sustainability. To use this technique, a problem formulation - objectives and constraints (quantitative measures of performance) and decision variables (actions that can be modified to improve the system) - must be identified. Although critically important for MOEA effectiveness, the problem formulations are not always developed with stakeholders' interests in mind. To ameliorate this issue, project workshops were organized to improve the tool's relevance as well as collaboratively build problem formulations that can be used in applications. There were interesting differences among the projects, which altered the findings of each workshop. Attendees ranged from a group of water managers on the Front Range of Colorado, to water utility representatives from across the country, to a set of designers, academics, and trade groups. The extent to which the workshop participants were already familiar with simulation tools contributed to their willingness to accept the solutions that were generated using the tool. Moreover, in some instances, brainstorming new objectives to include within the MOEA expanded the scope of the problem formulation, relative to the initial conception of the researchers. Through describing results across a diversity of projects, the goal of this presentation is to report on how our approach may inform future decision support collaboration with a variety of stakeholders and sectors.

Building a Shared Understanding of Phenology

NASA Astrophysics Data System (ADS)

Rosemartin, A.; Posthumus, E.; Gerst, K.

2017-12-01

The USA National Phenology Network (USA-NPN) seeks to advance the science of phenology and support the use of phenology information in decision-making. We envision that natural resource, human health, recreation and land-use decisions, in the context of a variable and changing climate, will be supported by USA-NPN products and tools. To achieve this vision we developed a logic model, breaking down the necessary inputs (e.g., IT infrastructure), participants, activities and the short- to long-term goals (e.g., use of phenological information in adaptive management). Here we compare the ongoing activities and outcomes of three recent collaborations to our logic model, in order to improve the model and inform future collaborations. At Midway Atoll National Wildlife Refuge, resource managers use the USA-NPN's phenology monitoring program to pinpoint the minimum number of days between initial growth and seed set in an invasive species. The data output and calendar visualizations that USA-NPN provides are sufficient to identify the appropriate treatment window. In contrast to a direct relationship with a natural resource manager using USA-NPN tools and products, some collaborations require substantive iterative work between partners. USA-NPN and National Park Service staff, along with academic researchers, assessed advancement in the timing of spring, and delivered the work in a format appropriate for park managers. Lastly, collaborations with indigenous communities reveal a requirement to reconsider the relationship between Western science and indigenous knowledge systems, as well as address ethical considerations and develop trust, before Western science can be meaningfully incorporated into decision-making. While the USA-NPN is a boundary organization, working in between federal agencies, states and universities, and is mandated to support decision-making, we still face challenges in generating usable science. We share lessons learned based on our experience with diverse and evolving partnerships.

Developing and Evaluating Communication Strategies to Support Informed Decisions and Practice Based on Evidence (DECIDE): protocol and preliminary results.

PubMed

Treweek, Shaun; Oxman, Andrew D; Alderson, Philip; Bossuyt, Patrick M; Brandt, Linn; Brożek, Jan; Davoli, Marina; Flottorp, Signe; Harbour, Robin; Hill, Suzanne; Liberati, Alessandro; Liira, Helena; Schünemann, Holger J; Rosenbaum, Sarah; Thornton, Judith; Vandvik, Per Olav; Alonso-Coello, Pablo

2013-01-09

Healthcare decision makers face challenges when using guidelines, including understanding the quality of the evidence or the values and preferences upon which recommendations are made, which are often not clear. GRADE is a systematic approach towards assessing the quality of evidence and the strength of recommendations in healthcare. GRADE also gives advice on how to go from evidence to decisions. It has been developed to address the weaknesses of other grading systems and is now widely used internationally. The Developing and Evaluating Communication Strategies to Support Informed Decisions and Practice Based on Evidence (DECIDE) consortium (http://www.decide-collaboration.eu/), which includes members of the GRADE Working Group and other partners, will explore methods to ensure effective communication of evidence-based recommendations targeted at key stakeholders: healthcare professionals, policymakers, and managers, as well as patients and the general public. Surveys and interviews with guideline producers and other stakeholders will explore how presentation of the evidence could be improved to better meet their information needs. We will collect further stakeholder input from advisory groups, via consultations and user testing; this will be done across a wide range of healthcare systems in Europe, North America, and other countries. Targeted communication strategies will be developed, evaluated in randomized trials, refined, and assessed during the development of real guidelines. Results of the DECIDE project will improve the communication of evidence-based healthcare recommendations. Building on the work of the GRADE Working Group, DECIDE will develop and evaluate methods that address communication needs of guideline users. The project will produce strategies for communicating recommendations that have been rigorously evaluated in diverse settings, and it will support the transfer of research into practice in healthcare systems globally.

A study on building data warehouse of hospital information system.

PubMed

Li, Ping; Wu, Tao; Chen, Mu; Zhou, Bin; Xu, Wei-guo

2011-08-01

Existing hospital information systems with simple statistical functions cannot meet current management needs. It is well known that hospital resources are distributed with private property rights among hospitals, such as in the case of the regional coordination of medical services. In this study, to integrate and make full use of medical data effectively, we propose a data warehouse modeling method for the hospital information system. The method can also be employed for a distributed-hospital medical service system. To ensure that hospital information supports the diverse needs of health care, the framework of the hospital information system has three layers: datacenter layer, system-function layer, and user-interface layer. This paper discusses the role of a data warehouse management system in handling hospital information from the establishment of the data theme to the design of a data model to the establishment of a data warehouse. Online analytical processing tools assist user-friendly multidimensional analysis from a number of different angles to extract the required data and information. Use of the data warehouse improves online analytical processing and mitigates deficiencies in the decision support system. The hospital information system based on a data warehouse effectively employs statistical analysis and data mining technology to handle massive quantities of historical data, and summarizes from clinical and hospital information for decision making. This paper proposes the use of a data warehouse for a hospital information system, specifically a data warehouse for the theme of hospital information to determine latitude, modeling and so on. The processing of patient information is given as an example that demonstrates the usefulness of this method in the case of hospital information management. Data warehouse technology is an evolving technology, and more and more decision support information extracted by data mining and with decision-making technology is required for further research.

Ethical Guidelines for Structural Interventions to Small-Scale Historic Stone Masonry Buildings.

PubMed

Hurol, Yonca; Yüceer, Hülya; Başarır, Hacer

2015-12-01

Structural interventions to historic stone masonry buildings require that both structural and heritage values be considered simultaneously. The absence of one of these value systems in implementation can be regarded as an unethical professional action. The research objective of this article is to prepare a guideline for ensuring ethical structural interventions to small-scale stone historic masonry buildings in the conservation areas of Northern Cyprus. The methodology covers an analysis of internationally accepted conservation documents and national laws related to the conservation of historic buildings, an analysis of building codes, especially Turkish building codes, which have been used in Northern Cyprus, and an analysis of the structural interventions introduced to a significant historic building in a semi-intact state in the walled city of Famagusta. This guideline covers issues related to whether buildings are intact or ruined, the presence of earthquake risk, the types of structural decisions in an architectural conservation project, and the values to consider during the decision making phase.

Bioinformatics for transporter pharmacogenomics and systems biology: data integration and modeling with UML.

PubMed

Yan, Qing

2010-01-01

Bioinformatics is the rational study at an abstract level that can influence the way we understand biomedical facts and the way we apply the biomedical knowledge. Bioinformatics is facing challenges in helping with finding the relationships between genetic structures and functions, analyzing genotype-phenotype associations, and understanding gene-environment interactions at the systems level. One of the most important issues in bioinformatics is data integration. The data integration methods introduced here can be used to organize and integrate both public and in-house data. With the volume of data and the high complexity, computational decision support is essential for integrative transporter studies in pharmacogenomics, nutrigenomics, epigenetics, and systems biology. For the development of such a decision support system, object-oriented (OO) models can be constructed using the Unified Modeling Language (UML). A methodology is developed to build biomedical models at different system levels and construct corresponding UML diagrams, including use case diagrams, class diagrams, and sequence diagrams. By OO modeling using UML, the problems of transporter pharmacogenomics and systems biology can be approached from different angles with a more complete view, which may greatly enhance the efforts in effective drug discovery and development. Bioinformatics resources of membrane transporters and general bioinformatics databases and tools that are frequently used in transporter studies are also collected here. An informatics decision support system based on the models presented here is available at http://www.pharmtao.com/transporter . The methodology developed here can also be used for other biomedical fields.

Decision Support System for hydrological extremes

NASA Astrophysics Data System (ADS)

Bobée, Bernard; El Adlouni, Salaheddine

2014-05-01

The study of the tail behaviour of extreme event distributions is important in several applied statistical fields such as hydrology, finance, and telecommunications. For example in hydrology, it is important to estimate adequately extreme quantiles in order to build and manage safe and effective hydraulic structures (dams, for example). Two main classes of distributions are used in hydrological frequency analysis: the class D of sub-exponential (Gamma (G2), Gumbel, Halphen type A (HA), Halphen type B (HB)…) and the class C of regularly varying distributions (Fréchet, Log-Pearson, Halphen type IB …) with a heavier tail. A Decision Support System (DSS) based on the characterization of the right tail, corresponding low probability of excedence p (high return period T=1/p, in hydrology), has been developed. The DSS allows discriminating between the class C and D and in its last version, a new prior step is added in order to test Lognormality. Indeed, the right tail of the Lognormal distribution (LN) is between the tails of distributions of the classes C and D; studies indicated difficulty with the discrimination between LN and distributions of the classes C and D. Other tools are useful to discriminate between distributions of the same class D (HA, HB and G2; see other communication). Some numerical illustrations show that, the DSS allows discriminating between Lognormal, regularly varying and sub-exponential distributions; and lead to coherent conclusions. Key words: Regularly varying distributions, subexponential distributions, Decision Support System, Heavy tailed distribution, Extreme value theory

A GIS-based decision support system for determining the shortest and safest route to forest fires: a case study in Mediterranean Region of Turkey.

PubMed

Akay, Abdullah E; Wing, Michael G; Sivrikaya, Fatih; Sakar, Dursun

2012-03-01

The ability of firefighting vehicles and staff to reach a fire area as quickly as possible is critical in fighting against forest fires. In this study, a Geographical Information System-based decision support system was developed to assist fire managers in determining the fastest and the safest or more reliable access routes from firefighting headquarters to fire areas. The decision support system was tested in the Kahramanmaras Forestry Regional Directoratein the Mediterranean region of Turkey. The study area consisted of forested lands which had been classified according to fire sensitivity. The fire response routing simulations considered firefighting teams located in 20 firefighting headquarter locations. The road network, the locations of the firefighting headquarters, and possible fire locations were mapped for simulation analysis. In alternative application simulations, inaccessible roads which might be closed due to fire or other reasons were indicated in the network analysis so that the optimum route was not only the fastest but also the safest and most reliable path. The selection of which firefighting headquarters to use was evaluated by considering critical response time to potential fire areas based on fire sensitivity levels. Results indicated that new firefighting headquarters should be established in the region in order to provide sufficient firefighting response to all forested lands. In addition, building new fire access roads and increasing the design speed on current roads could also increase firefighting response capabilities within the study area.

Arms control is everyone`s business: The United States and the United Nations at the mid-point of the 1990`s

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

Lehman, R.F. II

1993-03-01

This presentation encourages current efforts in arms control, non- proliferation, and peacekeeping. Verification is heralded as a confidence building method to bring about more openness in international relations. It is purported that openness has already enhanced democratic forces around the world. The insistence on strict compliance with the decisions of the United Nations Security Council is a show of support for international law. It is recommended that international norms on human rights, non-proliferation, and non-aggression be strengthened.

Fuzzy-Neural Controller in Service Requests Distribution Broker for SOA-Based Systems

NASA Astrophysics Data System (ADS)

Fras, Mariusz; Zatwarnicka, Anna; Zatwarnicki, Krzysztof

The evolution of software architectures led to the rising importance of the Service Oriented Architecture (SOA) concept. This architecture paradigm support building flexible distributed service systems. In the paper the architecture of service request distribution broker designed for use in SOA-based systems is proposed. The broker is built with idea of fuzzy control. The functional and non-functional request requirements in conjunction with monitoring of execution and communication links are used to distribute requests. Decisions are made with use of fuzzy-neural network.

Symposium on Applied Mathematical Programming and Modeling (APMOD93) Held in Budapest, Hungary on January 6-8, 1993. Volume of Extended Abstracts

DTIC Science & Technology

1993-01-08

rectangular ones. Therefore, symmetrical equivalent solutions go by group of four and will have the same cost. Figuret. Our B&B method will not create, study ...If group members will agree in the ranking of a subset of the alternatives (the top set of one, two, three, four -_.., alternatives), what changes...T., Szillery A. Spreadsheet-Based Model Building and Multiple Criteria Group Decision Support 49 Black, J.A., Seyed-Mosseini, S.M. Traffic Models for

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

Anderson, Katherine H.; Cutler, Dylan S.; Olis, Daniel R.

REopt is a techno-economic decision support model used to optimize energy systems for buildings, campuses, communities, and microgrids. The primary application of the model is for optimizing the integration and operation of behind-the-meter energy assets. This report provides an overview of the model, including its capabilities and typical applications; inputs and outputs; economic calculations; technology descriptions; and model parameters, variables, and equations. The model is highly flexible, and is continually evolving to meet the needs of each analysis. Therefore, this report is not an exhaustive description of all capabilities, but rather a summary of the core components of the model.

A framework to evaluate research capacity building in health care

PubMed Central

Cooke, Jo

2005-01-01

Background Building research capacity in health services has been recognised internationally as important in order to produce a sound evidence base for decision-making in policy and practice. Activities to increase research capacity for, within, and by practice include initiatives to support individuals and teams, organisations and networks. Little has been discussed or concluded about how to measure the effectiveness of research capacity building (RCB) Discussion This article attempts to develop the debate on measuring RCB. It highlights that traditional outcomes of publications in peer reviewed journals and successful grant applications may be important outcomes to measure, but they may not address all the relevant issues to highlight progress, especially amongst novice researchers. They do not capture factors that contribute to developing an environment to support capacity development, or on measuring the usefulness or the 'social impact' of research, or on professional outcomes. The paper suggests a framework for planning change and measuring progress, based on six principles of RCB, which have been generated through the analysis of the literature, policy documents, empirical studies, and the experience of one Research and Development Support Unit in the UK. These principles are that RCB should: develop skills and confidence, support linkages and partnerships, ensure the research is 'close to practice', develop appropriate dissemination, invest in infrastructure, and build elements of sustainability and continuity. It is suggested that each principle operates at individual, team, organisation and supra-organisational levels. Some criteria for measuring progress are also given. Summary This paper highlights the need to identify ways of measuring RCB. It points out the limitations of current measurements that exist in the literature, and proposes a framework for measuring progress, which may form the basis of comparison of RCB activities. In this way it could contribute to establishing the effectiveness of these interventions, and establishing a knowledge base to inform the science of RCB. PMID:16253133

Building damage assessment from PolSAR data using texture parameters of statistical model

NASA Astrophysics Data System (ADS)

Li, Linlin; Liu, Xiuguo; Chen, Qihao; Yang, Shuai

2018-04-01

Accurate building damage assessment is essential in providing decision support for disaster relief and reconstruction. Polarimetric synthetic aperture radar (PolSAR) has become one of the most effective means of building damage assessment, due to its all-day/all-weather ability and richer backscatter information of targets. However, intact buildings that are not parallel to the SAR flight pass (termed oriented buildings) and collapsed buildings share similar scattering mechanisms, both of which are dominated by volume scattering. This characteristic always leads to misjudgments between assessments of collapsed buildings and oriented buildings from PolSAR data. Because the collapsed buildings and the intact buildings (whether oriented or parallel buildings) have different textures, a novel building damage assessment method is proposed in this study to address this problem by introducing texture parameters of statistical models. First, the logarithms of the estimated texture parameters of different statistical models are taken as a new texture feature to describe the collapse of the buildings. Second, the collapsed buildings and intact buildings are distinguished using an appropriate threshold. Then, the building blocks are classified into three levels based on the building block collapse rate. Moreover, this paper also discusses the capability for performing damage assessment using texture parameters from different statistical models or using different estimators. The RADARSAT-2 and ALOS-1 PolSAR images are used to present and analyze the performance of the proposed method. The results show that using the texture parameters avoids the problem of confusing collapsed and oriented buildings and improves the assessment accuracy. The results assessed by using the K/G0 distribution texture parameters estimated based on the second moment obtain the highest extraction accuracies. For the RADARSAT-2 and ALOS-1 data, the overall accuracy (OA) for these three types of buildings is 73.39% and 68.45%, respectively.

Multiple Criteria Decision Analysis (MCDA) for evaluating new medicines in Health Technology Assessment and beyond: The Advance Value Framework.

PubMed

Angelis, Aris; Kanavos, Panos

2017-09-01

Escalating drug prices have catalysed the generation of numerous "value frameworks" with the aim of informing payers, clinicians and patients on the assessment and appraisal process of new medicines for the purpose of coverage and treatment selection decisions. Although this is an important step towards a more inclusive Value Based Assessment (VBA) approach, aspects of these frameworks are based on weak methodologies and could potentially result in misleading recommendations or decisions. In this paper, a Multiple Criteria Decision Analysis (MCDA) methodological process, based on Multi Attribute Value Theory (MAVT), is adopted for building a multi-criteria evaluation model. A five-stage model-building process is followed, using a top-down "value-focused thinking" approach, involving literature reviews and expert consultations. A generic value tree is structured capturing decision-makers' concerns for assessing the value of new medicines in the context of Health Technology Assessment (HTA) and in alignment with decision theory. The resulting value tree (Advance Value Tree) consists of three levels of criteria (top level criteria clusters, mid-level criteria, bottom level sub-criteria or attributes) relating to five key domains that can be explicitly measured and assessed: (a) burden of disease, (b) therapeutic impact, (c) safety profile (d) innovation level and (e) socioeconomic impact. A number of MAVT modelling techniques are introduced for operationalising (i.e. estimating) the model, for scoring the alternative treatment options, assigning relative weights of importance to the criteria, and combining scores and weights. Overall, the combination of these MCDA modelling techniques for the elicitation and construction of value preferences across the generic value tree provides a new value framework (Advance Value Framework) enabling the comprehensive measurement of value in a structured and transparent way. Given its flexibility to meet diverse requirements and become readily adaptable across different settings, the Advance Value Framework could be offered as a decision-support tool for evaluators and payers to aid coverage and reimbursement of new medicines. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Effects of Newly Designed Hospital Buildings on Staff Perceptions: A Pre-Post Study to Validate Design Decisions.

PubMed

Schreuder, Eliane; van Heel, Liesbeth; Goedhart, Rien; Dusseldorp, Elise; Schraagen, Jan Maarten; Burdorf, Alex

2015-01-01

This study investigates effects of the newly built nonpatient-related buildings of a large university medical center on staff perceptions and whether the design objectives were achieved. The medical center is gradually renewing its hospital building area of 200,000 m.(2) This redevelopment is carefully planned and because lessons learned can guide design decisions of the next phase, the medical center is keen to evaluate the performance of the new buildings. A pre- and post-study with a control group was conducted. Prior to the move to the new buildings an occupancy evaluation was carried out in the old setting (n = 729) (pre-study). Post occupation of the new buildings another occupancy evaluation (post-study) was carried out in the new setting (intervention group) and again in some old settings (control group) (n = 664). The occupancy evaluation consisted of an online survey that measured the perceived performance of different aspects of the building. Longitudinal multilevel analysis was used to compare the performance of the old buildings with the new buildings. Significant improvements were found in indoor climate, perceived safety, working environment, well-being, facilities, sustainability, and overall satisfaction. Commitment to the employer, working atmosphere, orientation, work performance, and knowledge sharing did not improve. The results were interpreted by relating them to specific design choices. We showed that it is possible to measure the performance improvements of a complex intervention being a new building design and validate design decisions. A focused design process aiming for a safe, pleasant and sustainable building resulted in actual improvements in some of the related performance measures. © The Author(s) 2015.

Leveraging organizational dynamics in buildings to change behavior

NASA Astrophysics Data System (ADS)

Hewitt, Elizabeth L.

Buildings may be stationary, but they are not static; they are dynamic and active collectives of agents and actors, and play an important cultural and social role in shaping norms and influencing outcomes in the built environment. This research develops and applies a unique framework that conceptualizes the urban multifamily residential building as an organization, and seeks to use this lens to better understand the role of organizational characteristics in influencing energy efficiency in buildings. This work finds that an organizational analogy is a fruitful approach for understanding buildings, and that buildings in many ways can and do function successfully as organizations. In particular, eight organizational characteristics are explored here that extend well to buildings. These eight organizational characteristics are also explored more deeply to support an argument that some buildings have an organizational advantage that well positions them to undertake energy efficiency initiatives. One organizational characteristic -- the ownership type of the building -- is determined to be particularly important in driving energy outcomes in multifamily buildings in New York City. In particular, it was found that cooperative buildings in the New York City housing market consume less energy citywide than other types of multifamily properties, holding all else equal. Conversely, it was also found that rental buildings tend to consume more energy citywide. Subsequent qualitative case study work in a small Brooklyn cooperative building offers a deeper understanding of organizational decentralization and its role in driving decision-making and outcomes in the building. Additional comparative work in two rental properties -- one high-income and one low-income -- adds additional context and understanding to economic considerations such as the influence of income in overriding centralized efforts to operate the building efficiently. Ultimately, this research develops an analogy of buildings-as-organizations -- a conceptual framework -- to better understand tangible built space. It posits that all buildings can function as organizations, and extends this framework to the urban multifamily building to advance knowledge of energy efficiency.

Flooding During Drought: Learning from Stakeholder Engagement & Partner Coordination in the California-Nevada Drought Early Warning System (DEWS)

NASA Astrophysics Data System (ADS)

Sheffield, A. M.

2017-12-01

After more than 5 years of drought, extreme precipitation brought drought relief in California and Nevada and presents an opportunity to reflect upon lessons learned while planning for the future. NOAA's National Integrated Drought Information System (NIDIS) California-Nevada Drought Early Warning System (DEWS) in June 2017 convened a regional coordination workshop to provide a forum to discuss and build upon past drought efforts in the region and increase coordination, collaboration and information sharing across the region as a whole. Participants included federal, tribal, state, academic, and local partners who provided a post-mortem on the recent drought and impacts as well as recent innovations in drought monitoring, forecasts, and decision support tools in response to the historic drought. This presentation will highlight lessons learned from stakeholder outreach and engagement around flooding during drought, and pathways for moving forward coordination and collaboration in the region. Additional focus will be on the potential opportunities from examining California decision making calendars from this drought. Identified gaps and challenges will also be shared, such as the need to connect observations with social impacts, capacity building around available tools and resources, and future drought monitoring needs. Drought will continue to impact California and Nevada, and the CA-NV DEWS works to make climate and drought science readily available, easily understandable and usable for decision makers; and to improve the capacity of stakeholders to better monitor, forecast, plan for and cope with the impacts of drought.

Lessons from COASST: How Does Citizen Science Contribute to Natural Resource Management & Decision-Making?

NASA Astrophysics Data System (ADS)

Metes, J.; Ballard, H. L.; Parrish, J.

2016-12-01

As many scholars and practitioners in the environmental field turn to citizen science to collect robust scientific data as well as engage with wider audiences, it is crucial to build a more complete understanding of how citizen science influences and affects different interests within a social-ecological system. This research investigates how federal, state, and tribal natural resource managers interact with data from the Coastal Observation & Seabird Survey Team (COASST) project—a citizen science program that trains participants to monitor species and abundance of beach-cast birds on the Pacific Northwest Coast. Fifteen coastal and fisheries managers who previously requested COASST data were interviewed about how and why they used data from the project and were asked to describe how information gained from COASST affected their management decisions. Results suggest that broadly, managers value and learn from the program's capacity to gather data spanning a wide spatial-temporal range. This contribution to baseline monitoring helps managers signal and track both short- and long-term environmental change. More specifically, managers use COASST data in conjunction with other professional monitoring programs, such as the National Marine Fisheries Observer Program, to build higher degrees of reliability into management decisions. Although managers offered diverse perspectives and experiences about what the role of citizen science in natural resource management generally should be, there was agreement that agencies on their own often lack personnel and funding required to sufficiently monitor many crucial resources. Additionally, managers strongly suggested that COASST and other citizen science projects increased public awareness and support for agency decision-making and policies, and indirect yet important contribution to natural resource management.

Evolving the US Climate Resilience Toolkit to Support a Climate-Smart Nation

NASA Astrophysics Data System (ADS)

Tilmes, C.; Niepold, F., III; Fox, J. F.; Herring, D.; Dahlman, L. E.; Hall, N.; Gardiner, N.

2015-12-01

Communities, businesses, resource managers, and decision-makers at all levels of government need information to understand and ameliorate climate-related risks. Likewise, climate information can expose latent opportunities. Moving from climate science to social and economic decisions raises complex questions about how to communicate the causes and impacts of climate variability and change; how to characterize and quantify vulnerabilities, risks, and opportunities faced by communities and businesses; and how to make and implement "win-win" adaptation plans at local, regional, and national scales. A broad coalition of federal agencies launched the U.S. Climate Resilience Toolkit (toolkit.climate.gov) in November 2014 to help our nation build resilience to climate-related extreme events. The site's primary audience is planners and decision makers in business, resource management, and government (at all levels) who seek science-based climate information and tools to help them in their near- and long-term planning. The Executive Office of the President assembled a task force of dozens of subject experts from across the 13 agencies of the U.S. Global Change Research Program to guide the site's development. The site's ongoing evolution is driven by feedback from the target audience. For example, based on feedback, climate projections will soon play a more prominent role in the site's "Climate Explorer" tool and case studies. The site's five-step adaptation planning process is being improved to better facilitate people getting started and to provide clear benchmarks for evaluating progress along the way. In this session, we will share lessons learned from a series of user engagements around the nation and evidence that the Toolkit couples climate information with actionable decision-making processes in ways that are helping Americans build resilience to climate-related stressors.

A Cryogenic Fluid System Simulation in Support of Integrated Systems Health Management

NASA Technical Reports Server (NTRS)

Barber, John P.; Johnston, Kyle B.; Daigle, Matthew

2013-01-01

Simulations serve as important tools throughout the design and operation of engineering systems. In the context of sys-tems health management, simulations serve many uses. For one, the underlying physical models can be used by model-based health management tools to develop diagnostic and prognostic models. These simulations should incorporate both nominal and faulty behavior with the ability to inject various faults into the system. Such simulations can there-fore be used for operator training, for both nominal and faulty situations, as well as for developing and prototyping health management algorithms. In this paper, we describe a methodology for building such simulations. We discuss the design decisions and tools used to build a simulation of a cryogenic fluid test bed, and how it serves as a core technology for systems health management development and maturation.

Building Green: The Adoption Process of LEED- and Energy Star-Rated Office Buildings

ERIC Educational Resources Information Center

Malkani, Arvin P.

2012-01-01

There are opportunities for green building technology in office buildings to produce energy savings and cost efficiencies that can produce a positive economic and environmental impact. In order for these opportunities to be realized, however, decision makers must appreciate the value of green building technology. The objective of this research is…

Earthquake Vulnerability Assessment for Hospital Buildings Using a Gis-Based Group Multi Criteria Decision Making Approach: a Case Study of Tehran, Iran

NASA Astrophysics Data System (ADS)

Delavar, M. R.; Moradi, M.; Moshiri, B.

2015-12-01

Nowadays, urban areas are threatened by a number of natural hazards such as flood, landslide and earthquake. They can cause huge damages to buildings and human beings which necessitates disaster mitigation and preparation. One of the most important steps in disaster management is to understand all impacts and effects of disaster on urban facilities. Given that hospitals take care of vulnerable people reaction of hospital buildings against earthquake is vital. In this research, the vulnerability of hospital buildings against earthquake is analysed. The vulnerability of buildings is related to a number of criteria including age of building, number of floors, the quality of materials and intensity of the earthquake. Therefore, the problem of seismic vulnerability assessment is a multi-criteria assessment problem and multi criteria decision making methods can be used to address the problem. In this paper a group multi criteria decision making model is applied because using only one expert's judgments can cause biased vulnerability maps. Sugeno integral which is able to take into account the interaction among criteria is employed to assess the vulnerability degree of buildings. Fuzzy capacities which are similar to layer weights in weighted linear averaging operator are calculated using particle swarm optimization. Then, calculated fuzzy capacities are included into the model to compute a vulnerability degree for each hospital.

Optimal Decision Model for Sustainable Hospital Building Renovation—A Case Study of a Vacant School Building Converting into a Community Public Hospital

PubMed Central

Juan, Yi-Kai; Cheng, Yu-Ching; Perng, Yeng-Horng; Castro-Lacouture, Daniel

2016-01-01

Much attention has been paid to hospitals environments since modern pandemics have emerged. The building sector is considered to be the largest world energy consumer, so many global organizations are attempting to create a sustainable environment in building construction by reducing energy consumption. Therefore, maintaining high standards of hygiene while reducing energy consumption has become a major task for hospitals. This study develops a decision model based on genetic algorithms and A* graph search algorithms to evaluate existing hospital environmental conditions and to recommend an optimal scheme of sustainable renovation strategies, considering trade-offs among minimal renovation cost, maximum quality improvement, and low environmental impact. Reusing vacant buildings is a global and sustainable trend. In Taiwan, for example, more and more school space will be unoccupied due to a rapidly declining birth rate. Integrating medical care with local community elder-care efforts becomes important because of the aging population. This research introduces a model that converts a simulated vacant school building into a community public hospital renovation project in order to validate the solutions made by hospital managers and suggested by the system. The result reveals that the system performs well and its solutions are more successful than the actions undertaken by decision-makers. This system can improve traditional hospital building condition assessment while making it more effective and efficient. PMID:27347986

Optimal Decision Model for Sustainable Hospital Building Renovation-A Case Study of a Vacant School Building Converting into a Community Public Hospital.

PubMed

Juan, Yi-Kai; Cheng, Yu-Ching; Perng, Yeng-Horng; Castro-Lacouture, Daniel

2016-06-24

Much attention has been paid to hospitals environments since modern pandemics have emerged. The building sector is considered to be the largest world energy consumer, so many global organizations are attempting to create a sustainable environment in building construction by reducing energy consumption. Therefore, maintaining high standards of hygiene while reducing energy consumption has become a major task for hospitals. This study develops a decision model based on genetic algorithms and A* graph search algorithms to evaluate existing hospital environmental conditions and to recommend an optimal scheme of sustainable renovation strategies, considering trade-offs among minimal renovation cost, maximum quality improvement, and low environmental impact. Reusing vacant buildings is a global and sustainable trend. In Taiwan, for example, more and more school space will be unoccupied due to a rapidly declining birth rate. Integrating medical care with local community elder-care efforts becomes important because of the aging population. This research introduces a model that converts a simulated vacant school building into a community public hospital renovation project in order to validate the solutions made by hospital managers and suggested by the system. The result reveals that the system performs well and its solutions are more successful than the actions undertaken by decision-makers. This system can improve traditional hospital building condition assessment while making it more effective and efficient.

How Satellites Have Contributed to Building a Weather Ready Nation

NASA Astrophysics Data System (ADS)

Lapenta, W.

2017-12-01

NOAA's primary mission since its inception has been to reduce the loss of life and property, as well as disruptions from, high impact weather and water-related events. In recent years, significant societal losses resulting even from well forecast extreme events have shifted attention from the forecast alone toward ensuring societal response is equal to the risks that exist for communities, businesses and the public. The responses relate to decisions ranging from coastal communities planning years in advance to mitigate impacts from rising sea level, to immediate lifesaving decisions such as a family seeking adequate shelter during a tornado warning. NOAA is committed to building a "Weather-Ready Nation" where communities are prepared for and respond appropriately to these events. The Weather-Ready Nation (WRN) strategic priority is building community resilience in the face of increasing vulnerability to extreme weather, water, climate and environmental threats. To build a Weather-Ready Nation, NOAA is enhancing Impact-Based Decision Support Services (IDSS), transitioning science and technology advances into forecast operations, applying social science research to improve the communication and usefulness of information, and expanding its dissemination efforts to achieve far-reaching readiness, responsiveness and resilience. These four components of Weather-Ready Nation are helping ensure NOAA data, products and services are fully utilized to minimize societal impacts from extreme events. Satellite data and satellite products have been important elements of the national Weather Service (NWS) operations for more than 40 years. When one examines the uses of satellite data specific to the internal forecast and warning operations of NWS, two main applications are evident. The first is the use of satellite data in numerical weather prediction models; the second is the use of satellite imagery and derived products for mesoscale and short-range weather warning and prediction. The purpose of this paper is to highlight the value of the satellite component of the global observing system to NWS operational weather forecasting and emphasize how these data form a critical component of the NWS ability to protect life and property and ensure economic well-being.

Key stakeholders' perceptions of the acceptability and usefulness of a tablet-based tool to improve communication and shared decision making in ICUs.

PubMed

Ernecoff, Natalie C; Witteman, Holly O; Chon, Kristen; Chen, Yanquan Iris; Buddadhumaruk, Praewpannarai; Chiarchiaro, Jared; Shotsberger, Kaitlin J; Shields, Anne-Marie; Myers, Brad A; Hough, Catherine L; Carson, Shannon S; Lo, Bernard; Matthay, Michael A; Anderson, Wendy G; Peterson, Michael W; Steingrub, Jay S; Arnold, Robert M; White, Douglas B

2016-06-01

Although barriers to shared decision making in intensive care units are well documented, there are currently no easily scaled interventions to overcome these problems. We sought to assess stakeholders' perceptions of the acceptability, usefulness, and design suggestions for a tablet-based tool to support communication and shared decision making in ICUs. We conducted in-depth semi-structured interviews with 58 key stakeholders (30 surrogates and 28 ICU care providers). Interviews explored stakeholders' perceptions about the acceptability of a tablet-based tool to support communication and shared decision making, including the usefulness of modules focused on orienting families to the ICU, educating them about the surrogate's role, completing a question prompt list, eliciting patient values, educating about treatment options, eliciting perceptions about prognosis, and providing psychosocial support resources. The interviewer also elicited stakeholders' design suggestions for such a tool. We used constant comparative methods to identify key themes that arose during the interviews. Overall, 95% (55/58) of participants perceived the proposed tool to be acceptable, with 98% (57/58) of interviewees finding six or more of the seven content domains acceptable. Stakeholders identified several potential benefits of the tool including that it would help families prepare for the surrogate role and for family meetings as well as give surrogates time and a framework to think about the patient's values and treatment options. Key design suggestions included: conceptualize the tool as a supplement to rather than a substitute for surrogate-clinician communication; make the tool flexible with respect to how, where, and when surrogates can access the tool; incorporate interactive exercises; use video and narration to minimize the cognitive load of the intervention; and build an extremely simple user interface to maximize usefulness for individuals with low computer literacy. There is broad support among stakeholders for the use of a tablet-based tool to improve communication and shared decision making in ICUs. Eliciting the perspectives of key stakeholders early in the design process yielded important insights to create a tool tailored to the needs of surrogates and care providers in ICUs. Copyright © 2016 Elsevier Inc. All rights reserved.

A Geo-Distributed System Architecture for Different Domains

NASA Astrophysics Data System (ADS)

Moßgraber, Jürgen; Middleton, Stuart; Tao, Ran

2013-04-01

The presentation will describe work on the system-of-systems (SoS) architecture that is being developed in the EU FP7 project TRIDEC on "Collaborative, Complex and Critical Decision-Support in Evolving Crises". In this project we deal with two use-cases: Natural Crisis Management (e.g. Tsunami Early Warning) and Industrial Subsurface Development (e.g. drilling for oil). These use-cases seem to be quite different at first sight but share a lot of similarities, like managing and looking up available sensors, extracting data from them and annotate it semantically, intelligently manage the data (big data problem), run mathematical analysis algorithms on the data and finally provide decision support on this basis. The main challenge was to create a generic architecture which fits both use-cases. The requirements to the architecture are manifold and the whole spectrum of a modern, geo-distributed and collaborative system comes into play. Obviously, one cannot expect to tackle these challenges adequately with a monolithic system or with a single technology. Therefore, a system architecture providing the blueprints to implement the system-of-systems approach has to combine multiple technologies and architectural styles. The most important architectural challenges we needed to address are 1. Build a scalable communication layer for a System-of-sytems 2. Build a resilient communication layer for a System-of-sytems 3. Efficiently publish large volumes of semantically rich sensor data 4. Scalable and high performance storage of large distributed datasets 5. Handling federated multi-domain heterogeneous data 6. Discovery of resources in a geo-distributed SoS 7. Coordination of work between geo-distributed systems The design decisions made for each of them will be presented. These developed concepts are also applicable to the requirements of the Future Internet (FI) and Internet of Things (IoT) which will provide services like smart grids, smart metering, logistics and environmental monitoring.

The patient-centered outcomes research institute should focus on high-impact problems that can be solved quickly.

PubMed

Sox, Harold

2012-10-01

The Affordable Care Act created the Patient-Centered Outcomes Research Institute (PCORI) to help patients, clinicians, and policy makers make well-informed decisions about health care. Because its funding expires in 2019, the institute has little time in which to produce timely, practice-changing results that will build public support for comparative effectiveness research. PCORI should plan its research agenda strategically, so that it addresses research questions that comparative effectiveness research could answer quickly and decisively. To date, the institute has not chosen this path. In January 2012 PCORI's first research agenda described broad research priorities rather than specific clinical questions. The institute must drive the burgeoning discipline of comparative effectiveness research forward, starting with a research project agenda that conveys a sense of urgency and strategic direction.

Lessons Learned on Effective Co-production of Drought Science and Decision Support Tools with the Wind River Reservation Tribal Water Managers

NASA Astrophysics Data System (ADS)

McNeeley, S.; Ojima, D. S.; Beeton, T.

2015-12-01

The Wind River Reservation in west-central Wyoming is home of the Eastern Shoshone and Northern Arapaho Tribes. The reservation has experienced severe drought impacts on Tribal livelihoods and cultural activities in recent years. Scientists from the North Central Climate Science Center, the National Drought Mitigation Center, the High Plains Regional Climate Center, and multiple others are working in close partnership with the tribal water managers on a reservation-wide drought preparedness project that includes a technical assessment of drought risk, capacity building to train managers on drought and climate science and indicators, and drought planning. This talk will present project activities to date along with the valuable and transferrable lessons learned on effective co-production of actionable science for decision making in a tribal context.

Health policy in a new key: setting democratic priorities.

PubMed

Jennings, B

1993-01-01

Health policy in the United States is entering an era in which explicitly value-based allocation decisions require direct attention. Policies concerning access to care, financing, and utilization management will necessarily have redistributive effects. For these policies to command social legitimacy and political support, some consensus will have to emerge around the values and ideals justifying these policies. This article addresses the problems of conceptual clarification and democratic process raised by the prospect of an explicitly value-based allocation policy. It offers a conceptual matrix distinguishing the scope of the issue of allocation in health care. Drawing on the activities of community health decisions projects in several states, it also offers suggestions about building a participatory and educational process at the grassroots level that might lead to a democratic consensus suitable for guiding policy choice.

Information warehouse - a comprehensive informatics platform for business, clinical, and research applications.

PubMed

Kamal, Jyoti; Liu, Jianhua; Ostrander, Michael; Santangelo, Jennifer; Dyta, Ravi; Rogers, Patrick; Mekhjian, Hagop S

2010-11-13

Since its inception in 1997, the IW (Information Warehouse) at the Ohio State University Medical Center (OSUMC) has gradually transformed itself from a single purpose business decision support system to a comprehensive informatics platform supporting basic, clinical, and translational research. The IW today is the combination of four integrated components: a clinical data repository containing over a million patients; a research data repository housing various research specific data; an application development platform for building business and research enabling applications; a business intelligence environment assisting in reporting in all function areas. The IW is structured and encoded using standard terminologies such as SNOMED-CT, ICD, and CPT. The IW is an important component of OSUMC's Clinical and Translational Science Award (CTSA) informatics program.

Application of life-cycle assessment (LCA) methodology for valorization of building demolition materials and products

NASA Astrophysics Data System (ADS)

Sara, Balazs; Antonini, Ernesto; Tarantini, Mario

2001-02-01

The VAMP project (VAlorization of building demolition Materials and Products, LIFE 98/ENV/IT/33) aims to build an effective and innovative information system to support decision making in selective demolition activity and to manage the valorization (recovery-reuse-recycling) of waste flows produced by the construction and demolition (C&D) sector. The VAMP information system will be tested it in Italy in some case studies of selective demolition. In this paper the proposed demolition-valorization system will be compared to the traditional one in a life cycle perspective, applying LCA methodology to highlight the advantages of VAMP system from an eco-sustainability point of view. Within the system boundaries demolition processes, transport of demolition wastes and its recovery/treatment or disposal in landfill were included. Processes avoided due to reuse-recycling activities, such as extraction of natural resources and manufacture of building materials and components, were considered too. In this paper data collection procedure applied in inventory and impact assessment phases and a general overview about data availability for LCA studies in this sector are presented. Results of application of VAMP methodology to a case study are discussed and compared with a simulated traditional demolition of the same building. Environmental advantages of VAMP demolition-valorization system are demonstrated quantitatively emphasizing the special importance of reuse of building components with high demand of energy for manufacture.

RAMPART (TM): Risk Assessment Method-Property Analysis and Ranking Tool v.4.0

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

Carson, Susan D.; Hunter, Regina L.; Link, Madison D.

RAMPART{trademark}, Risk Assessment Method-property Analysis and Ranking Tool, is a new type of computer software package for the assessment of risk to buildings. RAMPART{trademark} has been developed by Sandia National Laboratories (SNL) for the U.S. General Services Administration (GSA). RAMPART {trademark} has been designed and developed to be a risk-based decision support tool that requires no risk analysis expertise on the part of the user. The RAMPART{trademark} user interface elicits information from the user about the building. The RAMPART{trademark} expert system is a set of rules that embodies GSA corporate knowledge and SNL's risk assessment experience. The RAMPART{trademark} database containsmore » both data entered by the user during a building analysis session and large sets of natural hazard and crime data. RAMPART{trademark} algorithms use these data to assess the risk associated with a given building in the face of certain hazards. Risks arising from five natural hazards (earthquake, hurricane, winter storm, tornado and flood); crime (inside and outside the building); fire and terrorism are calculated. These hazards may cause losses of various kinds. RAMPART{trademark} considers death, injury, loss of mission, loss of property, loss of contents, loss of building use, and first-responder loss. The results of each analysis are presented graphically on the screen and in a written report.« less

Energy Signal Tool for Decision Support in Building Energy Systems

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

Henze, G. P.; Pavlak, G. S.; Florita, A. R.

2014-12-01

A prototype energy signal tool is demonstrated for operational whole-building and system-level energy use evaluation. The purpose of the tool is to give a summary of building energy use which allows a building operator to quickly distinguish normal and abnormal energy use. Toward that end, energy use status is displayed as a traffic light, which is a visual metaphor for energy use that is either substantially different from expected (red and yellow lights) or approximately the same as expected (green light). Which light to display for a given energy end use is determined by comparing expected to actual energy use.more » As expected, energy use is necessarily uncertain; we cannot choose the appropriate light with certainty. Instead, the energy signal tool chooses the light by minimizing the expected cost of displaying the wrong light. The expected energy use is represented by a probability distribution. Energy use is modeled by a low-order lumped parameter model. Uncertainty in energy use is quantified by a Monte Carlo exploration of the influence of model parameters on energy use. Distributions over model parameters are updated over time via Bayes' theorem. The simulation study was devised to assess whole-building energy signal accuracy in the presence of uncertainty and faults at the submetered level, which may lead to tradeoffs at the whole-building level that are not detectable without submetering.« less

Consolidation of a WSN and Minimax Method to Rapidly Neutralise Intruders in Strategic Installations

PubMed Central

Conesa-Muñoz, Jesus; Ribeiro, Angela

2012-01-01

Due to the sensitive international situation caused by still-recent terrorist attacks, there is a common need to protect the safety of large spaces such as government buildings, airports and power stations. To address this problem, developments in several research fields, such as video and cognitive audio, decision support systems, human interface, computer architecture, communications networks and communications security, should be integrated with the goal of achieving advanced security systems capable of checking all of the specified requirements and spanning the gap that presently exists in the current market. This paper describes the implementation of a decision system for crisis management in infrastructural building security. Specifically, it describes the implementation of a decision system in the management of building intrusions. The positions of the unidentified persons are reported with the help of a Wireless Sensor Network (WSN). The goal is to achieve an intelligent system capable of making the best decision in real time in order to quickly neutralise one or more intruders who threaten strategic installations. It is assumed that the intruders’ behaviour is inferred through sequences of sensors’ activations and their fusion. This article presents a general approach to selecting the optimum operation from the available neutralisation strategies based on a Minimax algorithm. The distances among different scenario elements will be used to measure the risk of the scene, so a path planning technique will be integrated in order to attain a good performance. Different actions to be executed over the elements of the scene such as moving a guard, blocking a door or turning on an alarm will be used to neutralise the crisis. This set of actions executed to stop the crisis is known as the neutralisation strategy. Finally, the system has been tested in simulations of real situations, and the results have been evaluated according to the final state of the intruders. In 86.5% of the cases, the system achieved the capture of the intruders, and in 59.25% of the cases, they were intercepted before they reached their objective. PMID:22737008

Climate Generation: Advancing Climate Action through Education, Public Engagement and Youth Leadership

NASA Astrophysics Data System (ADS)

Poppleton, K. L. I.

2017-12-01

Climate Generation: A Will Steger Legacy empowers youth, educators, decision-makers and the public to foster climate literacy and action with the goal of building a more equitable and resilient future. We have over eleven years of experience delivering high-quality K-12 education, public engagement and youth leadership programming, reaching over 75,000 people, 35,000 students and 17,000 educators since 2006. By engaging educators, youth, and the public, we believe that communities can be better positioned to build a resilient and equitable future. For this reason we strive to engage with all these sectors through innovative programming and policy initiatives. Communities are resilient when individuals are connected to each other, resources, and decision-makers. Sharing personal narratives, and highlighting locally relevant solutions are all tools that Climate Generation employs to engage the public. We do this through community wide convenings, as well as sector specific events including at breweries, art fairs, and businesses. Education is also an integral piece for sustained action on climate change. We support educators with a science-based, interdisciplinary model of climate change education that engages all learners, and fosters climate literacy and action. We develop curriculum and offer professional development, encouraging teachers to develop today's students into action-competent citizens. Finally, Climate Generation recognizes the importance of empowering high school youth as a key strategy in transitioning to a just and sustainable future for all. We believe in the inherent genius of youth and know from experience that mentorship fosters powerful youth leadership at the community level, inspiring peers, family members, and local decision-makers to take critical action on climate change solutions. In order to accelerate and implement action on climate change we must take a multi-faceted approach: we are building public will for strong climate action at the local and state level; preparing educators and their students to understand the problem and implement clean energy solutions; and pushing our decision-makers to do the right thing via pressure from their constituents, including youth, who can effectively articulate equitable policy solutions and hold officials accountable.

Development of weightage for criteria affecting in retrofitting of existing building in Higher Learning Institution with clean energy initiatives

NASA Astrophysics Data System (ADS)

Izie Adiana Abidin, Nur; Aminuddin, Eeydzah; Zakaria, Rozana; Mazzuana Shamsuddin, Siti; Sahamir, Shaza Rina; Shahzaib, Jam; Nafis Abas, Darul

2018-04-01

Campus university building is the Higher Learning Institution (HLI) involves complex activities and operations, conserving the energy has become paramount important. There are several efforts taken by universities to improve its current energy use such as policy development, education, and adaption of energy conservation solution through retrofitting. This paper aims to highlight the importance of the criteria affecting in retrofitting of existing buildings with clean energy in order to achieve zero energy balance in buildings. The focus is given to the development of criteria for solar photovoltaic (solar PV), wind turbines and small-scale hydropower. A questionnaire survey was employed and distributed to the green building expert practitioner. Factor Analysis, Factor Score, and Weightage Factor were adapted as a method of analysis in order to produce the final result with weightage output for prioritization and ranking of the relevant criteria. The result performed assists to provide the stakeholders an overview of the important criteria that should be considered especially during the decision making to retrofit the existing buildings with clean energy resources. The criteria developed are also to establish a structured decision-making process and to ensure the selection of the decision or alternatives achieve the desired outcome.

Systems to support health technology assessment (HTA) in member states of the European union with limited institutionalization of HTA.

PubMed

Moharra, Montse; Espallargues, Mireia; Kubesch, Nadine; Estrada, Maria-Dolors; Parada, Antoni; Vondeling, Hindrik; Lo Scalzo, Alessandra; Cristofides, Stelios; Turk, Eva; Raab, Martin

2009-12-01

The aim of this study was to support health technology assessment (HTA) capacity building in Member States of the European Union with limited experience or without institutionalized HTA. The main output is a Handbook on HTA Capacity Building. The methods used were worldwide surveys of (i) HTA organizations, (ii) information management units, and (iii) HTA educational programs. The results of two surveys (i & ii) were combined with expert opinion to produce the Handbook on HTA Capacity Building. Survey of HTA organizations (n = 41, response rate 35 percent). Most of the organizations were established by the government (61 percent), and all were not-for-profit. Working on HTA (80.5 percent) and doing research (63.4 percent) were the main lines of activity. Survey on information management units (n = 23, response rate 23 percent). Most (74.2 percent) of the responding HTA agencies reported having personnel dedicated to HTA information services. Survey on HTA educational programs (n = 48, response rate 60 percent). In total, nine Master of Science (MSc) programs were identified (three MSc in HTA and six MSc in HTA-related areas). Handbook on HTA Capacity Building. A group of twenty experts from thirteen countries developed the handbook. It consists of nine chapters focusing on HTA institutional development (structural setup, work processes, and visibility). Setting up organizational structures and establishing effective HTA programs that guide key policy decisions is a challenging task. There are no standard models or pathways. "One size fits all" is not a useful principle because of the wide systemic and cultural differences between countries. The Handbook on HTA Capacity Building includes approaches for overall institutional development, especially in formulating objectives, setting up structures, and defining work processes.

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

None

The Building America team NorthernSTAR investigated opportunities to use the massive customer networks of the home service industry as a means to connect homeowners to home-performance solutions. Home service companies could provide a pathway to advance building-science-guided upgrades by being in close proximity to homeowners when a decision-making moment is at hand. Established trust provides an opportunity for the company to deliver sound information and influence during a remodeling decision.

Build, Buy, Open Source, or Web 2.0?: Making an Informed Decision for Your Library

ERIC Educational Resources Information Center

Fagan, Jody Condit; Keach, Jennifer A.

2010-01-01

When improving a web presence, today's libraries have a choice: using a free Web 2.0 application, opting for open source, buying a product, or building a web application. This article discusses how to make an informed decision for one's library. The authors stress that deciding whether to use a free Web 2.0 application, to choose open source, to…

A Hybrid Backward-Forward Iterative Model for Improving Capacity Building of Earth Observations for Sustainable Societal Application

NASA Astrophysics Data System (ADS)

Hossain, F.; Iqbal, N.; Lee, H.; Muhammad, A.

2015-12-01

When it comes to building durable capacity for implementing state of the art technology and earth observation (EO) data for improved decision making, it has been long recognized that a unidirectional approach (from research to application) often does not work. Co-design of capacity building effort has recently been recommended as a better alternative. This approach is a two-way street where scientists and stakeholders engage intimately along the entire chain of actions from design of research experiments to packaging of decision making tools and each party provides an equal amount of input. Scientists execute research experiments based on boundary conditions and outputs that are defined as tangible by stakeholders for decision making. On the other hand, decision making tools are packaged by stakeholders with scientists ensuring the application-specific science is relevant. In this talk, we will overview one such iterative capacity building approach that we have implemented for gravimetry-based satellite (GRACE) EO data for improved groundwater management in Pakistan. We call our approach a hybrid approach where the initial step is a forward model involving a conventional short-term (3 day) capacity building workshop in the stakeholder environment addressing a very large audience. In this forward model, the net is cast wide to 'shortlist' a set of highly motivated stakeholder agency staffs who are then engaged more directly in 1-1 training. In the next step (the backward model), these short listed staffs are then brought back in the research environment of the scientists (supply) for 1-1 and long-term (6 months) intense brainstorming, training, and design of decision making tools. The advantage of this backward model is that it allows for a much better understanding for scientists of the ground conditions and hurdles of making a EO-based scientific innovation work for a specific decision making problem that is otherwise fundamentally impossible in conventional training workshops. We demonstrate here our experience of implementing this hybrid model for capacity building for groundwater management for Pakistan Council for Research on Water Resources (PCRWR) with the ultimate goal of empowering naitonal agencies in their ability to monitor groundwater storage changes independently from satellites.

Injury perceptions of bombing survivors--interviews from the Oklahoma City bombing.

PubMed

Glenshaw, Mary T; Vernick, Jon S; Frattaroli, Shannon; Brown, Sheryll; Mallonee, Sue

2008-01-01

Bombings, including the 1995 Oklahoma City bombing, remain an important public health threat. However, there has been little investigation into the impressions of injury risk or protective factors of bombing survivors. This study analyzes Oklahoma City bombing survivors' impressions of factors that influenced their risk of injury, and validates a hazard timeline outlining phases of injury risk in a building bombing. In-depth, semi-structured interviews were conducted within a sample of Oklahoma City bombing survivors. Participants included 15 injured and uninjured survivors, who were located in three buildings surrounding the detonation site during the attack. Risk factor themes included environmental glass, debris, and entrapment. Protective factors included knowledge of egress routes, shielding behaviors to deflect debris, and survival training. Building design and health status were reported as risk and protective factors. The hazard timeline was a useful tool, but should be modified to include a lay rescue phase. The combination of a narrative approach and direct questioning is an effective method of gathering the perceptions of survivors. Investigating survivors' impressions of building bombing hazards is critical to capture injury exposures, behavior patterns, and decision-making processes during actual events, and to identify interventions that will be supported by survivors.

Introduction of New Vaccines: Decision-making Process in Bangladesh

PubMed Central

Sarma, Haribondhu; Bari, Tajul I.; Koehlmoos, Tracey P.

2013-01-01

The understanding of the decision-making process in the introduction of new vaccines helps establish why vaccines are adopted or not. It also contributes to building a sustainable demand for vaccines in a country. The purpose of the study was to map and analyze the formal decision-making process in relation to the introduction of new vaccines within the context of health policy and health systems and identify the ways of making decisions to introduce new vaccines in Bangladesh. During February-April 2011, a qualitative assessment was made at the national level to evaluate the decision-making process around the adoption of new vaccines in Bangladesh. The study population included: policy-level people, programme heads or associates, and key decision-makers of the Government, private sector, non-governmental organizations, and international agencies at the national level. In total, 13 key informants were purposively selected. Data were collected by interviewing key informants and reviewing documents. Data were analyzed thematically. The findings revealed that the actors from different sectors at the policy level were involved in the decision-making process in the introduction of new vaccines. They included policy-makers from the ministries of health and family welfare, finance, and local government and rural development; academicians; researchers; representatives from professional associations; development partners; and members of different committees on EPI. They contributed to the introduction of new vaccines in their own capacity. The burden of disease, research findings on vaccine-preventable diseases, political issues relating to outbreaks of certain diseases, initiatives of international and local stakeholders, pressure of development partners, the Global Alliance for Vaccines and Immunization (GAVI) support, and financial matters were the key factors in the introduction of new vaccines in Bangladesh. The slow introduction and uptake of new vaccines is a concern in the country. Rapid action on the application of GAVI support and less time taken by the Government in processing the implementation and administrative work may expedite the introduction of new vaccines in future in this country. PMID:23930339

Introduction of new vaccines: decision-making process in Bangladesh.

PubMed

Uddin, Jasim; Sarma, Haribondhu; Bari, Tajul I; Koehlmoos, Tracey P

2013-06-01

The understanding of the decision-making process in the introduction of new vaccines helps establish why vaccines are adopted or not. It also contributes to building a sustainable demand for vaccines in a country. The purpose of the study was to map and analyze the formal decision-making process in relation to the introduction of new vaccines within the context of health policy and health systems and identify the ways of making decisions to introduce new vaccines in Bangladesh. During February-April 2011, a qualitative assessment was made at the national level to evaluate the decision-making process around the adoption of new vaccines in Bangladesh. The study population included: policy-level people, programme heads or associates, and key decision-makers of the Government, private sector, non-governmental organizations, and international agencies at the national level. In total, 13 key informants were purposively selected. Data were collected by interviewing key informants and reviewing documents. Data were analyzed thematically. The findings revealed that the actors from different sectors at the policy level were involved in the decision-making process in the introduction of new vaccines. They included policy-makers from the ministries of health and family welfare, finance, and local government and rural development; academicians; researchers; representatives from professional associations; development partners; and members of different committees on EPI. They contributed to the introduction of new vaccines in their own capacity. The burden of disease, research findings on vaccine-preventable diseases, political issues relating to outbreaks of certain diseases, initiatives of international and local stakeholders, pressure of development partners, the Global Alliance for Vaccines and Immunization (GAVI) support, and financial matters were the key factors in the introduction of new vaccines in Bangladesh. The slow introduction and uptake of new vaccines is a concern in the country. Rapid action on the application of GAVI support and less time taken by the Government in processing the implementation and administrative work may expedite the introduction of new vaccines in future in this country.

Consensus Building: A Key to School Transformation

ERIC Educational Resources Information Center

Baron, Daniel

2008-01-01

Consensus-based decision making can turn faculty meetings into meaningful and productive work sessions in which faculty members know that their input is respected and valued and important decisions are made. Reaching consensus has different meanings in different contexts. Decisions are made "by consensus" when the decision affects the entire…

Decision-Making Theory Applied to Architectural Programming: Some Research Implications.

ERIC Educational Resources Information Center

Green, Meg

The implications of delineating and determining the sequence of programming decisions are shown in the selection of building committee membership. The role relationships of client and architect are discussed in terms of decision-making function. Decision tables are described as aids in problem analysis. Other topics include information and…

Hybrid LCA model for assessing the embodied environmental impacts of buildings in South Korea

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

Jang, Minho, E-mail: minmin40@hanmail.net; Hong, Taehoon, E-mail: hong7@yonsei.ac.kr; Ji, Changyoon, E-mail: chnagyoon@yonsei.ac.kr

2015-01-15

The assessment of the embodied environmental impacts of buildings can help decision-makers plan environment-friendly buildings and reduce environmental impacts. For a more comprehensive assessment of the embodied environmental impacts of buildings, a hybrid life cycle assessment model was developed in this study. The developed model can assess the embodied environmental impacts (global warming, ozone layer depletion, acidification, eutrophication, photochemical ozone creation, abiotic depletion, and human toxicity) generated directly and indirectly in the material manufacturing, transportation, and construction phases. To demonstrate the application and validity of the developed model, the environmental impacts of an elementary school building were assessed using themore » developed model and compared with the results of a previous model used in a case study. The embodied environmental impacts from the previous model were lower than those from the developed model by 4.6–25.2%. Particularly, human toxicity potential (13 kg C{sub 6}H{sub 6} eq.) calculated by the previous model was much lower (1965 kg C{sub 6}H{sub 6} eq.) than what was calculated by the developed model. The results indicated that the developed model can quantify the embodied environmental impacts of buildings more comprehensively, and can be used by decision-makers as a tool for selecting environment-friendly buildings. - Highlights: • The model was developed to assess the embodied environmental impacts of buildings. • The model evaluates GWP, ODP, AP, EP, POCP, ADP, and HTP as environmental impacts. • The model presents more comprehensive results than the previous model by 4.6–100%. • The model can present the HTP of buildings, which the previous models cannot do. • Decision-makers can use the model for selecting environment-friendly buildings.« less

Clinical decision support alert malfunctions: analysis and empirically derived taxonomy.

PubMed

Wright, Adam; Ai, Angela; Ash, Joan; Wiesen, Jane F; Hickman, Thu-Trang T; Aaron, Skye; McEvoy, Dustin; Borkowsky, Shane; Dissanayake, Pavithra I; Embi, Peter; Galanter, William; Harper, Jeremy; Kassakian, Steve Z; Ramoni, Rachel; Schreiber, Richard; Sirajuddin, Anwar; Bates, David W; Sittig, Dean F

2018-05-01

To develop an empirically derived taxonomy of clinical decision support (CDS) alert malfunctions. We identified CDS alert malfunctions using a mix of qualitative and quantitative methods: (1) site visits with interviews of chief medical informatics officers, CDS developers, clinical leaders, and CDS end users; (2) surveys of chief medical informatics officers; (3) analysis of CDS firing rates; and (4) analysis of CDS overrides. We used a multi-round, manual, iterative card sort to develop a multi-axial, empirically derived taxonomy of CDS malfunctions. We analyzed 68 CDS alert malfunction cases from 14 sites across the United States with diverse electronic health record systems. Four primary axes emerged: the cause of the malfunction, its mode of discovery, when it began, and how it affected rule firing. Build errors, conceptualization errors, and the introduction of new concepts or terms were the most frequent causes. User reports were the predominant mode of discovery. Many malfunctions within our database caused rules to fire for patients for whom they should not have (false positives), but the reverse (false negatives) was also common. Across organizations and electronic health record systems, similar malfunction patterns recurred. Challenges included updates to code sets and values, software issues at the time of system upgrades, difficulties with migration of CDS content between computing environments, and the challenge of correctly conceptualizing and building CDS. CDS alert malfunctions are frequent. The empirically derived taxonomy formalizes the common recurring issues that cause these malfunctions, helping CDS developers anticipate and prevent CDS malfunctions before they occur or detect and resolve them expediently.

The Voice of the Pupils: An Experimental Comparison of Decisions Made by Elected Pupil Councils, Pupils in Referenda, and Teaching Staff

ERIC Educational Resources Information Center

Gilljam, Mikael; Esaiasson, Peter; Lindholm, Torun

2010-01-01

This article tests whether the form of decision-making used in school environments affects pupils' views on the legitimacy of the decisions made, and of the decision-making procedure. Building on political science theory on democratic decision-making, it compares pupils' reactions towards decisions made by pupil councils, by pupils via referendum,…

Early Design Energy Analysis Using Building Information Modeling Technology

DTIC Science & Technology

2011-11-01

building, (a) floor plan and (b) 3D image. ....................................... 50 Figure 28. Comparison of different energy estimates...when they make the biggest impact on building life-cycle costs. Traditionally, most building energy analyses have been conducted late in design, by...complete energy analysis. This method enables project teams to make energy conscious decisions early in design when they impact building life-cycle

Hydraulic Control Method for Heating Systems of High-Rise Buildings

NASA Astrophysics Data System (ADS)

Makarov, D.; Chernenkov, V.; Likhachev, I.

2017-11-01

The following article reflects the ideas of possibility to increase energy efficiency of heating systems in high-rise buildings. The article also includes the principle ways of high-rise building heating systems operation as well as traditional engineering decisions aimed at the elimination of the increased pressure effect in heaters. The main disadvantages of such decisions are also presented for the reader. Moreover, the article offers the way of operation for the above-mentioned systems together with the equipment that implements this operation. An economic impact from such energy-saving technology application has been also evaluated.

Implementation of quality improvement techniques for management and technical processes in the ACRV project

NASA Technical Reports Server (NTRS)

Raiman, Laura B.

1992-01-01

Total Quality Management (TQM) is a cooperative form of doing business that relies on the talents of everyone in an organization to continually improve quality and productivity, using teams and an assortment of statistical and measurement tools. The objective of the activities described in this paper was to implement effective improvement tools and techniques in order to build work processes which support good management and technical decisions and actions which are crucial to the success of the ACRV project. The objectives were met by applications in both the technical and management areas. The management applications involved initiating focused continuous improvement projects with widespread team membership. The technical applications involved applying proven statistical tools and techniques to the technical issues associated with the ACRV Project. Specific activities related to the objective included working with a support contractor team to improve support processes, examining processes involved in international activities, a series of tutorials presented to the New Initiatives Office and support contractors, a briefing to NIO managers, and work with the NIO Q+ Team. On the technical side, work included analyzing data from the large-scale W.A.T.E.R. test, landing mode trade analyses, and targeting probability calculations. The results of these efforts will help to develop a disciplined, ongoing process for producing fundamental decisions and actions that shape and guide the ACRV organization .

Integrating Strategic and Operational Decision Making Using Data-Driven Dashboards: The Case of St. Joseph Mercy Oakland Hospital.

PubMed

Jack Weiner; Balijepally, Venugopal; Tanniru, Mohan

2015-01-01

Hospitals have invested and continue to invest heavily in building information systems to support operations at various levels of administration. These systems generate a lot of data but fail to effectively convert these data into actionable information for decision makers. Such ineffectiveness often is attributed to a lack of alignment between strategic planning and information technology (IT) initiatives supporting operational goals. We present a case study that illustrates how the use of digital dashboards at St. Joseph Mercy Oakland (SJMO) Hospital in Pontiac, Michigan, was instrumental in supporting such an alignment. Driven by a focus on key performance indicators (KPIs), dashboard applications also led to other tangible and intangible benefits. An ability to track KPIs over time and against established targets, with drill-down capabilities, allowed leadership to hold staff members accountable for achieving their performance targets. By displaying the dashboards in prominent locations (such as operational unit floors, the physicians' cafeteria, and nursing stations), SJMO ushered in transparency in the planning and monitoring processes. The need to develop KPI metrics and drive data collection efforts became ingrained in the work ethos of people at every level of the organization. Although IT-enabled dashboards have been instrumental in supporting this cultural transformation, the focus of investment was the ability of technology to make collective vision and action the responsibility of all stakeholders.

Implementation of quality improvement techniques for management and technical processes in the ACRV project

NASA Astrophysics Data System (ADS)

Raiman, Laura B.

1992-12-01

Total Quality Management (TQM) is a cooperative form of doing business that relies on the talents of everyone in an organization to continually improve quality and productivity, using teams and an assortment of statistical and measurement tools. The objective of the activities described in this paper was to implement effective improvement tools and techniques in order to build work processes which support good management and technical decisions and actions which are crucial to the success of the ACRV project. The objectives were met by applications in both the technical and management areas. The management applications involved initiating focused continuous improvement projects with widespread team membership. The technical applications involved applying proven statistical tools and techniques to the technical issues associated with the ACRV Project. Specific activities related to the objective included working with a support contractor team to improve support processes, examining processes involved in international activities, a series of tutorials presented to the New Initiatives Office and support contractors, a briefing to NIO managers, and work with the NIO Q+ Team. On the technical side, work included analyzing data from the large-scale W.A.T.E.R. test, landing mode trade analyses, and targeting probability calculations. The results of these efforts will help to develop a disciplined, ongoing process for producing fundamental decisions and actions that shape and guide the ACRV organization .

Incorporating Natural Capital into Climate Adaptation Planning: Exploring the Role of Habitat in Increasing Coastal Resilience

NASA Astrophysics Data System (ADS)

Wedding, L.; Hartge, E. H.; Guannel, G.; Melius, M.; Reiter, S. M.; Ruckelshaus, M.; Guerry, A.; Caldwell, M.

2014-12-01

To support decision-makers in their efforts to manage coastal resources in a changing climate the Natural Capital Project and the Center for Ocean Solutions are engaging in, informing, and helping to shape climate adaptation planning at various scales throughout coastal California. Our team is building collaborations with regional planners and local scientific and legal experts to inform local climate adaptation decisions that might minimize the economic and social losses associated with rising seas and more damaging storms. Decision-makers are considering engineered solutions (e.g. seawalls), natural solutions (e.g. dune or marsh restoration), and combinations of the two. To inform decisions about what kinds of solutions might best work in specific locations, we are comparing alternate climate and adaptation scenarios. We will present results from our use of the InVEST ecosystem service models in Sonoma County, with an initial focus on protection from coastal hazards due to erosion and inundation. By strategically choosing adaptation alternatives, communities and agencies can work to protect people and property while also protecting or restoring dwindling critical habitat and the full suite of benefits those habitats provide to people.

How Anxiety Leads to Suboptimal Decisions Under Risky Choice Situations.

PubMed

Yang, Zhiyong; Saini, Ritesh; Freling, Traci

2015-10-01

The current research proposes that situationally activated anxiety--whether incidental or integral-impairs decision making. In particular, we theorize that anxiety drives decisionmakers to more heavily emphasize subjective anecdotal information in their decision making, at the expense of more factual statistical information--a deleterious heuristic called the anecdotal bias. Four studies provide consistent support for this assertion. Studies 1A and 1B feature field experiments that demonstrate the role of incidental anxiety in enhancing the anecdotal bias in a choice context. Study 2 builds on these findings, manipulating individuals' incidental anxiety and showing how this affects the anecdotal bias in the context of message evaluations. Study 2 also provides direct evidence that only high-arousal negative emotions such as anxiety/worry enhance the anecdotal bias, not just any negative emotion (e.g., sadness). While the first three studies examine how incidental anxiety impacts choice, the last study demonstrates the effect of integral anxiety on decision making, manipulating anxiety by intensifying participants' perceived risk. Our results show that--consistent with findings from our first three studies--the anecdotal bias is enhanced when anxiety is heightened by individuals' perception of risk. © 2015 Society for Risk Analysis.

Collaborative deliberation: a model for patient care.

PubMed

Elwyn, Glyn; Lloyd, Amy; May, Carl; van der Weijden, Trudy; Stiggelbout, Anne; Edwards, Adrian; Frosch, Dominick L; Rapley, Tim; Barr, Paul; Walsh, Thom; Grande, Stuart W; Montori, Victor; Epstein, Ronald

2014-11-01

Existing theoretical work in decision making and behavior change has focused on how individuals arrive at decisions or form intentions. Less attention has been given to theorizing the requirements that might be necessary for individuals to work collaboratively to address difficult decisions, consider new alternatives, or change behaviors. The goal of this work was to develop, as a forerunner to a middle range theory, a conceptual model that considers the process of supporting patients to consider alternative health care options, in collaboration with clinicians, and others. Theory building among researchers with experience and expertise in clinician-patient communication, using an iterative cycle of discussions. We developed a model composed of five inter-related propositions that serve as a foundation for clinical communication processes that honor the ethical principles of respecting individual agency, autonomy, and an empathic approach to practice. We named the model 'collaborative deliberation.' The propositions describe: (1) constructive interpersonal engagement, (2) recognition of alternative actions, (3) comparative learning, (4) preference construction and elicitation, and (5) preference integration. We believe the model underpins multiple suggested approaches to clinical practice that take the form of patient centered care, motivational interviewing, goal setting, action planning, and shared decision making. Copyright © 2014 Elsevier Ireland 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.

Applicability and economic efficiency of earthquake retrofit measures on existing buildings in Bucharest, Romania

NASA Astrophysics Data System (ADS)

Bostenaru, M.

2009-04-01

The research discussed in this contribution contains two aspects: on one side the economic efficiency of seismic retrofit measures, and on the other their applicability. The research was limited to housing buildings. Bucharest, the capital of Romania, was the object of the research. Strong earthquakes affect Bucharest about three times in a century, the damaging earthquakes of the 20th century being in 1940 and 1977. Other strong earthquakes occurred in 1986 and 1990. Since it is a broad topic, first the building type was determined, which should serve further research. For this scope the building types of the 20th century, which are common in Bucharest, Romania, were investigated. For each building type reports have been written, which comprised the earthquake resilient features, the seismic defficiencies, the damage patterns and the retrofit measures. Each of these features was listed for elements of the building. A first result of the research was an integrated system in order to include latter aspects in the planning in the first steps. So already at the building survey attention has to be paid on how a building is subdivided in order to be able to determine the economic efficiency of the planned action. So were defined the `retrofit elements`. In a first step the characteristics were defined, through which these retrofit elements (for example column, wall part between two windows) can be recognised in the building survey. In a further one, which retrofit measures can be connected to these. Diagrams were built, in order to visualise these findings. For each retrofit element and the corresponding measure the costs were calculated. Also, these retrofit elements and the measures connected to them were modelled for the simulation with the structural software, so that the benefit of the measures could be determined. In the part which regarded the economic efficiency, benefits and costs of retrofit measures had to be compared, so the improvement in the rigidity, ductility and/or strength of the structure at different retrofit measures with its costs. In order to investigate the improvement in the seismic characteristics numerous simulations of the earthquake impact on reinforced concrete frame buildings were conducted and in that context conventional strengthening measures with reinforced concrete and steel were considered. In these reinforced concrete frame buildings interwar buildings from Bucharest were modelled, as these proved to be the most vulnerable in the initial investigation. For the investigation of the economic efficiency also the damages through earthquakes were simulated. With help of a characteristic of the software used so called performance points could be set, so at the end of the simulation it could be seen how strongly was damaged the steel and respectively the concrete in the reinforced concrete element and so was conducted a classification of the strength of the damages in different retrofit elements. These simulations were done for the 1977, 1986 and 1990 earthquakes, as for these the strong motion records were digitally available. For two simple models alternatives of retrofit actions and their locations were fully simulated, while for real building models customised retrofit strategies considering more retrofit elements within the strategy were employed. To the benefit belong not only the improvement of the structural behaviour, as often assumed in earthquake engineering circles. There belong also aesthetical and sociologic aspects. In order to give these aspects their rights, a decision tree was developed, in which the actors are the engineer, the architect, the investor and the user. The retrofit measures were evaluated with two different decision systems. This was the part about the applicability. Further research would serve to see how can be used the developed method for the strategic planning, in which not only single buildings but whole urban areas build the object. The research was funded by the Research Training Network 450 "Natural Disasters" supported by the DFG (German Research Network), 2000-2004 while the result was published with support from a subsequent research project of the author, CA'REDIVIVUS, which continued the research, supported by the European Commission, in 2006.

Supporting students in building interdisciplinary connections across physics and biology

NASA Astrophysics Data System (ADS)

Turpen, Chandra

2014-03-01

Our research team has been engaged in the iterative redesign of an Introductory Physics course for Life Science (IPLS) majors to explicitly bridge biology and physics in ways that are authentic to the disciplines. Our interdisciplinary course provides students opportunities to examine how modeling decisions (e.g. knowing when and how to use different concepts, identifying implicit assumptions, making and justifying assumptions) may differ depending on canonical disciplinary aims and interests. Our focus on developing students' interdisciplinary reasoning skills requires 1) shifting course topics to focus on core ideas that span the disciplines, 2) shifting epistemological expectations, and 3) foregrounding typically tacit disciplinary assumptions. In working to build an authentic interdisciplinary course that bridges physics and biology, we pay careful attention to supporting students in constructing these bridges. This course has been shown to have important impacts: a) students seek meaningful connections between the disciplines, b) students perceive relevance and utility of ideas from different disciplines, and c) students reconcile challenging disciplinary ideas. Although our focus has been on building interdisciplinary coherence, we have succeeded in maintaining strong student learning gains on fundamental physics concepts and allowed students to deepen their understanding of challenging concepts in thermodynamics. This presentation will describe the shifts in course content and the modern pedagogical approaches that have been integrated into the course, and provide an overview of key research results from this project. These results may aid physicists in reconsidering how they can meaningfully reach life-science students. This work is supported by NSF-TUES DUE 11-22818, the HHMI NEXUS grant, and a NSF Graduate Research Fellowship (DGE 0750616).

SemantEco: a semantically powered modular architecture for integrating distributed environmental and ecological data

USGS Publications Warehouse

Patton, Evan W.; Seyed, Patrice; Wang, Ping; Fu, Linyun; Dein, F. Joshua; Bristol, R. Sky; McGuinness, Deborah L.

2014-01-01

We aim to inform the development of decision support tools for resource managers who need to examine large complex ecosystems and make recommendations in the face of many tradeoffs and conflicting drivers. We take a semantic technology approach, leveraging background ontologies and the growing body of linked open data. In previous work, we designed and implemented a semantically enabled environmental monitoring framework called SemantEco and used it to build a water quality portal named SemantAqua. Our previous system included foundational ontologies to support environmental regulation violations and relevant human health effects. In this work, we discuss SemantEco’s new architecture that supports modular extensions and makes it easier to support additional domains. Our enhanced framework includes foundational ontologies to support modeling of wildlife observation and wildlife health impacts, thereby enabling deeper and broader support for more holistically examining the effects of environmental pollution on ecosystems. We conclude with a discussion of how, through the application of semantic technologies, modular designs will make it easier for resource managers to bring in new sources of data to support more complex use cases.

A Multidisciplinary Research Agenda for Understanding Vaccine-Related Decisions

PubMed Central

Larson, Heidi; Leask, Julie; Aggett, Sian; Sevdalis, Nick; Thomson, Angus

2013-01-01

There is increasingly broad global recognition of the need to better understand determinants of vaccine acceptance. Fifteen social science, communication, health, and medical professionals (the “Motors of Trust in Vaccination” (MOTIV) think tank) explored factors relating to vaccination decision-making as a step to building a multidisciplinary research agenda. One hundred and forty seven factors impacting decisions made by consumers, professionals, and policy makers on vaccine acceptance, delay, or refusal were identified and grouped into three major categories: cognition and decision-making; groups and social norms; and communication and engagement. These factors should help frame a multidisciplinary research agenda to build an evidence base on the determinants of vaccine acceptance to inform the development of interventions and vaccination policies. PMID:26344114

The effectiveness of health impact assessment in influencing decision-making in Australia and New Zealand 2005–2009

PubMed Central

2013-01-01

Background Health Impact Assessment (HIA) involves assessing how proposals may alter the determinants of health prior to implementation and recommends changes to enhance positive and mitigate negative impacts. HIAs growing use needs to be supported by a strong evidence base, both to validate the value of its application and to make its application more robust. We have carried out the first systematic empirical study of the influence of HIA on decision-making and implementation of proposals in Australia and New Zealand. This paper focuses on identifying whether and how HIAs changed decision-making and implementation and impacts that participants report following involvement in HIAs. Methods We used a two-step process first surveying 55 HIAs followed by 11 in-depth case studies. Data gathering methods included questionnaires with follow-up interview, semi-structured interviews and document collation. We carried out deductive and inductive qualitative content analyses of interview transcripts and documents as well as simple descriptive statistics. Results We found that most HIAs are effective in some way. HIAs are often directly effective in changing, influencing, broadening areas considered and in some cases having immediate impact on decisions. Even when HIAs are reported to have no direct effect on a decision they are often still effective in influencing decision-making processes and the stakeholders involved in them. HIA participants identify changes in relationships, improved understanding of the determinants of health and positive working relationships as major and sustainable impacts of their involvement. Conclusions This study clearly demonstrates direct and indirect effectiveness of HIA influencing decision making in Australia and New Zealand. We recommend that public health leaders and policy makers should be confident in promoting the use of HIA and investing in building capacity to undertake high quality HIAs. New findings about the value HIA stakeholders put on indirect impacts such as learning and relationship building suggest HIA has a role both as a technical tool that makes predictions of potential impacts of a policy, program or project and as a mechanism for developing relationships with and influencing other sectors. Accordingly when evaluating the effectiveness of HIAs we need to look beyond the direct impacts on decisions. PMID:24341545

Actionable knowledge and strategic decision making for bio- and agroterrorism threats: building a collaborative early warning culture.

PubMed

Mårtensson, Per-Åke; Hedström, Lars; Sundelius, Bengt; Skiby, Jeffrey E; Elbers, Armin; Knutsson, Rickard

2013-09-01

Current trends in biosecurity and cybersecurity include (1) the wide availability of technology and specialized knowledge that previously were available only to governments; (2) the global economic recession, which may increase the spread of radical non-state actors; and (3) recent US and EU commission reports that reflect concerns about non-state actors in asymmetric threats. The intersectoral and international nature of bioterrorism and agroterrorism threats requires collaboration across several sectors including intelligence, police, forensics, customs, and other law enforcement organizations who must work together with public and animal health organizations as well as environmental and social science organizations. This requires coordinated decision making among these organizations, based on actionable knowledge and information sharing. The risk of not sharing information among organizations compared to the benefit of sharing information can be considered in an "information sharing risk-benefit analysis" to prevent a terrorism incident from occurring and to build a rapid response capability. In the EU project AniBioThreat, early warning is the main topic in work package 3 (WP 3). A strategy has been generated based on an iterative approach to bring law enforcement agencies and human and animal health institutes together. Workshops and exercises have taken place during the first half of the project, and spin-off activities include new preparedness plans for institutes and the formation of a legal adviser network for decision making. In addition, a seminar on actionable knowledge was held in Stockholm, Sweden, in 2012, which identified the need to bring various agency cultures together to work on developing a resilient capability to identify early signs of bio- and agroterrorism threats. The seminar concluded that there are a number of challenges in building a collaborative culture, including developing an education program that supports collaboration and shared situational awareness.

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.

Engineering-Geological Data Model - The First Step to Build National Polish Standard for Multilevel Information Management

NASA Astrophysics Data System (ADS)

Ryżyński, Grzegorz; Nałęcz, Tomasz

2016-10-01

The efficient geological data management in Poland is necessary to support multilevel decision processes for government and local authorities in case of spatial planning, mineral resources and groundwater supply and the rational use of subsurface. Vast amount of geological information gathered in the digital archives and databases of Polish Geological Survey (PGS) is a basic resource for multi-scale national subsurface management. Data integration is the key factor to allow development of GIS and web tools for decision makers, however the main barrier for efficient geological information management is the heterogeneity of data in the resources of the Polish Geological Survey. Engineering-geological database is the first PGS thematic domain applied in the whole data integration plan. The solutions developed within this area will facilitate creation of procedures and standards for multilevel data management in PGS. Twenty years of experience in delivering digital engineering-geological mapping in 1:10 000 scale and archival geotechnical reports acquisition and digitisation allowed gathering of more than 300 thousands engineering-geological boreholes database as well as set of 10 thematic spatial layers (including foundation conditions map, depth to the first groundwater level, bedrock level, geohazards). Historically, the desktop approach was the source form of the geological-engineering data storage, resulting in multiple non-correlated interbase datasets. The need for creation of domain data model emerged and an object-oriented modelling (UML) scheme has been developed. The aim of the aforementioned development was to merge all datasets in one centralised Oracle server and prepare the unified spatial data structure for efficient web presentation and applications development. The presented approach will be the milestone toward creation of the Polish national standard for engineering-geological information management. The paper presents the approach and methodology of data unification, thematic vocabularies harmonisation, assumptions and results of data modelling as well as process of the integration of domain model with enterprise architecture implemented in PGS. Currently, there is no geological data standard in Poland. Lack of guidelines for borehole and spatial data management results in an increasing data dispersion as well as in growing barrier for multilevel data management and implementation of efficient decision support tools. Building the national geological data standard makes geotechnical information accessible to multiple institutions, universities, administration and research organisations and gather their data in the same, unified digital form according to the presented data model. Such approach is compliant with current digital trends and the idea of Spatial Data Infrastructure. Efficient geological data management is essential to support the sustainable development and the economic growth, as they allow implementation of geological information to assist the idea of Smart Cites, deliver information for Building Information Management (BIM) and support modern spatial planning. The engineering-geological domain data model presented in the paper is a scalable solution. Future implementation of developed procedures on other domains of PGS geological data is possible.

Assessing the usability and potential value of seasonal climate forecasts in land management decisions in the southwest UK: challenges and reflections

NASA Astrophysics Data System (ADS)

Soares, Marta Bruno

2017-06-01

The potential usability and benefits of seasonal climate forecasts (SCF) to help inform decision-making processes is widely accepted. However, the practical use of SCF in Europe is still fairly recent and, as such, current knowledge of the added benefits of SCF in supporting and improving decision-making is limited. This study is based on research conducted to co-develop a semi-operational climate service prototype - the Land Management Tool (LMTool) - with farmers in South West regions of the UK. The value of the SCF provided to the farmers was examined to help us understand the usability and (potential) value of these forecasts in farmers' decisions during the winter months of 2015/2016. The findings from the study point to the need to explore and develop (new) research methods capable of addressing the complexity of the decision-making processes, such as those in the farming sector. The farmers who used the SCF perceived it as useful and usable as it helped them change and adapt their decision-making and thus, avoid unnecessary costs. However, to fully grasp the potential value of using SCF, farmers emphasised the need for the provision of SCF for longer periods of time to allow them to build trust and confidence in the information provided. This paper contributes to ongoing discussions about how to assess the use and value of SCF in decision-making processes in a meaningful and effective way.

Effectiveness of capacity building interventions relevant to public health practice: a systematic review.

PubMed

DeCorby-Watson, Kara; Mensah, Gloria; Bergeron, Kim; Abdi, Samiya; Rempel, Benjamin; Manson, Heather

2018-06-01

This systematic review assessed the effectiveness of capacity building interventions relevant to public health practice. The aim is to inform and improve capacity building interventions. Four strategies were used: 1) electronic database searching; 2) reference lists of included papers; 3) key informant consultation; and 4) grey literature searching. Inclusion (e.g., published in English) and exclusion criteria (e.g., non-English language papers published earlier than 2005) are outlined with included papers focusing on capacity building, learning plans, or professional development plans within public health and related settings, such as non-governmental organizations, government, or community-based organizations relating to public health or healthcare. Outcomes of interest included changes in knowledge, skill or confidence (self-efficacy), changes in practice (application or intent), and perceived support or supportive environments, with outcomes reported at the individual, organizational or systems level(s). Quality assessment of all included papers was completed. Fourteen papers were included in this review. These papers reported on six intervention types: 1) internet-based instruction, 2) training and workshops, 3) technical assistance, 4) education using self-directed learning, 5) communities of practice, and 6) multi-strategy interventions. The available literature showed improvements in one or more capacity-building outcomes of interest, mainly in terms of individual-level outcomes. The available literature was moderate in quality and showed a range of methodological issues. There is evidence to inform capacity building programming and how interventions can be selected to optimize impact. Organizations should carefully consider methods for analysis of capacity building interventions offered; specifically, through which mechanisms, to whom, and for which purpose. Capacity-building interventions can enhance knowledge, skill, self-efficacy (including confidence), changes in practice or policies, behaviour change, application, and system-level capacity. However in applying available evidence, organizations should consider the outcomes of highest priority, selecting intervention(s) effective for the outcome(s) of interest. Examples are given for selecting intervention(s) to match priorities and context, knowing effectiveness evidence is only one consideration in decision making. Future evaluations should: extend beyond the individual level, assess outcomes at organizational and systems levels, include objective measures of effect, assess baseline conditions, and evaluate features most critical to the success of interventions.

Research | Argonne National Laboratory

Science.gov Websites

, and Decision Analytics Energy Systems Analysis Engines and Fuels Friction, Wear, and Lubrication Vehicle Technologies Buildings and Climate-Environment Energy, Power, and Decision Analytics Energy

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

A General Water Resources Regulation Software System in China

NASA Astrophysics Data System (ADS)

LEI, X.

2017-12-01

To avoid iterative development of core modules in water resource normal regulation and emergency regulation and improve the capability of maintenance and optimization upgrading of regulation models and business logics, a general water resources regulation software framework was developed based on the collection and analysis of common demands for water resources regulation and emergency management. It can provide a customizable, secondary developed and extensible software framework for the three-level platform "MWR-Basin-Province". Meanwhile, this general software system can realize business collaboration and information sharing of water resources regulation schemes among the three-level platforms, so as to improve the decision-making ability of national water resources regulation. There are four main modules involved in the general software system: 1) A complete set of general water resources regulation modules allows secondary developer to custom-develop water resources regulation decision-making systems; 2) A complete set of model base and model computing software released in the form of Cloud services; 3) A complete set of tools to build the concept map and model system of basin water resources regulation, as well as a model management system to calibrate and configure model parameters; 4) A database which satisfies business functions and functional requirements of general water resources regulation software can finally provide technical support for building basin or regional water resources regulation models.

Understanding service disengagement from the perspective of case managers.

PubMed

Stanhope, Victoria; Henwood, Benjamin F; Padgett, Deborah K

2009-04-01

Disengagement from services by persons experiencing homelessness and co-occurring disorders challenges the mental health system and the frontline providers who build clinical relationships that end prematurely. This qualitative study explored how case managers understand and respond to disengagement. This study was conducted at four programs serving persons with co-occurring disorders experiencing homelessness. The qualitative design used a case study approach based on in-depth interviews with 18 case managers about 29 cases of disengagement. The study compared their accounts with predisengagement interviews when available and the postdeparture residential status of consumers. Themes were derived by independent coding and consensus. Case managers attributed disengagement primarily to substance relapse and a preference for alternative living arrangements. The following themes emerged: seeing disengagement as part of their work, believing disengagement to be poor decision making on the part of the consumer, and coping with the revolving-door syndrome. The majority of consumers experienced homelessness after disengagement. The study illustrated the challenge of building hope-instilling relationships with consumers when faced with the reality of frequent disengagement. In an era of recovery-oriented services and consumer choice, case managers need support when faced with consumer decisions to leave treatment settings. Greater program flexibility may also help to reduce disengagement.

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.

Design of a radiator shade for testing in a simulated lunar environment

NASA Technical Reports Server (NTRS)

Huff, Jaimi; Remington, Randy; Tang, Toan

1992-01-01

The National Aeronautics and Space Administration (NASA) and The Universities Space Research Association (USRA) have chosen the parabolic/catenary concept from their sponsored Fall 1991 lunar radiation shade project for further testing and development. NASA asked the design team to build a shading device and support structure for testing in a vacuum chamber. Besides the support structure for the catenary shading device, the design team was asked to develop a system for varying the shade shape so that the device can be tested at different focal lengths. The design team developed concept variants and combined the concept variants to form overall designs. Using a decision matrix, an overall design was selected by the team from several overall design alternatives. Concept variants were developed for three primary functions. The three functions were structural support, shape adjustments, and end shielding. The shade adjustment function was divided into two sub-functions, arc length adjustment, and width adjustment.

The Art of Restraint: How Experienced Program Leaders Use Their Authority to Support Youth Agency.

PubMed

Larson, Reed W; Izenstark, Dina; Rodriguez, Gabriel; Perry, S Cole

2016-12-01

The staff of youth development programs perform a delicate balancing act between supporting youth agency and exercising necessary authority. To understand this balancing in daily practice, we interviewed 25 experienced (M = 14 years) leaders of arts, leadership, and technology programs for high-school-aged youth. We obtained accounts of when, how, and why they gave advice, set limits, and "supported youth when disagreeing." Qualitative analysis found surprising similarities across leaders. They used authority to give advice and set limits, but did so with reasoned restraint. Maximizing youth's opportunities to learn from experience was central in their decision making. They described employing authority in intentional ways aimed at helping youth's work succeed, strengthening youth's agency, and building skills for agency (e.g., critical thinking, "clarifying intent"). © 2015 The Authors. Journal of Research on Adolescence © 2015 Society for Research on Adolescence.

Patient-tailored prioritization for a pediatric care decision support system through machine learning.

PubMed

Klann, Jeffrey G; Anand, Vibha; Downs, Stephen M

2013-12-01

Over 8 years, we have developed an innovative computer decision support system that improves appropriate delivery of pediatric screening and care. This system employs a guidelines evaluation engine using data from the electronic health record (EHR) and input from patients and caregivers. Because guideline recommendations typically exceed the scope of one visit, the engine uses a static prioritization scheme to select recommendations. Here we extend an earlier idea to create patient-tailored prioritization. We used Bayesian structure learning to build networks of association among previously collected data from our decision support system. Using area under the receiver-operating characteristic curve (AUC) as a measure of discriminability (a sine qua non for expected value calculations needed for prioritization), we performed a structural analysis of variables with high AUC on a test set. Our source data included 177 variables for 29 402 patients. The method produced a network model containing 78 screening questions and anticipatory guidance (107 variables total). Average AUC was 0.65, which is sufficient for prioritization depending on factors such as population prevalence. Structure analysis of seven highly predictive variables reveals both face-validity (related nodes are connected) and non-intuitive relationships. We demonstrate the ability of a Bayesian structure learning method to 'phenotype the population' seen in our primary care pediatric clinics. The resulting network can be used to produce patient-tailored posterior probabilities that can be used to prioritize content based on the patient's current circumstances. This study demonstrates the feasibility of EHR-driven population phenotyping for patient-tailored prioritization of pediatric preventive care services.

Expert System Shells for Rapid Clinical Decision Support Module Development: An ESTA Demonstration of a Simple Rule-Based System for the Diagnosis of Vaginal Discharge

PubMed Central

2012-01-01

Objectives This study demonstrates the feasibility of using expert system shells for rapid clinical decision support module development. Methods A readily available expert system shell was used to build a simple rule-based system for the crude diagnosis of vaginal discharge. Pictures and 'canned text explanations' are extensively used throughout the program to enhance its intuitiveness and educational dimension. All the steps involved in developing the system are documented. Results The system runs under Microsoft Windows and is available as a free download at http://healthcybermap.org/vagdisch.zip (the distribution archive includes both the program's executable and the commented knowledge base source as a text document). The limitations of the demonstration system, such as the lack of provisions for assessing uncertainty or various degrees of severity of a sign or symptom, are discussed in detail. Ways of improving the system, such as porting it to the Web and packaging it as an app for smartphones and tablets, are also presented. Conclusions An easy-to-use expert system shell enables clinicians to rapidly become their own 'knowledge engineers' and develop concise evidence-based decision support modules of simple to moderate complexity, targeting clinical practitioners, medical and nursing students, as well as patients, their lay carers and the general public (where appropriate). In the spirit of the social Web, it is hoped that an online repository can be created to peer review, share and re-use knowledge base modules covering various clinical problems and algorithms, as a service to the clinical community. PMID:23346475

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

Scolozzi, Rocco, E-mail: rocco.scolozzi@fmach.it; Geneletti, Davide, E-mail: geneletti@ing.unitn.it

Habitat loss and fragmentation are often concurrent to land conversion and urbanization. Simple application of GIS-based landscape pattern indicators may be not sufficient to support meaningful biodiversity impact assessment. A review of the literature reveals that habitat definition and habitat fragmentation are frequently inadequately considered in environmental assessment, notwithstanding the increasing number of tools and approaches reported in the landscape ecology literature. This paper presents an approach for assessing impacts on habitats on a local scale, where availability of species data is often limited, developed for an alpine valley in northern Italy. The perspective of the methodology is multiple scalemore » and species-oriented, and provides both qualitative and quantitative definitions of impact significance. A qualitative decision model is used to assess ecological values in order to support land-use decisions at the local level. Building on recent studies in the same region, the methodology integrates various approaches, such as landscape graphs, object-oriented rule-based habitat assessment and expert knowledge. The results provide insights into future habitat loss and fragmentation caused by land-use changes, and aim at supporting decision-making in planning and suggesting possible ecological compensation. - Highlights: Black-Right-Pointing-Pointer Many environmental assessments inadequately consider habitat loss and fragmentation. Black-Right-Pointing-Pointer Species-perspective for defining habitat quality and connectivity is claimed. Black-Right-Pointing-Pointer Species-based tools are difficult to be applied with limited availability of data. Black-Right-Pointing-Pointer We propose a species-oriented and multiple scale-based qualitative approach. Black-Right-Pointing-Pointer Advantages include being species-oriented and providing value-based information.« less

A New Framework for Addressing Adverse Childhood and Community Experiences: The Building Community Resilience Model.

PubMed

Ellis, Wendy R; Dietz, William H

We propose a transformative approach to foster collaboration across child health, public health, and community-based agencies to address the root causes of toxic stress and childhood adversity and to build community resilience. Physicians, members of social service agencies, and experts in toxic stress and adverse childhood experiences (ACEs) were interviewed to inform development of the Building Community Resilience (BCR) model. Through a series of key informant interviews and focus groups, we sought to understand the role of BCR for child health systems and their partners to reduce toxic stress and build community resilience to improve child health outcomes. Key informants indicated the intentional approach to ACEs and toxic stress through continuous quality improvement (data-driven decisions and program development, partners testing and adapting to changes to their needs, and iterative development and testing) which provides a mechanism by which social determinants or a population health approach could be introduced to physicians and community partners as part of a larger effort to build community resilience. Structured interviews also reveal a need for a framework that provides guidance, structure, and support for child health systems and community partners to develop collective goals, shared work plans, and a means for data-sharing to reinforce the components that will contribute to community resilience. Key informant interviews and focus group dialogues revealed a deep understanding of the factors related to toxic stress and ACEs. Respondents endorsed the BCR approach as a means to explore capacity issues, reduce fragmented health care delivery, and facilitate integrated systems across partners in efforts to build community resilience. Current financing models are seen as a potential barrier, because they often do not support restructured roles, partnership development, and the work to sustain upstream efforts to address toxic stress and community resilience. Copyright © 2017 Academic Pediatric Association. Published by Elsevier Inc. All rights reserved.

Spatial decision supporting for winter wheat irrigation and fertilizer optimizing in North China Plain

NASA Astrophysics Data System (ADS)

Yang, Xiaodong; Yang, Hao; Dong, Yansheng; Yu, Haiyang

2014-11-01

Production management of winter wheat is more complicated than other crops since its growth period is covered all four seasons and growth environment is very complex with frozen injury, drought, insect or disease injury and others. In traditional irrigation and fertilizer management, agricultural technicians or farmers mainly make decision based on phenology, planting experience to carry out artificial fertilizer and irrigation management. For example, wheat needs more nitrogen fertilizer in jointing and booting stage by experience, then when the wheat grow to the two growth periods, the farmer will fertilize to the wheat whether it needs or not. We developed a spatial decision support system for optimizing irrigation and fertilizer measures based on WebGIS, which monitoring winter wheat growth and soil moisture content by combining a crop model, remote sensing data and wireless sensors data, then reasoning professional management schedule from expert knowledge warehouse. This system is developed by ArcIMS, IDL in server-side and JQuery, Google Maps API, ASP.NET in client-side. All computing tasks are run on server-side, such as computing 11 normal vegetable indexes (NDVI/ NDWI/ NDWI2/ NRI/ NSI/ WI/ G_SWIR/ G_SWIR2/ SPSI/ TVDI/ VSWI) and custom VI of remote sensing image by IDL; while real-time building map configuration file and generating thematic map by ArcIMS.

How experimental biology and ecology can support evidence-based decision-making in conservation: avoiding pitfalls and enabling application.

PubMed

Cooke, Steven J; Birnie-Gauvin, Kim; Lennox, Robert J; Taylor, Jessica J; Rytwinski, Trina; Rummer, Jodie L; Franklin, Craig E; Bennett, Joseph R; Haddaway, Neal R

2017-01-01

Policy development and management decisions should be based upon the best available evidence. In recent years, approaches to evidence synthesis, originating in the medical realm (such as systematic reviews), have been applied to conservation to promote evidence-based conservation and environmental management. Systematic reviews involve a critical appraisal of evidence, but studies that lack the necessary rigour (e.g. experimental, technical and analytical aspects) to justify their conclusions are typically excluded from systematic reviews or down-weighted in terms of their influence. One of the strengths of conservation physiology is the reliance on experimental approaches that help to more clearly establish cause-and-effect relationships. Indeed, experimental biology and ecology have much to offer in terms of building the evidence base that is needed to inform policy and management options related to pressing issues such as enacting endangered species recovery plans or evaluating the effectiveness of conservation interventions. Here, we identify a number of pitfalls that can prevent experimental findings from being relevant to conservation or would lead to their exclusion or down-weighting during critical appraisal in a systematic review. We conclude that conservation physiology is well positioned to support evidence-based conservation, provided that experimental designs are robust and that conservation physiologists understand the nuances associated with informing decision-making processes so that they can be more relevant.

How experimental biology and ecology can support evidence-based decision-making in conservation: avoiding pitfalls and enabling application

PubMed Central

Birnie-Gauvin, Kim; Lennox, Robert J.; Taylor, Jessica J.; Rytwinski, Trina; Rummer, Jodie L.; Franklin, Craig E.; Bennett, Joseph R.; Haddaway, Neal R.

2017-01-01

Abstract Policy development and management decisions should be based upon the best available evidence. In recent years, approaches to evidence synthesis, originating in the medical realm (such as systematic reviews), have been applied to conservation to promote evidence-based conservation and environmental management. Systematic reviews involve a critical appraisal of evidence, but studies that lack the necessary rigour (e.g. experimental, technical and analytical aspects) to justify their conclusions are typically excluded from systematic reviews or down-weighted in terms of their influence. One of the strengths of conservation physiology is the reliance on experimental approaches that help to more clearly establish cause-and-effect relationships. Indeed, experimental biology and ecology have much to offer in terms of building the evidence base that is needed to inform policy and management options related to pressing issues such as enacting endangered species recovery plans or evaluating the effectiveness of conservation interventions. Here, we identify a number of pitfalls that can prevent experimental findings from being relevant to conservation or would lead to their exclusion or down-weighting during critical appraisal in a systematic review. We conclude that conservation physiology is well positioned to support evidence-based conservation, provided that experimental designs are robust and that conservation physiologists understand the nuances associated with informing decision-making processes so that they can be more relevant. PMID:28835842

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.

Building Magnets at Brookhaven National Laboratory: A Condensed Account

NASA Astrophysics Data System (ADS)

Willen, Erich

2017-09-01

The development of superconducting wire and cable in the late twentieth century enabled high-field magnets and thus much higher beam-collision energies in accelerators. These higher collision energies have allowed experimentalists to probe further into the structure of matter at the most fundamental, subatomic level. The behavior of the early universe, where these high energies prevailed, and its evolution over time are the realm their experiments seek to investigate. The subject has aroused the curiosity of the public as well as scientists and has facilitated the support needed to build and operate such expensive machines and experiments. The path forward has not been easy, however. Success in most projects has been mixed with failure, progress with ineptitude. The building of high energy accelerators is mostly a story of capable people doing their best to develop new and unusual technology toward some defined goal, facing both success and failure along the way. It is also a story of administrative imperatives that had unpredictable effects on a project's success, depending mostly on the people in the administrative roles and the decisions that they made.

Building capacity to secure healthier and safer working conditions for healthcare workers: A South African-Canadian collaboration.

PubMed

Yassi, Annalee; Nophale, Letshego E; Dybka, Lyndsay; Bryce, Elizabeth; Kruger, Willem; Spiegel, Jerry

2009-01-01

Healthcare workers face difficult working conditions, particularly where HIV and tuberculosis add to understaffing. Questionnaires, workplace assessments, and discussion groups were conducted at a regional hospital in South Africa to obtain baseline data and input from the workforce in designing interventions. Findings highlighted weaknesses in knowledge, for example regarding the use of N95 respirators and safe handling of sharps, and suggested the need for improved training. Access to supplies and personal protective equipment was the major reported reason for failure to follow proper procedures; this was confirmed by workplace assessments. Discussion groups highlighted the important role for worker Health and Safety Committees (HSC), including in combating stigma and encouraging reporting. Interest in data to support decision-making resulted in development of the Occupational Health and Safety Information System (OHASIS); further training of HSCs is still needed. Multi-stakeholder international collaboration aimed at building HSC capacity is well-received.

Qualitative Description of Spatial Quality in Inclusive Architecture.

PubMed

Ryhl, Camilla; Kajita, Masashi; Sørensen, René

2016-01-01

Universal design (UD) has gained global significance and is in the process of institutionalisation in the Nordic Region. This is despite an urgent necessity for developing the theoretical basis and practical applicability of UD. Reflecting this need for furthering the comprehensive understanding of spatial implication of UD, this paper aims to contribute for articulating a means to assess the quality of UD in architecture. Drawing upon numerous cases from research conducted at the Danish Building Research Institute, the paper focuses on sensory aspects of spatial quality, and discusses as well as reflects an applied method for producing the qualitative description of selected buildings that embody UD through creative solutions. The qualitative description of collected examples appears to be effective in delineating sensory aspects of spatial experience; however the systematic development of assessment criteria is essential in order to support students and designers to make responsible decisions in shaping built environments that are accessible and inclusive but also enjoyable.

Doctors, Lawyers and Advance Care Planning: Time for Innovation to Work Together to Meet Client Needs

PubMed Central

Douglas, Maureen; Simon, Jessica; Fassbender, Konrad

2016-01-01

Health organizations in Canada have invested considerable resources in strategies to improve knowledge and uptake of advance care planning (ACP). Yet barriers persist and many Canadians do not engage in the full range of ACP behaviours, including writing an advance directive and appointing a legally authorized decision-maker. Not engaging effectively in ACP disadvantages patients, their loved ones and their healthcare providers. This article advocates for greater collaboration between health and legal professionals to better support clients in ACP and presents a framework for action to build connections between these typically siloed professions. PMID:28032821

SERVIR Support to NSDI Efforts in Mesoamerica, Africa and the Himalayas

NASA Technical Reports Server (NTRS)

Delgado, Francisco

2014-01-01

SERVIR is a joint effort between NASA, USAID to build or improve capacities in developing regions to help adaptation to climate change by taking advantage of Earth Observation data for decision making. The project began in 2004, in Mesoamerica, partnering with the Central American Commission for Environment and Development(CCAD), the World Bank and CATHALAC. CATHALAC, located in Panama, serves as the regional hub for Mesoamerica since 2005. Two additional regional hubs have been established (in Easters & Western Africa - at RCMRD, Kenya, and The Himalayas- at ICIMOD, Nepal), and two more regional hubs are soon to be launched.

A case of cooperation in the European OR education

NASA Astrophysics Data System (ADS)

Miranda, João; Nagy, Mariana

2011-12-01

European cooperation is a relevant subject that contributes to building a competitive network of high education institutions. A case of teacher mobility on behalf of the Erasmus programme is presented: it considers some Operations Research topics and the development of the Lego on My Decision module. The module considers eight lecture hours in four sessions: (i) the introductory session, to focus on the basics of computational linear algebra, linear programming, integer programming, with computational support (Excel®); (ii) the interim session, to address modelling subjects in a drop by-session; (iii) the advanced session, on the sequence of (i), to consider uncertainty and also how to use multi-criteria decision-making methods; (iv) the final session, to perform the evaluation of learning outcomes. This cooperation at European level is further exploited, including curricula normalisation and adjustments, cultural exchanges and research lines sharing in the idea of promoting the mobility of students and faculty.

Science-policy processes for transboundary water governance.

PubMed

Armitage, Derek; de Loë, Rob C; Morris, Michelle; Edwards, Tom W D; Gerlak, Andrea K; Hall, Roland I; Huitema, Dave; Ison, Ray; Livingstone, David; MacDonald, Glen; Mirumachi, Naho; Plummer, Ryan; Wolfe, Brent B

2015-09-01

In this policy perspective, we outline several conditions to support effective science-policy interaction, with a particular emphasis on improving water governance in transboundary basins. Key conditions include (1) recognizing that science is a crucial but bounded input into water resource decision-making processes; (2) establishing conditions for collaboration and shared commitment among actors; (3) understanding that social or group-learning processes linked to science-policy interaction are enhanced through greater collaboration; (4) accepting that the collaborative production of knowledge about hydrological issues and associated socioeconomic change and institutional responses is essential to build legitimate decision-making processes; and (5) engaging boundary organizations and informal networks of scientists, policy makers, and civil society. We elaborate on these conditions with a diverse set of international examples drawn from a synthesis of our collective experiences in assessing the opportunities and constraints (including the role of power relations) related to governance for water in transboundary settings.

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.