Decision Support Technology Research Articles

Developing Clinical Reasoning Strategies

Incorporating decision support research and technology, such as computerized "best practice" clinical pathways, into patient care management is recommended or decreasing cognitive demands on nurses. Criticized for not representing "real-time" patient care, these standardized approaches may be used in concert with strategies for developing nurses' own clinical reasoning. Real-time clinical information processing activities are offered for staff educators to augment the development of clinical reasoning for both experienced and less-experienced nurses' decision making.

Legislation Aims to Hasten Transition To Electronic Health Information System

Back to table of contents Previous article Next article Government NewsFull AccessLegislation Aims to Hasten Transition To Electronic Health Information SystemChristine LehmannChristine LehmannSearch for more papers by this authorPublished Online:20 Aug 2004https://doi.org/10.1176/pn.39.16.0390008bTwo bills were introduced in Congress last month to expand the use of information technology in the health care system.Rep. Patrick Kennedy: “Structural flaws in our health care system cost tens of thousands of lives and hundreds of billions of dollars each year.”The bill by Sen. Judd Gregg (R-N.H.), chair of the Health, Education, Labor, and Pensions (HELP) Committee, parallels the federal health information technology strategy outlined by Health and Human Services (HHS) Secretary Tommy Thompson last month (Original article: see story above). It establishes federal leadership by creating an Office of Health Information Technology (HIT) within HHS headed by HIT coordinator David Brailer, M.D., Ph.D. It also promotes the development of data standards and implementation, funds incentives, and creates standardized measures of quality of care.The bill that Rep. Patrick Kennedy (D-R.I.) introduced is the Josie King Act (HR 4880), named after an 18-month-old girl who died due to a medical error that was preventable, according to Kennedy's press release.Kennedy announced the legislation in June as the Quality, Efficiency, Standards, and Technology (QUEST) for Healthcare Transformation Act (Psychiatric News, July 16). However, the bill was expanded before it was officially introduced as the Josie King Act in July.The legislation calls for regional electronic networks to enable patients and health care professionals to exchange information in a private and secure manner, according to the release.Kennedy's bill also calls for developing standardized measures of health care professionals' performance and annual public measures that could lead to a new “pay for performance” initiative.The bill also includes these provisions:A new scholarship program to create a cadre of health care leaders with the skills and orientation to promote a “relentless drive for higher quality at lower cost.”The creation of the Center for Clinical Decision-Support Technology, whose mission is to improve the integration of medical knowledge into computerized clinical information systems.Technical assistance for physicians to redesign how they deliver health care to maximize the benefit of new technologies and processes.“Our health care system failed Josie King, as it's failed so many people,” said Kennedy. “As incredible as our medical care can be, structural flaws in our health care system cost tens of thousands of lives and hundred of billions of dollars each year. We can and must do better.”Twenty percent of tests and labs ordered are redundant and avoidable if the results of previous tests were available, the release states. Clinicians use evidence-based medicine only 55 percent of the time, and information technology spending in health care is less than one-third of similar spending in banking, according to the release.S 2710 can be accessed online by searching on the bill number at<http://thomas.loc.gov>. Kennedy's bill, HR 4880, was not online by press time; his press release is posted at<www.house.gov/apps/list/press/ri01_kennedy/pr_040721.html>.▪ ISSUES NewArchived

Intelligent aircraft maintenance support system using genetic algorithms and case-based reasoning

The maintenance of aircraft components is crucial for avoiding aircraft accidents and aviation fatalities. To provide reliable and effective maintenance support, it is important for the airline companies to utilise previous repair experience with the aid of advanced decision support technology. Case-based reasoning (CBR) is a machine learning method that adapts previous similar cases to solve current problems. To effectively retrieve similar aircraft maintenance cases, this research proposes using a CBR system to aid electronic ballast fault diagnosis of Boeing 747-400 airplanes. By employing genetic algorithms (GA) to enhance dynamic weighting and the design of non-similarity functions, the proposed CBR system is able to achieve superior learning performance as compared to those with either equal/varied weights or linear similarity functions.

Expert decision support system use, disuse, and misuse: a study using the theory of planned behavior

Researchers in the past decade have been actively investigating technology use and disuse among conventional and communications technologies. However, recent advancements in expert systems technology has led to new questions about technology use. Where communications technology, such as e-mail or group collaboration software, facilitates co-evolution of problem solving and decision making among people, expert systems create a transaction between user and computer where ultimately, the computer generates the recommended courses of action. This also differs from conventional decision support tools that merely gather information to inform a human decision maker. This empirical study used theory of planned behavior to formulate hypotheses about the use, disuse, and misuse of an expert system decision support (EDSS) technology. It was found that EDSS use was negatively related to errors, whereas misuse of EDSS was positively related to errors. More positive attitudes and social influences led to increased EDSS use, while perceptions of control had no apparent effect. The interaction of social influences and attitudes had a significant non-linear relationship with EDSS misuse.

Current barriers and possible solutions to effective project team formation and deployment within a large construction organisation

The characteristics of the construction industry present an extremely challenging context for effective human resource management (HRM). The dynamic project-based nature of the industry results in extreme fluctuations in organisations’ workloads and requires teams to form, develop and disband relatively quickly. Thus, the importance of efficient management of employee resourcing activities cannot be understated. This paper reports on the findings of research which explored employee resourcing practices within large UK construction firms. The results suggest that managers currently attempt to carry out some strategic planning with regards to employee resourcing, but that this does not necessarily translate into effective operational practice which simultaneously takes account of organisational, project and individual employee needs. A new approach for more effective employee resourcing decision-making, based on encouraging the involvement of the employees in the deployment process, is put forward as a management tool which informs effective team formation and deployment. However, this will require the acceptance of both decision-support technology and of employee input into what is currently a tacit, management-oriented decision process.

The syntax and semantics of the PROforma guideline modeling language

PROforma is an executable process modeling language that has been used successfully to build and deploy a range of decision support systems, guidelines, and other clinical applications. It is one of a number of recent proposals for representing clinical protocols and guidelines in a machine-executable format (see 〈www.openclinical.org〉). In this report, the authors outline the task model for the language and provide an operational semantics for process enactment together with a semantics for expressions, which may be used to query the state of a task during enactment. The operational semantics includes a number of public operations that may be performed on an application by an external agent, including operations that change the values of data items, recommend or make decisions, manage tasks that have been performed, and perform any task state changes that are implied by the current state of the application. Disclosure: PROforma has been used as the basis of a commercial decision support and guideline technology Arezzo (Infermed, London, UK; details in text).

Fuzzy logic and intelligent agents: towards the next step of capital budgeting decision support

The economic life of large investments necessitates constant dynamic managerial actions. To be able to act in an optimal way in the dynamic management of large investments managers need to have constant access to information about the real time situation of the investment, as well as access to up‐to‐date information about changes in the business environment. Looks at how emerging soft computing technologies will help to provide a better support in such a context and then to frame a support system that will make an integrated application of the technologies. Introduces traditional and advanced methods for capital budgeting and investment decision making, then presents a process view of the real option framework based investment management, and develops a holistic framework for an agent‐facilitated capital budgeting system using a fuzzy real option approach. Discusses how intelligent agents can be applied to collect decision information, and to facilitate the integration of foresight information into capital budgeting process, and how the agents can be constructed. Finally, elaborates on the managerial implications of the proposed decision support technology.

Translations of risk: Decision making in a cancer genetics service

This paper reports on the routine decision making practices of health professionals working within a genetics service. Specifically the paper focuses on professionals' assessments of whether patients are at increased risk of inheriting a gene that predisposes the individual to developing cancer. By analysing professionals' talk and actions whilst assessing risk, the paper develops an understanding of both routine and complex decision making. Whilst some decisions were unproblematic, there were a number of situations in which geneticists appear to challenge the decision rules. Such situations occur when faced with a borderline case, an interesting case, when the patient appears particularly anxious or when the rules themselves are judged to be inadequate. Whilst decision support technologies are able to assist clinical decision making they are not relied upon by geneticists above and beyond their own knowledge. Thus, when knowledge is uncertain the decisions that clinicians make are not a consequence of the standard application of scientific protocols but are locally determined according to experience, circumstance and case. This suggests that the transfer of decision support technologies to general practice or to the general public are unlikely to be effective, given the importance of clinical experience to the risk assessment process.

Integrating gis components with knowledge discovery technology for environmental health decision support

This paper presents a new category of decision-support tools that builds on today's Geographic Information Systems ( gis) and On-Line Analytical Processing ( olap) technologies to facilitate Geographic Knowledge Discovery ( gkd). This new category, named Spatial olap ( solap), has been an R&D topic for about 5 years in a few university labs and is now being implemented by early adopters in different fields, including public health where it provides numerous advantages. In this paper, we present an example of a solap application in the field of environmental health: the ICEM-SE project. After having presented this example, we describe the design of this system and explain how it provides fast and easy access to the detailed and aggregated data that are needed for gkd and decision-making in public health. The solap concept is also described and a comparison is made with traditional gis applications.

The propensity of liquid phases forming during coal-opportunity fuel (biomass) cofiring as a function of ash chemistry and temperature : Miller, S. F. et al. Proceedings of the International Technical Conference on Coal Utilization & Fuel Systems, 2002, 1, (27), 465–475

Crop phenology is fundamental for understanding crop growth and development, and increasingly influences many agricultural management practices. Water deficits are one environmental factor that can influence crop phenology through shortening or lengthening the developmental phase, yet the phenological responses to water deficits have rarely been quantified. The objective of this paper is to provide an overview of a decision support technology software tool, PhenologyMMS V1.2, developed to simulate the phenology of various crops for varying levels of soil water. The program is intended to be simple to use, requires minimal information for calibration, and can be incorporated into other crop simulation models. It consists of a Java interface connected to FORTRAN science modules to simulate phenological responses. The complete developmental sequence of the shoot apex correlated with phenological events, and the response to soil water availability for winter and spring wheat (Triticum aestivum L.), winter and spring barley (Hordeum vulgare L.), corn (Zea mays L.), sorghum (Sorghum bicolor L.), proso millet (Panicum milaceum L.), hay/foxtail millet [Setaria italica (L.) P. Beauv.], and sunflower (Helianthus annus L.) were created based on experimental data and the literature. Model evaluation consisted of testing algorithms using “generic” default phenology parameters for wheat (i.e., no calibration for specific cultivars was used) for a variety of field experiments to predict developmental events. Results demonstrated that the program has general applicability for predicting crop phenology and can aid in crop management.

Developments in decision technologies

Progress in information and decision technology is allowing increasingly complex organisational problems to become structured and tamed. While decision technology is constantly improving, we report on current research which provides a view of important developments in the field. Advances in decision support, decision methodologies and implementation technologies are discussed.

The Impact of Expert Decision Support Systems on the Performance of New Employees

Decision support technology, expert systems, executives information systems, and artificial neural networks have been reported to be useful tools to enhance the performance of managers as they helped them to gain more knowledge, experiences, and expertise and consequently enhance the quality of the decision making. They can also be used as a training tool to transfer the knowledge of the expert to middle and top management and thus improve the performance of new employees. This communication reports the conclusions of a study conducted to verify the impact of the use of the EDSS technology (expert decision support systems) on the performance and satisfaction of new employees in the business world. A laboratory experiment using the control groups and the treatment groups was held to test the research model. The results indicate that EDSS technologies do have a positive impact on the performance of the users.

Potential uses for geographic information system-based planning and decision support technology in intensive food animal production.

Although geographic information systems (GIS) have been used in many disciplines, the available technology in planning and decision support has only recently begun to be used in intensive animal production, in areas such as confined animal feeding operations. GIS-based planning and decision support systems have the potential to enhance many aspects of intensive animal production, such as disease monitoring and prevention, emergency management and nutrient waste disposal. Current uses of GIS in animal production are reviewed. Potential uses are illustrated using the example of the poultry industry on the Delmarva Peninsula, USA.

Decision support, learning and rural resource management

Decision support technologies and paradigms have their origins in management and information sciences but have been widely proposed as providing a basis for improving management for sustainability rural resource management. As such, they provide a means of helping managers to deal with increased information, increasingly complex decisions and to professionalise their activities. However, decision support has, in practice, had limited impact in many rural resource management contexts. Failures can be attributed to non-delivery, non-adoption and to unexpected negative impacts where they are adopted. This paper proposes a response to these challenges by reappraising the role of decision support and proposing a generic framework for the implementation of decision support as a broader initiative than the development of a decision support output, and one that aims to foster learning and co-learning.

Emerging paradigms of cognition in medical decision-making

The limitations of the classical or traditional paradigm of decision research are increasingly apparent, even though there has been a substantial body of empirical research on medical decision-making over the past 40 years. As decision-support technology continues to proliferate in medical settings, it is imperative that “basic science” decision research develop a broader-based and more valid foundation for the study of medical decision-making as it occurs in the natural setting. This paper critically reviews both traditional and recent approaches to medical decision making, considering the integration of problem-solving and decision-making research paradigms, the role of conceptual knowledge in decision-making, and the emerging paradigm of naturalistic decision-making. We also provide an examination of technology-mediated decision-making. Expanding the scope of decision research will better enable us to understand optimal decision processes, suitable coping mechanisms under suboptimal conditions, the development of expertise in decision-making, and ways in which decision-support technology can successfully mediate decision processes.

Past, present, and future of decision support technology

Since the early 1970s, decision support systems (DSS) technology and applications have evolved significantly. Many technological and organizational developments have exerted an impact on this evolution. DSS once utilized more limited database, modeling, and user interface functionality, but technological innovations have enabled far more powerful DSS functionality. DSS once supported individual decision-makers, but later DSS technologies were applied to workgroups or teams, especially virtual teams. The advent of the Web has enabled inter-organizational decision support systems, and has given rise to numerous new applications of existing technology as well as many new decision support technologies themselves. It seems likely that mobile tools, mobile e-services, and wireless Internet protocols will mark the next major set of developments in DSS. This paper discusses the evolution of DSS technologies and issues related to DSS definition, application, and impact. It then presents four powerful decision support tools, including data warehouses, OLAP, data mining, and Web-based DSS. Issues in the field of collaborative support systems and virtual teams are presented. This paper also describes the state of the art of optimization-based decision support and active decision support for the next millennium. Finally, some implications for the future of the field are discussed.

Community coronary units: strategies to promote pre-hospital thrombolysis.

Early diagnosis and the early delivery of pre-hospital thrombolysis in cases of acute myocardial infarction (AMI) have been shown to decrease mortality. Despite strong evidence of its benefits, pre-hospital thrombolysis rates are still worryingly low. The challenge is to empower community practitioners to deliver thrombolysis. In the Grampian region there is a network of community hospitals which have been equipped with both videoconferencing and remote telemetry equipment. This allows realtime consultation with the local accident and emergency department and coronary care unit. Early trials of the system show that clinical information can be viewed in realtime, with transfer of a 12-lead electrocardiogram at 60 s intervals. This will give general practitioners unprecedented access to specialist advice. Our aim is to use a combination of teaching and decision support technology to ensure that all patients with AMI have the opportunity to access timely and appropriate prehospital thrombolysis.

Sprawl decisions: A simulation and decision support tool for citizens and policy makers

This paper describes a project, and computer application of the same name, called Sprawl Decisions. The purpose of Sprawl Decisions is to design, build, and test (in both laboratory and real-world settings) simulations and decision support technologies to overcome perceptual, social-psychological, organizational, and technological barriers to achieving effective urban design and environmental negotiations and decisions. The key goal of the project is to develop decision support technologies that can assist citizens to be more knowledgeable and effective spokespersons for their interests in a sustainable built environment. A prototype application that links land use planning choices with cost estimations, and environmental, resource, and visual impacts is described.

Implications of buyer decision theory for design of e-commerce websites

In the rush to open their website, e-commerce sites too often fail to support buyer decision-making and search, resulting in a loss of sale and the customer's repeat business. This paper reviews why this occurs and the failure of many B2C and B2B website executives to understand that appropriate decision support and search technology cannot be fully bought off-the-shelf. Our contention is that significant investment and effort is required at any given website in order to create the decision support and search agents needed to properly support buyer decision-making. We provide a framework to guide such effort (derived from buyer behavior choice theory); review the open problems that e-catalog sites pose to the framework and to existing search engine technology; discuss underlying design principles and guidelines; validate the framework and guidelines with a case study; and discuss lessons learned and steps needed to better support buyer decision behavior in the future. Future needs are also pinpointed.

Knowledge Management Technology for Decision Support: an empirical examination

This paper reports the results of an empirical examination of the effectiveness of one type of knowledge management technology, namely 'contextual knowledge repository', for supporting individual decision makers in a predictive judgement task context. 31 volunteer subjects participated in the study. The results indicate that a given technology was fairly useful, but insufficient to maximally enhance individual decision making. On one hand, subjects were found to extract more knowledge and make significantly smaller decision errors than their notional naive counterparts. On the other hand, subjects tended to extract less knowledge and make significantly larger decision errors compared to notional optimal counterparts. These findings suggest that individuals could potentially benefit from those knowledge management technologies that would provide additional explicit analytical and procedural knowledge, or those that would facilitate sharing of tacit knowledge through interaction with others. Future research is necessary to address these issues.