Advances in Methodology and Applications of Decision Support Systems

These Proceedings are composed of a selection of papers of the Workshop on Advances in Methodology and Applications of Decision Support Systems, organized by the System and Decision Sciences (SDS) Program of IIASA and the Japan Institute of Systems Research (JISR). The workshop was held at IIASA on August 20-22, 1990. The Methodology of Decision Analysis (MDA) Project of the SDS Program focuses on a system-analytical approach to decision support and is devoted to developing methodology, software and applications of decision support systems concentrated primarily around interactive systems for data analysis, interpretation and multiobjective decisionmaking, including uncertainty analysis and group decision making situations in both their cooperative and noncooperative aspects. The objectives of the research on decision support systems (DSS) performed in cooperation with the MDA Project are to: compare various approaches to decision support systems; advance theory and methodology of decision support; convert existing theories and methodologies into usable (simple to use, user-friendly and robust) tools that could easily be used in solving real-life problems. A principal characteristic of decision support systems is that they must be tuned to specific decision situations, to complex real-life characteristics of every application. Even if the theory and methodology of decision support is quite advanced, every application might provide impulses for further theoretical and methodological advances. Therefore the principle underlying this project is that theoretical and methodological research should be strongly connected to the implementation and applications of its results to sufficiently complicated, real-life examples. This approach results in obtaining really applicable working tools for decision support. The papers for this Proceedings have been selected according to the above summarized framework of the research activities. Therefore, the papers deal both with theoretical and methodological problems and with real-life applications

Considerations in development of expert systems for real-time space applications

Over the years, demand on space systems has increased tremendously and this trend will continue for the near future. Enhanced capabilities of space systems, however, can only be met with increased complexity and sophistication of onboard and ground systems. Artificial Intelligence and expert system techniques have great potential in space applications. Expert systems could facilitate autonomous decision making, improve in-orbit fault diagnosis and repair, enhance performance and reduce reliance on ground support. However, real-time expert systems, unlike conventional off-line consultative systems, have to satisfy certain special stringent requirements before they could be used for onboard space applications. Challenging and interesting new environments are faced while developing expert system space applications. This paper discusses the special characteristics, requirements and typical life cycle issues for onboard expert systems. Further, it also describes considerations in design, development, and implementation which are particularly important to real-time expert systems for space applications

HMM-based decision model for smart home environment

The smart home environment typically includes various systems with high level of heterogeneity characteristics. Smart home environment are configured in such a way that it comfort driven as well as achieving optimized security and task-oriented without human intervention inside the home. Smart home environment contain diversified systems ranging from entertainment to automation like devices that is heterogeneous in nature. For the reason that of systems heterogeneity, it is frequently challenging to execute interoperation around them and realize desired services preferred by the home occupants. The interoperation complexity stands at the bottleneck in ensuring various tasks executed jointly among diversified systems in smart home environment. In this paper, we present a Hidden-Markov Model (HMM) based decision model for smart home environment by providing decision support ability. The implementation has been carried out in such a way that quality information is acquired among the systems to demonstrate the effectiveness of interoperability among them. This proposed decision model is tested and proven that there is an elevated amount of reliability on this decision model in the smart home setting

Particularities of Solving the Problems of Support for Managerial Decision Making in Production and Economic Systems Using the Statistical Data

The subject of this paper is the decision making processes in production and economic systems conditioned by implementation of goods innovation projects as well as economic and mathematical models and methods of managing the processes. The research object viewed in the paper is the construction of models of goods innovation projects implementation and the ways of implementation thereof based on the mathematical apparatus and statistical data. The paper discusses a method of constructing the models of support for managerial decision making in production and economic systems and working with them based on simulation and mathematical programming methods. The task of selecting the production and economic systems for implementation of projects as well as of forming the production and economic system portfolios is worded in general. The author also pays attention to the questions of designing and using the information systems based on simulation approaches for supporting the decision making, studying the goods innovation projects at various development stages, and the production and economic systems implementing them. A method of forming and transferring data is suggested the implementation of which will allow solving the tasks of support for decision making in production and economic systems based on statistical data and criterial methods as well as perform risk assessment and measure the sensitivity of the results obtained to changing characteristics of the projects and the influence of the environment. Keywords: decision making support; mathematical programming; volume scheduling; innovation project; production and economic system; data processing; statistical data. JEL Classifications: C44, C55, C63, C8

Developing a Prototype System for Integrating Pharmacogenomics Findings into Clinical Practice

Findings from pharmacogenomics (PGx) studies have the potential to be applied to individualize drug therapy to improve efficacy and reduce adverse drug events. Researchers have identified factors influencing uptake of genomics in medicine, but little is known about the specific technical barriers to incorporating PGx into existing clinical frameworks. We present the design and development of a prototype PGx clinical decision support (CDS) system that builds on existing clinical infrastructure and incorporates semi-active and active CDS. Informing this work, we updated previous evaluations of PGx knowledge characteristics, and of how the CDS capabilities of three local clinical systems align with data and functional requirements for PGx CDS. We summarize characteristics of PGx knowledge and technical needs for implementing PGx CDS within existing clinical frameworks. PGx decision support rules derived from FDA drug labels primarily involve drug metabolizing genes, vary in maturity, and the majority support the post-analytic phase of genetic testing. Computerized provider order entry capabilities are key functional requirements for PGx CDS and were best supported by one of the three systems we evaluated. We identified two technical needs when building on this system, the need for (1) new or existing standards for data exchange to connect clinical data to PGx knowledge, and (2) a method for implementing semi-active CDS. Our analyses enhance our understanding of principles for designing and implementing CDS for drug therapy individualization and our current understanding of PGx characteristics in a clinical context. Characteristics of PGx knowledge and capabilities of current clinical systems can help govern decisions about CDS implementation, and can help guide decisions made by groups that develop and maintain knowledge resources such that delivery of content for clinical care is supported

AN ONTOLOGICAL ANALYSIS OF SOME FUNDAMENTAL INFORMATION SYSTEMS CONCEPTS

This paper describes how ontological concepts can be used to model information systems. We view an information system as an object that is independent of its use or its technology of implementation. The main premise of the model is that an information system is a representation of a real-world system, and as such it should possess certain characteristics, We show how the model can be used to define various concepts such as real-time, batch, data processing, management reporting, decision support, controls, and decomposition. Furthermore, we show how the model may serve as the foundation of a theory of systems analysis and design. In particular, it provides a formal definition of information systems specifications and a normative model of decomposition

Considerations in development of expert systems for real-time space applications

Over the years demand on space systems have been increased tremendously and this trend will continue for the near future. The enhanced capabilities of space systems, however, can only be met with increased complexity and sophistication of onboard and ground systems, and artificial intelligence and expert system concepts have a significant role in space applications. Expert systems could facilitate decision making, improved fault diagnosis and repair, enhanced performance and less reliance on ground support. However, some requirements have to be fulfilled before practical use of flight-worthy expert systems for onboard (and ground) operations. This paper discusses some of the characteristics and important considerations in design, development, implementation and use of expert systems for real-life space applications. Further, it describes a typical life cycle of expert system development and its usage

A Contingency Model Of Dss Success: An Empirical Investigation

The importance of contingent relationships between variables influencing MIS implementations has often been emphasized. This study tests ten propositions regarding the contingent relationships influencing the implementation of a certain class of information systems, generally called Decision Support Systems (DSS). These propositions are derived from a contingency framework that groups the variables relevant to DSS implementations into four categories. These are the characteristics of: the decision maker/user, the DSS, the decision environment, and the implementation process. It is posited that the successful implementation of DSS depends not only on the direct effects of variables in each category, but also on the overall fit between these variables. DSS implementation success is defined as high user satisfaction and system usage.;Based on the proposed framework, ten propositions regarding specific contingent or fit relationships between variable pairs from the four categories of the framework are suggested. Defined as multiplicative effects between the variable pairs concerned, the propositions were tested in a field survey of DSS in 9 organizations from the insurance, banking, and utility industries.;The results of the study indicate that multiplicative effects do not account for a significant portion of the observed variance in the three dependent variables, over and above the portion accounted for by the main effects. The results also show that the main effect variable, DSS flexibility, accounts for nearly half the observed variance in user information satisfaction. These results and the fact that a relatively high proportion of the variance in the three dependent variables was accounted by the main effect variables DSS flexibility, decision maker/user willingness to change, and involvement in implementation, leads to the conclusion that, for DSS implementations, multiplicative effects are unimportant. On the other hand, DSS flexibility appears as a primary consideration to keep in mind in implementing DSS

Understanding end-user support for health information technology: a theoretical framework

Background Support is often considered an important factor for successful implementation and realising the benefits of health information technology (HIT); however, there is a dearth of research on support and theoretical frameworks to characterise it. Objective To develop and present a comprehensive, holistic, framework for characterising enduser support that can be applied to various settings and types of information systems. Method Scoping review of the medical informatics and information systems literature. Results A theoretical framework of end-user support is presented. It includes the following facets: support source, location of support, support activities, and perceived characteristics of support and support personnel. Conclusion The proposed framework may be a useful tool for describing and characterising enduser support for HIT. it may also be used by decision makers and implementation leaders for planning purposes

Information Systems and Healthcare XX: Toward Seamless Healthcare with Software Agents

Healthcare processes are frequently fragmented and often badly supported with IT. Inter- and intra-organizational communication and media frictions complicate the continuous provision of information according to the principle of information logistics. Based on extensive literature review, we present the vision of seamless healthcare with horizontally and vertically integrated healthcare processes enabled by seamless IT support. Its implementation requires the establishment of a communication infrastructure and the deployment of adequate standards in healthcare. There are already comprehensive approaches for dealing with integrating heterogeneous information systems. However, they lack a common communication infrastructure and do not support proactivity and flexibility which are dominant characteristics in healthcare. We propose a software agent-based approach for realizing the vision of seamless healthcare. We present a corresponding implementation for integrating heterogeneous information systems in the context of the German Health Telematics Infrastructure. Based on the concept and the implementation, we show that the modular approach is capable of supporting a wide range of different applications. We furthermore outline which facets of an agent-based solution could be implemented in an operative real-world environment. In closing we derive implications for IT decision makers in healthcare and show directions for future approaches for reducing information logistics related deficits in healthcare