Integration of decision support systems to improve decision support performance

Decision support system (DSS) is a well-established research and development area. Traditional isolated, stand-alone DSS has been recently facing new challenges. In order to improve the performance of DSS to meet the challenges, research has been actively carried out to develop integrated decision support systems (IDSS). This paper reviews the current research efforts with regard to the development of IDSS. The focus of the paper is on the integration aspect for IDSS through multiple perspectives, and the technologies that support this integration. More than 100 papers and software systems are discussed. Current research efforts and the development status of IDSS are explained, compared and classified. In addition, future trends and challenges in integration are outlined. The paper concludes that by addressing integration, better support will be provided to decision makers, with the expectation of both better decisions and improved decision making processes

Spatial analysis, decision support systems (DSS) and land use design: the case-study of antique viability system in San Martino valley (Lombardy, Italy)

This paper concerns the development of a Decision Support System (DSS), which is a system able to support temporal and spatial choices about land use design, in order to project and manage the antique viability system in San Martino valley (located in Lombardy, Italy) The main purpose is providing to a project manager necessary information to help him to understand problems (in particular concerning the spatial system of viability), therefore assists him to analyze the question from different points of view. This process needs a particular informative architecture, based on a complex and relational structured system (DSS) able to produce response for the whole decision process. The DSS is interfaced with a GIS in order to manage cartography and alphanumeric files with geo-referenced data. It works on information which are supposed to be indispensable for the planners of the San Martino valley.

Toward a Maturity Model for DSS Development Processes

Despite recent progress with Decision support systems (DSS) development methodologies, a gap still exist in terms of theability to assess the maturity of an organization with respect to its DSS development process. A need exist to be able todescribe DSS development processes at a meta-level. Equally important is the ability to provide organization withprescriptions to increase the maturity of their DSS development processes.In this paper, we propose a Decision Support System Maturity Model (DSS-MM). The model draws on extant literaturerelated to DSS development methodologies, practices and processes to identify pertinent DSS development practices anddefine maturity models for these practices. From a theoretical perspective, this research presents the first maturity modelspecifically targeting DSS development. From a practical perspective, the model provides a framework for organizations toassess their DSS development maturity level and devise process improvement initiatives to address any limitations withexisting practices

Designing an automated clinical decision support system to match clinical practice guidelines for opioid therapy for chronic pain

Abstract Background Opioid prescribing for chronic pain is common and controversial, but recommended clinical practices are followed inconsistently in many clinical settings. Strategies for increasing adherence to clinical practice guideline recommendations are needed to increase effectiveness and reduce negative consequences of opioid prescribing in chronic pain patients. Methods Here we describe the process and outcomes of a project to operationalize the 2003 VA/DOD Clinical Practice Guideline for Opioid Therapy for Chronic Non-Cancer Pain into a computerized decision support system (DSS) to encourage good opioid prescribing practices during primary care visits. We based the DSS on the existing ATHENA-DSS. We used an iterative process of design, testing, and revision of the DSS by a diverse team including guideline authors, medical informatics experts, clinical content experts, and end-users to convert the written clinical practice guideline into a computable algorithm to generate patient-specific recommendations for care based upon existing information in the electronic medical record (EMR), and a set of clinical tools. Results The iterative revision process identified numerous and varied problems with the initially designed system despite diverse expert participation in the design process. The process of operationalizing the guideline identified areas in which the guideline was vague, left decisions to clinical judgment, or required clarification of detail to insure safe clinical implementation. The revisions led to workable solutions to problems, defined the limits of the DSS and its utility in clinical practice, improved integration into clinical workflow, and improved the clarity and accuracy of system recommendations and tools. Conclusions Use of this iterative process led to development of a multifunctional DSS that met the approval of the clinical practice guideline authors, content experts, and clinicians involved in testing. The process and experiences described provide a model for development of other DSSs that translate written guidelines into actionable, real-time clinical recommendations.http://deepblue.lib.umich.edu/bitstream/2027.42/78267/1/1748-5908-5-26.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78267/2/1748-5908-5-26.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/78267/3/1748-5908-5-26-S3.TIFFhttp://deepblue.lib.umich.edu/bitstream/2027.42/78267/4/1748-5908-5-26-S2.TIFFhttp://deepblue.lib.umich.edu/bitstream/2027.42/78267/5/1748-5908-5-26-S1.TIFFPeer Reviewe

A new model for the development of information systems

The most commonly used systems specification and design techniques in commercial computing are described and compared; Information Engineering as proposed by James Martin, A Framework for Information Definition-Muitiview proposed by Wood-Harper et al, Real-world Modeling as described by Jackson, Structured Analysis and Design as In Demarco, Yourdon and Constantine and Output-Oriented Structured Requirement Definition proposed by Orr. In addition, system prototyping is discussed, including the role of prototyping in large software development projects and as a tool for the design of human-computer interfaces. Other areas described and discussed include decision support systems (DSS) and knowledge based management support systems. The context is in the design and development approaches for DSS, prototyping for DSS, expert system for DSS and the integration of DSS and information system. The design and development of human-computer interface is also discussed in relation to user Interface complexity and adaptive interfaces. Further, the important issue of user involvement and support within the development process Is discussed. Thus, weaknesses of current approaches to the system development process are identified and a new model for the development of information system is proposed. In proposing the model, data and functional analysis structured method and methodology for decision support systems (DSS) development is presented including guidelines for the development of knowledge based DSS. The new proposed model is put to test in the design, development and implementation of large integrated commercial systems including DSS. Results and discussion on the use of the model is reported with special consideration to the users' and developers' view of the model. Finally the objectives of this research program are examined in relation to what has been achieved during this program of research. The prospect of using the model for the development of information systems are concluded with references to current and future goals

A knowledge-based decision support system for payload scheduling

This paper presents the development of a prototype Knowledge-based Decision Support System, currently under development, for scheduling payloads/experiments on space station missions. The DSS is being built on Symbolics, a Lisp machine, using KEE, a commercial knowledge engineering tool

System evaluation for a decision support system

System evaluation is a necessary step in system development process to measure the successfulness of a system. However, this step has often been overlooked by system developers during the development process. This study aimed to discuss several system evaluations for Decision Support Systems (DSSs) and to explain the methodology used to evaluate a DSS model. In this study, a DSS model has been developed to assist decision makers to select an appropriate tree species to be planted for commercial tree planting. Based on few literatures, eight usability factors (efficiency, understandability, operability, attractiveness, error prevention, learnability, accuracy and effectiveness) have been identified for the evaluation process. The results present the usability level for each factor and indicated the tested DSS model is in the excellent level. It is anticipated that system developers can improve the DSS based on these findings as well as from the comments and suggestions made by the respondents

Aspects of automation of selective cleaning

Cleaning (pre-commercial thinning) is a silvicultural operation, primarily used to improve growing conditions of remaining trees in young stands (ca. 3 - 5 m of height). Cleaning costs are considered high in Sweden and the work is laborious. Selective cleaning with autonomous artificial agents (robots) may rationalise the work, but requires new knowledge. This thesis aims to analyse key issues regarding automation of cleaning; suggesting general solutions and focusing on automatic selection of main-stems. The essential requests put on cleaning robots are to render acceptable results and to be cost competitive. They must be safe and be able to operate independently and unattended for several hours in a dynamic and non-deterministic environment. Machine vision, radar, and laser scanners are promising techniques for obstacle avoidance, tree identification, and tool control. Horizontal laser scannings were made, demonstrating the possibility to find stems and make estimations regarding their height and diameter. Knowledge regarding stem selections was retrieved through qualitative interviews with persons performing cleaning. They consider similar attributes of trees, and these findings and current cleaning manuals were used in combination with a field inventory in the development of a decision support system (DSS). The DSS selects stems by the attributes species, position, diameter, and damage. It was used to run computer-based simulations in a variety of young forests. A general follow-up showed that the DSS produced acceptable results. The DSS was further evaluated by comparing its selections with those made by experienced cleaners, and by a test in which laymen performed cleanings following the system. The DSS seems to be useful and flexible, since it can be adjusted in accordance with the cleaners’ results. The laymen’s results implied that the DSS is robust and that it could be used as a training tool. Using the DSS in automatic, or semi-automatic, cleaning operations should be possible if and when selected attributes can be automatically perceived. A suitable base-machine and thorough research, regarding e.g. safety, obstacle avoidance, and target identification, is needed to develop competitive robots. However, using the DSS as a training-tool for inexperienced cleaners could be an interesting option as of today

A system dynamics-based simulation study for managing clinical governance and pathways in a hospital

This paper examines the development of clinical pathways in a hospital in Australia based on empirical clinical data of patient episodes. A system dynamics (SD)-based decision support system (DSS) is developed and analyzed for this purpose. System dynamics was used as the simulation modeling tool because of its rigorous approach in capturing interrelationships among variables and in handling dynamic aspects of the system behavior in managing healthcare. The study highlights the scenarios that will help hospital administrators to redistribute caseloads amongst admitting clinicians with a focus on multiple Diagnostic Related Groups (DRG’s) as the means to improve the patient turnaround and hospital throughput without compromising quality patient care. DRG’s are the best known classification system used in a casemix funding model. The classification system groups inpatient stays into clinically meaningful categories of similar levels of complexity that consume similar amounts of resources. Policy explorations reveal various combinations of the dominant policies that hospital management can adopt. The analyses act as a scratch pad for the executives as they understand what can be feasibly achieved by the implementation of clinical pathways given a number of constraints. With the use of visual interfaces, executives can manipulate the DSS to test various scenarios. Experimental evidence based on focus groups demonstrated that the DSS can enhance group learning processes and improve decision making. The simulation model findings support recent studies of CP implementation on various DRG’s published in the medical literature. These studies showed substantial reductions in length of stay, costs and resource utilization

Teaching Tip: Improving Student Performance by Introducing a No-Code Approach: A Course Unit of Decision Support Systems

No-code/low-code app development is transforming traditional information system development paradigms. This teaching tip uses an example of course unit of decision support systems (DSS) to demonstrate that introducing no-code system implementation assignments into a course as a replacement for computer programming language exercises can improve student learning. It presents the pedagogical design and the teaching method of no-code DSS implementation. The contents of the pedagogy include key concepts of no-code development, workshops of no-code DSS implementation, and assignments for students. This course unit demands about one-third-credit-hour workload, and can be embedded in a three-credit-hour business course. The preliminary evidence has indicated that the teaching method of no-code DSS implementation is useful for business students