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Results for “Decision Support Systems, Management”

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At least 19 recordsLinked to original sources
PubMed1995

Business modeling tools for managing decision support systems.

We sought to investigate the role of business modeling tools in facilitating the implementation of interactive decision support systems (DSS) for laboratory test ordering. We have recently shown that Ripple Down Rules (RDR), a new strategy for building expert systems (ES), enables institutions to build DSS maintained by local experts without knowledge engineering support. While DSS hold great promise for improving health outcomes by providing doctors with timely access to care guidelines, implementation will require careful planning and change management. The Situated, Strategic, and AI-Enhanced method was used to define and assess a DSS-driven process change. DECmodelTM, a graphical business modeling application, was used to build representations of current (paper-based) and future (ES-supported) test ordering environments. Models described both the interactions between new processes and the impact on healthcare quality of ES-supported DSS. Models were able to represent the key processes involved in test ordering and the impact of DSS. Users could interact with the model to examine the time and cost implications of the transition from current to future states. The level of detail in which processes could be examined was readily controlled by the user. We have shown that graphical business modeling applications are useful tools for enabling institutions to view the impact of DSS. Accuracy of models should be maximized in workshops involving key management personnel. Whilst the impact of modeling on the cost and quality of DSS implementation remains to be established, we believe these tools are valuable for institutions planning to align DSS technologies to their service needs.

Australia↗
PubMedDate not supplied

INFORM: development of information management and decision support systems for High Dependency Environments.

The long-term aim in the INFORM Project is to develop, evaluate and implement a new generation of Information Systems for hospital High Dependency Environments (HDE-Intensive Care Units, Neonatal Units, Burns Units. Operating and Recovery Rooms, and other specialised areas). The distinguishing feature of the HDE is the very large amount of data that is collected through monitors and paper records about the state of critically ill patients; this has made the role of the staff a technical one in addition to a caring one. The INFORM System will integrate Decision Support with on-line, off-line and observed patient data and, in addition, will incorporate and integrate unit management features. In the Exploratory Phase of the Project, functional requirements have been set out. These are based on four components: conceptual model of the HDE; evaluation of existing HDE Information Systems; development of a novel software architecture using a Knowledge-Based Systems (KBS) methodology, and based on a critical review of KBS applied to the HDE: monitoring of appropriate leading-edge technological developments. The conceptual model has two components: a patient-related information model, and a department-related cost model. The patient-related model is identifying key and difficult areas of decision making. A key aspect of INFORM is integration of clinical Decision Support for these areas into the Information System through a layered software architecture. The lower layers are concerned with monitoring and alarming and the higher levels with patient assessment and therapy planning. The functionality and interconnection of these layers are being determined.

Decision Support Systems, Management↗
PubMed1994

Integration of data driven decision support into the HELIOS environment.

The development of large-scale, clinically accepted decision support systems (DSS) calls for powerful and commonly available methods and tools for knowledge acquisition, system realisation, and knowledge base maintenance. The paper addresses problems associated with the integration of knowledge-based systems within the clinical setting with special reference to (i) data driven decision support, (ii) the Arden Syntax as a knowledge representation format and, (iii) the HELIOS software engineering environment. Architecture of a DSS based on Arden Syntax and its integration in the HELIOS environment are presented. Realisation of the DSS is discussed in relation to client-server architecture and object-oriented databases, which are essential concepts of the HELIOS environment. Sharability and reusability of the knowledge, together with commonality of used software tools are also discussed.

Database Management Systems↗
PubMed1995

The Philippine management information system for public health programs, vital statistics, mortality and notifiable diseases.

Strengthening the information support for decision making has been identified as an important first step toward improving the efficiency, effectiveness, and equitability of the health care system in the Philippines. A Philippine-German Cooperation is in partnership toward developing a need-responsive and cost-effective Health and Management Information System (HAMIS). Four information baskets are being strengthened specifically to address these needs in a cost-effective way: public health information systems, hospital information systems, information systems on economics and financing, information systems on good health care management. BLACKBOX is the management information system for public health programs, vital statistics, mortality and notifiable diseases of the Philippines. It handles and retrieves all data that is being collected by public health workers routinely all over the Philippines. The eventual aim of BLACKBOX is to encourage the development of an information culture in which health managers actively utilise information for rational planning and decision making for a knowledge based health care delivery.

Cost-Benefit Analysis↗
PubMed1991

INFORM: integrated support for decisions and activities in intensive care.

Many medical decision support systems that have been developed in the past have failed to enter routine clinical practice. Often this is because the developers have failed to analyse in sufficient detail the precise user requirements, because they have produced a system which takes too narrow a view of the patient, or because the decision support facilities have not been sufficiently well integrated into the routine clinical data handling activities. In this paper we discuss how the AIM-INFORM project is setting out to deal with these issues, in the context of the provision of decision support in the intensive care unit.

Artificial Intelligence↗
PubMed1993

Towards a statistically oriented decision support system for the management of septicaemia.

The first decision-support system designed for the management of septicaemia was MYCIN. Although MYCIN played a vital role in the conception of knowledge-based systems, it never became an established clinical system. This paper describes an alternative decision-support system for septicaemia management currently under development at St. Thomas' Hospital (London) where a large database of septicaemia episodes has been compiled. The three statistical approaches that have been considered are described. These are (i) relative frequencies, (ii) the naive Bayes method and (iii) logistic regression. We also discuss how the concept of probabilistic influence diagrams could be of benefit to the development and implementation of the decision-support system.

Adult↗
PubMed1989

Advanced Multi-Attribute Scoring Technique (AMAST): a model scoring methodology for the request for proposal (RFP).

The continued demand for more efficient and functionally rich automated systems will force health care facilities into a changing and complex marketplace. As the Request for Proposal (RFP) will be the key document in the systems acquisition process, it is imperative that a systematic process must be established to evaluate the vast array of data collected. It is suggested in this paper that the effective application of the Advanced Multi-Attribute Scoring Technique (AMAST) will assist in this process, enhance the decision making process and reduce the risk associated with systems development and procurement.

Competitive Bidding↗
PubMedDate not supplied

Developing decision support systems: a change in emphasis.

Against a backdrop of many demonstrably proficient expert systems that are not routinely used, and a user community that is skeptical of the benefits of using such technology in healthcare, the AIM funded Dilemma project is attempting to introduce decision support technology into shared care environments within scenarios from the specialties of oncology and cardiology. This paper outlines the experiences of one work-package of the Dilemma project which is concerned with the development of applications with a decision support component for use in shared care of coronary artery disease patients. We suggest reasons why expert systems have failed to gain acceptance in the past, and conclude that a shift in emphasis from building expert systems to building clinically useful applications that have an expert system component may improve the chances of acceptance of this technology in the future.

Coronary Disease↗
PubMedDate not supplied

An object oriented decision support system for the planning of health resource allocation.

The health resource allocation problem is discussed in this paper. An object-oriented system, which consists of two parts is proposed and its implemented prototype is illustrated. The first part consists of a Geographical Information System which is able to acquire and store both geographical information regarding the territory under investigation and the socio-epidemiological information and the resource distribution in that moment on the same territory. The second part refers to the strategies and the relative algorithms carried out (using a Decision Support System) to obtain the best solution (allocation of new resources optimizing the cost/benefit ratio) after that the user has fixed a goal (e.g., the decrease of the incidence of a given disease) and has defined some constraints (e.g., a fixed budget, a given set of available resources, etc.). The object-oriented database stores different scenarios, depending on the different goals and constraints defined in input. A user friendly interface was also implemented.

Decision Making, Computer-Assisted↗
PubMed1993

Integrated clinical decision support using an object-oriented database management system.

Clinical decision support systems assist in diagnosis, alert to abnormal conditions, and manage patient data. Such systems tend to emphasize one of these features at the expense of the others and tend to be developed on an ad hoc basis. In this work, a technique is developed for creating an integrated clinical decision support system wholly within a general-purpose object-oriented database management system. The diagnostic and alerting requirements are accomplished with encapsulated methods and a novel use of the object-oriented database management class-hierarchy structure. The patient data management requirement is satisfied by the normal data management capabilities of the object-oriented DBMS.

Aphasia↗
PubMed1991

The future of decision support systems in hospital management.

This article discusses the evolution of decision support systems (DSS) within the hospital management environment. It begins with an outline of the historical factors leading to the need for this technology, then goes on to review the unique data-processing attributes a DSS offers and the requisite changes hospital management must make to maximize the benefits of these systems. The purpose is to provide hospital managers and other interested individuals with an overview of DSS functionality. Increasingly restrictive hospital reimbursement systems have created an economic incentive to install DSS technology and refine management structures to take advantage of the enhanced data-processing capabilities. A DSS enables a hospital to organize data captured by its information system on a product-line basis. This capability affords management with an entirely new way of analyzing a hospital's financial performance. Hospitals, traditionally organized on a departmental basis, must change their management structures in order to effectively use the data provided by a DSS.

Cost-Benefit Analysis↗
PubMed1994

Uniform system for the evaluation of substances. I. Principles and structure.

In April 1994, the first version of the Uniform System for the Evaluation of Substances (USES 1.0) was launched to comply with an action point of the Netherlands National Environmental Policy Plan. USES is a tool for the rapid, quantitative assessment of the hazards and risks of chemical substances, including new substances, existing substances, agricultural pesticides and biocides. It was developed to be applied as a decision-support system by the central government, by industry and institutes in the private sector and by international fora. Since hazard and risk assessment must be transparent to all users and easy to perform, USES 1.0 is well documented and available as a computer program. An overview of this system will be presented including its objectives, the national and international framework, the general principles involved, as well as the structure and the content of the models used.

Animals↗
PubMed1994

The design of an emergency operating procedure in process control systems: a case study of a refrigeration system in an ammonia plant.

The purpose of this study was to develop a method to aid and support human operators in emergency operations. A conceptual model of system performance was constructed in order to observe the constraints of human capabilities under emergency conditions. Then the influence of emergent events and the applicable condition of procedural design principles were discussed. In order to help operators in handling the emergent event, a decision table support and a computer support were developed according to historical data and principles of procedural design. In order to verify the effects of above methods, a simulated experiment of handling the emergent event in the refrigeration system of an ammonia plant was performed. As shown by the experimental results, the support methods successfully improved the response speed of the subject, but did not improve accuracy. The results also revealed that the decision table support had a better effect on simple error type, whereas the 16-breadth computer support had a better effect on both the simple error type and complex error type.

Adult↗
PubMed1993

A decision support system using milk progesterone tests to improve fertility in commercial dairy herds.

MOIRA (the Management of Insemination through Routine Analysis) is a computer program that is a module of DAISY, the Dairy Information System. This decision support system uses the results of milk progesterone tests to determine when to inseminate cows. The MOIRA program plans a series of weekly tests for each cow, to check for cyclicity. Subsequently, the program lists cows for alternate day tests to identify the days when they should be served, and if necessary, a cow can be served without being seen in heat. The work which led to the development of MOIRA showed that ovulation detection rates of 98 per cent were achieved; in commercial herds the rate is around 85 per cent. As pregnancy rates were unchanged, the effect of MOIRA was to reduce calving to conception interval from 90 to 85 days and the culling rate for failure to conceive from 13 per cent to 5 per cent in one herd and from 104 to 100 days and 21 per cent to 12 per cent in another herd. The use of the program produced an estimated extra net profit for the farmers of pounds 52/cow in the first herd and pounds 54/cow in the second.

Animal Husbandry↗