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At least 19 recordsLinked to original sources
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↗
PubMed1988

Computers in hospital management and improvements in patients care--new trends in the United States.

This article discusses the current state of informations systems in hospital management. Decision Support Systems (DSS) for the management, administrative and patient care units of the hospital are described. These DSS's include market planning, nurse scheduling and blood screening systems. Trends for future uses of information systems in the hospital environment are addressed.

Blood Banks↗
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↗
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↗
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↗
PubMed1991

Managing information: the role of decision support systems.

This paper defines the role of a decision support system in managing information within a hospital environment. It discusses the use of such a system as a catalyst for change in the clinical as well as financial management of patient cases. A case study highlights one hospital's use of a decision support system. The paper concludes with a discussion of the patient care uses of a decision support system in measuring quality and clinical outcomes, tracking resource utilization, predicting utilization, and setting standards and protocols.

Accounting↗
PubMed1992

Inform: conceptual modelling of intensive care information systems.

Intensive care of a patient requires heavy monitoring and versatile therapeutic actions. These produce a huge amount of patient information. A problem exists in managing this data and other information from all supporting activities creating a need for an automated information management system. To have a sound basis for future automated information systems in intensive care unit (ICU), a conceptual model is created to cover both the clinical and other activities of the ICU. The conceptual model consists of data flow diagrams and entity-relationship diagrams with underlying common data dictionary. A modern CASE tool is utilized to build the model. The work forms a part of AIM-INFORM project, which has a purpose to develop information management and decision support systems for high dependency environment.

Computer Simulation↗
PubMedDate not supplied

A flexible nurse scheduling support system.

Salaries paid to nursing personnel constitute the largest chunk of a hospital's budget. Therefore, this human resource must be utilized efficiently. Hospitals provide continuous service without the exception of holidays and personal preferences. This causes the nurses' discontent in shift scheduling. And the consequence of this discontent is the nurse shortage. This and the pressures on hospitals to limit costs increase the importance of the nurse scheduling problem. Scheduling nursing personnel in hospitals is very complex due to the variety of conflicting interests or objectives between hospitals and nurses. Also, the demand, which varies widely 24-h a day 7-day a week is skill specific and hard to forecast. In the face of this complexity, the present nurse scheduling models have met with little success. In this paper, we propose a more flexible decision support system that will satisfy the interests of both hospitals and nurses through alternative models that attempt to accommodate flexible work patterns as it integrates time of the day (TOD) and day of the week (DOW) scheduling problems.

Decision Support Systems, Management↗
PubMed1992

An extended SQL for temporal data management in clinical decision-support systems.

We are developing a database implementation to support temporal data management for the T-HELPER physician workstation, an advice system for protocol-based care of patients who have HIV disease. To understand the requirements for the temporal database, we have analyzed the types of temporal predicates found in clinical-trial protocols. We extend the standard relational data model in three ways to support these querying requirements. First, we incorporate timestamps into the two-dimensional relational table to store the temporal dimension of both instant- and interval-based data. Second, we develop a set of operations on timepoints and intervals to manipulate timestamped data. Third, we modify the relational query language SQL so that its underlying algebra supports the specified operations on timestamps in relational tables. We show that our temporal extension to SQL meets the temporal data-management needs of protocol-directed decision support.

Acquired Immunodeficiency Syndrome↗
PubMedDate not supplied

Integration of knowledge-based system and database for identification of disturbances in fluid and electrolyte balance.

We describe a knowledge-based system which automatically identifies fluid and electrolyte disorders in intensive care patients. The knowledge-based system was built and interfaced to an existing patient data management system (PDMS) in Kuopio University Central Hospital to evaluate the potential of knowledge-based techniques in information management and decision support in the high dependency environment. Because of the integration, the system does not require any manual data input, and it provides a natural extension and increased performance to a current patient data management system used in clinical practise. The paper discusses design considerations and gives the system description. The evaluation of the experimental system in clinical use showed that it performed almost as well as junior clinicians of the intensive care unit.

Artificial Intelligence↗
PubMed1991

WING--entering a new phase of electronic data processing at the Giessen University Hospital.

At the Giessen University Hospital electronic data processing systems have been in routine use since 1975. In the early years developments were focused on ADT functions (admission/discharge/transfer) and laboratory systems. In the next decade additional systems were introduced supporting various functional departments. In the mid-eighties the need to stop the ongoing trend towards more and more separated stand-alone systems was realized and it was decided to launch a strategic evaluation and planning process which sets the foundation for an integrated hospital information system (HIS). The evaluation of the HELP system for its portability into the German hospital environment was the first step in this process. Despite its recognized capabilities in integrating decision support and communication technologies, and its powerful HIS development tools, the large differences between American and German hospital organization, influencing all existing HELP applications, and the incompatibility of the HELP tools with modern software standards were two important factors forcing the investigation of alternative solutions. With the HELP experience in mind, a HIS concept for the Giessen University Hospital was developed. This new concept centers on the idea of a centralized relational patient database on a highly reliable database server, and clinical front-end applications which might be running on various other computer systems (mainframes, departmental UNIX satellites or PCs in a LAN) integrated into a comprehensive open HIS network. The first step towards this integrated approach was performed with the implementation of ADT and results reporting functions on care units.

Database Management Systems↗
PubMed1990

KADIS--a computer-aided decision support system for improving the management of type-I diabetes.

Despite the introduction of new therapeutic aids such as insulin pumps and injectors, blood glucose test tapes, particular insulin formulations, and the physiological basis-bolus principle of insulin dosage regimes, the metabolic care of most insulin-dependent patients is still insufficient. One potential tool of further improving the results in diabetes treatment consists in the application of computer-aided procedures to estimate individually optimal regimes. Employing a validated mathematical model of the glucose/insulin metabolic control system and individual sets of data from patients' self-monitoring, a software package was developed on a micro-computer which allowed both the retrospective analysis of data resulting from the therapeutic process, and the prospective simulation of the outcome of alterations in the regime in terms of glycaemia and insulinaemia. The two parts of the programme provide either for the patient or for the physician an interactive mode of working with the computer. The system is now being validated by means of a long-term follow-up study in type-I diabetic patients. It may be used mainly in diabetic outpatient centers and as a tool of educating, training, and motivating patients.

Computer Simulation↗