Biomedical subjects

O Wigertz

Publications and source records attributed to O Wigertz.

At least 37 records · Page 2Linked to original sources

PubMed1994

Experiences from the use of data-driven decision support in different environments.

The paper reports experiences from the implementation and use of data-driven decision support based on the Arden Syntax in three different environments: in a health-care centre, in a clinical laboratory, and in a research department. Methods and tools used for realization of decision support systems (DSSs) are shortly presented, and integration aspects of the DSS with running clinical applications and existing patient databases are discussed. The application areas are also described, together with validation procedures for the developed knowledge modules.

Artificial Intelligence↗

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↗

PubMed1994

The HELIOS medical software engineering environment.

The aim of the HELIOS project is to create an integrated Software Engineering Environment (SEE) to facilitate the development and maintenance of medical applications. HELIOS is made of a set of software components, communicating through a software bus called the HELIOS Unification Bus. The object oriented paradigm is used both as the basic structure for building the software components and as the methodology for modelling, storing and retrieving the entities and procedures used in an application. Development standards include UNIX as operating system and X Window/MOTIF as windowing environment. One of the target applications for the HELIOS prototype is the development of a multimedia medical workstation as a front end to a hospital information system.

Computer Systems↗

PubMed1994

The component-based architecture of the HELIOS medical software engineering environment.

The constitution of highly integrated health information networks and the growth of multimedia technologies raise new challenges for the development of medical applications. We describe in this paper the general architecture of the HELIOS medical software engineering environment devoted to the development and maintenance of multimedia distributed medical applications. HELIOS is made of a set of software components, federated by a communication channel called the HELIOS Unification Bus. The HELIOS kernel includes three main components, the Analysis-Design and Environment, the Object Information System and the Interface Manager. HELIOS services consist in a collection of toolkits providing the necessary facilities to medical application developers. They include Image Related services, a Natural Language Processor, a Decision Support System and Connection services. The project gives special attention to both object-oriented approaches and software re-usability that are considered crucial steps towards the development of more reliable, coherent and integrated applications.

Computer Communication Networks↗

PubMed1994

Data driven medical decision support based on Arden Syntax within the HELIOS environment.

Methods and tools for development of data driven decision support systems (DSSs) is an integral part of the HELIOS software engineering environment. The DSS development environment includes tools for knowledge acquisition and knowledge base construction, provides trigger mechanisms for evocation of the knowledge base and an inference engine for execution control of appropriate parts of the knowledge base during run-time. The tools are part of the HELIOS service components and are integrated within the HELIOS communication framework. The work is based on the Arden Syntax, a standard for knowledge representation, allowing medical logic modules (MLMs) to be shared and transferred between institutions.

Artificial Intelligence↗

PubMed1993

Pre-compiling medical logic modules into C++ in building medical decision support systems.

Development of medical knowledge bases is a time-consuming process, and no single medical institution can develop medical knowledge bases covering all areas of medicine. The use of medical knowledge representation standards such as the Arden Syntax is an attempt to enhance the writability and readability of computer-stored knowledge and facilitate transfer and sharing among institutions. A method for the realisation of decision support systems based on knowledge formulated according to the Arden Syntax is presented. An essential tool in this process is a medical logic module (MLM) pre-compiler, translating MLMs into an object-oriented programming language, C++. Advantages of the C++ approach compared with other alternatives are discussed.

Artificial Intelligence↗

PubMed1993

Influence of "outliers" on the association between laboratory data and histopathological findings in liver biopsy.

Discriminant analysis techniques were used to predict the histopathological findings in liver biopsy specimens in asymptomatic patients with slightly to moderately raised routine liver tests. Moderate to severe fibrosis and/or inflammation were treated as indication for biopsy. Two methods were used to classify patients. One was the dichotomous discrimination between "biopsy necessary" or "biopsy not necessary" groups of patients. The other involved combining two discriminant functions trained separately for recognition of fibrosis or inflammation, and then combined to predict the biopsy necessity. Detection of outliers by standard techniques, directly available in the SPSS-X package, was performed before starting discrimination procedures. Both "sharp" assignment rules and continuous scoring rules were applied to the classification problem. The correct classification rate reached over 85% for the algorithms tested. In the majority of cases the classification was found to be "non-doubtful". Elimination of outliers (especially by standardized residuals) improved the global correct classification rate, but only slightly improved assignment to the "biopsy necessary" group. Routine and complementary laboratory findings were found to be the most discriminating; answers to questionnaire and ultrasound examination were less important. Selection of the most diagnostic features based on "clean" data without outliers enabled us to find interesting medical associations, which were previously masked by extremely asymptomatic values outlying from the main body of the "biopsy necessary" group.

Biopsy↗

PubMed1993

MultiLink--an intermediary system for multi-database access.

The design and implementation is described of MultiLink, a desktop system for direct enduser access to remote bibliographic information. The system is an application of a client-server technique based on a campuswide network, with the objective to assist end-users to accomplish the information--retrieval process by capturing knowledge and expertise for searches in query formulations. MultiLink, via intelligent interfaces, allows users to access several dozens of bibliographic databases. The application integrates regional, national and international resources, and brings library services to the user's desktop level.

Databases, Bibliographic↗

PubMed1992

Multi centre systems analysis study of primary health care: a study of socio-organizational and human factors.

The information management systems to support health programmes are inadequate. As computers become cheaper and more powerful, their application in the strengthening of the information infrastructure becomes more feasible. However, the high cost of specialized applications software limits their potential, especially in developing countries. A multi-centre systems analysis, (a descriptive study using a questionnaire), was made of District Health Sites in developing countries to analyse whether a common specialized application software design for implementation at a primary health care centre was feasible. Responses to the questionnaires by physicians at the primary health centres were compared between district health sites using contingency tables. Significant inter-site differences in social factors existed, respondents had no prior experience, but with near unanimity (98%) accepted the idea of computer assistance in their work. However, general reservations (31%) and fears (26%) about computer interference in the doctor-patient relationship were expressed. The human factor must be considered in interface design and training before implementation.

Attitude of Health Personnel↗

PubMed1992

Impact on the management and delivery of primary health care by a computer-based information system.

Timely and accurate information forms the basis for management to plan and for care providers to take appropriate action. We report from a developing country a research project aimed to strengthen the information infrastructure with a computer at a Primary Health Centre. The software (MCHS) was designed to assist the care providers in the information management for the Maternal and Child Health (MCH) programme activities. In Phase I, a baseline survey was conducted to identify the needs and target groups. In Phase II, the MCHS was integrated into routine delivery of MCH to monitor the target population and help in evaluation. The research project's impact is reflected in enhanced utilization of services and quality in care, as seen by reduction of dropouts from the immunization program. In economic terms, we see that the costs for a fully immunised child are reduced with reduction of dropouts; thus, the computer system contributes to quality assurance and cost effectiveness in delivery of care.

Adolescent↗

PubMed1992

Towards an essential data set: applicability in the domain of maternal health services.

There is a need for consensus on the quantity of data that must be available in a computer-based information system of a health care organization. In this paper we take up the issue of defining the data content of an information system and introduce the concept of Essential Data Sets with an explicit methodology which was applied to define a data set for the Maternal Health Services program. A key step in the method was a recognized technique used in systems development process called data modelling, in this case infological modelling, by an interdisciplinary group. A preliminary set of 86 data elements was identified and it provided the foundation for development of an application software for discussion and a real-world testing framework. The acceptability of the data set was tested in a laboratory perspective by retrospective data entry from records of 94 pregnant women registered at a maternal health care center in Sweden. Data from a total of 1,318 prenatal visits, an outcome visit, and a postnatal visit for each woman was entered into a computer using the software, with no loss of information. Thus, in a short-term perspective the acceptability of the data set was demonstrated. The software has since been implemented for pilot prospective studies at sites in India and Sweden. The use of a common data protocol is an essential foundation for patient outcome research, especially as the trend of health care management has changed from a "process of care" orientation to an "outcome of care" orientation.

Electronic Data Processing↗

PubMed1991

A multicenter study of data collection and communication at primary health care centers.

Health care delivery is information intensive. As computer applications make information available to the decision maker with speed and accuracy, informatics applications will strengthen the infrastructure. This paper is the second part of a multicenter systems analysis study to design a common application software to support primary health care focused on information flow. We present the questionnaire analysis and observations from a field study of a district health site. Analyses using contingency tables revealed differences, some statistically significant. The field study confirmed that minor differences exist even within a district health site. Development of a common application software on the basis of information flow studies is feasible. However, to make optimum use of computer implementation, revision of the health information systems was recommended. It was suggested that application software be developed with the core data set required by the care providers to deliver and administrators to manage a vertical health program.

Communication↗

PubMed1991

Medical logic module (MLM) representation of knowledge in a ventilator treatment advisory system.

In any medical expert system it is the inherent knowledge that is the power of the system and not the particulars of its implementation. Therefore it would be valuable to use a representation that would allow: knowledge transfer between different systems, users, experts and 'importers' to be able to evaluate the logic, experts to easily input their knowledge and be guided how to use the syntax. Adren Syntax of Medical Logic Module is a proposed knowledge representation, fulfilling these criteria. The Arden Syntax has been used to represent rules and logic in a decision support system for ventilator therapy in patients with acute respiratory failure (ARF) that is under development. The medical experts involved in the project have used the Arden Syntax as a convenient way for transfer and storage of medical knowledge. The syntax is easy to learn and may be used with a minimum of training. In the present system, Medical Logical Modules have been used to represent knowledge pertinent to the initiation and maintenance phases of ventilator therapy.

Acute Disease↗

PubMed1991

Methods for knowledge extraction from a clinical database on liver diseases.

We performed exploratory data analysis (EDA) to examine the hidden structure in liver disease data. The purpose was to demonstrate the potential of statistical techniques for extracting knowledge from an active HIS (hospital information system) database with decision support. The goal is to give strong support to the creation of new rules or "tuning" of old rules in the knowledge base. This would facilitate utilization of large patient databases, now commonly available, to help build/update decision support systems for improved patient care. Several statistical techniques were investigated. Stepwise discriminant analysis was found to be a good method in discriminating among different disease classes. Results showed that classification strength of a few (3) variables was similar to all the available (19) variables. Other important issues in the work are treatment of missing values as well as atypical values in medical databases. In estimating missing values we utilized both statistical methods and artificial intelligence approaches. Both these approaches were promising in the estimation of missing values. The study showed that several statistical approaches are possible for knowledge extraction from clinical data collected retrospectively.

Artificial Intelligence↗

PubMed1991

Integrated approach for designing medical decision support systems with knowledge extracted from clinical databases by statistical methods.

In clinical research data is often studied by a particular method without previous analysis of quality or semantic contents which could link clinical database and data analytical (e.g. statistical) procedures. In order to avoid bias caused by this situation, we propose that the analysis of medical data should be divided into two main steps. In the first one we concentrate on conducting the quality, semantic and structure analyses. In the second step our aim is to build an appropriate dictionary of data analysis methods for further knowledge extraction. Methods like robust statistical techniques, procedures for mixed continuous and discrete data, fuzzy linguistic approach, machine learning and neural networks can be included. The results may be evaluated both using test samples and applying other relevant data-analytical techniques to the particular problem under the study.

Artificial Intelligence↗

PubMed1990

Extracting knowledge from a large primary health care database using a knowledge-based statistical approach.

Clinical databases from automated medical records represent a growing resource for deriving new medical knowledge. In this study a large primary health care database was explored with respect to the association between hypertension and diabetes. Data collection was made with a query language, and data analysis performed with an interactive knowledge-based statistical tool, MAXITAB, employing a multivariate tabular analysis technique. In the study population of 6660 patients the prevalence of diabetes was almost three times higher for hypertensive patients than for those with no hypertension. Conversely, the prevalence of hypertension was 2.6 times higher for diabetic patients than for those with no diabetes. The results support the assumption of a relationship between hypertension and diabetes, although the question of causality between the two diagnoses remains unsolved. Knowledge-based statistical tools of this kind may be feasible for exploring large clinical databases and may result in new medical hypotheses, worthy of further investigation.

Aged↗

PubMed1990

Integrating knowledge-based technology into computer aided ventilation systems.

A knowledge-based decision support system for respirator treatment, the KUSIVAR system, has been designed in cooperation between hospital, university and industry. Changes in patient data from respirator and monitoring equipment trigger a computer program that generates advice to the staff concerning e.g. therapy modes and respirator settings using expert systems and process control technology. A prototype has been built on an advanced development workstation, the Unisys Explorer, using the software Knowledge Engineering Environment (KEE). The clinical version is implemented on an Intel 80396-based microcomputer connected on-line via a data-acquisition processor to the respirator. The decision support software is implemented as a module under the Microsoft Windows multitasking environment and communicates with modules for data acquisition, database handling and data presentation by means of message passing using the Windows Dynamic Data Exchange protocol. The modules present coherent user interfaces by conforming to Microsoft Windows standards. The knowledge base is being extensively validated by an expert group in the ICU and the system will be evaluated through animal experiments and clinical studies.

Computer Systems↗

PubMed1989

Computer based information systems in primary health care--why?

The delivery of health care is information based. A host of computer-based information systems have been developed and implemented in the health care environment. The mere availability of the computer as a tool for information handling should, in itself, not be the cause for developing computer-based information systems. The earlier assumption of a cost-benefit impact with the development of such systems has not been effectively shown in all cases, and as seen in a report by van Bemmel, the recent trend is to apply other criteria in systems evaluation. Information is essential in health care related decision making. The properties of information are described to present a case for a computer-based information system to support primary health care delivery.

Computer Systems↗