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Biomedical subjects

O Wigertz

Publications and source records attributed to O Wigertz.

At least 19 recordsLinked to original sources
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↗
PubMed1989

Knowledge base design for decision support in respirator therapy.

A knowledge base is built for decision support applied to respirator therapy (the KUSIVAR project). The knowledge representation is object-oriented using frames to store multiple forms of knowledge: variable descriptions, transformation tables, rules and mathematical models. The system is data-driven, generating and displaying advice automatically triggered by changes in data from the respirator and the patient. The inferenceing mechanism is forward-chaining i.e. a rule is evaluated as soon as it's condition is satisfied. Temporal aspects of the reasoning are represented by a number of mechanisms, among others limited validity times for data, trend analysis and mathematical models. The knowledge base is organized according to disease groups and decision situation which simplifies knowledge acquisition and improves response times since it enables the system to focus on a limited set of rules in each situation. To test the feasibility of the system design a prototype has been built using Knowledge Engineering Environment (KEE) from Intellicorp on an Explorer workstation from Unisys. The production system, which is interfaced to a Siemens Elema Servo Ventilator 900C, is currently being implemented under the Microsoft Windows multitasking environment on a microcomputer based on an Intel 80386 processor.

Decision Support Techniques↗
PubMed1989

Teaching medical informatics to biomedical engineering students: experiences over 15 years.

The Departments of Biomedical Engineering and Medical Informatics at Linköping University in Sweden were established in 1972-1973. The main purpose was to develop and offer courses in medicine, biomedical engineering and medical informatics to students in electrical engineering and computer science, for a specialization in biomedical engineering and medical informatics. The courses total about 400 hours of scheduled study in the subjects of basic cell biology, basic medicine (terminology, anatomy, physiology), biomedical engineering and medical informatics. Laboratory applications of medical computing are mainly taught in biomedical engineering courses, whereas clinical information systems, knowledge based decision support and computer science aspects are included within the medical informatics courses.

Biomedical Engineering↗
PubMed1989

A knowledge-based system for data analysis and interpretation.

Traditionally, statistical packages are employed to derive or infer facts about a Universe of Discourse through data analysis and interpretation. It is analysis that serves to transform data into information. Statistical packages provide the users with relatively easy-to-use and powerful mechanics of data analysis, but up to now they do not provide much help with the design and strategies of the analysis. As such, there is a risk of misuse of these packages by statistically inexperienced users. We propose the use of knowledge-based interfaces to support this category of users in statistical evaluations. This paper discusses our experiences from the implementation of a knowledge-based system called MAXITAB. It provides guidance in the processes of data analysis and interpretation and has been programmed as an interface to the statistical package MINITAB.

Data Interpretation, Statistical↗
PubMed1989

The data dictionary--a controlled vocabulary for integrating clinical databases and medical knowledge bases.

The medical information systems of the future will probably include the entire medical record as well as a knowledge base, providing decision support for the physician during patient care. Data dictionaries will play an important role in integrating the medical knowledge bases with the clinical databases. This article presents an infological data model of such an integrated medical information system. Medical events, medical terms, and medical facts are the basic concepts that constitute the model. To allow the transfer of information and knowledge between systems, the data dictionary should be organized with regard to several common classification schemes of medical nomenclature.

Database Management Systems↗
PubMed1988

Computer simulation of cardiac pacing.

A mathematical model of the cardiac conduction system, including external pacemakers, has been developed. The heart is modeled as a network in which the impulse propagation is described by differential equations; several arrhythmia-generating mechanisms, such as modulated parasystole, reflection, macro and micro re-entry and block, can be simulated. Different kinds of pacemaker modes have been incorporated in the model, thus making it possible to simulate the interaction between the heart and the pacemaker. The model can be tuned by the user according to electrophysiological data so that pacemaker programs can be tested under different underlying conditions. During a simulation, the program generates ECG signals and pacemaker diagnostic diagrams. This model can be used for training and testing, and also as a support system when searching for the optimal pacing therapy for a particular patient.

Computer Simulation↗
PubMed1987

Computer simulation of cardiac arrhythmias.

A mathematical model of the cardiac conduction system has been developed. The mechanisms of cardiac arrhythmias are described mathematically, and the heart is modeled as a network, where each element is defined by a unique set of time parameters from the action potential. The mathematical description is separated from the network structure, thus making it possible to run the model with different network sizes. Simulated ECG curves are produced in each case. This model is especially suited for rhythm studies, and a variety of different cardiac arrhythmia mechanisms has been simulated such as reentry, reflection, modulated parasystole, and different kinds of block.

Action Potentials↗
PubMedDate not supplied

Knowledge-based systems in medicine--a Nordic research and development programme.

A Nordic research and development programme, 'KBS in Medicine' (KUSIN-MEDICINE), was run in 1986-89. Its main goal was to acquire an understanding of applying knowledge-based techniques in medicine and of the limitations of present-day artificial intelligence (AI) methodologies. The programme comprised four experimental installation sites (Tampere in Finland, Uppsala and Linköping in Sweden, and Aalborg in Denmark) each prototyping in one or more medical domains. The programme was financed by the Nordic Fund for Technological and Industrial Development, by national funds for applied research and by a number of industries. Prototype decision support systems were produced in the following domains: intensive care (Tampere, Uppsala, Linköping, Aalborg), clinical chemistry (Tampere, Uppsala) and clinical neurophysiology (Aalborg in collaboration with Turku and Uppsala). These served to transfer this technology to industry and helped to identify limitations of this technology.

Artificial Intelligence↗