[Plasma volume, extracellular fluid volume and heart minute volume in subjects with essential hypertension with low plasma renin activity].
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Biomedical subjects
Publications and source records attributed to R Haux.
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We present a simple, formal, lexicon-based method for automated indexing of diagnoses based on the Systematized Nomenclature of Medicine (SNOMED II), called the LBI-method. Part 1 gives an introduction to the LBI-method and presents its realization as application system SALBIDH. The underlying model states that a diagnosis is represented by a set of indices of any nomenclature. The LBI-method is defined as a composition of functions, which in turn define the 3 steps of the LBI-method: preprocessing, morphological analysis, and semantic analysis. Part 2 will focus on the design and the results of an evaluation study to judge the quality of the LBI-method. In this evaluation study the quality of automated indexing was examined as well as the quality of the retrieval of patient data by using automated indexed diagnoses.
In Pediatric Oncology in Germany, 90% of the patients are treated according to multicenter clinical trials, which means an enormous effort for documentation in the participating clinics. In order to enable multiple use of data for patient records as well as for clinical trials a computer-based documentation system for pediatric oncology (DOSPO) is being developed, which can be used nationwide. DOSPO currently comprises a minimum basic data set, which represents the common core of all multicenter trials and which has been approved by the German Society for Pediatric Oncology and Hematology (GPOH). It is intended to enhance the documentation by specific items of each clinical trial. Functions for computer-aided chemotherapy planning and medical report writing have already been implemented in the documentation system. Various centers in Germany are currently validating the system in routine use.
Taking as an example the special research programme ('Sonderforschungsbereich') in leukemia research and immunogenetics (SFB120) of the University of Tübingen, we intend to discuss how research subsystems should be built up, which functions they should take over and which network architecture is suitable. Furthermore, we examined to what extent research subsystems can be integrated in the computer-supported part of hospital information systems. It can easily be seen that no general solution exists for the structuring. The structure depends rather upon the specific problems and information requirements of individual research units. The clinical environment must be taken into account if research subsystems are to be integrated into the computer-supported part of a hospital information system. Especially in regard to the data protection aspect, we must keep in mind that the connection between subsystems must not necessarily result in the setup of a network for the corresponding computer systems.
Before introducing computers or other tools to support nursing care, it is important to have a clear picture of the information processing functions required in this area. This article presents a compendium of information processing functions used in nursing. This compendium can be used to support management of information systems in planning and monitoring nursing information systems. The article describes the development of the first version of this compendium and its evaluation in a pilot study. The results of this evaluation show that the compendium can be used to assess the quality of information processing in nursing.