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PubMed · 3897432

Practice-based data set for a nursing information system.

Abstract

It has been argued that nursing practice components are not sufficiently clarified to develop specifications for a nursing data set within an NIS. The purpose of this paper was to examine this assumption. Conclusions were drawn that both philosophically and conceptually, the components of practice are clear. In addition, a sufficient taxonomy for the content and structure of a data set is available. A draft of 17 items, categories, definitions, and rationale for inclusion is presented. Validity and reliability of the specified item-categories is discussed. As in any profession, work on the precision of patient descriptors and therapeutic interventions is ongoing. This work is greatly enhanced if a data set is computerized and the content and organization is consistent with practice components. Large-scale studies of item-categories can further refine the structure and organization of a nursing data set.

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BibTeXRIS

M Gordon. 1985. Practice-based data set for a nursing information system.. https://doi.org/10.1007/bf00992521

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Structure-based inhibitor design.

Time and costs associated with the discovery of new drugs have been significantly reduced by enzyme structure-based approaches to the discovery of new chemotherapeutic agents. However, fundamental components of the overall approach continue to rely on technologies which, by their nature, involve relatively random processes (i.e., combinatorial chemistry and high-throughput screening). Thus, the efficiency of the drug discovery process potentially could be further improved through better use of structural information. In this regard, three-dimensional structures of enzymes are now being solved at high resolution and/or in conformations that provide data that should be more useful for inhibitor design or discovery. Scientists are beginning to appreciate the importance of water as a possible competitor of inhibitors for binding to target enzymes. New computational algorithms are improving the efficiency of identifying flexible inhibitors from among the large numbers of compounds in chemical databases. Also, tools of molecular genetics together with structures of target enzymes are likely to be used more frequently in dealing with the development of resistance to novel chemotherapeutic agents. Instead of detailing success stories in structure-based drug discovery, the following article considers how future efforts to discover or design new drugs may increasingly rely on information about molecular targets and less on data acquired via approaches involving random methodologies.

Computers