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Pediatric Emergency Medicine Fellowship Programs.
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The N-CODES project moves to user testing.
For a technology to be implemented successfully, it must be thoroughly tested by the stakeholders who will use it in practice. This article reports on the user testing of the Nurse Computer Decision Support working prototype. Ten acute care nurses with varying levels of education and experience participated in the testing. The study's protocol consisted of a series of tasks requiring the participants to use the system while solving patient problems. Both quantitative and qualitative data on usability, ease of navigation, and nurse satisfaction were collected. The nurses ranked usability and ease of navigation highly. Nurses were excited about the system's clinical potential and felt that it would be useful to all practitioners regardless of experience. Testing the system in an actual clinical setting is the next step, but it is clear that the system has extraordinary potential to improve clinical decision making and patient outcomes.
A glossary of economic terms.
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Establishing inter-rater reliability scoring in a state trauma system.
Trauma systems rely on accurate Injury Severity Scoring (ISS) to describe trauma patient populations. Twenty-seven (27) Trauma Nurse Coordinators and Data Managers across the state of New South Wales, Australia trauma network were instructed in the uses and techniques of the Abbreviated Injury Scale (AIS) from the Association for the Advancement of Automotive Medicine. The aim is to provide accurate, reliable and valid data for the state trauma network. Four (4) months after the course a coding exercise was conducted to assess inter-rater reliability. The results show that inter-rater reliability is with accepted international standards.
Glossary for hereditary hearing impairment.
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Hand fellowships.
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A glossary of terms encountered in quality and customer service.
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Partitioning the UMLS semantic network.
The unified medical language system (UMLS) integrates many well-established biomedical terminologies. The UMLS semantic network (SN) can help orient users to the vast knowledge content of the UMLS Metathesaurus (META) via its abstract conceptual view. However, the SN itself is large and complex and may still be difficult to comprehend. Our technique partitions the SN into smaller meaningful units amenable to display on limited-sized computer screens. The basis for the partitioning is the distribution of the relationships within the SN. Three rules are applied to transform the original partition into a second more cohesive partition.
Evaluation and application of a semantic network partition.
Semantic networks (SNs) are excellent knowledge representation structures. However, large semantic networks are hard to comprehend. To overcome this difficulty, several methods of partitioning have been developed that rely on different mixes of structural and semantic methods. However, little has appeared in the literature concerning the question whether a partition of a semantic network creates subnetworks that agree with human insight. We address this issue by presenting a comparison between the results of an algorithmic partitioning method and a partition created by a group of experts. Subsequently, we show how a network partition can be used to generate various partial views of a semantic network, which facilitate user orientation. Examples from the Unified Medical Language System (UMLS) SN are used to demonstrate partial views.
DICOM structured report document type definition.
The Digital Imaging and Communications in Medicine (DICOM) standard recently introduced rules for the encoding, transmission and storage of the structured diagnostic report. This medical document can be stored and communicated with the images. It has a structure and may contain text, with links to other data such as images, waveforms and spatial or temporal coordinates. The prompt availability of the radiology report is crucial for implementing a Patient Electronic Record. Using the extensible markup language (XML) to encode the radiology report broadens its accessibly. This paper presents a document type definition (DTD) that accurately models the DICOM structured report content, structure, and constraints.
Structural semantic interconnections: a knowledge-based approach to word sense disambiguation.
Word Sense Disambiguation (WSD) is traditionally considered an Al-hard problem. A break-through in this field would have a significant impact on many relevant Web-based applications, such as Web information retrieval, improved access to Web services, information extraction, etc. Early approaches to WSD, based on knowledge representation techniques, have been replaced in the past few years by more robust machine learning and statistical techniques. The results of recent comparative evaluations of WSD systems, however, show that these methods have inherent limitations. On the other hand, the increasing availability of large-scale, rich lexical knowledge resources seems to provide new challenges to knowledge-based approaches. In this paper, we present a method, called structural semantic interconnections (SSI), which creates structural specifications of the possible senses for each word in a context and selects the best hypothesis according to a grammar G, describing relations between sense specifications. Sense specifications are created from several available lexical resources that we integrated in part manually, in part with the help of automatic procedures. The SSI algorithm has been applied to different semantic disambiguation problems, like automatic ontology population, disambiguation of sentences in generic texts, disambiguation of words in glossary definitions. Evaluation experiments have been performed on specific knowledge domains (e.g., tourism, computer networks, enterprise interoperability), as well as on standard disambiguation test sets.
The maternity care data project.
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Building knowledge for quality improvement in healthcare: an introductory glossary.
At the heart of organization-wide quality improvement in healthcare is the need to build knowledge for improvement that complements the subject matter knowledge of healthcare. Dr. W. Edwards Deming, the quality improvement pioneer, has suggested that "profound knowledge," or knowledge required for improvement, consists of four basic dimensions: Knowledge of the organization as a system. At its heart this knowledge is an understanding of the methods of production, the methods of improvement, and the aim of the entire enterprise. This concept was first presented by Deming at Mount Hakone, Japan, in 1950. In his book Out of the Crisis (1986), Deming illustrates the organization as a system. Knowledge of variation. This understanding comes from the awareness that a system of causes is at work producing any result. These sources of the variation, which can be observed in any process, are what must be acted upon to improve the results of the process. Studying the variation in a process can provide clues to the most economical actions that managers can take for improvement. It involves knowledge of the difference between common and special cause variation. Knowledge of psychology. The focus is on an awareness of the power of intrinsic motivation, a sense of self-worth and pride in what is done in the workplace. Theory of knowledge. How is new knowledge built? What is the purpose of knowledge? What is the nature of knowledge? Unless these issues are clear, it will not be easy to build useful knowledge. Deming has provided further insight into this framework in a recent unpublished essay and is currently working to further expand these concepts in additional publications in preparation. This framework helps build the knowledge necessary for the improvement of healthcare. As you work to build that knowledge, however, you will confront a wide variety of terms and a language that may in some ways be unfamiliar. In recognition of that, an introductory glossary is offered for your use and reference. With time, it can, should, and will be replaced by an expanded lexicon. Other sources that interested readers may wish to consult include the references listed at the end of the glossary.
Text mining for metabolic pathways, signaling cascades, and protein networks.
The complexity of the information stored in databases and publications on metabolic and signaling pathways, the high throughput of experimental data, and the growing number of publications make it imperative to provide systems to help the researcher navigate through these interrelated information resources. Text-mining methods have started to play a key role in the creation and maintenance of links between the information stored in biological databases and its original sources in the literature. These links will be extremely useful for database updating and curation, especially if a number of technical problems can be solved satisfactorily, including the identification of protein and gene names (entities in general) and the characterization of their types of interactions. The first generation of openly accessible text-mining systems, such as iHOP (Information Hyperlinked over Proteins), provides additional functions to facilitate the reconstruction of protein interaction networks, combine database and text information, and support the scientist in the formulation of novel hypotheses. The next challenge is the generation of comprehensive information regarding the general function of signaling pathways and protein interaction networks.
New antimicrobial agents approved by U.S Food and Drug Administration in 2000 and new indication for previously approved agents.
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Glossary of the World Trade Organisation and public health: part 1.
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