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eLearning for nursing and Health professionals in university: an overview.

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This research used a text data mining technique to extract useful information from nursing records within Electronic Medical Records. Although nursing records provide a complete account of a patient's information, they are not being fully utilized. Such relevant information as laboratory results and remarks made by doctors and nurses is not always considered. Knowledge concerning the condition and treatment of patients has been determined in a twofold manner: a text data mining technique identified the relations between feature vocabularies seen in past in-patient records accumulated on the University of Miyazaki Hospital's Electronic Medical Record, and extractions were made. The qualitative analysis result of in-patient nursing records used a text data mining technique to achieve the initial goal: a visual record of such informa-tion. The analysis discovered vocabularies relating to proper treatment methods and concisely summarized their extracts from in-patient nursing records. Important vocabularies that characterize each nursing record were also revealed. The results of this research will contribute to nursing work evaluation and education.
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Free text is helpful for entering information into electronic health records, but reusing it is a challenge. The need for language technology for processing Finnish and Swedish healthcare text is therefore evident; however, Finnish and Swedish are linguistically very dissimilar. In this paper we present a comparison of characteristics in Finnish and Swedish free-text nursing narratives from intensive care. This creates a framework for characterising and comparing clinical text and lays the groundwork for developing clinical language technologies. Our material included daily nursing narratives from one intensive care unit in Finland and one in Sweden. Inclusion criteria for patients were an inpatient period of least five days and an age of at least 16 years. We performed a comparative analysis as part of a collaborative effort between Finnish- and Swedish-speaking healthcare and language technology professionals that included both qualitative and quantitative aspects. The qualitative analysis addressed the content and structure of three average-sized health records from each country. In the quantitative analysis 514 Finnish and 379 Swedish health records were studied using various language technology tools. Although the two languages are not closely related, nursing narratives in Finland and Sweden had many properties in common. Both made use of specialised jargon and their content was very similar. However, many of these characteristics were challenging regarding development of language technology to support producing and using clinical documentation. The way Finnish and Swedish intensive care nursing was documented, was not country or language dependent, but shared a common context, principles and structural features and even similar vocabulary elements. Technology solutions are therefore likely to be applicable to a wider range of natural languages, but they need linguistic tailoring. The Finnish and Swedish data can be found at:
The purpose of this study was to cross-mapped maternity nursing records with ICNP 2.0. Narrative nursing notes were collected from 25 inpatients records which were decomposed and unified into single sentence and classified as nursing phenomena, nursing intervention and contextual information. The total numbers of nursing statements were 4,263 and the redundancy rate was 10.3 times. 219 (61.3%) statements were cross-mapped completely, 137 (38.4%) statements were mapped partially and only one (0.3%) statement was not mapped.
Aims and objectivesTo examine the psychometric properties of the Handover Evaluation Scale using exploratory and confirmatory factor analysis. Background Handover is a fundamental component of clinical practice and is essential to ensure safe patient care. Research indicates a number of problems with this process, with high variability in the type of information provided. Despite the reported deficits with handover practices internationally, guidelines and standardised tools for its conduct and evaluation are scarce. Further work is required to develop an instrument that measures the effectiveness of handover in a valid and reliable way. DesignSecondary analysis of data collected between 2006-2008 from nurses working on 24 wards across a large Australian healthcare service. MethodsA sample of 299 nurses completed the survey that included 20 self-report items which evaluated the effectiveness of handover. Data were analysed using exploratory factor analysis and confirmatory factor analysis supported by structural equation modelling. ResultsAnalyses resulted in a 14-item Handover Evaluation Scale with three subscales: (1) quality of information (six items), (2) interaction and support (five items) and (3) efficiency (three items). A fourth subscale, patient involvement (three items), was removed from the scale as it was not a good measure of handover. Conclusions The scale is a self-report, valid and reliable measure of the handover process. It provides a useful tool for monitoring and evaluating handover processes in health organisations, and it is recommended for use and further development. Relevance to clinical practiceMonitoring handover is an important quality assurance process that is required to meet healthcare standards. This reliable and valid scale can be used in practice to monitor the quality of handover and provide information that can form the basis of education and training packages and guidelines to improve handover policies and processes.
Cross-mapping the terms of International Classification for Nursing Practice (ICNP) with the handwritten nursing records of gynecological patients at one district of private teaching hospital in the south of Taiwan was conducted in July and August, 2004. The purpose of this study was to validate the applicability of ICNP for electronic nursing records in a gynecological setting. A Chinese version of the ICNP beta 2 browser was used to code nursing record sentences. Medical charts were reviewed until data were saturated. A total of sixty-two patient records were analyzed, producing 6,327 sentences, this included 1,918 sentences on nursing phenomena (30.3%) and 4,409 sentences on nursing action (69.7%). The ratio between the two was about 1:2.3. Coded sentences were compared according to the four levels of applicability with the original records, each was identified as a "perfect fit", "conceptual fit", "partial fit", or "unable to fit". Of the 6,327 sentences, 2,041 (32.3%) were designated as "perfect fit", 2,457 (38.8%) as "conceptual fit", 1,663 (26.3%) as "partial fit", and 166 (2.6%) as "unable to fit". The top ten most described nursing phenomena included: acute pain, high temperature, conscious change, potential infection risk, state of mind change, potential risk patient's mobility change endurance level, gastrointestinal function obstacles, changes in urination, anxiety, and diarrhea. The top ten most described nursing actions included: observe surgical wounds, monitor vital signs, changes of mentality, instruction on medication, arranging clinical check ups, wound infection prevention, urinary drainage tube and urine nature observation, checking for vaginal drainage, pre/post-operative healthcare, and discharge planning. Study results indicated that 71.1% of sentences could be cross-mapped. Further validation is suggested to validate ICNP in other gynecological hospitals.
L'analisi automatica dei testi: fare ricerca con il text mining. Carocci
  • S Bolasco
Bolasco, S. (2013). L'analisi automatica dei testi: fare ricerca con il text mining. Carocci.
L'analisi automatica e semi-automatica dei dati testuali. Software e istruzioni per l'uso
  • L Giuliano
  • G La Rocca
Giuliano, L., & La Rocca, G. (2008). L'analisi automatica e semi-automatica dei dati testuali. Software e istruzioni per l'uso. LED Edizioni Universitarie.
Construct validity and reliability of the Handover Evaluation Scale
  • O ' Connell
  • B Ockerby
  • C Hawkins
O'Connell, B., Ockerby, C., & Hawkins, M. (2014). Construct validity and reliability of the Handover Evaluation Scale. Journal of clinical nursing, 23(3-4), 560-570.
Natural language processing for nursing documentation
  • T Salakoski
  • S Salanterä
Salakoski, T., & Salanterä, S. (2005, June). Natural language processing for nursing documentation. In Second International Conference on Computational Intelligence in Medicine and Health Care (CIMED), Lissabon, Portugal.
Characteristics of Finnish and Swedish intensive care nursing narratives: a comparative analysis to support the development of clinical language technologies
  • H Allavin
  • E Carlsson
  • H Dalianis
  • R Danielsson-Ojala
  • V Daudaravicius
  • M Hassel
  • S Velupillai
Allavin, H., Carlsson, E., Dalianis, H., Danielsson-Ojala, R., Daudaravicius, V., Hassel, M., & Velupillai, S. (2011). Characteristics of Finnish and Swedish intensive care nursing narratives: a comparative analysis to support the development of clinical language technologies. J. Biomedical Semantics, 2(S-3), S1.