Objective Describe the terms used in written records of patients' progress by nurses. Methods Descriptive research with a quantitative method that used a software to extract terms related to 148,200 nursing documentations of patient's progress, from 2010 to 2012, in a university hospital in Curitiba - Paraná. The terms were normalized, if appropriate, in spelling, gender, number and tense; then corpus of 2.638 terms was classified for analysis. Results There were problems related to the identification of the records; the use of trade names for designating artifacts used in the nursing practice; unconventional acronyms and abbreviations; and colloquial terms. Records of terms contained in standardized language of nursing diagnoses were found. Conclusion The language used by nurses is heterogeneous. There is a tendency to use terms of specialized language, even when there is no formal terminology standardization in the institution.

This theoretical and reflective study aimed to assess the contribution of the ISO/TR 12300:2016 document for the mapping of nursing terminology. The referred document and related articles were used as an empirical framework. The study analyzed the content of the document, highlighting cardinality and equivalence principles. The standard presents conceptual and operational basis for mapping, with cardinality and equivalence as the support for the categorization of cross-terminology mapping in the area of nursing. Cardinality verifies candidate target terms to represent the source term, while the equivalence degree scale checks semantic correspondence. Among the principles included in the ISO/TR 12300:2016, cardinality and equivalence contribute to the accurate representation of the results of the cross-terminology mapping process and its use should decrease inconsistencies.

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O objetivo deste estudo foi identificar fatores de rotatividade e fidelização de profissionais de enfermagem. Estudo descritivo e quantitativo, envolvendo 102 profissionais de enfermagem desligados de serviços de saúde entre 2013 e 2014. Foram coletados dados por meio de um formulário eletrônico e, a partir da mineração de dados, descobertos padrões, posteriormente avaliados por cinco especialistas. Foram identificados como fatores de rotatividade e fidelização de profissionais de enfermagem: comunicação entre funcionários e chefia; repasse de assuntos importantes e mudanças na empresa; tratamento entre chefia e subordinado; oportunidade de influenciar a tomada de decisão; reconhecimento profissional, aliado ao crescimento na organização e promoções aos profissionais mais qualificados; salário adequado; carga de trabalho; e ambiente saudável. Os fatores identificados podem refletir em condições desfavoráveis ao trabalho dos profissionais de enfermagem, contribuindo para a rotatividade, se adequados e trabalhados pelos gestores, colaboram para melhores resultados na instituição e para a satisfação e fidelização dos profissionais.

Objective: Identify workflow factors in the operating room and their implications, which influence nurses' decision making. Method: Integrative review of the literature conducted through searches in the databases: Latin American and Caribbean Literature in Health Sciences; Nursing Database; Pubmed; Scopus and Cumulative Index to Nursing and Allied Health Literature. The results were organized into factors related to positive, negative and positive and negative implications. Results: The sample of 18 articles included examples of factors with positive implications, such as preoperative data collection, negative outcomes, such as lack of human, material and structural resources, and positive and negative outcomes, as preparation for certification. Conclusions: Factors that influence the decision-making process of nurses are associated to different conditions: client- related conditions and those conditions that go beyond the domain and organization of the surgical environment.

Objective: to reflect on the use of computational tools in the cross-mapping method between clinical terminologies. Method: reflection study. Results: the cross-mapping method consists of obtaining a list of terms through extraction and normalization; the connection between the terms of the list and those of the reference base, by means of predefined rules; and grouping of the terms into categories: exact or partial combination or, in more detail, similar term, more comprehensive term, more restricted term and non-agreeing term. Performed manually in many studies, it can be automated with the use of the Unified Medical Language System (UMLS). Obtaining the terms list can occur automatically by natural language processing algorithms, being that the use of rules to identify information in texts allows the expert's knowledge to be coupled to the algorithm, and it can be performed by techniques based on Machine Learning. When it comes to mapping terms using the 7-Axis model of the International Classification for Nursing Practice (ICNP®), the process can also be automated through natural language processing algorithms such as POS-tagger and the syntactic parser. Conclusion: the cross-mapping method can be intensified by the use of natural language processing algorithms. However, even in cases of automatic mapping, the validation of the results by specialists should not be discarded.

RESUMO:Objetivo: complementar os fatores relacionados à mortalidade infantil. Método: foram utilizados os dados do Sistema de Informação sobre Nascidos Vivos e do Sistema de Informação de Mortalidade, do período de 2010 a 2014, de um município do Estado do Paraná. Foram extraídas estatísticas descritivas, e utilizado mineração de dados, por meio dos algoritmos J48 e NPP. Resultados: foram identificadas relações entre o baixo peso ao nascer e a idade gestacional; observou-se que mães com mais de um nascido morto tiveram crianças prematuras; não foram identificadas associações entre a escolaridade materna e a mortalidade infantil; destacamse que 56,8% dos óbitos eram evitáveis, sendo a maioria reduzíveis por atenção adequada à mulher durante a gestação. Conclusão: são fatores relacionados à mortalidade infantil o baixo peso ao nascer, idade gestacional e anomalias, isso reforça a necessidade de políticas públicas voltadas à saúde materna e aos nascimentos prematuros. PALAVRAS-CHAVE: Mortalidade infantil; Mineração de dados;Inteligência artificial. FACTORS THAT CONTRIBUTE TO CHILDREN Ś MORTALIT Y ASSESSED THROUGH DATA MININGABSTRACT: To complement factors related to infant mortality. Data were retrieved from the Information System on Live Births and from the Information System of Mortality, between 2010 and 2014 in a municipality in the state of Paraná, Brazil. Descriptive statistics were taken and data mining was employed through algorithms J48 and NPP. Relationships between low weight at birth and pregnancy age were identified; it has been reported that mothers with more than one infant death had premature children; 56.8% of deaths were avoidable and lacked adequate care during pregnancy. Low weight at birth, pregnancy age and anomalies are factors related to infant mortality. Public policies towards mothers´ health and towards premature births are required.

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