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KMID : 1155220170420030223
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Journal of the Korean Society of Health Information and Health Statistics
2017 Volume.42 No. 3 p.223 ~ p.231
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The Network Analysis of Nursing Diagnoses for Children Admitted in Pediatric Units Determined by Nursing Students
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Moon Mi-Kyung
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Abstract
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Objectives: The purpose of this study was to identify key nursing diagnoses and sub groups of nursing diagnoses for children admitted in pediatric units using a Network Analysis.
Method: Data were obtained from 205 case reports submitted from nursing students who had done a clinical practicum in pediatric units. Five hundred and twenty-four NANDA-I nursing diagnoses were extracted from the case reports. Frequency, Centrality, and Clusters were generated by Network analysis with NetMiner 4.0.
Results: Seventy eight different nursing diagnoses were identified. In general pediatric nursing units, Hyperthermia was the most frequently used and highest degree centrality diagnosis. Ineffective airway clearness showed the highest between centrality. In a pediatric intensive care unit, Impaired gas exchange showed the highest frequency, degree centrality, and between centrality. Four sub-groups in general pediatric nursing units and 2 sub-groups in a pediatric intensive care unit were identified.
Conclusions: The results from this study could support clinical decision for selecting nursing diagnoses accurately and promptly.
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KEYWORD
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NANDA-international, Network analysis, Nursing diagnosis, Pediatric nursing
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