AIM: The study aims to describe the impacts of different data structuring methods used in nursing records or care plans. This systematic review examines what kinds of structuring methods have been evaluated and the effects of data structures on healthcare input, processes and outcomes in previous studies. MATERIALS AND METHODS: Retrieval from 15 databases yielded 143 papers. Based on Population (Participants), Intervention, Comparators, Outcomes elements and exclusion and inclusion criteria, the search produced 61 studies. A data extraction tool and analysis for empirical articles were used to classify the data referring to the study aim. Thirty-eight studies were included in the final analysis. FINDINGS: The study design most often used was a single measurement without any control. The studies were conducted mostly in secondary or tertiary care in institutional care contexts. The standards used in documentation were nursing classifications or the nursing process model in clinical use. The use of standardised nursing language (SNL) increased descriptions of nursing interventions and outcomes supporting daily care, and improving patient safety and information reuse. DISCUSSION: The nursing process model and classifications are used internationally as nursing data structures in nursing records and care plans. The use of SNL revealed various positive impacts. Unexpected outcomes were most often related to lack of resources. LIMITATIONS: Indexing of SNL studies has not been consistent. That might cause bias in database retrieval, and important articles may be lacking. The study design of the studies analysed varied widely. Further, the time frame of papers was quite long, causing confusion in descriptions of nursing data structures. CONCLUSION: The value of SNL is proven by its support of daily workflow, delivery of nursing care and data reuse. This facilitates continuity of care, thus contributing to patient safety. Nurses need more education and managerial support in order to be able to benefit from SNL.
AIM: The study aims to describe the impacts of different data structuring methods used in nursing records or care plans. This systematic review examines what kinds of structuring methods have been evaluated and the effects of data structures on healthcare input, processes and outcomes in previous studies. MATERIALS AND METHODS: Retrieval from 15 databases yielded 143 papers. Based on Population (Participants), Intervention, Comparators, Outcomes elements and exclusion and inclusion criteria, the search produced 61 studies. A data extraction tool and analysis for empirical articles were used to classify the data referring to the study aim. Thirty-eight studies were included in the final analysis. FINDINGS: The study design most often used was a single measurement without any control. The studies were conducted mostly in secondary or tertiary care in institutional care contexts. The standards used in documentation were nursing classifications or the nursing process model in clinical use. The use of standardised nursing language (SNL) increased descriptions of nursing interventions and outcomes supporting daily care, and improving patient safety and information reuse. DISCUSSION: The nursing process model and classifications are used internationally as nursing data structures in nursing records and care plans. The use of SNL revealed various positive impacts. Unexpected outcomes were most often related to lack of resources. LIMITATIONS: Indexing of SNL studies has not been consistent. That might cause bias in database retrieval, and important articles may be lacking. The study design of the studies analysed varied widely. Further, the time frame of papers was quite long, causing confusion in descriptions of nursing data structures. CONCLUSION: The value of SNL is proven by its support of daily workflow, delivery of nursing care and data reuse. This facilitates continuity of care, thus contributing to patient safety. Nurses need more education and managerial support in order to be able to benefit from SNL.
Authors: Hans Moen; Kai Hakala; Laura-Maria Peltonen; Henry Suhonen; Filip Ginter; Tapio Salakoski; Sanna Salanterä Journal: J Am Med Inform Assoc Date: 2020-01-01 Impact factor: 4.497
Authors: Hans Moen; Kai Hakala; Laura-Maria Peltonen; Hanna-Maria Matinolli; Henry Suhonen; Kirsi Terho; Riitta Danielsson-Ojala; Maija Valta; Filip Ginter; Tapio Salakoski; Sanna Salanterä Journal: J Biomed Semantics Date: 2020-09-01