{"title":"数据转换:概念分析。","authors":"Shuhong Luo, Hongwei Wang","doi":"10.1111/nuf.12801","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>The aims of this study are to clarify the concept of how data retrieved from electronic health records (EHR) are transformed into nurses' tacit knowledge for evidence-based practice from a cognitive perspective at a macro-organizational level, and to identify this concept's attributes, antecedents, and consequences in the nursing field.</p><p><strong>Source: </strong>A literature review was conducted by performing a search on scientific databases using the key terms \"data,\" \"transform,\" \"EHR,\" \"nursing,\" \"tacit knowledge,\" \"organization,\" \"data,\" \"interpretation,\" and \"healthcare.\" Forty-nine articles and four books were selected for the analysis. The process was audited by two independent experts to ensure neutrality and credibility.</p><p><strong>Conclusion: </strong>Data transforming is a complex cognitive process among different groups of data stakeholders at a macro-organizational level. The concept of data transforming has three attributes: analytical, respectful, and social. The antecedents of these attributes are skillful, immersive, and mission-driven. They have either positive or negative consequences for frontline nurses. These findings not only add to the body of knowledge but also serve as an important impetus for further theory development and research in nursing.</p>","PeriodicalId":51525,"journal":{"name":"NURSING FORUM","volume":"57 6","pages":"1491-1500"},"PeriodicalIF":2.2000,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Data transforming: A concept analysis.\",\"authors\":\"Shuhong Luo, Hongwei Wang\",\"doi\":\"10.1111/nuf.12801\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose: </strong>The aims of this study are to clarify the concept of how data retrieved from electronic health records (EHR) are transformed into nurses' tacit knowledge for evidence-based practice from a cognitive perspective at a macro-organizational level, and to identify this concept's attributes, antecedents, and consequences in the nursing field.</p><p><strong>Source: </strong>A literature review was conducted by performing a search on scientific databases using the key terms \\\"data,\\\" \\\"transform,\\\" \\\"EHR,\\\" \\\"nursing,\\\" \\\"tacit knowledge,\\\" \\\"organization,\\\" \\\"data,\\\" \\\"interpretation,\\\" and \\\"healthcare.\\\" Forty-nine articles and four books were selected for the analysis. The process was audited by two independent experts to ensure neutrality and credibility.</p><p><strong>Conclusion: </strong>Data transforming is a complex cognitive process among different groups of data stakeholders at a macro-organizational level. The concept of data transforming has three attributes: analytical, respectful, and social. The antecedents of these attributes are skillful, immersive, and mission-driven. They have either positive or negative consequences for frontline nurses. These findings not only add to the body of knowledge but also serve as an important impetus for further theory development and research in nursing.</p>\",\"PeriodicalId\":51525,\"journal\":{\"name\":\"NURSING FORUM\",\"volume\":\"57 6\",\"pages\":\"1491-1500\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2022-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"NURSING FORUM\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1111/nuf.12801\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"NURSING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"NURSING FORUM","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1111/nuf.12801","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"NURSING","Score":null,"Total":0}
Purpose: The aims of this study are to clarify the concept of how data retrieved from electronic health records (EHR) are transformed into nurses' tacit knowledge for evidence-based practice from a cognitive perspective at a macro-organizational level, and to identify this concept's attributes, antecedents, and consequences in the nursing field.
Source: A literature review was conducted by performing a search on scientific databases using the key terms "data," "transform," "EHR," "nursing," "tacit knowledge," "organization," "data," "interpretation," and "healthcare." Forty-nine articles and four books were selected for the analysis. The process was audited by two independent experts to ensure neutrality and credibility.
Conclusion: Data transforming is a complex cognitive process among different groups of data stakeholders at a macro-organizational level. The concept of data transforming has three attributes: analytical, respectful, and social. The antecedents of these attributes are skillful, immersive, and mission-driven. They have either positive or negative consequences for frontline nurses. These findings not only add to the body of knowledge but also serve as an important impetus for further theory development and research in nursing.
期刊介绍:
Nursing Forum is a peer-reviewed quarterly journal that invites original manuscripts that explore, explicate or report issues, ideas, trends and innovations that shape the nursing profession. Research manuscripts should emphasize the implications rather than the methods or analysis. Quality improvement manuscripts should emphasize the outcomes and follow the SQUIRE Guidelines in creating the manuscript. Evidence-based manuscripts should emphasize the findings and implications for practice and follow PICOT format. Concept analysis manuscripts should emphasize the evidence for support of the concept and follow an accepted format for such analyses.