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Mining a spinal cord injury clinical database for nursing information: A source of nursing knowledge.

机译:挖掘脊髓损伤临床数据库以获取护理信息:护理知识的来源。

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摘要

This is a descriptive exploratory analysis of a spinal cord injury (SCI) database from a mid-western Veterans' Administration (VA) hospital. The computerization of practice data elements including diagnoses, interventions and patient acuity provides the opportunity to explore the domain of SCI nursing practice from an actual practice perspective. Data mining techniques are used to determine if there are trends, patterns, or relationships in nursing diagnoses and nursing interventions that provide useful information that can contribute to knowledge about this specialty nursing practice. The theoretical framework of the study is Systems Theory and a model is presented to illustrate how data is processed and organized to become information and levels of knowledge.; The study population of 525 unique patients represents 1107 hospital admissions and 74,047 days of hospital care. Thirty-four percent of this veteran population is identified as service-connected for a spinal cord injury with most common level of injury at the C4-6 level resulting in quadriplegia. Frequency of admissions and lengths of stay reinforce the position of persons with SCI as outliers in the healthcare system. Eleven years of data reviewed indicate a stable pattern of nursing diagnoses and interventions in this setting. The 4750 diagnostic labels in the database are shown to represent 161 nursing diagnoses that are clustered into 20 diagnostic categories. These categories are used as variables in the development of four models of neural nets used to determine their predictive power as related to LOS. All four neural net models indicate that the diagnostic categories achieve over a 77% accuracy rate in the prediction of LOS. An awareness of the stable patterns of clustered nursing diagnoses and nursing interventions in this database can be useful in planning for resource allocation, competency identification, and orientation to this specialty nursing practice.; Study results identify as issues in nursing database research the need for the inclusion of nursing data in hospital information systems, the need for standardized language in data capture, and the need to include nursing data in data warehouses. Nursing data must be used to generate information that validates the impact of nursing care, supports nursing research, and ensures that nursing has a voice in the development of healthcare policy.
机译:这是对中西部退伍军人管理局(VA)医院的脊髓损伤(SCI)数据库的描述性探索性分析。包括诊断,干预和患者敏锐度在内的实践数据元素的计算机化提供了从实际实践的角度探索SCI护理实践领域的机会。数据挖掘技术用于确定护理诊断和护理干预措施中是否存在趋势,模式或关系,这些趋势,模式或关系提供有用的信息,这些信息可有助于特定专业护理实践的知识。该研究的理论框架是系统理论,并提出了一个模型来说明如何处理和组织数据以成为信息和知识水平。 525名独特患者的研究人群代表1107例入院和74,047天的住院治疗。该退伍军人中有34%被确定与脊髓损伤相关,其中最常见的损伤水平为C4-6,导致四肢瘫痪。入院频率和住院时间可加强SCI患者在医疗保健系统中的地位。回顾了11年的数据表明,在这种情况下,护理诊断和干预措施具有稳定的模式。数据库中的4750个诊断标签显示为代表161个护理诊断,这些诊断被分为20个诊断类别。这些类别在开发用于确定其与LOS相关的预测能力的四种神经网络模型中用作变量。所有四个神经网络模型均表明,诊断类别在LOS预测中的准确率超过77%。了解该数据库中聚集的护理诊断和护理干预措施的稳定模式,对于规划资源分配,能力识别以及对这种专业护理实践的定位很有帮助。研究结果确定了在护理数据库研究中需要将护理数据包括在医院信息系统中,在数据捕获中需要使用标准化语言以及在数据仓库中包括护理数据是需要解决的问题。必须使用护理数据来生成信息,以验证护理的影响,支持护理研究并确保护理在医疗保健政策的制定中具有发言权。

著录项

  • 作者

    Kraft, Margaret Ross.;

  • 作者单位

    Loyola University of Chicago.;

  • 授予单位 Loyola University of Chicago.;
  • 学科 Health Sciences Nursing.
  • 学位 Ph.D.
  • 年度 2003
  • 页码 275 p.
  • 总页数 275
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 预防医学、卫生学;
  • 关键词

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