Maas Meridean L, Delaney Connie
John A Hartford Center of Geriatric Nursing Excellence, University of Iowa Health College of Nursing, Iowa City 52246, USA.
Med Care. 2004 Feb;42(2 Suppl):II40-8. doi: 10.1097/01.mlr.0000109291.44014.cb.
The use of large clinical datasets to assess the effectiveness of health care is of growing interest in continuing efforts to understand the impact of healthcare costs on quality. Correspondingly, there is a greater need to define and measure outcomes that are sensitive to nursing interventions. However, concerns exist about the ability to amass and use large clinical nursing datasets to assess the effectiveness of nursing interventions. Some nursing studies have used large clinical datasets to examine patterns of nursing diagnoses, interventions, and outcomes. Among patient populations, however, systematic effectiveness studies of nursing process and outcome linkages at the individual nurse and patient level of analysis are essentially nonexistent. This is largely the result of slow development of nursing classifications, reference terminologies, and reference information standards. Nursing information systems have an unprecedented potential for documentation of nursing practice, as well as the accumulation and analysis of large clinical datasets, to improve nursing performance, increase nursing knowledge, and provide data and information necessary for nursing to participate in the formulation of healthcare policy.
A literature search shows that a common framework is beginning to evolve that represents nursing's essential information, eg, the Nursing Minimum Data Set, Management Minimum Data Set, and several standardized nursing languages. Extensive research and other initiatives have produced 1) nursing languages and reference terminologies that span healthcare settings; 2) information models; and 3) standards for datasets supporting information systems. A number of issues remain, however, that concern the development of uniform nursing datasets, definitions of outcomes, quality of nursing data, information system design, and methods of data analysis. We review nursing process outcome research, clarify issues inherent in nursing effectiveness research, and discuss implications for nursing and health policy.
利用大型临床数据集来评估医疗保健的有效性，在持续努力理解医疗成本对质量的影响方面，正日益受到关注。相应地，更有必要定义和衡量对护理干预敏感的结果。然而，对于收集和使用大型临床护理数据集来评估护理干预的有效性，人们存在担忧。一些护理研究已使用大型临床数据集来检查护理诊断、干预措施及结果的模式。然而，在患者群体中，在个体护士和患者层面分析护理过程与结果联系的系统性有效性研究基本不存在。这主要是由于护理分类、参考术语和参考信息标准发展缓慢所致。护理信息系统在记录护理实践以及积累和分析大型临床数据集方面具有前所未有的潜力，可用于改善护理绩效、增加护理知识，并提供护理参与制定医疗保健政策所需的数据和信息。
文献检索表明，一个代表护理基本信息的通用框架正开始形成，例如护理最小数据集、管理最小数据集以及几种标准化护理语言。广泛的研究和其他举措已产生了：1）涵盖医疗保健环境的护理语言和参考术语；2）信息模型；3）支持信息系统的数据集标准。然而，仍存在一些问题，涉及统一护理数据集的开发、结果定义、护理数据质量、信息系统设计以及数据分析方法。我们回顾护理过程结果研究，阐明护理有效性研究中固有的问题，并讨论对护理和卫生政策的影响。
