使用护理最小数据集（NMDS和NMMDS）及统一医院出院数据集（UHDDS）存储库来描述患者问题及护理治疗模式。
Describing patient problems & nursing treatment patterns using nursing minimum data sets (NMDS & NMMDS) & UHDDS repositories.
作者信息
Delaney C, Reed D, Clarke M
机构信息
University of Iowa, Iowa City, Iowa, USA.
出版信息
Proc AMIA Symp. 2000:176-9.
Dramatic changes in health care have intensified practitioners' efforts to access and use information to determine more efficacious approaches to patient outcomes. The overall goal of the study is to measure the influence of nursing informatics clinical reasoning decision support interventions on patient outcomes. This paper describes Phases I of the study: the methodology for establishing and testing the usefulness of large data repositories comprised of three minimum data sets, including the Nursing Minimum Data Set (NMDS), the Nursing Management Minimum Data Set (NMMDS), and the Uniform Hospital Discharge Data Set (UHDDS), and the American Nurses Association Quality Indicators to support effectiveness research. The use of generic data modeling to construct a clinical nursing repository of more than 477,000 electronic records is discussed. Patient problem and treatment profiles, patterns, and variations based on standardized analyzing classifications are described for inpatient adult samples, and nursing and medical diagnosis groups.
医疗保健领域的巨大变革加大了从业者获取和利用信息的力度，以确定更有效的患者治疗方法。该研究的总体目标是衡量护理信息学临床推理决策支持干预措施对患者治疗效果的影响。本文描述了该研究的第一阶段：建立和测试由三个最小数据集组成的大数据存储库的有用性的方法，这三个数据集包括护理最小数据集（NMDS）、护理管理最小数据集（NMMDS）和统一医院出院数据集（UHDDS），以及美国护士协会质量指标以支持有效性研究。讨论了使用通用数据建模构建一个包含超过477,000条电子记录的临床护理存储库。针对成人住院样本、护理和医疗诊断组，描述了基于标准化分析分类的患者问题和治疗概况、模式及差异。
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