Nursing Needs Big Data and Big Data Needs Nursing
Nursing Needs Big Data and Big Data Needs Nursing
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DOI：
10.1111/jnu.12159
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发表时间：
2015-09-01
影响因子：
3.4
通讯作者：
Bakken, Suzanne
中科院分区：
文献类型：
--
作者：
Brennan, Patricia Flatley;Bakken, Suzanne
目的当代医疗保健中的大数据计划将受益于与护理科学和护理实践的更好整合；反过来，护理科学和护理实践将从数据科学倡议中获益良多。大数据仅次于学术研究(例如，组学)和心脏血流传感器或Twitter订阅等日常观察。新兴的数据科学方法确保利用这些数据来改善患者护理。组织构建大数据包含超出人类理解的数据，这些数据以标准计算机系统无法管理的数量存在，到达的速度不受研究人员的控制，并且具有传统查询中找不到的不精确程度。管理大数据并从中获得洞察力的数据科学方法正在兴起。方法主要方法包括调查新兴的联邦大数据倡议，以及探索从护理信息学研究到护理已经准备好参与大数据革命的基准的范例。结论现有的大数据分析方法为护理参与大数据革命提供了必要但不充分的基础。护士的社会政策声明指导了大数据和数据科学的原则性、伦理视角。这对实践中的基础和高级临床护士、与数据科学家合作的护士科学家以及护士数据科学家都有意义。临床关系大数据和数据科学有可能在理解患者现象和定制针对患者的个性化干预策略方面提供更丰富的内容。
PurposeContemporary big data initiatives in health care will benefit from greater integration with nursing science and nursing practice; in turn, nursing science and nursing practice has much to gain from the data science initiatives. Big data arises secondary to scholarly inquiry (e.g., -omics) and everyday observations like cardiac flow sensors or Twitter feeds. Data science methods that are emerging ensure that these data be leveraged to improve patient care.Organizing ConstructBig data encompasses data that exceed human comprehension, that exist at a volume unmanageable by standard computer systems, that arrive at a velocity not under the control of the investigator and possess a level of imprecision not found in traditional inquiry. Data science methods are emerging to manage and gain insights from big data.MethodsThe primary methods included investigation of emerging federal big data initiatives, and exploration of exemplars from nursing informatics research to benchmark where nursing is already poised to participate in the big data revolution. We provide observations and reflections on experiences in the emerging big data initiatives.ConclusionsExisting approaches to large data set analysis provide a necessary but not sufficient foundation for nursing to participate in the big data revolution. Nursing's Social Policy Statement guides a principled, ethical perspective on big data and data science. There are implications for basic and advanced practice clinical nurses in practice, for the nurse scientist who collaborates with data scientists, and for the nurse data scientist.Clinical RelevanceBig data and data science has the potential to provide greater richness in understanding patient phenomena and in tailoring interventional strategies that are personalized to the patient.