College of Nursing, University of Cincinnati, Cincinnati, Ohio, USA.
James M. Anderson Center for Health Systems Excellence, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA.
Nurs Inq. 2024 Jul;31(3):e12648. doi: 10.1111/nin.12648. Epub 2024 Jun 12.
Big data refers to extremely large data generated at high volume, velocity, variety, and veracity. The nurse scientist is uniquely positioned to leverage big data to suggest novel hypotheses on patient care and the healthcare system. The purpose of this paper is to provide an introductory guide to understanding the use and capability of big data for nurse scientists. Herein, we discuss the practical, ethical, social, and educational implications of using big data in nursing research. Some practical challenges with the use of big data include data accessibility, data quality, missing data, variable data standards, fragmentation of health data, and software considerations. Opposing ethical positions arise with the use of big data, and arguments for and against the use of big data are underpinned by concerns about confidentiality, anonymity, and autonomy. The use of big data has health equity dimensions and addressing equity in data is an ethical imperative. There is a need to incorporate competencies needed to leverage big data for nursing research into advanced nursing educational curricula. Nursing science has a great opportunity to evolve and embrace the potential of big data. Nurse scientists should not be spectators but collaborators and drivers of policy change to better leverage and harness the potential of big data.
大数据是指在高容量、高速率、多样化和真实性下产生的极其庞大的数据。护士科学家在利用大数据提出关于患者护理和医疗保健系统的新假设方面具有独特的优势。本文旨在为护士科学家提供一个理解大数据使用和功能的入门指南。在此，我们讨论了在护理研究中使用大数据的实际、伦理、社会和教育影响。使用大数据的一些实际挑战包括数据可访问性、数据质量、缺失数据、变量数据标准、健康数据碎片化和软件考虑因素。使用大数据会引发对立的伦理立场，支持和反对使用大数据的论点是基于对保密性、匿名性和自主性的担忧。大数据的使用具有公平性，解决数据公平性是一项道德义务。需要将利用大数据进行护理研究所需的能力纳入高级护理教育课程中。护理科学有很大的机会发展并接受大数据的潜力。护士科学家不应该只是旁观者，而应该成为政策变革的合作者和推动者，以更好地利用和利用大数据的潜力。
