As U.S. health care facilities struggle to fill current registered nurse staffing vacancies, a more critical nurse undersupply is predicted over the next twenty years. In response, many institutions are doubling their efforts to attract and retain nurses. To that end, foreign nurses are increasingly being sought, creating a lucrative business for new recruiting agencies both at home and abroad. This paper examines past and current foreign nurse use as a response to nurse shortages and its implications for domestic and global nurse workforce policies.
The ability to collect and store data has grown at a dramatic rate in all disciplines over the past two decades. Healthcare has been no exception. The shift toward evidence-based practice and outcomes research presents significant opportunities and challenges to extract meaningful information from massive amounts of clinical data to transform it into the best available knowledge to guide nursing practice. Data mining, a step in the process of Knowledge Discovery in Databases, is a method of unearthing information from large data sets. Built upon statistical analysis, artificial intelligence, and machine learning technologies, data mining can analyze massive amounts of data and provide useful and interesting information about patterns and relationships that exist within the data that might otherwise be missed. As domain experts, nurse researchers are in ideal positions to use this proven technology to transform the information that is available in existing data repositories into useful and understandable knowledge to guide nursing practice and for active interdisciplinary collaboration and research.
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