Big data and cutting-edge analytic methods in nursing research challenge nurse scientists to extend the data sources and analytic methods used for discovering and translating knowledge.
The purpose of this study was to identify, analyze, and synthesize exemplars of big data nursing research applied to practice and disseminated in key nursing informatics, general biomedical informatics, and nursing research journals.
Big Data, data science, and precision medicine/health research priorities and initiatives are permeating nursing and health care (https://datascience.nih.gov/). The predictable seeds for Big Data, which are characterized by data volume, variability, veracity, velocity, and variety, were planted by the “information explosion” (a term first used 70 years ago in 1941, Oxford English Dictionary).
Nursing Administration Quarterly (NAQ)
Oct-Dec 2015;39(4):333-9
doi: 10.1097/NAQ.0000000000000132
Journal of Nursing Administration (JONA)
Volume 45, Number 10, pp 503-510
Nursing Economics (Nurs Econ)
Jan-Feb 2016;34(1):7-14; quiz 15.
The purpose of this study was to create information models from flowsheet data using a data-driven consensus-based method. Electronic health records contain a large volume of data about patient assessments and interventions captured in flowsheets that measure the same "thing," but the names of these observations often differ, according to who performs documentation or the location of the service (eg, pulse rate in an intensive care, the emergency department, or a surgical unit documented by a nurse or therapist or captured by automated monitoring).
March 2016
Patient engagement is an important element in transitioning care delivery to achieve population health management goals. Providers are challenged to develop care delivery processes that better engage patients in their life journey across the healthcare continuum. Nurse leaders are central to this process. Building upon the American Organization of Nurse Executives competencies for nurse executives, the nurse manager role requires specific skills to translate the vision of patient engagement into practice.
Nursing Economics (Nurs Econ)
Jan-Feb 2015;33(1):14-9, 25
There is a growing body of evidence of the relationship of nurse staffing to patient, nurse, and financial outcomes. With the advent of big data science and developing big data analytics in nursing, data science with the reuse of big data is emerging as a timely and cost-effective approach to demonstrate nursing value. The Nursing Management Minimum Date Set (NMMDS) provides standard administrative data elements, definitions, and codes to measure the context where care is delivered and, consequently, the value of nursing.
Nursing Economics (Nurs Econ)
Mar-Apr 2016;34(2):66-71, 89.