Journal
ADVANCES IN NURSING SCIENCE
Volume 38, Issue 3, Pages 241-251Publisher
LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1097/ANS.0000000000000081
Keywords
adverse patient outcomes; big data science; conceptual model; health information technology; nurse continuity; nurse staffing
Categories
Funding
- National Institutes of Health, National Institute of Nursing Research [RO1 NR012949]
- Agency for Healthcare Research and Quality [1R36HS023072-01]
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The influence of the staffing variable relational nurse continuity on patient outcomes has been rarely studied and with inconclusive results. Multiple definitions and an absence of systematic methods for measuring the influence of continuity have resulted in its exclusion from nurse-staffing studies and conceptual models. We present a new conceptual model and an innovative use of health information technology to measure relational nurse continuity and to demonstrate the potential for bringing the results of big data science back to the bedside. Understanding the power of big data to address critical clinical issues may foster a new direction for nursing administration theory development.
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