Mining routinely collected acute data to reveal non-linear relationships between nurse staffing levels and outcomes
Abstract
Objectives
Nursing is a safety critical activity but not easily quantified. This makes the building of predictive staffing models a challenge. The aim of this study was to determine if relationships between registered and non-registered nurse staffing levels and clinical outcomes could be discovered through the mining of routinely collected clinical data. The secondary aim was to examine the feasibility and develop the use of ‘big data’...Paper Details
Title
Mining routinely collected acute data to reveal non-linear relationships between nurse staffing levels and outcomes
Published Date
Dec 1, 2016
Journal
Volume
6
Issue
12
Pages
e011177 - e011177
Citation AnalysisPro
You’ll need to upgrade your plan to Pro
Looking to understand the true influence of a researcher’s work across journals & affiliations?
- Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
- Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.
Notes
History