Advancing Continuous Predictive Analytics Monitoring
| Autor: | Kevin Sullivan, J. Randall Moorman, James Forrest Calland, Rebecca R. Kitzmiller, Angela D. Skeeles-Worley, Jessica Keim-Malpass, Matthew T. Clark, Curt Lindberg, Robert H. Tai, Ruth A. Anderson |
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| Rok vydání: | 2018 |
| Předmět: |
business.industry
Early signs 030208 emergency & critical care medicine Context (language use) Predictive analytics Critical Care Nursing Data science Variety (cybernetics) 03 medical and health sciences 0302 clinical medicine Workflow Action (philosophy) Medicine 030212 general & internal medicine business |
| Zdroj: | Critical Care Nursing Clinics of North America. 30:273-287 |
| ISSN: | 0899-5885 |
| DOI: | 10.1016/j.cnc.2018.02.009 |
| Popis: | In the intensive care unit, clinicians monitor a diverse array of data inputs to detect early signs of impending clinical demise or improvement. Continuous predictive analytics monitoring synthesizes data from a variety of inputs into a risk estimate that clinicians can observe in a streaming environment. For this to be useful, clinicians must engage with the data in a way that makes sense for their clinical workflow in the context of a learning health system (LHS). This article describes the processes needed to evoke clinical action after initiation of continuous predictive analytics monitoring in an LHS. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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