Advancing Continuous Predictive Analytics Monitoring: Moving from Implementation to Clinical Action in a Learning Health System.

Journal Article (Journal Article)

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.

Full Text

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Duke Authors

Anderson, Ruth A.

Cited Authors

Keim-Malpass, J; Kitzmiller, RR; Skeeles-Worley, A; Lindberg, C; Clark, MT; Tai, R; Calland, JF; Sullivan, K; Randall Moorman, J; Anderson, RA

Published Date

June 2018

Published In

Critical Care Nursing Clinics of North America

Volume / Issue

30 / 2

Start / End Page

273 - 287

PubMed ID

29724445

Electronic International Standard Serial Number (EISSN)

1558-3481

International Standard Serial Number (ISSN)

0899-5885

Digital Object Identifier (DOI)

10.1016/j.cnc.2018.02.009

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