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

Crit Care Nurs Clin North Am. 2018 Jun;30(2):273-287. doi: 10.1016/j.cnc.2018.02.009.

Abstract

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.

Keywords: Implementation science; Learning health system; Predictive analytics monitoring; Stakeholder driven design; Streaming design.

MeSH terms

  • Data Interpretation, Statistical*
  • Decision Support Systems, Clinical*
  • Evidence-Based Practice
  • Focus Groups
  • Humans
  • Intensive Care Units
  • Models, Statistical
  • Monitoring, Physiologic / statistics & numerical data
  • Monitoring, Physiologic / trends*