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CONCERN Implementation Toolkit

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Consolidating nurse knowledge, perception, and expertise to create predictive tools that provide early warnings about deteriorating patient health

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Problem

Nurse expertise includes the ability to pick up cues about patients’ health from subtle changes in behavior or appearance. Nurses share these clinical assessments in patients’ electronic health records—both in the content of their comments and when and how often they make them. Unfortunately, these assessments are often buried in form fields and not analyzed as a whole. As a result, the insights are often overlooked by care teams in favor of measures seen as more objective. This can make it difficult for nurses to engage the care team when they feel patients are at risk.

What We Are Doing

CONCERN (COmmunicating Narrative Concerns Entered by RNs) is a predictive tool that extracts nurses’ expert and knowledge-driven behaviors within patient health records and transforms them into observable data that support early prediction of organ failure or other critical conditions in hospitalized patients. CONCERN has been positively accepted by clinicians and a clinical trial is currently underway. To scale this success, Columbia University Irving Medical Center in New York will partner with three hospital systems—Mass General Brigham in Massachusetts, Vanderbilt University Medical Center in Tennessee, and Washington University School of Medicine/Barnes-Jewish Hospital in St. Louis, Missouri—to test the effectiveness of their implementation toolkit, developed to support large-scale adoption of the tool.

Sarah Collins Rossetti Assistant Professor of Biomedical Informatics and Nursing, Columbia University Irving Medical Center
CONCERN shows what nurses already know: Our risk identification is not simply a subjective ‘clinical hunch’. We’re demonstrating that nurses have objective, expert-based knowledge that drives their practice, and we’re positioning nurses as knowledge workers with tremendous value to the entire care team.

 

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