Concern Toolkit

Communicating Narrative Concerns Entered by RNs:
The CONCERN algorithm predicts patient decline based on nursing documentation

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.

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.


• American Nurses Foundation Reimagining Nursing Initiative (RN Initiative)
Project Title:
CONCERN Implementation Toolkit: Advancing technology-enabled nursing expertise and equitable predictions 

• National Institute of Nursing Research (NINR)
Grant #: 1R01NR016941-01 Communicating Narrative Concerns Entered by RNs (CONCERN): Clinical Decision Support Communication for Risky Patient States

What is CONCERN?

Toolkit Resources