# Communicating narrative Concerns entered by RNs (CONCERN)

> **NIH NIH R01** · COLUMBIA UNIVERSITY HEALTH SCIENCES · 2020 · $595,773

## Abstract

PROJECT SUMMARY/ABSTRACT
Annually, more than 200,000 patients die in U.S. hospitals from cardiac arrest1 and over 130,000 patients
inpatients deaths are attributed to sepsis.2 These deaths are preventable if patients who are at risk are
detected earlier. Our prior work found that nursing documentation within electronic health records (EHRs)
contains information that could contribute to early detection and treatment, but these data are not being
analyzed and exposed by EHRs to clinicians to initiate interventions quickly enough to save patients.3–6 We
defined a new source of predictive data by analyzing the frequency and types of nursing documentation that
indicated nurses' increased surveillance and level of concern for a patient. These data documented in the 48
hours preceding a cardiac arrest and hospital mortality were predictive of the event.3 While clinicians strive to
provide the best care, there is a systematic problem within hospital settings of non-optimal communication
between nurses and doctors leading to delays in care for patient at risk.6–8,9 Well-designed and tested EHRs
are able to trend data and support communication and decision making, but too often fall short of these goals
and actually increase clinician cognitive load through fragmented information displays, “note bloat”, and
information overload.10 Substitutable Medical Applications & Reusable Technologies (SMARTapps) using Fast
Health Interoperability Resource (FHIR) standard allow for open sharing and use of innovations across EHR
systems. The aim of this project is to design and evaluate a SMARTapp on FHIR used across two large
academic medical centers that exposes to physicians and nurses our new predictive data source from
nursing documentation to increase care team situational awareness of at risk patients to decrease
preventable adverse outcomes. The SMARTapp we will design and evaluate is the Communicating
Narrative Concerns Entered by RNs (CONCERN) Clinical Decision Support (CDS) system. This will be
integrated at four hospitals part of two health systems, Brigham and Women's Hospital (BWH) and Newton
Wellesley Hospital (NWH), part of Partners Healthcare System (PHS) in Boston, and NewYork-Presbyterian
Hospital-Columbia University Medical Center (NYP-CUMC) and The Allen Hospital, part of New York
Presbyterian Health System (NYP) in New York. Specifically, we will: 1) validate desired thresholds for the
CONCERN SMARTapp, 2) integrate the CONCERN SMARTapp for early warning of risky patient states within
CDS tools, 3) evaluate the CONCERN SMARTapp on primary outcomes of in-hospital mortality and length of
stay and secondary outcomes of cardiac arrest, unanticipated transfers to the intensive care unit, and 30-day
hospital readmission rates. The methods we will use include: data-mining and natural language processing,
factorial design surveys, simulation testing for evaluating team-based situational awareness, and outcomes
evaluation in the Medical Intensive Care Units...

## Key facts

- **NIH application ID:** 9869048
- **Project number:** 5R01NR016941-04
- **Recipient organization:** COLUMBIA UNIVERSITY HEALTH SCIENCES
- **Principal Investigator:** Kenrick Dwain Cato
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $595,773
- **Award type:** 5
- **Project period:** 2017-04-06 → 2023-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9869048

## Citation

> US National Institutes of Health, RePORTER application 9869048, Communicating narrative Concerns entered by RNs (CONCERN) (5R01NR016941-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9869048. Licensed CC0.

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