Automated Identification of Adults at Risk for In-Hospital Clinical Deterioration

The authors used a validated model with electronic-medical-record data to identify hospitalized patients at high risk for clinical deterioration. The intervention, which involved remote monitoring by nurses who reviewed records of high-risk patients and communicated with in-hospital rapid-response t...

Full description

Saved in:
Bibliographic Details
Published inThe New England journal of medicine Vol. 383; no. 20; pp. 1951 - 1960
Main Authors Escobar, Gabriel J, Liu, Vincent X, Schuler, Alejandro, Lawson, Brian, Greene, John D, Kipnis, Patricia
Format Journal Article
LanguageEnglish
Published United States Massachusetts Medical Society 12.11.2020
Subjects
Adult
Aged
Alert Fatigue, Health Personnel - prevention & control
Automation
Clinical Deterioration
Electronic Health Records
Electronic medical records
Female
Hospital Mortality
Hospitalization
Hospitals
Humans
Laboratories
Laboratory Critical Values
Length of Stay - statistics & numerical data
Male
Middle Aged
Models, Theoretical
Morbidity
Mortality
Multivariate Analysis
Nurses
Nursing Staff, Hospital
Patient Readmission - statistics & numerical data
Patients
Prediction models
Risk Assessment - methods
Risk groups
Teams
Telemetry
Vital signs
Online AccessGet full text

Cover

More Information
Summary:The authors used a validated model with electronic-medical-record data to identify hospitalized patients at high risk for clinical deterioration. The intervention, which involved remote monitoring by nurses who reviewed records of high-risk patients and communicated with in-hospital rapid-response teams, was associated with decreased 30-day mortality.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0028-4793
1533-4406
DOI:10.1056/NEJMsa2001090