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Early Warning System for Clinical Deterioration on General Hospital Wards

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ClinicalTrials.gov Identifier: NCT01280942
Recruitment Status : Completed
First Posted : January 21, 2011
Last Update Posted : July 27, 2012
Information provided by (Responsible Party):

January 19, 2011
January 21, 2011
July 27, 2012
January 2011
May 2012   (Final data collection date for primary outcome measure)
Transfer to ICU or unexpected death within 24 hrs of identification by the EWS algorithm [ Time Frame: Within 24 hrs of an EWS alert ]
The proportion of patients transferred to ICU, and the time from EWS detection to ICU transfer in patients, for intervention and control wards.
Same as current
Complete list of historical versions of study NCT01280942 on ClinicalTrials.gov Archive Site
Clinical outcomes and process measures [ Time Frame: Hospital discharge (avg = 3 days) ]
Processes of care (fluid rescuscitation, escalation of antibiotics), length of stay, acquired organ dysfunction, and causes of CPR or ICU transfer
Same as current
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Early Warning System for Clinical Deterioration on General Hospital Wards
Early Warning System for Clinical Deterioration on General Hospital Wards.
The goal is to develop a two-tiered monitoring system to improve the care of patients at risk for clinical deterioration on general hospital wards (GHWs) at Barnes-Jewish Hospital (BJH). The investigators hypothesize that the use of an automated early warning system (EWS) that identifies patients at risk of clinical deterioration, with notification of nurses on the GHWs when patients are identified, will reduce the risk of ICU transfer or death within 24 hrs of an alert. As a substudy, the investigators will pilot the use of a wireless pulse oximeter to establish feasibility and to develop algorithms for a real-time event detection system (RDS) in these high-risk patients.
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Allocation: Randomized
Intervention Model: Crossover Assignment
Masking: None (Open Label)
Primary Purpose: Prevention
  • Escalation of Care
  • Cardiopulmonary Arrest
  • Respiratory Arrest
  • Severe Sepsis
  • Septic Shock
  • Behavioral: EWS Nursing Alerts
    An automated algorithm (EWS) will identify patients at potential risk of clinical deterioration. When a patient satisfies the algorithm, a nurse on the patient's ward will be notified. S/he will assess the patient and institute any interventions that are clinically required.
  • Device: Wireless Remote Sensor
    A subset of patients will be consented to wear a wireless sensor device which will monitor heart rate and level of oxygen in the blood.
  • No Intervention: Control
    Patients admitted to 4 GHWs designated as controls. Nurses will not be notified when patients on these GHWs satisfy the EWS algorithm. They will also not wear the wireless sensor devices.
  • Experimental: Nurse notification of EWS alert
    Patients admitted to 4 GHWs designated as intervention wards at BJH. Nurses will be notified when patients on these wards satisfy the EWS algorithm. Some patients will be asked to wear the wireless remote sensors.
    • Behavioral: EWS Nursing Alerts
    • Device: Wireless Remote Sensor
Bailey TC, Chen Y, Mao Y, Lu C, Hackmann G, Micek ST, Heard KM, Faulkner KM, Kollef MH. A trial of a real-time alert for clinical deterioration in patients hospitalized on general medical wards. J Hosp Med. 2013 May;8(5):236-42. doi: 10.1002/jhm.2009. Epub 2013 Feb 25.

*   Includes publications given by the data provider as well as publications identified by ClinicalTrials.gov Identifier (NCT Number) in Medline.
May 2012
May 2012   (Final data collection date for primary outcome measure)

Inclusion Criteria:

  • All patients age 18 and above, hospitalized in GHWs at Barnes Jewish Hospital.

Exclusion Criteria:

  • Minors, patients younger than 18 years old.
Sexes Eligible for Study: All
18 Years and older   (Adult, Senior)
Contact information is only displayed when the study is recruiting subjects
United States
7322-01 ( Other Grant/Funding Number: BJH Foundation/ICTS )
Not Provided
Not Provided
Tom Bailey, MD, Washington University
Tom Bailey, MD
Not Provided
Principal Investigator: Thomas C Bailey, MD Washington University School of Medicine
Washington University School of Medicine
July 2012

ICMJE     Data element required by the International Committee of Medical Journal Editors and the World Health Organization ICTRP