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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
Results First Posted : February 14, 2018
Last Update Posted : February 14, 2018
Sponsor:
Information provided by (Responsible Party):
Washington University School of Medicine

Brief Summary:
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.

Condition or disease Intervention/treatment Phase
Escalation of Care Cardiopulmonary Arrest Respiratory Arrest Severe Sepsis Septic Shock Behavioral: EWS Nursing Alerts Device: Wireless Remote Sensor Not Applicable

Study Type : Interventional  (Clinical Trial)
Actual Enrollment : 20031 participants
Allocation: Randomized
Intervention Model: Crossover Assignment
Intervention Model Description: Random allocation of study wards to intervention and control, with washout period and crossover of assignment.
Masking: None (Open Label)
Primary Purpose: Prevention
Official Title: Early Warning System for Clinical Deterioration on General Hospital Wards.
Study Start Date : January 2011
Actual Primary Completion Date : May 2012
Actual Study Completion Date : May 2012

Resource links provided by the National Library of Medicine


Arm Intervention/treatment
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
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.




Primary Outcome Measures :
  1. 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 or death within 24 hrs of identification by the EWS algorithm for intervention and control wards.


Secondary Outcome Measures :
  1. Clinical Outcomes and Process Measures [ Time Frame: Hospital discharge ]
    length of stay



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Ages Eligible for Study:   18 Years and older   (Adult, Older Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
Criteria

Inclusion Criteria:

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

Exclusion Criteria:

  • Minors, patients younger than 18 years old.

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT01280942


Locations
United States, Missouri
Barnes Jewish Hospital
Saint Louis, Missouri, United States, 63108
Sponsors and Collaborators
Washington University School of Medicine
Investigators
Principal Investigator: Thomas C Bailey, MD Washington University School of Medicine

Publications of Results:
Responsible Party: Washington University School of Medicine
ClinicalTrials.gov Identifier: NCT01280942     History of Changes
Other Study ID Numbers: 10-0514
7322-01 ( Other Grant/Funding Number: BJH Foundation/ICTS )
First Posted: January 21, 2011    Key Record Dates
Results First Posted: February 14, 2018
Last Update Posted: February 14, 2018
Last Verified: February 2018

Keywords provided by Washington University School of Medicine:
clinical deterioration
detection algorithms
automated warning systems

Additional relevant MeSH terms:
Heart Arrest
Shock, Septic
Sepsis
Apnea
Heart Diseases
Cardiovascular Diseases
Infection
Systemic Inflammatory Response Syndrome
Inflammation
Pathologic Processes
Shock
Respiration Disorders
Respiratory Tract Diseases
Signs and Symptoms, Respiratory
Signs and Symptoms