Early Warning System for Clinical Deterioration on General Hospital Wards

NCT ID: NCT01280942

Last Updated: 2018-02-14

Study Results

Results available

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Basic Information

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Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

20031 participants

Study Classification

INTERVENTIONAL

Study Start Date

2011-01-31

Study Completion Date

2012-05-31

Brief Summary

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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.

Detailed Description

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Conditions

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Escalation of Care Cardiopulmonary Arrest Respiratory Arrest Severe Sepsis Septic Shock

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

CROSSOVER

Random allocation of study wards to intervention and control, with washout period and crossover of assignment.
Primary Study Purpose

PREVENTION

Blinding Strategy

NONE

Study Groups

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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.

Group Type NO_INTERVENTION

No interventions assigned to this group

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.

Group Type EXPERIMENTAL

EWS Nursing Alerts

Intervention Type BEHAVIORAL

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.

Wireless Remote Sensor

Intervention Type DEVICE

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.

Interventions

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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.

Intervention Type BEHAVIORAL

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.

Intervention Type DEVICE

Eligibility Criteria

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Inclusion Criteria

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

Exclusion Criteria

* Minors, patients younger than 18 years old.
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Washington University School of Medicine

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Thomas C Bailey, MD

Role: PRINCIPAL_INVESTIGATOR

Washington University School of Medicine

Locations

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Barnes Jewish Hospital

St Louis, Missouri, United States

Site Status

Countries

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United States

References

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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.

Reference Type RESULT
PMID: 23440923 (View on PubMed)

Other Identifiers

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7322-01

Identifier Type: OTHER_GRANT

Identifier Source: secondary_id

10-0514

Identifier Type: -

Identifier Source: org_study_id

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