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Study of an Electronic Health Record-embedded Severe Sepsis Early Warning Alert

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Read our disclaimer for details.
 
ClinicalTrials.gov Identifier: NCT02376842
Recruitment Status : Completed
First Posted : March 3, 2015
Last Update Posted : November 17, 2015
Sponsor:
Information provided by (Responsible Party):
N. Lance Downing, MD, Stanford University

Brief Summary:
The investigators hypothesize that implementing an electronic health record-based early warning system for severe infections (severe sepsis) will decrease the time to antibiotic order. The study will consist of an algorithm which will monitor lab values, vital signs, and nursing documentation for signs of severe sepsis. When these criteria are met, an alert will be delivered via the electronic health record to a nurse and doctor and simultaneously an alert via pager to another nurse. The investigators plan to randomize which patients will generate these alerts and analyze the data after collecting information for approximately 6 months which will be sufficient to detect a 10% difference in the two patient groups.

Condition or disease Intervention/treatment Phase
Severe Sepsis Behavioral: Severe sepsis early warning best practice alert Behavioral: Standard care Not Applicable

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Study Type : Interventional  (Clinical Trial)
Actual Enrollment : 1149 participants
Allocation: Randomized
Intervention Model: Parallel Assignment
Masking: Single (Care Provider)
Official Title: Single-blind Randomized Trial of a Commercially Sold Electronic Health Record Based Severe Sepsis Early Warning Best Practice Alert.
Study Start Date : November 2014
Actual Primary Completion Date : March 2015
Actual Study Completion Date : March 2015

Resource links provided by the National Library of Medicine

MedlinePlus related topics: Sepsis

Arm Intervention/treatment
Active Comparator: Severe sepsis early warning best practice alert
Patients in this arm will actively generate the alert.
Behavioral: Severe sepsis early warning best practice alert
Placebo Comparator: Standard care
This arm will be the current standard of care and will not generate the alert.
Behavioral: Standard care



Primary Outcome Measures :
  1. Percentage of patients with an antibiotic order within 3 hours of the alert [ Time Frame: 3 hours ]
    Time from when the alert fires until appropriate antibiotics are ordered will be measured via the electronic health record and a sample of cases will be verified by manual chart review.



Information from the National Library of Medicine

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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:

  • Admitted to Stanford Hospital (inpatient or observation status) to any medical or surgical service for at least 24 hours during the period of the study

Exclusion Criteria:

  • Admitted to an intensive-care level service (MICU, SICU, CVICU, CCU)
  • Patient code status is DNR/C (comfort care only)
  • Patients less than 18 years of age at time of admission.
  • Emergency Department patients (may be included in the near future)

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): NCT02376842


Locations
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United States, California
Stanford Hospital
Stanford, California, United States, 94305
Sponsors and Collaborators
Stanford University
Publications of Results:
Other Publications:
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Responsible Party: N. Lance Downing, MD, Principle Investigator, Stanford University
ClinicalTrials.gov Identifier: NCT02376842    
Other Study ID Numbers: 3675309
First Posted: March 3, 2015    Key Record Dates
Last Update Posted: November 17, 2015
Last Verified: November 2015
Keywords provided by N. Lance Downing, MD, Stanford University:
severe sepsis infection
Additional relevant MeSH terms:
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Sepsis
Toxemia
Infections
Systemic Inflammatory Response Syndrome
Inflammation
Pathologic Processes