Effect of Automated Real-time Feedback on Early Sepsis Care
NCT ID: NCT05625464
Last Updated: 2022-11-23
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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COMPLETED
NA
3269 participants
INTERVENTIONAL
2020-12-01
2021-11-30
Brief Summary
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Unfortunately, a recent study demonstrated that every hour of delay to the completion of a sepsis bundle, including antibiotic administration, was associated with a 4% increase in risk-adjusted hospital mortality.
One strategy to improve the care and outcomes of patients with sepsis is the use of information technology to support our providers in a targeted manner. Technology has already been developed and deployed to help with the early identification of patients with sepsis using a Best Practice Alert (BPA), which has been in place at our hospital since 2017. This pop-up window alerts the team to the possibility of sepsis based on data within the medical record. However, once the alert is accepted or declined, the BPA does not offer ongoing support to clinicians, leaving the clinician to track and execute multiple time-based and inter-dependent sepsis bundle measures in a busy, hectic environment. To augment this existing tool, here we propose to study the efficacy of a novel technology called the Sepsis Care Tracking Platform (SCTP) to provide ongoing support at the bedside to providers, thus improving the care we deliver to patients.
SCTP is a monitoring and notification platform that aims to increase the timely delivery of key elements of evidence-based sepsis care. This platform, which was built by clinicians for clinicians, leverages the electronic medical record (EMR) to track real-time compliance with key components of the CMS SEP-1 bundle - timely antibiotics, blood cultures prior to antibiotics, initial lactate, and repeat lactate for those patients with an initially elevated level. SCTP underwent technical validation in Fall 2019 with a pilot in the MGH Emergency Department. The pilot confirmed that SCTP correctly identified missing bundle elements and paged the appropriate team members connected with the patient's care. The pilot also did not find alarm fatigue to be an issue. We hypothesize that SCTP will increase our hospital's compliance with sepsis process metrics and improve patient outcomes.
By monitoring real-time data and automatically alerting bedside providers to missing elements within an actionable timeframe, SCTP has the potential to drive improvements in clinical care even in the extremely busy and complex environment of the emergency department and inpatient units.
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Detailed Description
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Conditions
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Study Design
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RANDOMIZED
PARALLEL
PREVENTION
TRIPLE
Study Groups
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Intervention
Received SCTP monitoring and standard of care
SCTP
Real-time automated monitoring of the electronic medical record to identify suspected sepsis patients without completion of sepsis bundle measures within 1-hour of the completion deadline and generated reminder pages. Clinicians responsible for patients randomized to the intervention receive reminder pages whereas no pages are sent for control arm patients.
Control
Received standard of care only
No interventions assigned to this group
Interventions
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SCTP
Real-time automated monitoring of the electronic medical record to identify suspected sepsis patients without completion of sepsis bundle measures within 1-hour of the completion deadline and generated reminder pages. Clinicians responsible for patients randomized to the intervention receive reminder pages whereas no pages are sent for control arm patients.
Eligibility Criteria
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Inclusion Criteria
2. Who triggered a sepsis best practice advisory that was subsequently acknowledged by a treating clinician as "yes, sepsis possible"
Exclusion Criteria
2. Sepsis best practice advisory triggered while the patient is in an intensive care unit
3. Sepsis best practice advisory triggered while the patient is in a perioperative care area
18 Years
ALL
No
Sponsors
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Crico
OTHER
Massachusetts General Hospital
OTHER
Responsible Party
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Kyan Safavi
Assistant Professor
Locations
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Massachusetts General Hospital
Boston, Massachusetts, United States
Countries
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Other Identifiers
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2020P002676
Identifier Type: -
Identifier Source: org_study_id
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