Linking Novel Diagnostics With Data-Driven Clinical Decision Support in the Emergency Department

NCT ID: NCT05335135

Last Updated: 2022-04-19

Study Results

Results pending

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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Recruitment Status

UNKNOWN

Total Enrollment

300000 participants

Study Classification

OBSERVATIONAL

Study Start Date

2022-02-01

Study Completion Date

2024-01-31

Brief Summary

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The primary objective of this study is to validate the use of an electronic clinical decision support (CDS) tool, TriageGO with Monocyte Distribution Width (TriageGO-MDW), in the emergency department (ED). TriageGO-MDW is non-device CDS designed to support emergency clinicians (nurses, physicians and advanced practice providers) in performing risk-based assessment and prioritization of patients during their ED visit. This study will follow an effectiveness-implementation hybrid design via the following three aims (phases), to be executed sequentially:

(Aim 1) Validate the TriageGO-MDW algorithm locally using retrospective data at ED study sites.

(Aim 2) Deploy TriageGO-MDW integrated with the electronic medical record (EMR) and perform user assessment.

(Aim 3) Evaluate TriageGO-MDW in steady state with respect to clinical, process, and perceived utility outcomes.

Detailed Description

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Conditions

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Inpatient Hospitalization, Intensive Care Unit Admission, Inpatient Mortality, Sepsis and Septic Shock

Study Design

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Observational Model Type

COHORT

Study Time Perspective

OTHER

Study Groups

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Pre-Implementation

Usual care will be provided during all ED patient encounters.

Usual Care

Intervention Type OTHER

Clinical care without decision support provided by TriageGo-MDW

Post-Implementation

TriageGo-MDW CDS will be made available during all ED patient encounters at two points in the ED care continuum: (1) shortly after arrival during initial ED triage (First Triage) and (2) after initial laboratory results have been populated within the EHR. General illness severity estimates will be provided to nurses at ED triage in the form of recommended triage acuity scores (CDS for First Triage). General illness severity estimates along with estimated risk for specific outcomes including sepsis and septic shock will be presented to clinicians after laboratory results have populated (CDS for Early Assessment). TriageGO-MDW risk estimates will be generated by machine learning algorithms using routinely available clinical data as predictor inputs. Nurses and clinicians will receive risk estimates within existing EHR workflows, along with brief and rapidly interpretable explanations of the logic driving each risk estimate.

TriageGO-MDW Clinical Decision Support

Intervention Type OTHER

TriageGO-MDW is non-device clinical decision support that provides patient-level clinical risk estimates based on clinical data derived from the electronic health record

Interventions

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TriageGO-MDW Clinical Decision Support

TriageGO-MDW is non-device clinical decision support that provides patient-level clinical risk estimates based on clinical data derived from the electronic health record

Intervention Type OTHER

Usual Care

Clinical care without decision support provided by TriageGo-MDW

Intervention Type OTHER

Eligibility Criteria

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Inclusion Criteria

Inclusion Criteria: Adult patients receiving care at a study site ED

Exclusion Criteria: None
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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University of Kansas

OTHER

Sponsor Role collaborator

Beckman Coulter, Inc.

INDUSTRY

Sponsor Role collaborator

Truman Medical Center

OTHER

Sponsor Role collaborator

Stocastic, LLC

INDUSTRY

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Scott Levin, PhD

Role: PRINCIPAL_INVESTIGATOR

Stocastic, LLC

Jeremiah Hinson, PhD/MD

Role: PRINCIPAL_INVESTIGATOR

Stocastic, LLC

Nima Sarani, MD

Role: PRINCIPAL_INVESTIGATOR

University of Kansas

Kevin O'Rourke, MD

Role: PRINCIPAL_INVESTIGATOR

Truman Medical Center

Locations

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Kansas University Medical Center

Kansas City, Kansas, United States

Site Status RECRUITING

University Health Truman Medical Center

Kansas City, Missouri, United States

Site Status RECRUITING

Countries

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United States

Central Contacts

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Eric Hamrock

Role: CONTACT

4013420373

Facility Contacts

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Nima Sarani, MD

Role: primary

Kevin O'Rourke, MD

Role: primary

References

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Levin S, Toerper M, Hamrock E, Hinson JS, Barnes S, Gardner H, Dugas A, Linton B, Kirsch T, Kelen G. Machine-Learning-Based Electronic Triage More Accurately Differentiates Patients With Respect to Clinical Outcomes Compared With the Emergency Severity Index. Ann Emerg Med. 2018 May;71(5):565-574.e2. doi: 10.1016/j.annemergmed.2017.08.005. Epub 2017 Sep 6.

Reference Type BACKGROUND
PMID: 28888332 (View on PubMed)

Dugas AF, Kirsch TD, Toerper M, Korley F, Yenokyan G, France D, Hager D, Levin S. An Electronic Emergency Triage System to Improve Patient Distribution by Critical Outcomes. J Emerg Med. 2016 Jun;50(6):910-8. doi: 10.1016/j.jemermed.2016.02.026. Epub 2016 Apr 25.

Reference Type BACKGROUND
PMID: 27133736 (View on PubMed)

Crouser ED, Parrillo JE, Seymour C, Angus DC, Bicking K, Tejidor L, Magari R, Careaga D, Williams J, Closser DR, Samoszuk M, Herren L, Robart E, Chaves F. Improved Early Detection of Sepsis in the ED With a Novel Monocyte Distribution Width Biomarker. Chest. 2017 Sep;152(3):518-526. doi: 10.1016/j.chest.2017.05.039. Epub 2017 Jun 15.

Reference Type BACKGROUND
PMID: 28625579 (View on PubMed)

Other Identifiers

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21-STOC-101

Identifier Type: -

Identifier Source: org_study_id

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