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.
Study Type
OBSERVATIONAL
Enrollment
300,000
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
Clinical care without decision support provided by TriageGo-MDW
Kansas University Medical Center
Kansas City, Kansas, United States
RECRUITINGUniversity Health Truman Medical Center
Kansas City, Missouri, United States
RECRUITINGCritical Care
Admission to an intensive care unit within 24 hours of ED disposition; Prediction performance of machine learning algorithms that underly TriageGO-MDW for this outcome will be measured
Time frame: baseline (pre-intervention)
Critical Care
Admission to an intensive care unit within 24 hours of ED disposition; Prediction performance of machine learning algorithms that underly TriageGO-MDW for this outcome will be measured
Time frame: during post-implementation steady state (approximately 3 months after intervention)
In-Hospital Mortality
Death during index hospital encounter; Prediction performance of machine learning algorithms that underly TriageGO-MDW for this outcome will be measured
Time frame: baseline (pre-intervention)
In-Hospital Mortality
Death during index hospital encounter; Prediction performance of machine learning algorithms that underly TriageGO-MDW for this outcome will be measured
Time frame: during post-implementation steady state (approximately 3 months after intervention)
Emergent Surgery
procedure in the operating room within 12 hours of ED arrival; Prediction performance of machine learning algorithms that underly TriageGO-MDW for this outcome will be measured
Time frame: baseline (pre-intervention)
Emergent Surgery
procedure in the operating room within 12 hours of ED arrival; Prediction performance of machine learning algorithms that underly TriageGO-MDW for this outcome will be measured
Time frame: during post-implementation steady state (approximately 3 months after intervention)
Sepsis
Prediction performance of machine learning algorithms that underlie TriageGO-MDW for this outcome will be measured
Time frame: baseline (pre-intervention)
Sepsis
Prediction performance of machine learning algorithms that underlie TriageGO-MDW for this outcome will be measured
Time frame: during post-implementation steady state (approximately 3 months after intervention)
Septic Shock
Meeting septic shock criteria within 24 hours of ED arrival; Prediction performance of machine learning algorithms that underly TriageGO-MDW for this outcome will be measured
Time frame: baseline (pre-intervention)
Septic Shock
Meeting septic shock criteria within 24 hours of ED arrival; Prediction performance of machine learning algorithms that underly TriageGO-MDW for this outcome will be measured
Time frame: during post-implementation steady state (approximately 3 months after intervention)
Viral Infection
Testing positive for influenza or Covid-19 (SARS-CoV-2) infection within 24 hours of ED arrival; Prediction performance of machine learning algorithms that underly TriageGO-MDW for this outcome will be measured
Time frame: baseline (pre-intervention)
Viral Infection
Testing positive for influenza or Covid-19 (SARS-CoV-2) infection within 24 hours of ED arrival; Prediction performance of machine learning algorithms that underly TriageGO-MDW for this outcome will be measured
Time frame: during post-implementation steady state (approximately 3 months after intervention)
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