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TriageGO

TriageGO
3 verified clients

Overview


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It has 3 verified clients.
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TriageGO integrates with major EMRs such as Epic, Cerner.

DESCRIPTION

TriageGO is a software tool that leverages machine learning to suggest an acuity-level at triage, based on the likelihood of various ED (emergency department) outcomes. The tool supports the nurse by providing an actionable data point and, combined with their own clinical judgement, enables the nurse to sort patients into the correct trajectories for care in the Emergency Department. TriageGO empowers the clinician to better-differentiate patients based on their clinical risk, and in doing so, has impactful operational benefits; decreasing time-to-provider, time-to-emergent care for high-risk patients, and time-to-discharge across the board. TriageGO is seamlessly embedded within the EHR (Epic & Cerner) so that it is not disruptive to the clinician's workflow.

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EHR integration

Acute care EMR
Required
Epic, Cerner
None provided
Use cases and differentiators

When a patient comes into an Emergency Department (ED), they are triaged into one of five acuity-levels; 1 being high-acuity, likely in need of intensive care or emergency intervention, 5 being low-acuity, not likely to need intensive care, emergency intervention, or hospitalization, and therefore likely to be discharged home. The current methodology of triage in most United States EDs is a manual desicion tree based on anticipated resource-utilization. However, using this system, the majority of patients are assigned to an acuity-level 3, with poor differentiation based on their actual clinical risk (as resource utilization is a poor proxy for clinical risk). This can make it very difficult for clinicians to properly identify which of these mid-acuity patients needs care most urgently, and often creates a clutter effect causing increased wait-times in the ED. 

When TriageGO is installed within the triage workflow in an ED, it helps the nurse to discern a patient's actual clinical risk, and prioritize them appropriately. When patients are sorted into the correct trajectories for care immediately upon being triaged, the clutter effect is reduced. EDs who use TriageGO observe decreased time-to-provider, time-to-ICU, time-to-OR, time-to-admission, and time-to-discharge. 

Pediatric application of TriageGO is the same, except the model is adjusted for pediatric clinical presentations. 

Emergency Nurses, Emergency Physicians, Emergency Dept Administrators

TriageGO embodies the principles of Open Innovation fostered by EHRs like Epic & Cerner who support an app-market-style ecosystem. While some risk-predictive features exist within current EHRs, there is no comparable solution for risk-stratification at triage, trained on the data within that hospital's instance of the EHR. 

There is one similar product on the market known as KATE from Mednition. This product still relies in the resource-based ESI methodology of triage. One hospital using KATE reported just 65% accuracy in triage asignment. In an evaluation done at Johns Hopkins, where TriageGO was invented, the tool demonstrated 78% sensitivity to identify patients who went on to need critical care, and a 120% improvement over ESI to identify those who went on to need an emergency procedure. It was also observed that using TriageGO, the rate of low-acuity patients who were ultimately hospitalized went from 6% to 3%. 

Company information

Media


Images

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TriageGO Demo Screen.png
Videos

TriageGO_Animation v5.mp4
Downloads

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Johns Hopkins White Paper.pdf

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