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Description
Compatibility Level
Clients
Use cases
EHR integrations
Client types
Differentiators
Keywords
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Company details
Jump to:
Categories
Solutions
Description
Compatibility Level
Clients
Use cases
EHR integrations
Client types
Differentiators
Keywords
Media
Company details
eCART
eCART

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Categories

Solutions

Description

Product Description:
Proprietary Machine Learning models through an API service to predict the temporal health status of patients living with chronic disease. Models are trained on a robust and generalizable data set, including EHR data, SDOH, and RPM data. For example, Myia can predict with 90% accuracy hospitalization risk for a polychronic population in the following risk bins: 1-14 days, 15-30 days, 31-90+ days. Our predictive services are crucial for smart triage, patient program eligibility, and cost effective scaling of virtual care and RPM. Our service can function with or without RPM data.
About Myia Health:

Myia is a data driven operating system for virtual care. Myia equips Patients and Clinicians with the tools needed for the patients transition from hospital at home, to 30 day readmit avoidance, to traditional RPM. The shift to value-based reimbursement models necessitates more preventative models of care, Myia's platform crosses these models and facilitates cost savings. Myia is partnering with the leading healthcare organizations around the country. Partners like Mercy Virtual, one of the country's leaders in continuous and preventative chronic care management, including patients with Heart Failure, COPD, Diabetes, and Hypertension. Myia improves quality of life for patients and predicts and prevents costly medical events for care providers. Myia takes a device agnostic approach to daily patient monitoring, applies proprietary machine learning for smart triage, and has a clinician centric application to surface the right patient at the right time into workflow. Partnerships with BioIntellisense and Dispatch health bring a complete Hospital at Home offering to the market.

Product Description:

Health systems use eCART to quickly and efficiently direct clinical resources toward their most critical patients and ensure timely and consistent care. Our sophisticated reporting and benchmarking further empower clinical leadership to understand and drive practice patterns. eCART draws upon readily available patient data from the EHR, rapidly quantifies disease severity, and predicts likelihood of critical illness onset, hours before it happens. Built upon more than a decade of ongoing scientific research, eCART was developed at the University of Chicago by Dr. Dana Edelson, MD, MS and Dr. Matthew Churpek, MD, PhD and is well chronicled in published literature. The analytic and workflow have been in use in clinical practice since 2016.

About AgileMD:

At AgileMD, we are building the most advanced real-time predictive analytics and clinical pathways platform for hospitals.

To date, AgileMD tools have been used on nearly 2.5 million patients by more than 80,000 providers in over 150 hospitals, including some of the nation's leading academic medical centers. AgileMD is backed by premier accelerators MATTER, YCombinator, and Rock Health, and our cutting-edge analytics are built on a decade of ongoing research at the University of Chicago. In 2021, AgileMD garnered nearly $3 million in combined federal research and development funding from the National Institutes of Health (NIH) and Health and Human Services (HHS) to further advance our platform.

Compatibility level

Select which hospital or health system you work at and see a personalized compatibility level.

Clients

Select which hospital or health system you work at and see the client list

Use Cases

Description:

None provided

Pediatric use cases:

None provided

Users:

None provided

Description:

eCART anticipates all cause clinical deterioration in medical-surgical (ward) patients. The tool is used to prevent failure to rescue and improve timely ICU transfers.

Pediatric use cases:

We have a pediatric version of the eCART analytic (pCART) and would be happy to discuss a research partnership for this tool. 

Users:

Medical-surgical nurses and providers, rapid response teams

EHR Integrations

Integrations:

None provided

EMR Integration & Relevant Hardware:

Use case dependent

EMRs Supported:

Epic, Cerner, Meditech, Allscripts, NextGen, athena, GE, eClinicalWorks, Other, Allscripts/Eclipsys, Athenahealth

Hardware Compatibility:

Desktop, Mobile / Tablet (web optimized), Mobile / Tablet (native app)

Integrations:

Acute care EMR

EMR Integration & Relevant Hardware:

Required

EMRs Supported:

Epic, Cerner, Meditech

Hardware Compatibility:

Desktop, Mobile / Tablet (web optimized)

Client Types

Differentiators

Differentiators vs EHR Functionality:

There are no homegrown options that do all that Myia is capable of from a Clinical Perspective. Myia can be used to monitor patient data in four major settings, Inpatient, Hospital at Home, 30 Day readmit avoidance programs, long term RPM programs.

Differentiators vs Competitors:

Myia is the only RPM vendor that we are aware of with Data Scientist on staff as well as Data Analyst who work to stratify data and work with Clients to maximize the value of the Myia platform. By looking across patients clinical indication Myia can predict who should be on the program as well as whom is likely to require a hospital visit. These analytics help reduce costs and patient outcomes.

Differentiators vs EHR Functionality:
  • 10+ years of published academic literature on value over other early warning scores
  • Analytics derived and validated in robust patient datasets 
  • Built by clinicians for clinicians, with full cross-team workflow to ensure risk scores are understood and acted upon
Differentiators vs Competitors:
  • 8+ years in clinical use
  • High sensitiviy and specificity, meaning fewer false alarms and more efficient focus on the highest risk patients
  • Integrated workflow to ensure that risk scores are not ignored and action is taken
  • Robust reporting and benchmarking to drive quality improvement
  • Deep EHR-integration

Keywords

Images

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Videos

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Downloads

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Alternatives

Company Details

Founded in 2017

Founded in 2011

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