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

Categories

Solutions

Description

Product Description:
EarlySign’s COVID Complications AlgoMarker Identifies individuals at increased risk for having COVID-19 complications. With the goal of prioritizing patients for COVID-19 testing and treatment, this new AlgoMarker aids in triaging patients by reducing chart review time to determine whether they are potentially at high risk for hospitalization, complications, and mortality.
About Medial EarlySign:
Medial EarlySign develops an AI algorithmic platform for the discovery of clinical insights that indicate the likelihood of disease from basic medical information, such as blood test results, and other EMR data. Called AlgoMarkers, its predictive engines are built in collaboration with healthcare organizations, through the combination of 10s of millions of patient years-worth of data, clinical rigor and some of the most brilliant algorithmic minds. The company develops clinical decision support and population health solutions that can assist in the early prediction of clinical outcomes related to cancers, metabolic, immune and infectious diseases. These tools are designed to place at the fingertips of healthcare organizations only those insights that could prove critical in disease management and prevention empowering them with proactive, predictive and personalized care management capabilities
Product Description:

HOPE-CAT is a machine-learning-based risk-assessment algorithm that identifies factors that may indicate the development of cardiovascular conditions that lead to maternal morbidity and mortality. By monitoring a pregnant patient's aggregated health data (e.g., medical records, wearables and device data, and self-reported data) in real time, HOPE-CAT stratifies a patient's risk and alerts providers to changes in a patient's risk status.

About Invaryant:
Invaryant is a Georgia-based health tech company enabling safer healthcare through integrated, real-world data and patented technologies. Our platform connects patients with those who make healthy possible, creating a secure, real-time, inter- & extraoperable environment for patient safety. Who benefits from Invaryant? • Patients • Physicians and other providers (in-person and telehealth) • Researchers • Patient safety programs (such as REMS and pharmacovigilance)

Compatibility level

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Clients

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Use Cases

Description:

None provided

Pediatric use cases:

None provided

Users:

None provided

Description:

Detect risks related to cardiovascular events and disease in pregnancy and postpartum.


Aid in earlier diagnosis of conditions leading to maternal morbidity and mortality.

Pediatric use cases:

None provided

Users:

Patients, Practitioners, OBGYNs, Midwives, Nurse Practitioners, Doulas, Cardiologists, Emergency Medicine

EHR Integrations

Integrations:

None provided

EMR Integration & Relevant Hardware:

None provided

EMRs Supported:

None provided

Hardware Compatibility:

None provided

Integrations:

Not applicable

EMR Integration & Relevant Hardware:

Required

EMRs Supported:

Epic, Cerner, Meditech, Allscripts, NextGen, athena, GE, eClinicalWorks, McKesson

Hardware Compatibility:

Desktop, Mobile / Tablet (web optimized)

Client Types

None provided

Differentiators

Differentiators vs EHR Functionality:

None provided

Differentiators vs Competitors:

None provided

Differentiators vs EHR Functionality:

Current efforts to reduce cardiovascular-based maternal morbidity and mortality are reactive. Often occurring in a disjointed system, patient encounters and, consequently, data collection occur every few weeks or months over the course of a pregnancy, and even less frequently postpartum.

HOPE-CAT constantly monitors a patient's aggregated health data (e.g., medical records, wearable and device data, and self-reported data) in real time, stratifies a patient's risk, and alerts providers to changes in a patient's risk status.

The machine-learning-based technology identifies signs of risk sooner than would be discovered in a clinical setting, prompting proactive intervention and reducing outcomes of maternal morbidity and mortality.

Differentiators vs Competitors:

HOPE-CAT is a proactive tool that identifies signs of risk before a patient experiences complications or a medical emergency, prompting intervention and fostering proactive care, unlike other diagnostic and treatment models.

Keywords

Images

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Videos

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Downloads

No content provided

Alternatives

Company Details

Founded in 2009

Founded in 2015

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