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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
HCC Accuracy
HCC Accuracy

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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:

PulseData's ML/AI solution identifies undiagnosed and under-diagnosed patients at risk for chronic conditions and significantly improves HCC accuracy.

About PulseDataAI:

PulseData is advancing healthcare with data-driven actionable clinical insights giving payers, providers and other value-based care organizations the power to improve clinical and financial outcomes, close care gaps, and improve HEDIS and CAHPS scores. PulseData leverages large, diverse datasets and deep clinical expertise to effectively identify patients with chronic conditions. Using cutting-edge machine learning and AI models, PulseData enables early intervention, equipping healthcare teams with informed, data-driven insights precisely when they matter most – at the point of care.

PulseData’s thoughtful model development avoids machine learning biases, prioritizes model explainability and ensures optimal model performance. Our tailored collaborative approach with our valued clients creates meaningful, impactful, and relevant workflows. The resulting actionable insights can be viewed on our platform and seamlessly integrated into clinical workflows to enhance and support care management workflows.

At the nexus of technology and healthcare, PulseData empowers providers to make well-informed decisions, which improve patient outcomes, reduce costs, and improve program performance. Learn More at pulsedata.ai.

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:

Improve HCC Accuracy

Pediatric use cases:

None provided

Users:

PulseData's ML/AI solution identifies undiagnosed and under-diagnosed patients at risk for chronic conditions and significantly improves HCC accuracy.

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, Ambulatory EMR, Ancillary EMR, ERP system, Patient portal, Pop health platform, Home health, Behavioral health, Community based organizations, ADT, Access +/or revenue cycle, Credentialing, Website / public online sources, Other

EMR Integration & Relevant Hardware:

Recommended, but not required

EMRs Supported:

Epic, Cerner, Meditech, Allscripts, NextGen, athena, GE, eClinicalWorks, McKesson, Other, Allscripts/Eclipsys, Athenahealth, Azalea Health/Prognosis, CPSI, Evident, Healthland, MEDHOST, MedWorx, QuadraMed, Self-developed, Would prefer not to disclose, Point Click Care

Hardware Compatibility:

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

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:

PulseData's ML/AI solution identifies undiagnosed and under-diagnosed patients at risk for chronic conditions and significantly improves HCC accuracy.

Differentiators vs Competitors:

PulseData's ML/AI solution identifies undiagnosed and under-diagnosed patients at risk for chronic conditions and significantly improves HCC accuracy.

Keywords

Images

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Videos

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Downloads

No content provided

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PulseData Overview 2023.pdf

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Company Details

Founded in 2017

Founded in 2016

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