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

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:

The Pieces Ambulatory Platform further enhances documentation through two primary mechanisms: first, by generating a comprehensive lifetime summary from patient data, providing essential context for each visit; and second, by integrating Pieces in Your Pocket’s intelligent voice feature with pre-drafted note, allowing providers to effectively document actions taken or planned for the patient. This input is processed with natural language processing (NLP) and natural language generation (NLG) techniques, ensuring semantic clarity and reducing cognitive load for clinicians. This functionality not only minimizes documentation time but also alleviates cognitive overload, enabling providers to focus on delivering quality care.

About Pieces:

Our mission is to better people’s health and wellbeing. We do that by combining artificial intelligence with deep clinical knowledge to predict outcomes and present actionable information to healthcare providers. We also connect people to needed community services and community services to one another. By reducing manual effort our customers can spend more of their time helping people rather than entering, organizing or sifting through data.

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

Product Capabilities

The Pieces Ambulatory Platform leverages context-awareness by integrating and interpreting diverse patient data from ambulatory EHRs. It dynamically adjusts patient risk scores, personalizes insights, and modulates alert thresholds based on the patient’s current condition, medical history. This ensures proactive care interventions, minimizes unnecessary interruptions, and provides a holistic view of the patient, enabling care teams to deliver more efficient, tailored care.

It integrates natively with ambulatory EHR systems, ensuring a consistent user experience across devices and platforms, from desktops to mobile applications. By aligning with care team workflows and providing real-time insights directly within the EHR, the platform minimizes disruption and enhances efficiency, enabling care teams to focus on delivering high-quality, patient-centered care.

The Pieces Ambulatory Platform supports scalability and interoperability, making it suitable for deployment across individual clinics, ambulatory networks, and large healthcare systems. Its architecture allows seamless integration with multiple EHR platforms through open standards and APIs, ensuring compatibility with existing healthcare IT systems and devices. The platform's modular design enables efficient scaling, from small clinics to expansive healthcare systems, while maintaining consistent functionality and performance. This capability facilitates future expansion and allows organizations to adapt to evolving needs without disrupting workflows, making it a robust solution for diverse care settings.

With low/negligible hallucination rates in its AI models, the Pieces ambulatory platform consistently generates accurate and trustworthy patient summaries. This reliability is critical in tailoring clear, concise, and actionable insights for care teams, ensuring that critical information is always available, even during connectivity challenges, to support informed decision-making and efficient patient care.

The Pieces Ambulatory Platform delivers measurable impact by providing clear metrics and analytics that demonstrate its value in improving patient care and operational efficiency. It aligns with key performance indicators such as reducing length of stay, enhancing documentation quality, and decreasing clinician burnout. By offering tools for continuous quality improvement, such as real-time performance dashboards and detailed impact reports, the platform empowers organizations to track progress, optimize workflows, and achieve their clinical and financial goals effectively.

The Pieces Ambulatory Platform ensures robust data protection and compliance with healthcare regulations by adhering to HIPAA standards, safeguarding patient privacy, and enabling secure data sharing among relevant care team members. The platform's TX-RAMP certification further demonstrates its commitment to maintaining rigorous security protocols for cloud-based services, ensuring compliance with Texas state requirements. Additionally, Pieces is actively upgrading to FEDRAMP certification, which will enhance its ability to meet federal security and privacy standards. These measures include granular access controls, audit trails, and advanced encryption, ensuring that patient information is shared securely and only with authorized individuals, supporting both privacy and care coordination.

Use Cases

Description:

None provided

Pediatric use cases:

None provided

Users:

None provided

Description:

None provided

Pediatric use cases:

None provided

Users:

None provided

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

Hardware Compatibility:

None provided

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:

Pieces summary and insights are placed within the EHR, i.e. within the clinician's workflow in the EHR. 

Instead of presenting an array of data, Pieces Working Summary generates real-time, concise summaries of complicated hospital cases, mimicking what a physician would write. 

Differentiators vs Competitors:

None provided

Keywords

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Company Details

Founded in 2017

Founded in 2015

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