MedeAnalytics Data Fabric

 

Powerful data fabric accelerating digital transformation

MedeAnalytics Data Fabric is a unified analytics framework purpose-built to help healthcare companies understand real-time, high-quality, high-fidelity data and apply actionable insights to current and future needs. It provides an accessible visualization of underlying data sources and data lake that enables easier information management and maximizes the value of your data.

The foundation of our architecture

Our data fabric is the foundation for a robust architecture of solutions and services—each meticulously designed to help payers and providers achieve their goals.

Each thread of the data fabric—interoperability, visualization, predictive analytics, augmented analytics, benchmarking, and more—plays a key role in helping you make decisions confidently and see measurable impact.

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Components of our data fabric

MedeEnrich™

Data lake, master person index,
and self-service capabilities

The key to turning raw data into meaningful insights is data orchestration. With more than two decades of research and development fueling its capabilities, MedeEnrich is our unrivaled technology for data orchestration, enrichment, cataloging and quality assurance. It is tailored to enable commingling of ad-hoc, non-standard data sources—such as SDoH or productivity data—with the goal of creating an analytical source of truth for your enterprise.

MedeWorks™

Highly scalable data visualization
 

Leveraging a combination of proprietary and industry-standard national data sets, MedeWorks contains built-in benchmarking and drill-down capabilities to help users easily visualize data, spot trends, make comparisons and ask better questions. The platform also boasts 200+ pre-built, customizable analytics views, a user-friendly look, feel, and experience, and extensive security measures and provisioning capabilities.

MedeElevate™

Augmented analytics
 

Healthcare organizations need innovative analytics capabilities to capitalize on data, reduce human error, and drive cost efficiencies. MedeElevate offers intuitive visualization, predictive analytics, benchmarking, guided analysis, and machine learning—helping payers and providers make efficient decisions and realize positive outcomes. Platform capabilities include automatic, customizable text-based narratives on charts; predictive search within reports, charts, and fields; and a robust rules engine supporting outlier identification and root cause analyses.

Why our data fabric is superior

What you're used to
What we offer

Multiple disconnected data sources that are hard to ingest and unify

What you're used to
What we offer

Black box platform

What you're used to
What we offer

Limited integration

What you're used to
What we offer

Disparate and non-standard platform management

What you're used to
What we offer

Significant reporting lag time

What you're used to
What we offer

Inflexibility

Get our take on industry trends

Why managed Medicaid/Medicare health plans need analytics to improve outcomes

Why managed Medicaid/Medicare health plans need analytics to improve outcomes

September 21, 2021

Managed care organizations that provide healthcare services to Medicare/Medicaid members are dedicated to improving the health and wellness of these underserved populations, especially those living in rural areas.   

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Using consumer analytics to steer health-related decisions

September 7, 2021

Companies tap into what people like to eat and drink, how we purchase consumables, where we like to shop, what shows we might like to stream, whether we vote, and so on. If you have ever created a profile on a streaming application (think Netflix or Amazon), you will receive recommended books, movies and other items just as soon as you start surfing.

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Data Science into your Organization

Run: Bringing Data Science into your Organization

August 30, 2021

In this three-part series, we’ve been detailing a tiered approach to introducing and incorporating data science into your organization. In Part One: Crawl and Part Two: Walk, we discussed how to get started from scratch and start building out a dedicated data science program. Today, we’ll dive into the third and final phase to see how to grow quality, centralize governance, incorporate user feedback, and more.

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Data Science into your Organization part 2

Walk: Bringing Data Science into your Organization

August 23, 2021

In this three-part series, we’re exploring a tiered approach to introducing and incorporating data science into your organization. In Part One: Crawl, we discussed how to get started from scratch. Today in Part Two: Walk, we’ll address issues that may emerge and how to overcome them, how to build out a dedicated data science team, and more.

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