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Solutions
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

Categories

Solutions

Description

Product Description:
The VDT Affinitē Risk Adjustment module includes: • Multi-user access to the stand-alone Risk Adjustment Module of the Affinitē platform for CMS HCC Risk Adjustment. With Affinitē Risk, HEALTH PLAN NAME will receive the following: o Implementation o Data Integration and Analytics, Warehousing and Daily Processing o Dashboard high-level insights including the status of HCC capture, the performance of providers and provider groups, and HCC opportunities o Reporting o Estimated RAF scores at the member, provider, and provider group level based on claims data o Estimated member level RAF score build-up incorporating demographics, acute and chronic HCCs, disease interactions, and HCC payment count o Identification of HCCs obtained from claims data and chart review o Visibility into detailed claim data, highlighting HCCs that impact the RAF score o Visibility into detailed pharmacy data including refill status and ordering provider o Comparison of estimated RAF scores for current and prior year(s) o Identification of Missing HCCs (year-over-year gaps) for all open years at the member level o Member level identification of possible suspect HCCs based on claims and supplemental data for all open years. o Preparation of RAPS claim submission files in CMS required format o Preparation of RAPS supplemental submission files from chart review in CMS required format o Ability to monitor providers and provider group related to HCC capture, HCC gaps and average RAF score o Train-the-trainer training and support on the VDT Affinitē solution
About Vital Data Technology, LLC:

Vital Data Technology empowers health plans to continuously improve outcomes, accelerate compliance and control costs. Vital Data’s Affinitē™ platform unifies formerly siloed data and leverages artificial intelligence and machine learning to drive actionable interventions. The platform’s modules include: Affinitē™ PlanLink™ for real-time CareFlow™ automation and case management for stakeholders throughout the care continuum; Affinitē™ ProviderLink™ for prioritized, actionable patient interventions; MyVitalData™ for mobile app member engagement; Affinitē™ Quality for optimization of quality management and HEDIS® performance, and Affinitē™ Risk for Hierarchical Condition Category (HCC) risk adjustment.

Vital Data Technology is trusted by health plans nationwide across Medicare Advantage, Medicare, Medicaid, commercial and self-funded adult and pediatric populations and has received NCQA HEDIS® Certification for five consecutive years. For more information visit: www.VitalDataTech.com or call (866) 482-8399.

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

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:

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

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Company Details

Founded in 2015

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