Prospective Risk Adjustment

A member-centered approach to risk

CARAT Analytics is a cloud-based analytics portal that supports your population health management efforts to monitor risk scores and identify gaps between documentation and ICD-10 and HCC codes. CARAT Analytics focuses on making data clear and actionable, helping identify trends, sort, and prioritize where greatest opportunities exist.


CARAT ProviderAssist concurrently supports the provider, with suggestions directly with the EHR to close gaps and to treat for and validate M.E.A.T. criteria.

Brings in all healthcare data, structured and unstructured, from any EHR


Ensuring accurate risk and revenue with concurrent ICD-10 and HCC coding from clinical notes

Reduce cost of retrospective audits during RAPS to EDPS migration

Real-time, automatic M.E.A.T. / T.A.M.P.E.R. validation

Completely configurable integration and user experience

Proven Capabilities

Our findings involving numerous health plans and MCOs, hundreds of providers and thousands of patient encounters, Cybexys demonstrated the power of CARAT to resolve under-coding and to lower risk exposure to RADV audits.

Under-documentation – Prior-years’ documented chronic conditions that were not included in the current year’s clinical notes.

Under-scoring – the provider failed to assign proper ICD-10 codes to capture the severity of the diseases; however, the clinical notes support higher severity and complexity.

RADV Exposure / CDI Improvements – the provider missed proper documentation to support evidence of Monitoring, Evaluating, Assessing and Treating (M.E.A.T.) for the patient conditions included in the claims.

CARAT ProviderAssist

CARAT ProviderAssist provides a concurrent review of clinical documentation during each encounter, presenting coding and documentation gaps in real-time from within the EHR. CARAT ProviderAssist identifies the severity of each patient condition and encouraging actions to inform their care and support clinical documentation consistent with [M]onitoring, [E]valuating, [A]ssessing, [T]reating criteria (M.E.A.T.) for each HCC code in the patient record.

CARAT eliminates the need for chase lists, allowing health plans to optimize for risk and quality at the provider level in real-time.

Supporting Care Continuity

CARAT approaches every encounter with a retrospective analysis of the patient record to provide timely insight into clinical care, risk, and quality. CARAT is able to handle “big data” across multiple EHRs, including structured and unstructured data, including images / PDFs of diagnostic tests and documentation.

CARAT brings this retrospective analysis into the current encounter, informing providers to inform their care and support clinical documentation consistent with [M]onitoring, [E]valuating, [A]ssessing, [T]reating criteria (M.E.A.T.) for each HCC code in the patient record.

AI-Powered Productivity

Productivity is at the heart of CARAT’s success. The CARAT AI automates manual workflows for classification teams, providers, and coders. With the simplicity of suggested codes and M.E.A.T. documentation assists presented in the CARAT ProviderAssist EHR add-on, risk adjustment activities have been reduced to just five minutes a day. CARAT eliminates the need for chase lists and changes the coder workflow from costly review to simple verification.

Increase X5* Provider Productivity

Retrospective review auto-updates the problem list

M.E.A.T. opportunities presented concurrent to the encounter

Suggests ICD-10 and HCC codes with up to 95% accuracy

Within the EHR with push notifications for alerts by text or email

Filters out cases that reconcile

* Up to X5

Increase X3* Coder Productivity

ICD-10 and HCC codes automatically suggested for review

M.E.A.T. verification connects each criteria to its documentation for easy review

Multi-client first-in-first-out view and in-system communication supports collaboration

Filters out cases that reconcile


* Up to X3

Increase X2* Classification Productivity

22Analyze, normalize, and organize standard and non-standard data

Automate the classification of PDF documents, presenting them for review 





* Up to X2