AI-Driven Medical Record Review Technology

CAVO® is enterprise technology that streamlines the medical record review process by providing specific business process solutions to your organizational challenges in one multi-faceted platform.

AI-Driven Medical Record Review Technology

CAVO® is enterprise technology that streamlines the medical record review process by providing specific business process solutions to your organizational challenges in one multi-faceted platform.

Technology To Help Your Payer Organization

The CAVO® technology platform streamlines the medical record review process at both the functional and enterprise level. Using deep clinical and coding expertise in conjunction with NLP and ML as the backbone of our AI-driven use case deployment, CAVO facilitates a 10X faster claim or record review, significantly improves the financial outcome per FTE, and accelerates ongoing process improvement. Learn more about our payer solutions below.

$250MM

saved in claim expenses since CAVO’s inception

350%

average user productivity increase within 90 days of implementation

100+

insured members supported across commercial, medicare advantage, and managed Medicaid markets

32%

average reduction in administrative expenses

How CAVO Streamlines Critical Business Processes

Medical Management

CAVO enhances the collaborative review of medical records and complex authorizations requiring multiple touch points for review. CAVO extracts key information from medical records to ensure they are supported in provider-submitted forms and meet medical necessity.

Claims Administration

Instantaneously triage documents to determine if a medical record is complete, where an appeal needs to be routed, or convert paper claims into searchable, sortable data.

Payment Integrity

Leverage scarce clinical/coding staff and relevant medical records and claims to support clinical reviews—while maintaining consistent quality and better financial outcomes. Reduce review time with CAVO’s AI-driven sort, filter, annotate, highlight, and notation functionalities.

Fraud, Waste & Abuse

A scalable solution for FWA audits, regardless of database size or record volume. CAVO enables search across FWA cases or specific provider cases to prioritize suspects and build custom reports to surface medical record review trends by providers, DRG codes, and more.

Risk Adjustment

Search across medical records to easily identify populations requiring screening services. Clinical extractions include the identification of diagnoses within the medical record, including the context around a diagnosis. This allows for Risk Adjustment to identify HCCs within the medical record.

“Not only can reviewers easily pull up a patient’s entire file on the computer screen, now with a few keystrokes they can search a 10,000-page medical record and see all references to specific data points within seconds…[our] ultimate goal in switching to CAVO’s technology is to migrate all of our records into CAVO.”

Our Expertise Is Proven to Deliver Results

Discover how CAVO and its proven AI capabilities helped a national multi line managed care payer uncover $2MM+ in one IB review in less than 10 minutes.

Supercharge Your Data With CAVO's AI

CAVO Classify

Unstructured, complex data is quickly converted to a consistent and usable format through the use of AI to determine its unique source.

CAVO Extract

Critical components of usable and intelligently sorted data are quickly extracted and displayed to support particular business process use cases.

CAVO Predict

NLP and AI act as force multipliers for auditors, allowing them to focus their attention where needed instead of searching complex medical documents.

Built-In EMR API Access

Simplify the clinical documentation and record retrieval process for claims reviews with CAVO® Connect. With provider support, CAVO Connect enables health plan EMR access using FHIR to real-time data in medical records, itemized bills, and additional clinical documentation—while eliminating both provider and your plan’s costly administrative burden.