A TECHNOLOGY PLATFORM DELIVERING
Increased productivity I Immediate decreased cost containment spends I Digital access to review, sum, sort, and share IBs
TESTIMONIAL: CAVO® Payer Client
VIDEO: How CAVO® Benefits Payers
CAVO® Generates Immediate ROI in Areas Including
Itemized Bill Audits
Leverage clinical time by improving productivity and timeliness - while maintaining quality.
Nurses can share only findings—and further streamline doctors' time with CAVO®'s annotate, highlight, and notes functionalities.
Escalation to clinicians is facilitated through CAVO®.
CAVO® typically surfaces the needed DRG information within 1—2 searches.
Captures data from original itemized bill and displays it within a filterable format, enabling sorts by revenue codes, dates, and item descriptions.
Generate a PDF report automated with correct header data and items marked within system to share with providers.
Search across cases or search specific providers—including images—to prioritize suspects.
Build custom reports to surface trends by providers, DRG codes, etc.
Scalable solution, regardless of database size or total records.
Streamline the Medical Claims Review Process
Typical medical claims review processes require personnel manually sifting through medical records often comprised of hundreds of pages - at times to locate a single sentence. The CAVO® platform transforms the medical claims review process by intaking medical record documentation and aggregating siloed data from both images and documents. The data is combined into a central repository. Payer claims review teams are then able to use search functionality - including complex and pre-defined searches - to increase findings and leverage clinical resources.
Efficiently Assemble Documents and Automate Audits
Use CAVO® to create "findings" summaries utilizing our select, highlight, and annotate tools within the imaged medical record. The result is an efficient document including only data relevant to that claim.
Leverage CAVO® to automate audit segment today while facilitating future machine learning for claims reviews.