Surface and prioritize nonpayables
to complete more reviews, faster.
Getting started with health plan payment integrity review automation
CAVO Predict’s algorithms review and recommend prioritization of denied charges – and detail reasons for flagged charges. Claim reviewers easily accept or reject each suggestion, and CAVO Predict utilizes these decisions to continuously refine the machine learning model for that health plan’s reviews. Leverage CAVO Predict to streamline claims review processes, and to begin or enhance health plan payment integrity automation initiatives.
3 BENEFITS OF CAVO PREDICT
Positively impact health plan financials
Proactively identify those often missed, high-frequency charges
Move providers to pre-pay claim reviews
Increase payment integrity review productivity
Leverage your review team’s skillsets and time
Continuously refine machine learning and NLP models
Enables your review team’s ongoing decisions to build and refine plan-specific machine learning algorithms
Customize prediction rules with health plan policies and guidelines
WHY CHOOSE CAVO PREDICT
Leverage Our Resource Trifecta for Machine Learning
Healthcare Data Science Expertise
Data scientists specializing in healthcare claims review models build algorithms based on health plan business objectives.
Health Plan Claims Review-Specific Technology
CAVO, purpose-built as a payment integrity claim review solution, enables continuous machine learning model refinement based on ongoing review decisions.
Claims Review
Clinical Expertise
Clinicians are the liaisons and SMEs to help build and initially test the plan’s payment integrity machine learning model.
Partner with one payment integrity vendor Ι Minimize plan review time investment
CAVO® Predict – Itemized Bill Reviews
CAVO Predict – Itemized Bill Reviews flags specific suspect “IB” or “iBill” charges based on algorithms customized to your organization’s review processes and guidelines. Rather than exhaustively performing an itemized bill review, suspect charges are highlighted for human review and decision determination.
Itemized Bill Review NLP Example
In most cases, tubing is used for IVs and is reusable. However, when tubing is used as a feeding tube, it is only usable for a single patient. Using Natural Language Processing (NLP), CAVO Predict – Itemized Bill Reviews flags non-feeding tube charges for prioritized payer review and enables efficient decisions using our ibill review platform’s sort and filter features.
