Denials management is critical for healthcare providers to optimize revenue and reduce financial leakage caused by claim denials. We combine the approach of using Claims Data to identify what types of claims are getting denied using AI and Machine Learning; our automations can fix a claim before it’s submitted or after it’s denied. Our approach to solving the denials problems are:
Root Cause Analysis: Integrated AI helps identify the root causes of denials across the revenue cycle. Some items include:
- Consecutive Account Logic – Causes denials and compliance concerns with government payers. Recommendations for remediation can be solved with reports, supporting data and automation to fix these issues either before or after they occur.
- Category II Codes Leaking Revenue – Category II codes are commonly used for reporting, but due to their $0 charge amounts, they typically aren’t reviewed thoroughly. For example, a Pregnancy Billing scenario where $0 Category II codes were not being rebilled as their representative charges when the patient’s pregnancy concluded at a different organization.
- Provider Based Billing – AI identified problems with Provider Based Billing claims caused by service location PBB configuration issues. AI determined that a specific combination of billing provider and modifiers was causing the denials, allowing the organization to rectify their build, institute automation and prevent future denials.
- Authorization Denials – Using AI to analyze successful and unsuccessful Authorizations historically and using automation to request Prior Authorization correctly prevents the denial from occurring in the first place and leads to efficiencies.
- Registration Denials – AI identifies front-end issues related to incorrect coverage identification and filing order. By analyzing coordination of benefits information against subsequent rebills of those services, AI found gaps in Medicare filing order logic. In cases where claims were initially sent to the incorrect payer and had to be rebilled to the appropriate payer using automation.
- Attachment Denials – AI and Automation ensure that proper attachments are added to the claim before processing and fixes those that have been denied.
Average Annual KPI’s for a Provider with $2B Annual Net Patient Revenue:
- 85% of Claims more likely to get paid
Example: Blue Cross 15K Denials, 9600 Appeals, 7400 Successful Appeals, 6400 resulting in payment
- Decreased time in cycle by 75%
- Shorter AR Days
- Decreased rework
- Improve Accuracy
Standardized Systems & Payors this works with:
- Epic
- Cerner (Oracle)
- eCW
- Availity
- Medicare
- Medicaid
- State specific portals/websites
- Any Payor with a Portal and/or API Capability
- Any EMR/EHR both large and small.
