Healthcare Claims Analytics Tool - 8 Week Implementation

Protiviti’s customizable proprietary Healthcare Claims Analytics Tool leverages Microsoft Power BI to IMPROVE claim quality, REDUCE adjusted claims, REDUCE rework, and INCREASE visibility into the entire claim population as opposed to a sample for healthcare organizations.

Allowed Benefit Validation: Protiviti’s Healthcare Claims Analytics Tool has the capability to aggregate all claim data for one or more products (i.e. Medicare Advantage, Managed Medicaid, Commercial, etc.) and independently recalculate the allowed benefit amount based upon source data to determine if there is an error. The tool can assess claim data pre check run to prevent pricing errors and improve overall claim quality. The tool captures:

1. Claim Accuracy And Errors: Allowed Benefit amount for each claim line, Fee Schedule amounts as the tool references the source of truth (CMS, etc.)., Reimbursement rules being applied , Statutory/Regulatory Requirements
2. Fee Schedule Issues: Fee Schedule loads resulting in inaccurate rates utilized.
3. Errors Related To: First time claim payments thus reducing multiple adjustments and/or interest payments, Manual and auto-adjudicated claims because the tool independently calculates the allowed benefit amount, Non-Par Provider Reimbursement Rates (assuming reimbursement at 100%).

Member Cost Share Validation: Protiviti’s Healthcare Claims Analytics Tool can identify the accuracy of the member cost share payment by comparing the claim data to the benefit plan’s cost share structure. This can be applied to any product line (i.e. Medicare Advantage, Managed Medicaid, Commercial, etc.) The tool captures:

1. Member Overpayments based upon the plan benefits for each claim.
2. Errors Related To: In Network and Out of Network Benefits, Manual and auto-adjudicated claims because the tool independently calculates the cost share amount.

Benefits of Protiviti's Healthcare Claims Analytics Tool:

1. Scalable: Provides ability to analyze a full population of claims as opposed to sampling and incorporate multiple products and services
2. Deep Insights: Exceptions within the population based upon criteria, Underpayment and Overpayment Amounts in aggregate and individual claim line level, Trends in the data and pinpoint root causes of errors.
3. Identify: Exceptions within the population based upon criteria, Member Overpayment Amounts in aggregate and individual claim line level, Trends in the data and pinpoint root causes of errors.

Pricing varies depending on size of environment and amount of data