Tip: Use data analysis to identify potential fraud and abuse
Healthcare Auditing Weekly, July 1, 2008
Data analysis is an excellent tool for identifying potential fraud and abuse. Data analysis is the comparison of claim information and other related data to identify potential errors and/or potential frauds by claim characteristics individually or in the aggregate. Use these helpful methods and techniques to get the most out of data analysis:
- Identify areas of potential errors (e.g., services that may not be covered or not correctly coded) that pose the greatest risk
- Establish baseline data to recognize unusual trends, changes in utilization over time, or schemes to maximize reimbursement inappropriately
- Identify where there is need for local medical review policy
- Recommend claims-review strategies to efficiently prevent or address potential errors (e.g., prepayment edit specification or parameters)
- Produce innovative views of utilization or billing patterns that illuminate potential errors
- Recommend where there is a need to target high-volume or high-cost services that are being widely over utilized (this is important because these services will not appear as outliers and may be overlooked when, in fact, they pose the greatest financial risk)
This tip is adapted from The Healthcare Auditor’s Handbook. For more information about the book or to order your copy, visit HCMarketplace.
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