Pre-Pay, Post-Pay, And Blended Payment Integrity: Prevention Worth The Cure

By Anju Sah, HGS Healthcare

Today’s payers are increasingly focusing on optimizing claims management as part of a continuous effort to maximize operational cost savings. In fact, according to Black Book research, fraud management is projected to be one of fastest-growing payer services in the global healthcare BPO services market, with 92 percent of users citing it as a source of BPO value. Diligent attention to prevalent payment integrity issues is the fundamental requirement to combat the massive cost of recouping the overpaid amount. As a practice, payers deploy post-pay, pre-pay, or an amalgamated audit approach to detect, investigate, and recover overpaid claims or prevent overpayment.

Post-Pay Detection Approach

Until recently, most payers exercised the traditional “pay-and-chase” review approach to payment integrity, with efforts centered on post-payment recovery. In a post-pay review, paid claims data is mined and reviewed to assess payment integrity; revealing overpayment/underpayment/fraudulent claims. However, the administrative costs associated with this recovery approach are high.

Following the traditional approach also leads to friction between the payer and the provider apart from dropping efficiencies due to cross-department coordination in studying already paid claims.

This practice does yield lesser savings than the actual opportunity that exists. Research shows that improper claims payment and fraud contributes more than $250 billion to the annual cost of U.S. healthcare. Between 3 percent and 7 percent of all paid claims’ dollars have payment integrity issues, and waste is a $1 trillion problem driven by the way U.S. healthcare is organized, paid for, and delivered.

Pre-Pay Detection Approach

Driven by advanced technologies, an emerging paradigm is transforming payment integrity, with payers intently focusing on pre-payment review solutions to recover erroneous payment. Pre-pay detection results in direct savings and waste avoidance, substantially reducing downstream administrative cost invested in recouping the overpayment. Comprehensive predictive analytics, data mining, and advanced algorithms aid in avoiding claims paid incorrectly in the very first go.

Today’s integrated analytics and machine learning solutions deliver intelligence to identify issues in the claims cycle and address them before inaccurate payments are processed. The approach requires integrated platforms in conjunction with skilled labor to identify root cause to complement continual innovation of the pre-payment solution. This shifts the approach from detection and correction to prevention, resulting in higher ROI by way of overpayments that never occur.

The Blended Pre-/Post-Detection Approach

For truly optimized payment integrity, look to a blended and harmonized amalgamation of the pre- and post-pay detection approach. Keep in mind, however, that not all data will be available to back the pre-payment decision, due to the evolving dynamics in the healthcare industry. The idea is to find the appropriate balance of the two approaches, with dependability on data availability, technology proficiency, and workforce expertise. Pre-payment review avoids incorrect payment before the claim payment is processed, while post-payment aids in identifying trends to enhance the pre-payment solution.

Business process outsourcers (BPOs) can provide a range of comprehensive payment integrity blends of these pre- and post-payment solutions. These partners bring advanced predictive data analytics models, industry experience, and technological resources, to drive ROI for payers beyond (significant) cost savings. With the help of these experts, payer and providers can focus on their core processes and lean on partners for scale and sustainability to grow their business model. This impact transcends cost-containment for the ultimate in satisfaction and relationship building for those two key consumers of payer services—both member/patient and provider, alike.

About The Author

Anju Sah is General Manager of Operations at HGS Healthcare.