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Payment Integrity and Cost Containment in Healthcare

Payment Integrity and Cost Containment in Healthcare:

A Payment Harmonization Benchmark

Healthcare payers are continually seeking to optimize their operations and financial
results. They can do both through cost containment measures. While most payers have moderate levels of automation in their payment integrity processes, just how comprehensive the automation is, along with how they approach their processes, vary considerably.

Based on a Q1 2022 survey of 214 healthcare payer executives, the Payment Harmonization Index was designed to establish the current state of engagement with members, identify gaps throughout the member experience, and explore the interdependence among payers, providers, and members.

Findings from the study are presented in a series of five reports. This report is the
second in the series, highlighting findings from payment accuracy executives and
offering an outline for the next wave of payment integrity and cost containment between payers and providers.

Some of the key insights you’ll find in the report:

  1. The shift to pre-pay and beyond lies on the horizon.
  2. Provider abrasion remains a sticking point.
  3. Medicare and Medicaid claims require automation.
  4. Technology adoption is well underway, but plenty of manual processes remain.
  5. The path to automated adjudication is long.
  6. Current communication leaves room for improvement.

This study was based on a quantitative survey conducted in Q1 2022, in which 214 healthcare payer executives participated. Seventy-five percent of participants worked at health plans, and the balance worked at TPAs. The survey questions identified the priorities of healthcare B2B executives regarding payments modernization and explored the actions they put in place to meet those priorities.

The findings presented in this paper are drawn from the responses of 60 B2B payments executives across the U.S. and supplemented with additional context and analysis from Aite-Novarica Group research. The data presented have a 10-point margin of error at the 90% level of confidence.

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