US Healthcare System Strained by Rising Claim Denial Rates

Rising claim denial rates is one of the most critical revenue cycle issues the US healthcare system is currently facing.

The latest data from KaufmanHall suggests that 2022 was the worst fiscal year for hospitals and healthcare systems since the beginning of the COVID-19 pandemic. New data from March 2023 from a sampling of over 900 hospitals showed finances are beginning to stabilize with razor-thin profit margins. With wage inflation, surging costs, and delayed patient/service volume, healthcare organizations are feeling an immense strain on their bottom line. This financial pressure is compounded by increasing unresolved claims denials, accounting for an average annual loss of $5 million for healthcare systems.

Denials On the Rise

High claim denial rates have been a key contributor to struggling healthcare revenue cycles. Over the last five years, the data shows that claim denial rates have increased by 20 percent. The average claim denial rate across US healthcare systems is at a critical 10 percent or more. According to data compiled by the Medical Group Management Association (MGMA), nearly 20 percent of all claims are denied. Of those claims, a whopping 60 percent are never resubmitted.

A new analysis by Change Healthcare showed that the majority (63 percent) of denied claims are recoverable, but a lack of critical resources prevents healthcare systems from reworking or appealing claim denials. On average, providers can expect to spend $118 per claim on appeals and administrative costs. Staff turnover and training, an increasing backlog of denials, and antiquated claims processing methods all contribute to the US healthcare system’s significant claims denial issue.

Denial Trends

To improve the revenue cycle and boost the efficiency of claim processing, healthcare organizations need to understand the fundamental causes of claim denials. Most healthcare systems facing a claim denial issue experience one or more of the following systemic problems:

  1. Lack of Data Visibility: Many healthcare systems are contending with antiquated data reporting mechanisms. Without this data, it is difficult to diagnose the specific problems leading to a high percentage of claim denials. It is crucial to understand where in the revenue cycle denials are consistently occurring in order to optimize solutions for the future.
  2. Processing Complexities: With the rise of the massive insurance marketplace and the increase in high deductible health plans, insurance companies are pushing more financial responsibility onto patients. This can complicate the effective processing of complex claims for hospital administration staff. Mistakes at the processing level account for nearly 61 percentof initial claim denials.
  3. Disjointed Systems: Research done by Becker’s Hospital Review found that nearly 91% of rejected or denied claims were due to avoidable errors. Many of these errors can be attributed to disjointed systems that escalate inconsistencies in processing. Developing a consistent processing procedure across departments and at all levels of the claims processing system can reduce these errors and increase claim approval.

ERISA Recovery is Your Claim Denial Solution

As the healthcare market changes to meet increasing demands, individual practices and providers will spend more time, money, and limited resources chasing lost income from claim denials. No matter how efficient your claims processing system is, some claim denials are unavoidable. When claims are denied, ERISA Recovery can help recover and reinstate that income to boost your bottom line.

Our process is simple. We only require your reports. We use your data to uncover lost income and recover cash that would otherwise go uncollected. Our cutting-edge denials analytics provide essential data to help us optimize your claim denial review process and suggest long-term improvements to your claims appeal strategy. Our solutions can help you recover complex claims while depleting your backlog of aged or “dead” claims.