As highlighted in our previous article, denials management is a costly and labor-intensive process that impacts the financial health and operational efficiency of healthcare organizations. Industry estimates suggest that managing a single claim can cost as much as $124.50, and for a $5 billion hospital system, an average cost-to-collect of 3.74 percent equates to $187 million annually. However, leveraging global support and advanced technology offers new opportunities to lower costs and improve efficiency.
Reducing Costs with Outsourcing and Technology
Truly strategic or innovative providers, in order to lower their cost to collect while maintaining or increasing collections, are moving beyond reliance on internal resources and embracing innovative solutions that leverage technology and global expertise. One effective strategy is implementing a hybrid delivery model to manage denials that utilize global support teams. This approach not only reduces labor costs but also optimizes the use of internal resources, allowing staff to focus on the most complex and highest dollar appeals.
Additionally, implementing artificial intelligence (AI) and automation tools can significantly enhance denials management. With the advancement of technology, there are a range of tools that can further augment the denials management process:
- Predictive analytics: Utilizing predictive analytics to identify denial trends by diagnosis code, procedure code, payer-specific requirements and resolve issues before billing.
- Pre–bill: Utilizing predictive analytics to identify and escalate issues before the bill goes out accelerates cash and decreases denial rework.
- Post Bill – utilizing predictive analytics to identify denials with a high likelihood to be overturned and converted to cash, while highlighting those with low propensity to pay for denial steering committees to review.
- AI-driven interactions: Payer-facing AI systems can manage complex denial follow-up discussions, reducing the burden on internal staff.
- Automated appeal generation: Automated tools that synthesize clinical and billing data can accelerate the appeal process and improve success rates.
- Machine learning for payment forecasting: These technologies enable proactive revenue cycle management by anticipating future revenue patterns and potential discrepancies in real-time.
- AI agents: Use for denial inventory allocation, audit checks, claim status retrieval, and work queue management.
By harnessing these tools, healthcare organizations can mitigate losses associated with denials and create a framework that prioritizes high-return claims, ensuring a more robust financial outcome.
Proven Success Through Intelligent Automation
Healthcare finance leaders who have integrated automation into their revenue cycle operations reported a cost-to-collect as low as 2.9 percent, translating to considerable savings. In one notable case, the adoption of a hybrid approach using intelligent automation (IA) led to a reduction in the cost to collect below 2 percent. The investment in automation also allowed staff to focus on higher-value tasks, further driving efficiency.
Download the white paper "Redefining ROI in Denials Management" now to learn more about how to reduce the financial burden of denials management and deliver measurable improvements in ROI. Stay tuned for the next article in our series, where we will share best practices and insights for enhancing denials management outcomes.
Matthew Bridge
Ryan Chapin
