Denials can have a significant impact on organizations, including delayed or lost revenue, increased staff workload, and reduced productivity. To avoid these setbacks, health systems must take steps to establish an effective denials-prevention and management infrastructure. 

But it's not enough to simply establish an infrastructure aimed at preventing and managing denials. To drive long-term success, leaders must take a data-driven approach. 

While most organizations collect data on denied claims, many of them do not have access to the right data, making it difficult to determine the extent of their denials issues and truly understand why their claims are being denied.  

Without a clear process for addressing denials, organizations can struggle to identify trends, analyze them effectively, and address them. 

To ensure that they're getting the most out of their denials data, organizations should start by looking at their denials dashboard. A dashboard should be able to stratify information by payer and by the owning area. The owning area is the group responsible for correcting denials and identifying activities to prevent future denials.

The owning area can be identified through reason codes that are posted from a remittance and mapped into an organization's EMR. This provides insight into where the denial stemmed from, such as a missing authorization pointing to an issue in the front end.

Denials dashboards should include the reason for the denial, mapped to the owning area, to provide insight into the root cause. This will help organizations identify trends and areas for improvement and hold the responsible parties accountable for correcting and preventing denials.

Organizations should also remember that EMRs don't always accurately capture denials data — it's often inflated, sometimes double or triple counting denials, due to multiple denials on a single claim. Most importantly, organizations must understand that they can't analyze denials data if they can't extract accurate data.

There are clear advantages of taking a data-driven approach to denials, but many organizations grow overwhelmed with the sheer amount of raw data available to them, leading to what's sometimes called "analysis paralysis." 

However, a data-driven approach can actually make use of raw denials data. Without sufficient and organized data, it can be difficult to assess the root cause of denials and take steps to prevent them. As a result, organizations focus on managing denials, instead of addressing the key issues up front.

By leveraging data, organizations can identify and address the root causes of problems, leading to more effective prevention measures and fewer denials. 

To successfully execute a data-driven approach, leaders should follow six key steps:

The first step in this process is assessing the extent of the denials problem. Organizations will analyze reports and dashboards used in the denials process and identify trends using risk-based analytics. 

Once an organization has identified high-priority, high-return denials, they can then perform a root-cause analysis to determine the underlying causes of the denials. This will empower organizations to identify key areas of improvement and define margin improvement opportunities based on margin impact and risk.

The severity of an organization's denials problem will dictate the level of effort needed to invest in denials work, making it essential to determine the ROI and allocate the appropriate resources to the issue.

By identifying key areas of improvement through a root-case analysis, organizations can build a workflow queue based on the issues causing denials, thus prioritizing their recovery efforts based on yield.

When conducting root-cause analysis, taking a targeted approach is the key to success. Instead of trying to analyze every aspect of the denials problem, it's important to identify the high-impact areas and target the approach to prevention. This focused approach will help organizations achieve better results in preventing denials.

After conducting a root-cause analysis and identifying areas for improvement, organizations can then define a denial strategy. This involves designing the future state denial workflow and operating model, as well as providing change management support.

When designing the future state denial workflow and operating model, organizations must consider whether they have the necessary infrastructure to execute their planned strategy. It's also important to ensure that the right people are partnering across the organization, including the business office, clinical staff, and operational staff.

In addition, organizations must determine whether they're facing a one-off issue or a systemic one. This will impact how they approach a denials strategy and how they deploy resources to prevent and manage denials.

Change management support is a key part of implementing an effective denials strategy. This involves working with clinical and operational groups to educate them on their role within the denial process. By helping them understand the importance of participating in root-cause analysis and correcting denied accounts, organizations can ensure that everyone is aligned toward a common goal.

To enable a successful data-driven approach to denials prevention and management, organizations must optimize core operating systems in denials management, leverage predictive denial analytics to address issues before billing, and enable providers to automate administrative claim processes.

Optimizing core operating systems in denials management involves setting up work queues that separate denials by owning group and align with the root cause analysis.

Predictive analytics give organizations the ability to identify potential denials based on historical data before the bill goes out the door, allowing time to address any potential issues. This proactive approach can help organizations avoid denials before they occur.

Finally, enabling providers to automate administrative claim processes is crucial for avoiding dependency on a single person. Automation ensures that the process is streamlined, and providers can take all necessary steps.

Analytics-based monitoring is a critical component of a successful data-driven approach. It gives organizations the ability to quickly access performance data, which ensures that the fixes put in place to prevent denials deliver the expected results.

When analyzing denials data, leaders should monitor several KPIs like initial denial rates, final denial rates, and overturn rates. Initial denial rates represent the percentage of claims denied upon first submission, and final denial rates represent the percentage of claims denied after appeals have been exhausted. The overturn rate represents the percentage of denials overturned after the appeal.

Monitoring these KPIs allows organizations to track the effectiveness of their denials management and prevention strategy and identify areas for improvement.

After identifying areas of improvement through performance monitoring, leaders should aim to drive continuous change and improvement by communicating performance data in a way that promotes denials prevention and management across the organization.

Leaders should deploy a multidisciplinary denials taskforce to help facilitate the distribution of the information and denials strategy across the organization and build a supportive environment around an issue that can at times cause frustration.

Then, stakeholders across the organization must work to implement changes when trends are identified.

During the COVID-19 pandemic, leaders had to pivot to produce creative, alternative solutions to address the revenue cycle challenges they faced. Post pandemic, providers have noticed an upswing in denial rates across the county.

Now is the time to get back to bolstering the fundamentals and focus on the activities that can address the preventable denials. Revenue cycle management and the associated denials work are fundamental to revenue and financial success.