Rejected or denied claims represent hundreds of billions of dollars in lost revenue for healthcare organizations each year, costing them about 5% of their net revenue stream. While the recommended rate of denials is under 4%, the actual rate for many healthcare organizations is around 20%. The most efficient way to reduce the amount of lost revenue is to target the root cause of denied claims – something that is very difficult to do using Excel and existing revenue cycle management solutions.
The amount of data included in UB-04 forms along with the associated 835 transactions create increasingly complex scenarios. Pivot tables using Excel and Revenue Cycle Management dashboards can help hospitals explore denial patterns that are straightforward and one-dimensional. However, they fall short when it comes to identifying combinations of factors (e.g., denial type, account class, payer, and facility) that represent a specific driver of a denial pattern. Ayasdi for Denials Reduction draws on the power of our machine intelligence platform to surface all the patterns in your denied claims – including the complex denials patterns in the 65% of claims that typically go untouched. It rapidly analyzes thousands of attributes (such as procedure codes, provider locations, physician and payer-related information) and groups similar claims to reveal patterns. Most existing tools are incapable of surfacing these distinct patterns and denials management teams have limited resources to manually evaluate, fix, and resubmit individual claims.
Ayasdi for Denials Reduction quickly surfaces groups of similar claims that are frequently denied, along with the key characteristics and reasons for denial. Finding the precise combinations of procedures, physicians, and diagnostic codes that influence payment eligibility using conventional analytical tools is time-consuming and resource-intensive. Ayasdi automatically identifies actionable denial patterns by creating granular claims denial profiles for groups of similar claims. Each claim profile contains a rich description that includes the revenue impact. This allows your revenue cycle team to prioritize and take specific actions to prevent and reduce future denials. It saves analysts and medical billing specialists from having to guess and check which procedures, providers, and reason codes are in common within groups of denied claims.
The average cost of re-working a claim is $251. With hundreds of denied claims pouring in each day, providers need an efficient way of prioritizing claims for resubmission. Ayasdi for Denials Reduction helps classify newly denied claims and prioritize them for correction. It limits the investigation effort required to determine the root cause of the denial to fix the claim. This greatly improves the efficiency of the billing team and speeds payment reimbursement.
The insights discovered by analyzing denied claims can be used to proactively improve upstream coding changes by the medical staff that will avoid future denials. Instead of evaluating individual denied claims, a domain expert evaluates groups of similarly denied claims and suggests process improvements using the underlying characteristics of each of these groups. By identifying, modifying, and fixing processes upstream, hospitals can minimize the number of claims that are rejected or denied.
Granular claims profiles help streamline and prioritize claims resubmission work queues. For example, a biller working on appeals can now be routed a claim that already has the expected root cause flagged because it looks similar to one of the distinct claim profiles identified using the Ayasdi application.
The identified drivers of denial help inform upstream process changes, such as revising pre-certification procedures, targeting physician education, or updating coding practices, that can prevent future denials. Instead of creating broad education programs in the hope of changing physician behavior, you can drive targeted process changes suggested by each claim profile.
Ayasdi identifies actionable denial patterns by creating denial profiles for groups of similar claims. Each claim profile contains a rich description that includes the revenue impact. This allows your revenue cycle team to prioritize and take specific actions to prevent and reduce future denials.
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Ayasdi's denials management application is designed for large hospitals with a strong desire to improve performance in the revenue cycle. In Ayasdi's experience, those institutions that are committed to excellence can implement the changes necessary to recoup or avoid in the first place, tens of millions of dollars per year.SCHEDULE A LIVE DEMO