Hospital claims denials are steadily increasing. Can data analytics help your organization prevent denials and maximize revenue?
In emergency medicine, denied claims lead to the obvious cost of lost revenue, but they also are costly in terms of delayed cash flow and the cost of reworking claims.
Each emergency department strives to prevent denials, but the causes aren’t always the same. Determining the most actionable plan of attack requires careful analysis of trends and a clear, data-driven approach.
Proactive management of payer denials can be accomplished with the right mix of expertise and data analytics designed for emergency medicine.
Identifying Documentation Deficiencies and Downcoding
One of the most common reasons for denial is CARC Reason Code 50, “Not deemed a medical necessity by the payer.”
Although this seems to be explanation enough on the surface, determining the root cause requires a deeper dive. Often, it’s a case of missing or incomplete supporting documentation. The next likely root cause is a charge or coding error.
Getting to the bottom of denials and determining corrective actions requires a careful analysis.
Accessing Current and Historical Key Performance Metrics
Dashboards are a key tool for delving into root causes of denials. In the continuous, cyclical process of claims management, performance metrics that can indicate improvement include:
- Denial rates
- First-pass resolution rates
- Clean claims rates
- Days in A/R
- Denial write-offs
Benchmarking these to industry standards and setting incremental goals for improvement is a valuable strategy. Even small improvements in claim-denial rates can equal big revenue dollars.
Flagging Claims That Are Likely to Be Denied
The average cost to rework a claim is $25, and many claims are reworked multiple times. This does not account for revenue lost due to write-offs, slow pay, etc. Nearly 65% of denied claims are never even resubmitted!
It is always in an organization’s interest to take a preventative stance when it comes to claims denials. The clean claims rate (CCR) is the best measurement of billing efficacy, and maximizing it requires several initiatives, including:
- Updating and completing patient information
- Verifying eligibility prior to date of service
- Detailing documentation of procedures, case history, and other information
- Adhering to insurance claim-filing timelines, some of which are very tight
- Double-checking modifiers
The best way to accomplish all of these tasks is with automated systems that flag inconsistencies and missing information — before submission.
Using Training to Prevent Errors That Cause Denials
Continuous education for providers, revenue cycle staff, and coders is crucial to maintaining a low denial rate. Even an organization that has reached its goals can be derailed by changes to coding guidelines, an EHR upgrade, or a new documentation requirement.
While analytics and automated systems can catch a lot of issues that can be corrected before submission, getting it right the first time is always cost-effective. Organizations that invest in education and have an effective process for communicating and rolling out changes can better anticipate and prevent snags in the claims process.
In today’s reality of slim margins, maximizing revenue means using smart health care data solutions to pinpoint problem areas and creating swift action plans to remedy them. By using data analytics and customized claims-flagging strategies, hospitals can monitor performance, standardize clinical protocols, and quickly identify opportunities for improvement and training. Contact d2i to discover how our tools can help you prevent claims denials or to request a demo of our powerful analytics solutions.