Denials in healthcare
Denials is the equivalent of a four letter word in healthcare. As payer rules change and workloads increase, it becomes more challenging to get reimbursed for services than ever before.
For tools to support the upstream revenue cycle, see the link at the end of the post or click here.
I recently heard something that resonated. Healthcare organizations have two top-line priorities. Deliver top-quality services and get paid for doing so. While breakthroughs in medical science and technology continuously makes the quality of care better, it seems to be getting harder to get paid for that care.
The stats speak for themselves:
3.3% of Total Potential Revenue is Lost to Denials
of denials were preventable
Rate of claims denied on first pass
of denials never re-worked
It should go without saying that denied claims are one of the largest contributing factors to healthcare organizations not getting paid for their services. If we can drill down to the most common denial reasons, we can start to address the problems at the source.
Where are the problems?
In order to address the problems highlighted in the stats above, we need to understand the source of the problems. By breaking down the most common reasons for a denied claim, we can identify where to focus efforts for the largest impact.
It is estimated that 30%-40% of denials are the result of pre-service challenges. The most common denial reasons in the pre-service environment are:
|Registration Errors/ Inactive Policy:||28%|
|Service not covered:||15%|
|Authorization/ pre-certification missing:||5.8%|
|Improper coordination of benefits:||1.1%|
When looking at this list we can see that nearly 50% of all denials can be prevented with increased due diligence on the front-end of the revenue cycle. Not only that, but the majority of the missing or incorrect information leading to denials can be found right on the payer's website!
The plain truth is, for the most part, the front-end team isn't lazy or complacent. They are responsible for the lion's share of information going in to a clean claim, yet often get the least in terms of resources and support.
In an average environment, the front-end staff are speaking with patients and their families. They are juggling more than one patient's information at a time. They are answering phones and interfacing with their computers. They are interacting with clinical staff and usually tasked with overflow admin duties. It would be one thing if these scenarios were happening sequentially, but this is a glimpse of what the front-end staff is doing at one time and all the time. All while being held to perfection in the gathering and processing of information lest claims get denied.
In spite of these challenges that aren't likely to go away, there are steps you can take to help your front-end staff get it right the first time and change from denials management to denials prevention.
3 Steps to Moving Denials Management Upstream
All relevant information should be verified 100% of the time. You should be sure the information you have matches the information the payer has to avoid a technical denial. During this step, you should verify matches in:
- All patient informationName spelling
- Date of birth
- Social security number
- Insurance policy information
- Is the patient truly eligible with that payer
- Policy number/ member ID
- Effective dates
While 100% verification 100% of the time might seem simple to implement, the reality is revenue cycle leaders struggle to make sure this step is followed at all times.
The best way to make sure verification is happening all the time is taking the process out of human hands. By automating verification, you can be sure it is being run all the time and rely on staff to focus on correcting verification failures.
Once all verification has been done, some determinations need to be made.
- Is the service ordered covered by the patient's plan?
- Is prior-authorization/ pre-certification required?
- Is the procedure medically necessary?
Again, to get 100% compliance on determining eligibility, prior-authorization, and medical necessity, taking the responsibility out of human hands by making it an automated process is the best way. Unfortunately, automation in the determination stage is not as straight-forward as it is in verification.
Eligibility can be determined provided the ordering physician provided all of the information needed to determine if the service is covered by the patient's plan. Many payer websites give you the opportunity to enter the CPT code and determine if the service is covered. That makes automating determination of eligibility entirely possible.
Prior-authorization can be trickier to automate. Most payer websites make it possible to determine if prior-authorization is required. In some cases, getting electronic prior-authorization is entirely possible. What obviously can't be automated are peer-to-peer reviews, so it is important to reduce the number of peer-to-peer reviews required. In speaking with a health plan, we learned that up to 70% of reviews are triggered by missing information that could easily have been provided the first time. Ensuring all the necessary steps have been taken before submitting a prior-authorization request is the key to reducing peer-to-peer reviews, which allows for more automation.
Medical necessity, as we all know, is an art as much as a science. Automation opportunities for medical necessity are limited because much of the criteria lay in the physician's notes.
The key to leveraging automation in the determination phase is to automate what you can. By doing so, you eliminate the easier things so that your staff has more time to focus on the more challenging situations.
The final stage of the upstream revenue cycle is discovery. During the discovery stage, you identify information that is not readily available such as:
- Active insurance coverage for patients wrongly classified as self-pay
- Any existing secondary or tertiary coverage that had been missed
- Unidentified primary payers for Medicaid patients
In the discovery stage, automation is essential and crucial. The most ideal way to go about discovery is running information from every patient, regardless of insurance status, through all of your top payers. Without automating the process, it would take an entire team to run the queries every day. The pay off can be huge, though. One organization we work with averages 3% additional net patient revenue by taking discovery seriously and making it a routine part of their up-front process.