If you’ve looked at claim denial data from 2020, you know that in-network claim denial rates were at an all time high. There are a lot of variables that go into approving or denying medical claims, and many of the processes are manual or conducted by humans.
Why does that matter?
Some may blame the spike in in-network claim denials on COVID-19, and understandably so. An alternative theory is that these high rates could be caused by something as tiny as simple human error.
In this blog, we’re going to explore some interesting data points from a recent report released by Kaiser Family Foundation and identify how simple mistakes could lead to high claim denial rates.
The pandemic’s impact on claims
When Covid-19 reached pandemic levels in 2020, healthcare organizations did their best to evolve with the changing tides. One example is how they expanded services including additional coverage for telehealth services. While payers initially experienced cost-reductions due to the deferment of care, this had a snowball effect down the road as the pandemic waned. Those delays in care eventually caught up, and in many cases had a greater impact to care delivery and costs.
Due to the delays in care and the later onslaught of claims, the data that payers were using for rates and enrollment was skewed. This created a challenge for payers in 2021.
In addition to the above, another thing to consider is the claim denial rates for COVID-related cases. These claim denial rates were at 40%.
The reasons for this vary, but one thing is certain, the pandemic is not entirely to blame.
Reasons why claims get denied
There are many reasons why claims get denied. Some of them are because the data from the health system, provider, or the member was incorrect, not current, errors in coding, or incorrect dates. These denials have a root cause in that it is beyond the payer’s control.
Some common denial reasons as categorized by Healthcare.gov include:
- Denials due to lack of prior authorization or referral
- Denials due to an out-of-network provider
- Denials due to an exclusion of a service
- Denials based on medical necessity (reported separately for behavioral health and other services)
- Denials for all other reasons
When it comes to claims processing errors, this is a different story however. In 2020 (and today) There is been a shortage of claims processors, and due to this, an added burden on administrative staff to cover the extra demand.
Claims processing can be a fairly monotonous process, but each tiny step in the process may have a massive impact on whether or not a patient’s claims are paid.
A simple fix
Processing errors can contribute a lot to higher rates and higher in-network claims denials. If we look at the data, a tiny thing, like an error in matching an authorization to a claim could have a lasting impact. Health care is, at its core, a risk assessment game. Rates depend on it and so do your members.
Instead of leaving claims accuracy chance, why not take a proactive approach?
Robotic process automation can take over monotonous tasks as delegated by you and free up time so that your processors can focus on more complex and important tasks. Contact us today to learn more about how SymKey is helping our clients increase their auto-adjudication rates and improve accuracy while flattening the curve of claims volume to staff.