Few financial burdens are as crippling and unavoidable as hospital and health related bills. The risk of putting them off can be one’s life, but the costs can be staggering. It’s essential then that health insurance claims are understood and made responsibly. While there are many causes of health insurance denial, one of the most avoidable is registration and processing.
What this means in practice is that claims must be submitted carefully. This means submission at the right place, the right time, and with the right information. Human error is going to lead to most of the mistakes in these realms. That’s not to say that it is every individual’s fault for making errors. There are lots of factors working against the person submitting a claim.
For example, many insurance companies have state wide or even local localities which can easily be missed. Many insurance cards also lack key information which can make submission more challenging. Even worse, submitting a card’s information online can lead to digital error. This is especially prominent for physical cards which are photographed.
Luckily, there are modern alternatives which are making submission and processing more accessible. AI powered card readers such as Orbit are spearheading this movement. These new card readers are trained on and recognize insurance cards themselves, not just the text. This means that error is far less common on the reader’s side, and human error can be avoided entirely.
The other big benefit of newer reader systems is that they can capture, verify, and process all at once. This means submitting a claim will be quicker and goes through less steps, something which can help to reduce error. These readers can also help to identify the proper location for submitting a claim.
Of course, these new systems can’t save someone from poor coverage or misclaims. Instead they’re a simple and effective tool for making sure proper claims get through quickly and effectively. After all, the last thing anyone wants is losing out on insurance due to a simple error.