It’s that time of year again. Medicare fees are in danger of being slashed for 2012 and your revenue will be impacted.   Bah humbug! Since Medicare is a huge payer, almost every medical organization across the country will feel the impact of any cuts that are made. So, it is important to know how to quickly calculate the potential impact on your overall electronic payment revenue.

For this blog, I am going to use the following formula to determine the percentage impact to overall monthly electronic payment revenue:

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In the great TV series “M*A*S*H,” the character Radar could hear incoming helicopters carrying wounded soldiers from a long distance away  and he would yell “Incoming!” as they were getting close to the hospital. Well, the 5010 launch date is January 1, 2012 and all I can say is…. “Incoming!” Hopefully, most practices have been working diligently with their technology vendors, so they do not anticipate a large volume of new payer rejections when 5010 is implemented. However, it’s still a good idea to have your ‘radar’ ready and know how to quickly spot these rejections if they do occur.

The first step is to spot new rejections that you have not seen before. Assuming you use a clearinghouse, you will probably have access to data detailing each rejection category and rejection message. In this case, you can easily compare the top rejection messages for January 2012 to the previous few months. You should be on the lookout for any messages that are new – these can be easily spotted because the previous months will have zero rejections for that message.

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When it comes time to negotiate fee schedules with your payers, knowledge is power. And power can mean better contracted rates for your practice. Today, I would like to explore three metrics that may give you an edge and help you get what you deserve. So that we don’t have to go into too much detail about calculations, let’s assume your clearinghouse or practice management system can provide you with all of these statistics. If they can’t, you may want to ask why not and if they will be adding these features anytime soon.

The first metric to consider is the average paid percent. We compute this by taking the sum of your payments and dividing it by the sum of your submitted charges. In an ideal world, every dollar you submit for payment would be paid 100%. However, there are many reasons why this is not the case. Some examples include claim-specific negotiated discounts, payment bundling, capitation, and previous payment discrepancies. So what can you expect overall? For an average practice, the paid percent will be between 39% and 42%. However, the higher the percentage, the better your revenue will be. With this information, you should be able to compare each individual payer to that benchmark to see if they are better or worse.

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Imagine you are driving a Ferrari at top speed through the Italian countryside. What is the last thing you want to see? Speed bumps! That’s what it feels like when you have to deal with claim rejections – it slows down your revenue. In addition, using staff time to fix and resubmit those claims can be a slow process – especially when your office is already pressed for time.

So how do you avoid these “speed bumps?” The first step is to identify which rejections are occurring most often and which are more than just a one-time occurrence. One of the easiest ways to start this analysis is by running a report through your clearinghouse’s software. If your clearinghouse does not offer this option, you will have to manually go through rejection reports and analyze them by hand.

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Remark Codes are like a good mystery novel. They provide suspense, drama and a healthy dose of plot twists as you try to figure out what happened to your denied claim. When working on this mystery, you may be able to easily find clues through some analysis reports that will help you solve “The Case of the Rogue Remark Codes.”

According to the Washington Publishing Company, Remark Codes “convey information about remittance processing or to provide a supplemental explanation for an adjustment already described by a Claim Adjustment Reason Code.” Essentially, these codes provide organizations with critical information about the adjudication of a claim and explain why the adjustment was made.

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Despite every practice’s best efforts and best practices, not every claim is 100% clean of errors when it is first submitted – and that is OK because an effective and efficient clearinghouse should be able to help you catch many of these errors before the claim is ever sent to the payer.

Even if your clearinghouse catches a majority of errors, it is essential for all practices to know if a claim was rejected by the clearinghouse’s edits or by the payer’s edits. This knowledge is important to a healthy bottom line because rejections slow down revenue.

Given the choice between the two types of rejections, I always think that it is preferred to have your clearinghouse catch claim errors rather than the payer. At this point, people often ask me why one type of rejection is better than any other. The answer is simple – time. If you submit a bad claim to a clearinghouse – a good vendor will edit it and, if there are any edit errors, they will let you know very quickly—within minutes. Otherwise, it will take some time (possibly days or weeks) for the claim to go out to the payer, fail payer edits, and then return to you for your review. All of these steps take time, which slows down your revenue stream.

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Most providers and billing professionals understand the importance of tracking a practice’s “denied” claims—those for which insurers refuse to pay a dime. But there are other “hidden denials” that you also should be monitoring to prevent a slower, less obvious revenue drain.

I recently ran a report sampling more than five million claims and remits from late 2009, and found that about 7% were denied outright by payers. This is what I would call a traditional “denial” rate. Payers didn’t reimburse for any of the services on these claims.

A closer look at the denied 7% reveals that they cut across all types of diagnoses, from routine exams and vaccinations to cataracts and hypertension. Read More ›