To keep an oncology practice running smoothly, you need to have a good handle on billing and reimbursement. It’s crucial to ensure that claims are expedited and the insurance company pays what they owe. However, we know how challenging it is with the existing reimbursement landscape.
When you think you’ve submitted a clean claim, there can be an issue that leads to a delay. On the other hand, you can get reimbursed, but the amount is lower than expected due to a documentation issue. While these cases can be painful, they are avoidable through the latest technology and checking the documentation as often as possible.
This article will explain how you can improve reimbursement rates for your oncology practice.
Make Sure Demographic Information Is Up To Date
You would be surprised by how often the patient’s information is inaccurate or outdated. The data needs to be as accurate as possible to avoid denials. At every appointment, it’s vital to verify insurance and demographic information. A typo or old data can lead to a denial.
One way to accomplish this is through technology. To ensure claims go out cleanly, software can identify coverage, copays, deductible year to date, or other factors. Technology can help reduce demographic and insurance related denials.
Provide Full Documentation
With filing claims, you need to ensure you have all your ducks in a row when submitting a claim. Even if you feel like you have all the documentation, double-check to make sure. A missing document can often lead to an initial rejection, meaning you’ll have to go through the excruciating appeal process.
Not only that, but it can lead to lower reimbursements. To ensure that you get the reimbursements you deserve, be sure you have everything in order the first time.
Create a checklist of all the documentation required for your most common procedures and CPT codes, and check it twice. Then, when you’re submitting claims, be sure it lines up with your documentation checklist. We understand that this can be difficult for you to do independently, which is why machine learning is here to help.
Machine Learning Is Key
One way many oncology practices improve reimbursement is through machine learning. Machine learning involves artificial intelligence (AI) that is fed information relevant to your practice, and then it performs monotonous, time-consuming tasks that your staff lacks the bandwidth to complete.
In the context of oncology, one example of machine learning is technology that can look at your past claims and figure out what is the appropriate reimbursement amount for a claim.
You may fear your company being taken over by machines, which is understandable. AI is still improving, and a company built on AI alone will fail. However, many oncology practices succeed by combining both human and machine learning.
For example, machine learning can handle lower reimbursement insurance claims while having human eyes finalize the claims or work on complex or high dollar claims. This dynamic can save your company time, and money and increase your output by a significant amount.
Know The Insurance Payer
Another way to succeed with reimbursement is to know which insurance company you are dealing with. Many will have one of two types of contracts, either for service or the percent of charges, with the latter applying, particularly for hospitals.
A practice must read the rules the regulations a provider has to figure out how to play their game. For example, some providers will only accept certain IMRT charges or only allow specific procedures during certain times. While these rules can seem like a hassle, you must know them.
Getting your claim out the door as fast as possible is also vital. Some companies have strict time limits, so you need to ensure that everything is good to go when it comes out.
This sentiment doubles if you are dealing with a new insurance company, but you should keep yourself updated on older companies. They often change their policies, leading you to make a mistake if you miss something in a new update.
Hire Someone To Help
Current AI and machine learning can improve reimbursement rates for your practice, but as a company, you might not have enough time to invest in them. On the other hand, you also might be intimidated by technology.
Hiring a company to assist with building a new infrastructure for your oncology practice can help you earn in the long run allowing machine learning to reduce denials through clean claim submission. Another reason is that it can provide a more cogent payment portal for your patients.
Not only can an improved infrastructure benefit your reimbursement rates, but it can also lead to you saving money due to fewer people hours and because you can create a better system for collecting payments.
You can improve your reimbursement rates, and we can help. Reimbursement can be a complex subject, but you would be surprised by how often technology can streamline the process. The latest technology can save you and your workers valuable time, leading you to make investments in other aspects of your company. So look into these machine learning algorithms and always double-check the information to ensure it’s as accurate as possible.
If your oncology practice could benefit from improved revenue recovery, schedule a demo of our AI and machine learning-based A/R optimization solution here.