Using Business Intelligence and Analytics for Radiology Billing
It seems like data is everywhere you look. Businesses rely on marketing data, customer demographics, accounting numbers, and in-depth analytics to make daily decisions.
It seems like data is everywhere you look. Businesses rely on marketing data, customer demographics, accounting numbers, and in-depth analytics to make daily decisions. Experts espouse the use of business intelligence in manufacturing, health care, financial management, and other niches. What does this new reliance on data have to do with radiology billing? If you want to develop a profitable claims process, it turns out data plays a huge role.
Business Analysis and Denial Management
Traditionally, many organizations deal with claim denials on a singular basis. This is especially true when dealing with paper claims. The error is corrected, the missing information is attached, or the denial is appealed. When you get data involved in the radiology billing process, however, you may be able to stop claims denials at the source.
Avoiding denials has a variety of benefits, including:
- Each claim comes with more profit when you don’t work it more than once
- Reducing denials also reduces the chance of payer audits.
- Clean claims makes it more likely you’ll attract insurance contracts.
- A one-and-done approach to claims reduces the amount of labor hours it takes to receive payment on your services, allowing you to concentrate on the quality of patient care.
By using data about your denials to find problem areas in your processes, you can address future denials in bulk. For example, if 30 percent of your denials were for invalid insurance, you might realize there’s a problem in the insurance verification process or system. Addressing that problem can mean smoother sailing for your radiology billing. For hospital based radiology practices, this will involve keeping a watchful eye on your hospital or partnering facility. Your success is incumbent on the accuracy of information gathered at registration.
To conduct a data analysis of your denials, you need to gather information about denials over a certain time. You might consider all denials for a week or a month. Categorize the denials into reasons, including things like coding errors, missing documentation, claim information errors, and insurance verification errors.
Take a closer look at the denials that account for the biggest category. See if you can trace the denials to a root cause in your organization or your partnering facility/hospital. Causes could include a problem with your system, a staff member who needs more education, or a confusing set of instructions. Make appropriate changes to address the issue.
Wait a few weeks for the changes to take effect, then pull another set of denials to review. Hopefully, you’ll see a reduction in the amount of denials associated with that category. If not, then you may not have addressed the problem. If you do see a reduction, then move on to the next highest category. One of the purposes of business intelligence is to constantly improve processes, so, unless you never receive a denial, you shouldn’t think your radiology billing practices are perfect.
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