In an era of value-based payment reform that demands greater efficiency, medical billers don’t have time to waste. That’s why data should be at the heart of every billing analysis they perform. Without data—and the ability to glean immediate insights from it—billing professionals are essentially in the dark, not knowing whether the resources they devote to a process improvement effort will boost revenue or help them achieve their desired goal for greater efficiency.
“It’s hard to put your finger in the wind and say, ‘Ok, we need to do this to make more money or change this process to make things more efficient,’” says Chris Hall, Sr. Product Manager for Kareo Analytics. “Having data gives you the ability to make more informed decisions.”
Putting Data in the Driver’s Seat
The good news is that today’s medical practice software, especially when the EHR is integrated with the practice management software in a single platform, captures more data than ever before. It’s a tsunami of information that can only be tamed with the help of a good set of analytical tools, says Hall. As more practice management software incorporates analytics capabilities, billers can avoid manual—and oftentimes error-prone—data manipulation that may not even give them the information they need. With analytical tools, they can gather and interpret the right data in minutes rather than hours or even days, leaving more time for action.
“Billers can spend their time actualizing those revenue opportunities rather than trying to uncover them,” says Hall.
However, it’s important to note that not every analytics tool is created equally, and there are limitations to some of the more basic tools, including a lack of transparency regarding formulas and definitions, says Hall. He provides the example of net collection rate. A basic tool calculates this rate using an industry standard formula but doesn’t provide any transparency into the actual data and time periods that are used—something that he says can vary from vendor to vendor. Without this insight and information transparency, it becomes difficult to draw accurate conclusions and make important decisions related to performance, payroll and more.
Basic analytics tools also tend to provide a summary view without the ability to drill down into the details, says Hall. For example, billers may be able to view a sum of payments each month, but not dive into a specific line-item at the claim level to see precisely where that revenue originates and what services or procedures are denied.
“A really robust analytics tool is highly transparent,” says Hall. “It will tell you how things are calculated and give you access to the source data.” If billers want to do their own calculations manually, they can more easily verify that the information is correct and gain confidence in the analytics tools, he adds.
Boosting Performance Using Robust Billing Analytics
When billers use robust analytics tools, especially when managing multiple providers and practices, they benefit not only in terms of being able to trust in the data, but they’re also able to answer these five important questions:
1. Is the business growing?
With robust billing analytics, billers can track and trend data related to appointments, visits and patient volume to determine whether changes in volume are seasonal or whether the business is truly growing. “It starts to get interesting really quickly because you have the data. You can do a true analysis,” says Hall. Having this data helps physicians determine whether they may need to hire additional full-time or seasonal staff, including non-physician practitioners.
2. Is the practice missing out on revenue?
Billers must ensure that they bill and collect all of the revenue to which they’re entitled. With robust billing analytics, they can easily glean missed revenue opportunities by identifying the root cause of denials, such as repeated coding or demographic errors, says Hall. Having this data helps identify the need for physician or staff education, he adds. For example, a physician may need to document with greater specificity to avoid a medical necessity denial. Or a coder may need additional education related to a particular code set.
3. Does the practice maintain a healthy cashflow?
A basic tool provides the percent of accounts receivable over 90 days old, but a robust tool allows billers to drill down into why those payment delays occur. For example, is it a lag on the payer side (and if so, why) or an unpaid patient responsibility?
4. Which payers should the practice contract?
Some payer billing requirements are far more stringent than others, and some take significantly longer to pay. With robust billing analytics, billers can easily glean whether payers pay correctly based on their contracted rates and whether they pay in a timely manner. Another example is viewing how payers pay differently for the same procedures. With this information, physicians can be more selective with the payers they choose to add to their panel, says Hall. Even if there are fewer payers, practices have the confidence in knowing that those payers pay accurately and on time, he adds.
5. What can the practice offer to an Accountable Care Organization (ACO)?
A robust analytics tool provides data that billers can use to justify the practice’s potential contributions to an ACO or other type of innovative care model. Customizable reports can serve as a ‘data resume’ to prove efficiency.
Finding the Right Analytics Tool
In a market that’s quickly becoming saturated with analytics tools of all shapes and sizes, billers need to be able to focus on what matters most—finding a solution in which they can trust. “You need to be able to trust what the tool is telling you,” says Hall. When weighing available options, he says practices should consider the following questions:
- Can you easily customize reports and dashboards?
- Can you export, bookmark, and share data for easy access?
- Can you drill down into the data using a variety of filters (e.g., CPT code, payment posting date, plan type, payer, and specialty), or does the tool limit you to common filters?
- Does the tool provide data transparency, including formulas, definitions, and source data?
- Is the tool user-friendly? Does it respond quickly, and can you view the data on multiple types of devices, including mobile devices?
“A robust analytics tool puts information front and center at your fingertips,” says Hall. “The information, comes to you.”
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