How CERT Empowers You to Improve Billing and Coding Compliance

EDITOR’S NOTE: This is the second in a multi-part series on the Comprehensive Error Rate (CERT) study in which senior healthcare analyst Cohen describes how to read the study and interpret the data.

As I noted prior, the goal of the Comprehensive Error Rate Testing (CERT) study is to estimate the improper payments made to providers by the Medicare Administrative Contractors (MACs).

It is not supposed to be used to measure errors committed by individual providers; however, the contractors (auditors) use the CERT study as a way to target them. For example, if you get paid millions of dollars for some procedure codes or DRGs that have a high error rate, it increases the likelihood that those specific codes and/or DRGs will be audited.

Why? Because, statistically speaking, whatever the error rate reported by CERT is can help estimate the potential improper payments made to your provider and/or organization.

The results of the CERT study are contained within 81 individual tables, aggregated into several primary sections and appendices. The data contain an amazing amount of useful information, and it is important to understand how to read the tables in order to make the best use of the data. At the top of the analysis, CERT reports improper payments made by MACs under Part A (Hospital IPPS, Inpatient Prospective Payment System) and Part A (excluding Hospital IPPS). Part B consists of physician-based procedures and durable medical equipment, prosthetics, orthotics and supplies (DMEPOS). For 2023, CMS reviewed a total of 37,508 claims. A total of 8,408 were DMEPOS claims, 17,259 were for Part A (total) and 12,001 were for claims filed on behalf of Part B services. For Part A services, 8,506 were for services excluding Hospital IPPS, and 8,753 were for services including Hospital IPPS.

When reporting improper payments, CERT reports both overpayments and underpayments, and they break the root causes for the errors into five major categories:

1. No documentation;
2. Insufficient documentation;
3. Medical necessity;
4. Incorrect coding; and
5. Other.

Reading and understanding the tables is critical to understanding the results and applying them to help mitigate your own risk of improper coding and billing. 

Tables 5 through 13 report the top root causes by claim type (Part B, DMEPOS and Part A). Tables 1 through 4 report top root causes for skilled nursing facilities (SNFs), hospital outpatient, inpatient rehab facilities, and hospice. At the top level, figure 2, for example, illustrates the root causes for all claims. Figure 3 does the same, but breaks it down by claim type, as show below:

Here we can see that insufficient documentation is the number one cause of improper payments overall, with medical necessity being the majority issue for Part A Hospital IPPS claims.

Appendices A through N report statistics on a wide variety of claim types, procedures, facility types, root causes, etc. And they report both underpayments and overpayments. For each of these tables, the data are laid out by both raw dollars and rates (percentages). For most, these include both point estimates as well as confidence intervals, and this is important enough to understand to warrant an explanation here. Let’s look at a sample of table G1, which reports improper payment rates by service type for Part B services:

In table G1, we can see that established office visits (99211 to 99215) have an average improper payment rate of 6.4 percent. This is the point estimate. Notice that the next column shows the “95% Confident Interval.” What exactly does that mean? It means that if I were to conduct 100 audits of 955 claims selected at random (as was done here), then in 95 out of 100 of those audits, the true improper payment point estimate would be somewhere between 5.2 and 7.6 percent. In only five out of 100 reviews would the true improper payment amount be less than 5.2 percent or greater than 7.6 percent, due to something other than just normal variation.

Why is this important for a practice to know? Let’s say that you are subject to an audit by some outside source; say, a Unified Program Integrity Contractor (UPIC). They audit your established office visits and tell you that you have an error rate of 25 percent. Based on the national study conducted under the auspices of CERT, that high of an error rate would only be found in 5 percent or fewer audits. So, either you are one of those unlucky five out of 100, or (and more likely) the error rate has been overstated. When you see audit results that are significantly higher than what is reported by CERT, you should be suspicious of them – and if it were me, I would have a third party audit those same claims to validate their findings. 

This kind of large discrepancy is neither insignificant nor uncommon. In fact, not only do I see it very often in my post-audit work, but in most cases, the majority of those found to be improperly paid are reversed on appeal. 

Appendix H reports projected improper payments by referring provider. Let’s take a look at table H5, which reports improper payment rates for continuous positive airway pressure (CPAP) by referring provider. 

Look at the improper payment rate for internal medicine: 18.4 percent, with a 95-percent confidence interval of between 13.7 and 23.1 percent. If I am a contractor, like a UPIC, this is going to be a strong motivator for me to look at practices that are paid a lot of Medicare money for CPAP referrals. Think about it: if your practice is paid, say, $1 million, statistically speaking, you were likely overpaid somewhere between $137,000 and nearly a quarter of a million dollars. This is certainly incentive for an outside auditor to target your provider.

DMEPOS has perhaps the highest overall improper payment rates for all claim types. Look at what is reported in table I2:

Notice that, for orthopedic surgery, the mean improper payment rate is over 40 percent, and it’s even higher for podiatrists. So, if you are either an orthopedic provider or a podiatrist, you can expect to be subject to higher-than-average rates of outside auditing due simply to the statistics in the CERT study.

Some of the tables report multi-dimensional data. For example, table J1 reports improper payment rates by both provider type AND type of error for Part B services.

Here, for example, we see that the average improper payment rate for cardiologists is 16.1 percent. That means that for every $100 paid, $16 is paid in error. Note that the root cause of insufficient documentation is responsible for 83 percent of those improper payment determinations, while less than 1 percent is due to insufficient medical necessity.

Appendices K1 through K3 are always popular, as they report specifics on evaluation and management (E&M) codes. Another popular appendix is M because it reports underpayments. And as you can imagine, these are significantly less than overpayments. In fact, while overpayments account for the overwhelming majority of all improper payments, underpayments for Part B, for example, account for only 0.2 percent. There were no underpayments reported for DMEPOS services, and underpayments for Part A services were also in the 0.2-percent range.

I could go on, but the best way to become more familiar with the CERT study is to download the supplementary report and just dive in. Not every table is useful for every person or purpose, but there is enough information there to satisfy pretty much every data need. You can use the results as a benchmark against your own internal audit findings, as well as to help improve your compliance goals, objectives, and strategies.

Remember, knowledge is power, and the CERT study will give you the power to improve and enhance your billing and coding compliance.

And that’s the world according to Frank.