By Gabriel Perna for healthcare-informatics.com
Last December, the Department of Health and Human Services’ (HHS) Office of the Inspector General (OIG) painted an ugly picture of fraudulent use of electronic health records (EHRs) by hospitals and healthcare provider settings.
HHS OIG said that a good chunk of provider organizations they studied were not protecting patient data from potential misuse of data. Only 44 percent of hospitals surveyed had audit logs in their EHR and only one-quarter had policies regarding cutting-and-pasting content within the EHR. Only nine percent of respondents allowed patients to comment in the EHR to help verify data.
A year before that report, former HHS Secretary Kathleen Sebelius and U.S. Attorney General Eric Holder had put provider-based organizations on notice that the government was going to prevent EHR-related healthcare fraud activities like upcoding, the act of billing for a higher level of care than was delivered or care that wasn’t performed at all. In the past, the Office of the National Coordinator (ONC) and the Centers for Medicare and Medicaid Services (CMS) have held listening sessions on upcoding.
With all of this, upcoding must be an industrywide blight, correct? That was what Julia Adler-Milstein, Ph.D., University of Michigan School of Public Health assistant professor of information and Ashish K. Jha, M.D., Harvard professor of public health wanted to know. The researchers decided to analyze longitudinal data to determine whether or not hospitals that had adopted an EHR had a great increase of patients’ conditions and payments from Medicare, compared to those who hadn’t adopted an EHR. If they had, upcoding would be a likely perpetrator.
Their findings, published in a recent issue of Health Affairs, paint an altogether different kind of reality. Recently, Dr. Adler-Milstein spoke with Healthcare Informatics‘ Senior Editor, Gabriel Perna on the results of the study, whether or not EHR-related fraud is a serious problem, and if regulatory policy should focus on this issue. Below are excerpts from the interview.
Explain for our readers, those who don’t know, what upcoding is? Theoretically, how could a hospital upcode with an EHR?
Traditionally, when people say upcoding, what they mean is billing for care that wasn’t performed. So [a provider] would say we performed this whole array of tests and half of it wasn’t done. Another way of upcoding is upcoding severity of patients. Saying a patient was sicker than they really were, which results in higher reimbursement. It’s documenting or billing for care that doesn’t reflect reality.
In EHRs, there are order sets or boxes that could be clicked that could order an array of different tests or features. The electronic systems make it easier to order everything at once that may or may not happen. Another way EHRs could contribute is by copying and pasting notes. When you’re going through and billing care, you may see the same things and conclude that this patient was sicker and more was done for them.
Why made you want to do research on upcoding?
It really had to do with the fact that policymakers in Washington were ramping up efforts to track down and prosecute places that were using their EHRs to bill fraudulently. It looked like there were going to be significant resources devoted to the problem. My colleague [Dr. Jha] and I said the evidence that this is a problem isn’t really clear. We thought it was a perfect opportunity to do a study to see how widespread it is before federal dollars are spent trying to solve it.
How did you examine whether or not hospitals were using EHRs to upcode?
The first thing we did, we used data from the American Hospital Association (AHA) and their national survey of hospitals’ electronic functionalities. We used that to identify hospitals that had newly adopted an EHR. One year they didn’t have the set of functionalities for an EHR, and the next year they did. We were able to identify those that had newly adopted an EHR and those that had not adopted one at all in that time period. It gave us two groups to compare, people that did adopt and people that didn’t adopt. We compared hospitals that were similar in terms of match size and geographic region. The only difference was did they or didn’t they adopt an EHR.
In terms of looking to see if there was upcoding, we looked at two different measures. The first was case mix index, which determines the average severity of the patient population you’re serving. So if a hospital that adopted an EHR was documenting patients that were sicker, it would show up in case mix index. We also measured average payment for discharge. Were you paid more for each discharge? We adjusted for other things that could effect that outside the EHR. We compared the EHR adopters to the non-adopters on those two measures.
What did you find?
Ultimately, we found there was there no evidence that groups that had newly adopted an EHR had a higher rate of increase in case mix index or payments compared to those that didn’t. The key finding is that. What’s interesting is that both groups, which did and didn’t adopt an EHR, saw an increase in case mix index and coding over time. They did not stay flat. It’s just they actually increased the same amount. That tells us it’s not the EHR that is the cause of that. It’s broader trends that are going on.
Was there anything to suggest that this might be a problem in the near future?
I’d say in our findings, no. We really tried to look everywhere we could. We looked at the hospitals that you’d think would have the most incentive to upcode. We didn’t just ask if they adopted an EHR. We asked if they adopted functions within the EHR, such as computerized physician order entry (CPOE), that would lend itself to upcoding. Within our study, we looked thoroughly. But we didn’t look at outside of the hospital, at the emergency department (ED) and ambulatory settings, places where people have found evidence of upcoding. So while we don’t think it’s a problem within the hospital, there’s no way to say upcoding doesn’t go on.
One person, in an NPR article, suggested that you guys should have looked at outpatient records. What do you say to that?
There are two points to be made. First, why did we look at hospitals? Well, that’s where you’ll find the largest chunk of healthcare spending. We wanted to start there and look at the place where it has the potential to be the biggest problem. Now that we haven’t found it there, it’s feasible to look at other settings. There, the limitations becomes the data. We have pretty good data on hospital adoption of EHRs. We don’t have the same data to look at as far as when did an ED switch to EHR. At least, we don’t have the data in a way that’s easily public available. Once the data comes available it’s absolutely worth looking at. There are a lot of people working on this issue, this will not be the last and final word on this topic.
Should EHR policy be focused on preventing upcoding?
There is no doubt there should be some effort to focus on it. In the NPR piece, Don Simborg was quoted and he has been an advocate of fraud management solutions built into EMR software. That seems to be a feasible way to go about this.
To me, it’s a question of how much federal resources should go into identifying and tracking fraud. That’s where we could pull back a little. I don’t think we should spend a lot of time and money there. If there are low cost ways to track and identify fraud, we should be doing that.
The bigger picture, the whole reason we are adopting these systems, is to ensure they improve quality of care and efficiency of care. That’s where we need to focus. These unidentified consequences are bad, but if we don’t see the big picture, we will have lost it.