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Deconstructing the "Hidden" MU Requirements for Physicians

February 8, 2011
by Mark Hagland
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Interview: Jane Metzger, Principal Researcher, Emerging  Practices, CSC

A new report from the Falls Church, Va.-based CSC, “Physician Quality Reporting: The Hidden Requirements of Meaningful Use,” examines the many issues facing physicians and physician groups as “eligible professionals,” as defined by the Healthcare Information Technology for Economic and Clinical Health (HITECH) Act, move forward to pursue meaningful use under that program. The report’s authors, Jane Metzger, principal researcher, and Jared Rhoads, senior research analyst, are both members of the Waltham, Mass.-based Emerging Practices team at CSC. They conclude, just as they had when they analyzed meaningful use requirements in the inpatient sphere last year, that the MU requirements in the outpatient sphere are also far more complex and challenging than might appear at first glance.

HCI Editor-in-Chief Mark Hagland spoke recently with Jane Metzger regarding the results that she and Jared Rhoads articulated in their report, and explored the implications for providers. Below are excerpts from that interview.

Healthcare Informatics: What are the fundamental complexities underlying the ostensible meaningful use requirements for physicians under HITECH?

Jane Metzger: The basic answer is that you need a lot of data for quality measures that you won’t have in your EHR [electronic health record], even if you’ve met the Stage 1 requirements under meaningful use. And that message is the same with physicians, as it was when we studied hospitals. Now, the situation is the same, because the hospitals have to do 15 measures, but on the EP [eligible provider] side, it’s much more complex, because each EP has to do three core measures and three from the menu.

What’s more, the perspective we took was of that of the large medical group, and we figured, if it’s a multispecialty practice, by the time you’d pick the measures that are relevant to the different specialties, you’d end up having to satisfy most of the measures. So assuming that it’s a big medical group, the question we were trying to answer was, basically, what are the data capture challenges involved in meeting the measures?

And that’s an important distinction, because for an individual EP, there would be six measures. And one thing that the analysis we did shows is that you need to be thinking about the data capture that you’ll be doing for meaningful use, as you pick measures. So if you’re not going to do lab results in Stage 1, there’s a whole bunch of data you won’t be capturing.

And you’ll either have to do different measures, or figure out a way to get that data in. And the manual alternative would be pretty amazing, and I would argue, to the point of impracticable. So if we were a medical group setting out to figure out this puzzle, we’d want to be thinking about the quality reporting requirements, and how we’re going to meet the other functional requirements, in a meaningful, strategic way.

Jane Metzger

HCI: That speaks to a number of sub-issues, obviously.

Metzger: It does indeed, For example, it turns out that medication reconciliation is also going to be pretty important, because that’s how you find out about the meds that aren’t in the EHR, but that the patient is on. The reality is that, even though a lot of people thought, oh, we’ll get to quality reporting eventually, our major conclusion is that you’d better be thinking about quality measures as you develop your Stage 1 plan. Just to take one example, there are a lot of quality measures that use lab results; and for the measures you do pick, you’d better be sure you have all the data.

The other conclusion is that there’s a lot of data that is needed for the quality measures that won’t be captured through the inpatient EHR, because there isn’t really a structured designed into the EHR to make capturing that data easily. Fortunately, there is one element in the ambulatory EHR that is useful in this context, and it’s called the health maintenance profile.

Vendors and medical groups have relied on the health maintenance profile for years, and physician practices have been making use of it for years. And the health maintenance profile provides, for any given patient, a view of what health maintenance and disease management guidelines apply, and it translates those guidelines into measures.

For example, if we’re talking about a diabetic patient, that patient needs a hemoglobin A1c test every six months, or whatever the case may be. A lot of the wellness guidelines you would implement have to do with immunizations. So the health maintenance profile would include an immunization record as one of its items; and in my case, it would be able to note that I received my flu shot, but outside the particular medical practice (because I had mine at a community immunization drive). So there is a way, that’s built into most EHRs, to handle this data gap, but you have to work at it.

HCI: What will be the biggest challenges in this for most medical group IT and clinician leaders, in all this?

Metzger: I think they’re sort of on their own to figure out the data capture. The technology they use—their EHR will have to be certified that it can calculate and report. But they’re sort of on their own on how to capture the data.

HCI: When I read your report, I had the sense that no more than a small percentage of medical groups would be able to achieve this.

Metzger: Well, the amount of effort that Jared and I and our team have put into this was quite enormous. And I’m not aware that anyone else has analyzed this quite so thoroughly. And a lot of people thought, oh, their vendor was going to take care of it. And yes, the vendor has to demonstrate that their technology will calculate and report, but they only have to do three measures. And I think a lot of people thought this would be easier than it turns out, and that they’d probably get more help from their vendor on the data capture piece than it seems that they’re getting.

As I had mentioned earlier, I think people focused much more on the line items in Stage 1; but they didn’t focus on the measures. And it’s rather overwhelming—I have a notebook that’s probably 4 inches thick, of the measure specifications. And some of them changed from the interim rule to the final rule.

HCI: Do you think vendors also realize now that all these things are much more complex than anyone realized?

Metzger: As with all of information technology, the reality has always been that success is not about the tool, it’s really about the implementation. And I think there’s a lot about meaningful use that—assuming that a particular product has the basic capabilities—then, implementation builds on that. And I think meaningful use requires a pretty high degree of implementation. Indeed, quality measures are a pretty good example of that. Doing them requires thinking about data capture in a very granular way.

I’m actually surprised that people aren’t talking as much about encounter notes, because when, in our analysis, when we said, hey, here’s all the data you won’t have; well, the only place you could possibly find it would be in notes. And the only way you’d ever get it in a way you could use it for quality reporting, would be if the notes were structured, so that you could achieve automated capture. And it’s very hard to do because of the time constraints.

If you think about the physician in practice seeing a new patient, say, every 12 minutes or so, and you think about the current technology for achieving a structured note, and the demands of meaningful use, well, the data capture would either have to come out of structured notes or out of the health maintenance profile. Fortunately, the health maintenance profile is very structured, which is why it makes sense as a vehicle for data capture. In any case, it will remain a challenge for eligible providers to figure out how to achieve data capture in this context, which only adds to the complexity of the overall scenario.

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