A new approach to performance measurement harnesses the power of electronic health data to compute a single comprehensive metric to guide providers on the best way to treat individual patients. If successful, the measurement tool will improve care for patients and lead to more accurate reimbursement from payers for that care.

The measurement tool is being developed by the National Committee for Quality Assurance and Archimedes Inc. under a grant from the Robert Wood Johnson Foundation. The first problem the tool is attempting to fix is how cardiovascular disease is treated. Instead of measuring the impact of all the usual ways to treat cardiovascular diseases one by one—prescribing statins, lowering “bad” cholesterol and blood pressure to certain levels, getting a patient to quit smoking and so on—a sophisticated analysis of available electronic data on a patient determines the combined impact of the treatments on future health.

If pilot testing by the NCQA confirms the approach as useful and meaningful, it would free clinicians to do what works best for each patient in treating a chronic illness.

It’s a way to fit quality of care to a patient “and not manage to a measure,” says Mary Barton, M.D., the NCQA’s vice president for performance measurement. “The one-size-fits-all approach fits very few people well at all.”

Take the example of a heavy smoker with heart disease. Barton says that as a doctor, she can look at a range of measures, including blood sugar, blood pressure and low-density lipid (LDL) levels, and know that “the single most powerful thing I can do is to get this patient to quit smoking. And it would be worth my spending each of the 20-minute visits that I have with him in the first three months of the year going over nicotine-replacement options, referring him to the quit-smoking line—that would be more important and have a greater impact than any LDL management could.”

A detailed, multi-dimensional computer model, loaded with the findings of numerous clinical studies on various treatments and their documented outcomes, can “look at the treatment that a patient is getting, which is in the medical record, and we can calculate what the risk would have been without those treatments and what it is with the treatments,” says Don Morris, vice president or scientific product and technology development at Archimedes, a San Francisco-based healthcare modeling and analytics company. “And that tells us how much their medical treatment is reducing risk for that person.”

For providers and health plans, performance analysis becomes a simpler matter because “we can in one measure capture something (for which) previously we had to have lots of different measures for different activities,” says Morris. And progress on any one measure is less important than overall improvement.

The approach can assess both individual and organizational results. “It can calculate for each person, but then we roll that up for whatever population you’re asking about, whether it’s a health plan, or a clinic, or the performance of a particular physician,” Morris explains. “You can look at any population and see how effective your treatment is.”

Ultimately it tilts incentives away from those easy gains in nudging healthier patients’ scores and instead favors both preventive care and keen attention to the overall reduction in risk among more chronically ill people with room to improve. “It’s going to make it more important to reach that patient who’s really at risk,” says Morris.

The NCQA will spend about 18 months testing the feasibility of gathering all the data elements and assessing which are most viable and not as viable in arriving at the measure, says Barton.

Fundamentally, the use of such a risk score “brings what’s measured into alignment with what we’re trying to achieve, which is overall reduction in disease in the population,” says Morris. “What’s great is that with the availability of electronic data now, we can do this. And it’s not terribly difficult.”

“The question of the speed and spread of electronic records is one issue, and the fact that the marketplace (for EHRs) is rather chaotic, that EHRs are not uniformly equipped to be able to report quality measures,” Barton says. Despite those obstacles, “the prospect of electronic health records to improve the nature of measurement is hard to overstate.”