Can We Do Better? How Quality Measurement Can Help
Laurent G. Glance, M.D.
Monday, 1:10-2:10 p.m.
Hall H

Laurent G. Glance, M.D.

In its attempts to improve health care and reduce its cost, CMS is redesigning its reimbursement system to incentivize the quality of care instead of the volume of care. Monday’s FAER Helrich Research Lecture will address the limitations of quality measurement and whether payment reform will lead to better patient outcomes.

Laurent G. Glance, M.D., Professor and Vice Chair for Research at the University of Rochester, in New York, will present “Can We Do Better? How Quality Measurement Can Help,” from 1:10 to 2:10 p.m. tomorrow in Hall H.

“There is evidence that although our health care system at its best is one of the best in world, not all hospitals offer high-quality care,” Dr. Glance said. “Controlling health care cost is critical. Over the next 25 years, we will see a 75 percent increase in patients aged 65 and over. The Affordable Care Act (ACA) expands health care coverage to people without health care coverage.”

The ACA attempts to reimburse hospitals and physicians based on the quality of outcomes. Reducing complication rates and lowering readmissions can lead to substantial cost savings. In theory, process measures can improve adherence to “best practices,” leading to improved outcomes and lower costs. In practice, standardization often does not lead to better outcomes because of the absence of a strong link between processes of care and better outcomes, he said.

“The Achilles’ heel of process measures is, ‘Are those best practices in fact best practices? Will they lead to better outcomes?’” Dr. Glance asked, adding that data shows following best practices did not always lead to better outcomes. “So, CMS is shifting performance measurement away from processes of care and is focusing instead on outcomes.”

Also, outcomes measurement is challenging.

“It sounds straightforward, but it is not as straightforward as it sounds,” Dr. Glance said. “Hospitals cannot be compared simply by comparing their crude mortality or complication rates. Risk adjustment is necessary to account for differences in patient case mix and severity of disease. This requires accurate data on outcomes and clinical risk factors. CMS uses administrative data — billings data — to construct risk-adjusted outcome metrics. The alternative is to use more reliable, but much more expensive, clinical data.”

However, even having high-quality data does not solve all of the potential problems. Different risk-adjustment models — which include different risk factors — will frequently disagree on the identification of low- and high-quality outliers. Risk adjustment is not a perfect science, he said.

“Thus far, there is only very limited evidence to suggest that performance benchmarking leads to better patient outcomes, even when report card information is released to the public and is linked to financial incentives,” Dr. Glance said. “However, as those financial incentives become more important, it is likely that hospitals will invest more resources for quality improvement and that patient outcomes will improve.”