NQF: Why do healthcare measures matter?
HB: Measures and measurement are important tools to help drive improvement in the healthcare system. Measures that can really drive transformation are those that help us understand the things that matter most to patients: What was the result of care provided to them? Are they getting better? Are they able to access care when they need it? There are a lot of complex issues involved with these important outcome measures that have limited our ability to use them. But that’s changing, helped in part by foundational work that NQF is doing to advance measurement science, and the use of patient-reported outcome measures for performance measurement, in particular.
NQF: There is growing motivation to pay providers for care based on value, not volume of services provided. What is the role of measurement in this environment?
HB: Measurement of both quality and cost is a critical building block in our efforts to understand value. Value is essentially the outcomes that can be achieved relative to costs. To get at value, we need innovative, patient-centered outcome measures. We need to address those cross-cutting issues in measurement to clear the path for these important next-generation measures. NQF’s work on measurement science issues such as risk adjustment and linking cost and quality sets the foundation to move toward value.
NQF: What is measurement science, and what is NQF’s role in it?
HB: Measurement science explores the cross-cutting issues that affect the way measures are constructed and used so that we can get to the more meaningful measures needed in today’s rapidly changing healthcare system. NQF is leading the quality field in advancing the science of measurement. One example in this arena is our work on when and how to consider adjustment of outcomes for socioeconomic and other demographic factors. We also have focused on other difficult measurement science issues, such as measurement of low-volume rural providers. We are very excited by two new measurement science projects focused on attribution and measure variation. In the attribution project, we will explore best practices in attribution—how to assign the quality of patients’ health outcomes to specific providers when care for those patients is shared—and develop a set of principles. Our variation work will consider how to minimize unnecessary variation between similar measures to help make measurement more efficient. These cross-cutting measurement science projects provide critically needed guidance that affects all measures and settings.
