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Published in: Journal of General Internal Medicine 1/2016

01-04-2016 | Editorial

The Next Generation of Clinical Performance Measures

Author: David Atkins, MD, MPH

Published in: Journal of General Internal Medicine | Special Issue 1/2016

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Excerpt

Many are familiar with the adage that “you can’t improve what you can’t measure.” Adopting clinical performance measures was an important part of the VA transformation of the 1990s, and measuring clinical performance has become an integral part of current efforts to drive improvement under Medicare, the Affordable Care Act (ACA), and in programs run by private payers. Measuring clinical performance, however, is a health system intervention, and as such, needs to be carefully examined. This includes how measures are created, how they are implemented, and the evidence for their potential benefits and harms. The landscape of healthcare has also changed substantially since the advent of the performance measurement movement, and it is time to update our approach to measuring quality. Rather than setting a single standard, identifying a random number of patients to whom the measure should apply, and conducting manual chart reviews at a single point in time, we need to be assessing quality for the entire population, including the more complex patients. A world with electronic health records and a much richer array of administrative and clinical data allows us to update our approach to include measures that consider population health, episodes of care, changes over time, and individual circumstances. The Department of Veterans Affairs (VA), which operates the largest integrated healthcare system in the United States, is a key contributor to the emerging knowledge base regarding how best to create and implement performance measures. …
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Metadata
Title
The Next Generation of Clinical Performance Measures
Author
David Atkins, MD, MPH
Publication date
01-04-2016
Publisher
Springer US
Published in
Journal of General Internal Medicine / Issue Special Issue 1/2016
Print ISSN: 0884-8734
Electronic ISSN: 1525-1497
DOI
https://doi.org/10.1007/s11606-015-3575-0

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